From 126b91eab3d9577f38fae0823ab8229d97bed034 Mon Sep 17 00:00:00 2001 From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com> Date: Fri, 3 Oct 2025 14:32:35 -0700 Subject: [PATCH] Lorenze/native inference sdks (#3619) * ruff linted * using native sdks with litellm fallback * drop exa * drop print on completion * Refactor LLM and utility functions for type consistency - Updated `max_tokens` parameter in `LLM` class to accept `float` in addition to `int`. - Modified `create_llm` function to ensure consistent type hints and return types, now returning `LLM | BaseLLM | None`. - Adjusted type hints for various parameters in `create_llm` and `_llm_via_environment_or_fallback` functions for improved clarity and type safety. - Enhanced test cases to reflect changes in type handling and ensure proper instantiation of LLM instances. * fix agent_tests * fix litellm tests and usagemetrics fix * drop print * Refactor LLM event handling and improve test coverage - Removed commented-out event emission for LLM call failures in `llm.py`. - Added `from_agent` parameter to `CrewAgentExecutor` for better context in LLM responses. - Enhanced test for LLM call failure to simulate OpenAI API failure and updated assertions for clarity. - Updated agent and task ID assertions in tests to ensure they are consistently treated as strings. * fix test_converter * fixed tests/agents/test_agent.py * Refactor LLM context length exception handling and improve provider integration - Renamed `LLMContextLengthExceededException` to `LLMContextLengthExceededExceptionError` for clarity and consistency. - Updated LLM class to pass the provider parameter correctly during initialization. - Enhanced error handling in various LLM provider implementations to raise the new exception type. - Adjusted tests to reflect the updated exception name and ensure proper error handling in context length scenarios. * Enhance LLM context window handling across providers - Introduced CONTEXT_WINDOW_USAGE_RATIO to adjust context window sizes dynamically for Anthropic, Azure, Gemini, and OpenAI LLMs. - Added validation for context window sizes in Azure and Gemini providers to ensure they fall within acceptable limits. - Updated context window size calculations to use the new ratio, improving consistency and adaptability across different models. - Removed hardcoded context window sizes in favor of ratio-based calculations for better flexibility. * fix test agent again * fix test agent * feat: add native LLM providers for Anthropic, Azure, and Gemini - Introduced new completion implementations for Anthropic, Azure, and Gemini, integrating their respective SDKs. - Added utility functions for tool validation and extraction to support function calling across LLM providers. - Enhanced context window management and token usage extraction for each provider. - Created a common utility module for shared functionality among LLM providers. * chore: update dependencies and improve context management - Removed direct dependency on `litellm` from the main dependencies and added it under extras for better modularity. - Updated the `litellm` dependency specification to allow for greater flexibility in versioning. - Refactored context length exception handling across various LLM providers to use a consistent error class. - Enhanced platform-specific dependency markers for NVIDIA packages to ensure compatibility across different systems. * refactor(tests): update LLM instantiation to include is_litellm flag in test cases - Modified multiple test cases in test_llm.py to set the is_litellm parameter to True when instantiating the LLM class. - This change ensures that the tests are aligned with the latest LLM configuration requirements and improves consistency across test scenarios. - Adjusted relevant assertions and comments to reflect the updated LLM behavior. * linter * linted * revert constants * fix(tests): correct type hint in expected model description - Updated the expected description in the test_generate_model_description_dict_field function to use 'Dict' instead of 'dict' for consistency with type hinting conventions. - This change ensures that the test accurately reflects the expected output format for model descriptions. * refactor(llm): enhance LLM instantiation and error handling - Updated the LLM class to include validation for the model parameter, ensuring it is a non-empty string. - Improved error handling by logging warnings when the native SDK fails, allowing for a fallback to LiteLLM. - Adjusted the instantiation of LLM in test cases to consistently include the is_litellm flag, aligning with recent changes in LLM configuration. - Modified relevant tests to reflect these updates, ensuring better coverage and accuracy in testing scenarios. * fixed test * refactor(llm): enhance token usage tracking and add copy methods - Updated the LLM class to track token usage and log callbacks in streaming mode, improving monitoring capabilities. - Introduced shallow and deep copy methods for the LLM instance, allowing for better management of LLM configurations and parameters. - Adjusted test cases to instantiate LLM with the is_litellm flag, ensuring alignment with recent changes in LLM configuration. * refactor(tests): reorganize imports and enhance error messages in test cases - Cleaned up import statements in test_crew.py for better organization and readability. - Enhanced error messages in test cases to use `re.escape` for improved regex matching, ensuring more robust error handling. - Adjusted comments for clarity and consistency across test scenarios. - Ensured that all necessary modules are imported correctly to avoid potential runtime issues. --- lib/crewai/pyproject.toml | 4 +- .../src/crewai/agents/crew_agent_executor.py | 3 +- lib/crewai/src/crewai/crew.py | 36 +- lib/crewai/src/crewai/events/base_events.py | 9 +- .../src/crewai/events/types/llm_events.py | 20 +- .../crewai/events/types/tool_usage_events.py | 15 +- lib/crewai/src/crewai/lite_agent.py | 14 +- lib/crewai/src/crewai/llm.py | 292 +- lib/crewai/src/crewai/llms/base_llm.py | 442 ++- .../src/crewai/llms/providers/__init__.py | 0 .../llms/providers/anthropic/completion.py | 432 +++ .../crewai/llms/providers/azure/completion.py | 473 +++ .../llms/providers/gemini/completion.py | 497 +++ .../llms/providers/openai/completion.py | 484 +++ .../src/crewai/llms/providers/utils/common.py | 136 + lib/crewai/src/crewai/tools/tool_usage.py | 23 +- .../src/crewai/utilities/agent_utils.py | 12 +- lib/crewai/src/crewai/utilities/llm_utils.py | 12 +- .../src/crewai/utilities/reasoning_handler.py | 32 +- .../utilities/token_counter_callback.py | 20 +- lib/crewai/tests/agents/test_agent.py | 101 +- lib/crewai/tests/agents/test_lite_agent.py | 24 +- ...uator.test_evaluate_current_iteration.yaml | 435 +++ ....test_events_collection_batch_manager.yaml | 88 + ...me_user_trace_collection_user_accepts.yaml | 340 ++ ...ch_marked_as_failed_on_finalize_error.yaml | 92 + .../test_agent_custom_max_iterations.yaml | 377 +- .../test_agent_error_on_parsing_tool.yaml | 3350 +++++++++++++++++ .../test_agent_execute_task_basic.yaml | 72 + ...st_agent_execute_task_with_custom_llm.yaml | 72 + .../test_agent_execute_task_with_ollama.yaml | 72 + .../tests/cassettes/test_agent_execution.yaml | 72 + ...t_agent_execution_with_specific_tools.yaml | 165 + .../test_agent_execution_with_tools.yaml | 72 + .../test_agent_function_calling_llm.yaml | 957 +++++ ...t_agent_moved_on_after_max_iterations.yaml | 72 + ...put_when_guardrail_returns_base_model.yaml | 72 + ..._by_new_o_model_family_that_uses_tool.yaml | 80 + ...rmat_after_using_tools_too_many_times.yaml | 1531 ++++++++ ..._usage_check_even_with_disabled_cache.yaml | 80 + .../test_agent_respect_the_max_rpm_set.yaml | 80 + ...respect_the_max_rpm_set_over_crew_rpm.yaml | 1663 ++++++++ ..._use_specific_tasks_output_as_context.yaml | 766 ++++ .../test_agent_with_knowledge_sources.yaml | 653 ++++ ...with_knowledge_sources_extensive_role.yaml | 332 ++ ...owledge_sources_generate_search_query.yaml | 674 ++++ ..._with_query_limit_and_score_threshold.yaml | 666 ++++ ...ery_limit_and_score_threshold_default.yaml | 668 ++++ .../tests/cassettes/test_cache_hitting.yaml | 72 + .../test_disabling_cache_for_agent.yaml | 80 + ...r_context_for_first_task_hierarchical.yaml | 1766 +++++++++ ...gger_context_is_false_does_not_inject.yaml | 996 +++++ .../test_first_task_auto_inject_trigger.yaml | 600 +++ .../test_get_knowledge_search_query.yaml | 581 +++ .../test_kickoff_for_each_invalid_input.yaml | 90 + ...reated_with_correct_parameters[False].yaml | 72 + ...created_with_correct_parameters[True].yaml | 72 + ...ite_agent_returns_usage_metrics_async.yaml | 165 +- .../test_lite_agent_structured_output.yaml | 210 ++ .../test_litellm_auth_error_handling.yaml | 128 + lib/crewai/tests/cassettes/test_llm_call.yaml | 80 + .../test_llm_call_with_all_attributes.yaml | 72 + .../cassettes/test_llm_call_with_error.yaml | 156 + .../test_llm_call_with_string_input.yaml | 95 + .../test_llm_passes_additional_params.yaml | 115 + .../cassettes/test_logging_tool_usage.yaml | 80 + ...est_task_allow_crewai_trigger_context.yaml | 810 ++++ ...low_crewai_trigger_context_no_payload.yaml | 414 ++ ..._without_allow_crewai_trigger_context.yaml | 813 ++++ ...wer_is_the_final_answer_for_the_agent.yaml | 419 +++ ...sage_information_is_appended_to_agent.yaml | 797 ++++ lib/crewai/tests/test_crew.py | 51 +- lib/crewai/tests/test_llm.py | 68 +- lib/crewai/tests/utilities/test_converter.py | 24 +- lib/crewai/tests/utilities/test_events.py | 52 +- lib/crewai/tests/utilities/test_llm_utils.py | 51 +- uv.lock | 8 +- 77 files changed, 25026 insertions(+), 493 deletions(-) create mode 100644 lib/crewai/src/crewai/llms/providers/__init__.py create mode 100644 lib/crewai/src/crewai/llms/providers/anthropic/completion.py create mode 100644 lib/crewai/src/crewai/llms/providers/azure/completion.py create mode 100644 lib/crewai/src/crewai/llms/providers/gemini/completion.py create mode 100644 lib/crewai/src/crewai/llms/providers/openai/completion.py create mode 100644 lib/crewai/src/crewai/llms/providers/utils/common.py create mode 100644 lib/crewai/tests/cassettes/test_kickoff_for_each_invalid_input.yaml create mode 100644 lib/crewai/tests/cassettes/test_litellm_auth_error_handling.yaml create mode 100644 lib/crewai/tests/cassettes/test_llm_call_with_error.yaml create mode 100644 lib/crewai/tests/cassettes/test_llm_passes_additional_params.yaml diff --git a/lib/crewai/pyproject.toml b/lib/crewai/pyproject.toml index f67014d5d..5868a9277 100644 --- a/lib/crewai/pyproject.toml +++ b/lib/crewai/pyproject.toml @@ -11,7 +11,6 @@ dependencies = [ # Core Dependencies "pydantic>=2.11.9", "openai>=1.13.3", - "litellm==1.74.9", "instructor>=1.3.3", # Text Processing "pdfplumber>=0.11.4", @@ -83,6 +82,9 @@ watson = [ voyageai = [ "voyageai>=0.3.5", ] +litellm = [ + "litellm>=1.74.9", +] [project.scripts] diff --git a/lib/crewai/src/crewai/agents/crew_agent_executor.py b/lib/crewai/src/crewai/agents/crew_agent_executor.py index d912bdf3c..6067de509 100644 --- a/lib/crewai/src/crewai/agents/crew_agent_executor.py +++ b/lib/crewai/src/crewai/agents/crew_agent_executor.py @@ -114,7 +114,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin): self.messages: list[dict[str, str]] = [] self.iterations = 0 self.log_error_after = 3 - existing_stop = self.llm.stop or [] + existing_stop = getattr(self.llm, "stop", []) self.llm.stop = list( set( existing_stop + self.stop @@ -192,6 +192,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin): callbacks=self.callbacks, printer=self._printer, from_task=self.task, + from_agent=self.agent, ) formatted_answer = process_llm_response(answer, self.use_stop_words) diff --git a/lib/crewai/src/crewai/crew.py b/lib/crewai/src/crewai/crew.py index 16119a82a..3de22dee5 100644 --- a/lib/crewai/src/crewai/crew.py +++ b/lib/crewai/src/crewai/crew.py @@ -1,16 +1,16 @@ import asyncio -import json -import re -import uuid -import warnings from collections.abc import Callable from concurrent.futures import Future from copy import copy as shallow_copy from hashlib import md5 +import json +import re from typing import ( Any, cast, ) +import uuid +import warnings from opentelemetry import baggage from opentelemetry.context import attach, detach @@ -82,6 +82,7 @@ from crewai.utilities.planning_handler import CrewPlanner from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler from crewai.utilities.training_handler import CrewTrainingHandler + warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd") @@ -1353,13 +1354,34 @@ class Crew(FlowTrackable, BaseModel): def calculate_usage_metrics(self) -> UsageMetrics: """Calculates and returns the usage metrics.""" total_usage_metrics = UsageMetrics() + for agent in self.agents: - if hasattr(agent, "_token_process"): - token_sum = agent._token_process.get_summary() - total_usage_metrics.add_usage_metrics(token_sum) + if isinstance(agent.llm, BaseLLM): + llm_usage = agent.llm.get_token_usage_summary() + + total_usage_metrics.add_usage_metrics(llm_usage) + else: + # fallback litellm + if hasattr(agent, "_token_process"): + token_sum = agent._token_process.get_summary() + total_usage_metrics.add_usage_metrics(token_sum) + if self.manager_agent and hasattr(self.manager_agent, "_token_process"): token_sum = self.manager_agent._token_process.get_summary() total_usage_metrics.add_usage_metrics(token_sum) + + if ( + self.manager_agent + and hasattr(self.manager_agent, "llm") + and hasattr(self.manager_agent.llm, "get_token_usage_summary") + ): + if isinstance(self.manager_agent.llm, BaseLLM): + llm_usage = self.manager_agent.llm.get_token_usage_summary() + else: + llm_usage = self.manager_agent.llm._token_process.get_summary() + + total_usage_metrics.add_usage_metrics(llm_usage) + self.usage_metrics = total_usage_metrics return total_usage_metrics diff --git a/lib/crewai/src/crewai/events/base_events.py b/lib/crewai/src/crewai/events/base_events.py index 6287f42bd..4f4e80434 100644 --- a/lib/crewai/src/crewai/events/base_events.py +++ b/lib/crewai/src/crewai/events/base_events.py @@ -17,6 +17,11 @@ class BaseEvent(BaseModel): ) fingerprint_metadata: dict[str, Any] | None = None # Any relevant metadata + task_id: str | None = None + task_name: str | None = None + agent_id: str | None = None + agent_role: str | None = None + def to_json(self, exclude: set[str] | None = None): """ Converts the event to a JSON-serializable dictionary. @@ -31,7 +36,7 @@ class BaseEvent(BaseModel): def _set_task_params(self, data: dict[str, Any]): if "from_task" in data and (task := data["from_task"]): - self.task_id = task.id + self.task_id = str(task.id) self.task_name = task.name or task.description self.from_task = None @@ -42,6 +47,6 @@ class BaseEvent(BaseModel): if not agent: return - self.agent_id = agent.id + self.agent_id = str(agent.id) self.agent_role = agent.role self.from_agent = None diff --git a/lib/crewai/src/crewai/events/types/llm_events.py b/lib/crewai/src/crewai/events/types/llm_events.py index 32314ad4e..c6db9405d 100644 --- a/lib/crewai/src/crewai/events/types/llm_events.py +++ b/lib/crewai/src/crewai/events/types/llm_events.py @@ -7,19 +7,23 @@ from crewai.events.base_events import BaseEvent class LLMEventBase(BaseEvent): - task_name: str | None = None - task_id: str | None = None - - agent_id: str | None = None - agent_role: str | None = None - from_task: Any | None = None from_agent: Any | None = None def __init__(self, **data): + if data.get("from_task"): + task = data["from_task"] + data["task_id"] = str(task.id) + data["task_name"] = task.name or task.description + data["from_task"] = None + + if data.get("from_agent"): + agent = data["from_agent"] + data["agent_id"] = str(agent.id) + data["agent_role"] = agent.role + data["from_agent"] = None + super().__init__(**data) - self._set_agent_params(data) - self._set_task_params(data) class LLMCallType(Enum): diff --git a/lib/crewai/src/crewai/events/types/tool_usage_events.py b/lib/crewai/src/crewai/events/types/tool_usage_events.py index 22fc488ab..7fe9b897f 100644 --- a/lib/crewai/src/crewai/events/types/tool_usage_events.py +++ b/lib/crewai/src/crewai/events/types/tool_usage_events.py @@ -27,9 +27,20 @@ class ToolUsageEvent(BaseEvent): model_config = ConfigDict(arbitrary_types_allowed=True) def __init__(self, **data): + if data.get("from_task"): + task = data["from_task"] + data["task_id"] = str(task.id) + data["task_name"] = task.name or task.description + data["from_task"] = None + + if data.get("from_agent"): + agent = data["from_agent"] + data["agent_id"] = str(agent.id) + data["agent_role"] = agent.role + data["from_agent"] = None + super().__init__(**data) - self._set_agent_params(data) - self._set_task_params(data) + # Set fingerprint data from the agent if self.agent and hasattr(self.agent, "fingerprint") and self.agent.fingerprint: self.source_fingerprint = self.agent.fingerprint.uuid_str diff --git a/lib/crewai/src/crewai/lite_agent.py b/lib/crewai/src/crewai/lite_agent.py index e658bca1c..001075bc5 100644 --- a/lib/crewai/src/crewai/lite_agent.py +++ b/lib/crewai/src/crewai/lite_agent.py @@ -1,13 +1,13 @@ import asyncio -import inspect -import uuid from collections.abc import Callable +import inspect from typing import ( Any, cast, get_args, get_origin, ) +import uuid from pydantic import ( UUID4, @@ -351,7 +351,10 @@ class LiteAgent(FlowTrackable, BaseModel): ) # Calculate token usage metrics - usage_metrics = self._token_process.get_summary() + if isinstance(self.llm, BaseLLM): + usage_metrics = self.llm.get_token_usage_summary() + else: + usage_metrics = self._token_process.get_summary() # Create output output = LiteAgentOutput( @@ -400,7 +403,10 @@ class LiteAgent(FlowTrackable, BaseModel): elif isinstance(guardrail_result.result, BaseModel): output.pydantic = guardrail_result.result - usage_metrics = self._token_process.get_summary() + if isinstance(self.llm, BaseLLM): + usage_metrics = self.llm.get_token_usage_summary() + else: + usage_metrics = self._token_process.get_summary() output.usage_metrics = usage_metrics.model_dump() if usage_metrics else None # Emit completion event diff --git a/lib/crewai/src/crewai/llm.py b/lib/crewai/src/crewai/llm.py index 733b46c79..c3a759bae 100644 --- a/lib/crewai/src/crewai/llm.py +++ b/lib/crewai/src/crewai/llm.py @@ -1,13 +1,14 @@ +from collections import defaultdict +from collections.abc import Callable +from datetime import datetime import io import json import logging import os import sys import threading -from collections import defaultdict -from collections.abc import Callable -from datetime import datetime from typing import ( + TYPE_CHECKING, Any, Final, Literal, @@ -17,7 +18,6 @@ from typing import ( ) from dotenv import load_dotenv -from litellm.types.utils import ChatCompletionDeltaToolCall from pydantic import BaseModel, Field from crewai.events.event_bus import crewai_event_bus @@ -39,19 +39,42 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import ( ) from crewai.utilities.logger_utils import suppress_warnings -with suppress_warnings(): + +if TYPE_CHECKING: + from litellm import Choices + from litellm.exceptions import ContextWindowExceededError + from litellm.litellm_core_utils.get_supported_openai_params import ( + get_supported_openai_params, + ) + from litellm.types.utils import ChatCompletionDeltaToolCall, ModelResponse + from litellm.utils import supports_response_schema + +try: import litellm from litellm import Choices, CustomLogger from litellm.exceptions import ContextWindowExceededError from litellm.litellm_core_utils.get_supported_openai_params import ( get_supported_openai_params, ) - from litellm.types.utils import ModelResponse + from litellm.types.utils import ChatCompletionDeltaToolCall, ModelResponse from litellm.utils import supports_response_schema + LITELLM_AVAILABLE = True +except ImportError: + LITELLM_AVAILABLE = False + litellm = None # type: ignore + Choices = None # type: ignore + ContextWindowExceededError = Exception # type: ignore + get_supported_openai_params = None # type: ignore + ChatCompletionDeltaToolCall = None # type: ignore + ModelResponse = None # type: ignore + supports_response_schema = None # type: ignore + + load_dotenv() -litellm.suppress_debug_info = True +if LITELLM_AVAILABLE: + litellm.suppress_debug_info = True class FilteredStream(io.TextIOBase): @@ -275,6 +298,77 @@ class AccumulatedToolArgs(BaseModel): class LLM(BaseLLM): completion_cost: float | None = None + def __new__(cls, model: str, is_litellm: bool = False, **kwargs) -> "LLM": + """Factory method that routes to native SDK or falls back to LiteLLM.""" + if not model or not isinstance(model, str): + raise ValueError("Model must be a non-empty string") + + provider = model.partition("/")[0] if "/" in model else "openai" + + native_class = cls._get_native_provider(provider) + if native_class and not is_litellm: + try: + model_string = model.partition("/")[2] if "/" in model else model + return native_class(model=model_string, provider=provider, **kwargs) + except Exception as e: + import logging + + logger = logging.getLogger(__name__) + logger.warning( + f"Native SDK failed for {provider}: {e}, falling back to LiteLLM" + ) + + # FALLBACK to LiteLLM + if not LITELLM_AVAILABLE: + raise ImportError( + "Please install the required dependencies:\n" + "- For LiteLLM: uv add litellm" + ) + + instance = object.__new__(cls) + super(LLM, instance).__init__(model=model, is_litellm=True, **kwargs) + instance.is_litellm = True + return instance + + @classmethod + def _get_native_provider(cls, provider: str) -> type | None: + """Get native provider class if available.""" + if provider == "openai": + try: + from crewai.llms.providers.openai.completion import OpenAICompletion + + return OpenAICompletion + except ImportError: + return None + + elif provider == "anthropic" or provider == "claude": + try: + from crewai.llms.providers.anthropic.completion import ( + AnthropicCompletion, + ) + + return AnthropicCompletion + except ImportError: + return None + + elif provider == "azure": + try: + from crewai.llms.providers.azure.completion import AzureCompletion + + return AzureCompletion + except ImportError: + return None + + elif provider == "google" or provider == "gemini": + try: + from crewai.llms.providers.gemini.completion import GeminiCompletion + + return GeminiCompletion + except ImportError: + return None + + return None + def __init__( self, model: str, @@ -284,7 +378,7 @@ class LLM(BaseLLM): n: int | None = None, stop: str | list[str] | None = None, max_completion_tokens: int | None = None, - max_tokens: int | None = None, + max_tokens: int | float | None = None, presence_penalty: float | None = None, frequency_penalty: float | None = None, logit_bias: dict[int, float] | None = None, @@ -301,6 +395,11 @@ class LLM(BaseLLM): stream: bool = False, **kwargs, ): + """Initialize LLM instance. + + Note: This __init__ method is only called for fallback instances. + Native provider instances handle their own initialization in their respective classes. + """ self.model = model self.timeout = timeout self.temperature = temperature @@ -328,7 +427,7 @@ class LLM(BaseLLM): litellm.drop_params = True - # Normalize self.stop to always be a List[str] + # Normalize self.stop to always be a list[str] if stop is None: self.stop: list[str] = [] elif isinstance(stop, str): @@ -349,7 +448,8 @@ class LLM(BaseLLM): Returns: bool: True if the model is from Anthropic, False otherwise. """ - return any(prefix in model.lower() for prefix in ANTHROPIC_PREFIXES) + anthropic_prefixes = ("anthropic/", "claude-", "claude/") + return any(prefix in model.lower() for prefix in anthropic_prefixes) def _prepare_completion_params( self, @@ -514,10 +614,6 @@ class LLM(BaseLLM): # Add the chunk content to the full response full_response += chunk_content - # Emit the chunk event - if not hasattr(crewai_event_bus, "emit"): - raise Exception("crewai_event_bus must have an `emit` method") - crewai_event_bus.emit( self, event=LLMStreamChunkEvent( @@ -623,7 +719,9 @@ class LLM(BaseLLM): # --- 8) If no tool calls or no available functions, return the text response directly if not tool_calls or not available_functions: - # Log token usage if available in streaming mode + # Track token usage and log callbacks if available in streaming mode + if usage_info: + self._track_token_usage_internal(usage_info) self._handle_streaming_callbacks(callbacks, usage_info, last_chunk) # Emit completion event and return response self._handle_emit_call_events( @@ -640,7 +738,9 @@ class LLM(BaseLLM): if tool_result is not None: return tool_result - # --- 10) Log token usage if available in streaming mode + # --- 10) Track token usage and log callbacks if available in streaming mode + if usage_info: + self._track_token_usage_internal(usage_info) self._handle_streaming_callbacks(callbacks, usage_info, last_chunk) # --- 11) Emit completion event and return response @@ -671,11 +771,6 @@ class LLM(BaseLLM): ) return full_response - # Emit failed event and re-raise the exception - if not hasattr(crewai_event_bus, "emit"): - raise AttributeError( - "crewai_event_bus must have an 'emit' method" - ) from e crewai_event_bus.emit( self, event=LLMCallFailedEvent( @@ -702,8 +797,7 @@ class LLM(BaseLLM): current_tool_accumulator.function.arguments += ( tool_call.function.arguments ) - if not hasattr(crewai_event_bus, "emit"): - raise AttributeError("crewai_event_bus must have an 'emit' method") + crewai_event_bus.emit( self, event=LLMStreamChunkEvent( @@ -832,6 +926,7 @@ class LLM(BaseLLM): messages=params["messages"], ) return text_response + # --- 6) If there is no text response, no available functions, but there are tool calls, return the tool calls if tool_calls and not available_functions and not text_response: return tool_calls @@ -886,9 +981,6 @@ class LLM(BaseLLM): function_args = json.loads(tool_call.function.arguments) fn = available_functions[function_name] - # --- 3.2) Execute function - if not hasattr(crewai_event_bus, "emit"): - raise AttributeError("crewai_event_bus must have an 'emit' method") started_at = datetime.now() crewai_event_bus.emit( self, @@ -928,10 +1020,6 @@ class LLM(BaseLLM): function_name, lambda: None ) # Ensure fn is always a callable logging.error(f"Error executing function '{function_name}': {e}") - if not hasattr(crewai_event_bus, "emit"): - raise AttributeError( - "crewai_event_bus must have an 'emit' method" - ) from e crewai_event_bus.emit( self, event=LLMCallFailedEvent(error=f"Tool execution error: {e!s}"), @@ -982,9 +1070,6 @@ class LLM(BaseLLM): ValueError: If response format is not supported LLMContextLengthExceededError: If input exceeds model's context limit """ - # --- 1) Emit call started event - if not hasattr(crewai_event_bus, "emit"): - raise AttributeError("crewai_event_bus must have an 'emit' method") crewai_event_bus.emit( self, event=LLMCallStartedEvent( @@ -1021,10 +1106,10 @@ class LLM(BaseLLM): return self._handle_streaming_response( params, callbacks, available_functions, from_task, from_agent ) + return self._handle_non_streaming_response( params, callbacks, available_functions, from_task, from_agent ) - except LLMContextLengthExceededError: # Re-raise LLMContextLengthExceededError as it should be handled # by the CrewAgentExecutor._invoke_loop method, which can then decide @@ -1057,10 +1142,6 @@ class LLM(BaseLLM): from_agent=from_agent, ) - if not hasattr(crewai_event_bus, "emit"): - raise AttributeError( - "crewai_event_bus must have an 'emit' method" - ) from e crewai_event_bus.emit( self, event=LLMCallFailedEvent( @@ -1086,8 +1167,6 @@ class LLM(BaseLLM): from_agent: Optional agent object messages: Optional messages object """ - if not hasattr(crewai_event_bus, "emit"): - raise AttributeError("crewai_event_bus must have an 'emit' method") crewai_event_bus.emit( self, event=LLMCallCompletedEvent( @@ -1225,11 +1304,14 @@ class LLM(BaseLLM): if self.context_window_size != 0: return self.context_window_size + min_context = 1024 + max_context = 2097152 # Current max from gemini-1.5-pro + # Validate all context window sizes for key, value in LLM_CONTEXT_WINDOW_SIZES.items(): - if value < MIN_CONTEXT or value > MAX_CONTEXT: + if value < min_context or value > max_context: raise ValueError( - f"Context window for {key} must be between {MIN_CONTEXT} and {MAX_CONTEXT}" + f"Context window for {key} must be between {min_context} and {max_context}" ) self.context_window_size = int( @@ -1293,3 +1375,129 @@ class LLM(BaseLLM): litellm.success_callback = success_callbacks litellm.failure_callback = failure_callbacks + + def __copy__(self): + """Create a shallow copy of the LLM instance.""" + # Filter out parameters that are already explicitly passed to avoid conflicts + filtered_params = { + k: v + for k, v in self.additional_params.items() + if k + not in [ + "model", + "is_litellm", + "temperature", + "top_p", + "n", + "max_completion_tokens", + "max_tokens", + "presence_penalty", + "frequency_penalty", + "logit_bias", + "response_format", + "seed", + "logprobs", + "top_logprobs", + "base_url", + "api_base", + "api_version", + "api_key", + "callbacks", + "reasoning_effort", + "stream", + "stop", + ] + } + + # Create a new instance with the same parameters + return LLM( + model=self.model, + is_litellm=self.is_litellm, + temperature=self.temperature, + top_p=self.top_p, + n=self.n, + max_completion_tokens=self.max_completion_tokens, + max_tokens=self.max_tokens, + presence_penalty=self.presence_penalty, + frequency_penalty=self.frequency_penalty, + logit_bias=self.logit_bias, + response_format=self.response_format, + seed=self.seed, + logprobs=self.logprobs, + top_logprobs=self.top_logprobs, + base_url=self.base_url, + api_base=self.api_base, + api_version=self.api_version, + api_key=self.api_key, + callbacks=self.callbacks, + reasoning_effort=self.reasoning_effort, + stream=self.stream, + stop=self.stop, + **filtered_params, + ) + + def __deepcopy__(self, memo): + """Create a deep copy of the LLM instance.""" + import copy + + # Filter out parameters that are already explicitly passed to avoid conflicts + filtered_params = { + k: copy.deepcopy(v, memo) + for k, v in self.additional_params.items() + if k + not in [ + "model", + "is_litellm", + "temperature", + "top_p", + "n", + "max_completion_tokens", + "max_tokens", + "presence_penalty", + "frequency_penalty", + "logit_bias", + "response_format", + "seed", + "logprobs", + "top_logprobs", + "base_url", + "api_base", + "api_version", + "api_key", + "callbacks", + "reasoning_effort", + "stream", + "stop", + ] + } + + # Create a new instance with the same parameters + return LLM( + model=self.model, + is_litellm=self.is_litellm, + temperature=self.temperature, + top_p=self.top_p, + n=self.n, + max_completion_tokens=self.max_completion_tokens, + max_tokens=self.max_tokens, + presence_penalty=self.presence_penalty, + frequency_penalty=self.frequency_penalty, + logit_bias=copy.deepcopy(self.logit_bias, memo) + if self.logit_bias + else None, + response_format=copy.deepcopy(self.response_format, memo) + if self.response_format + else None, + seed=self.seed, + logprobs=self.logprobs, + top_logprobs=self.top_logprobs, + base_url=self.base_url, + api_base=self.api_base, + api_version=self.api_version, + api_key=self.api_key, + callbacks=copy.deepcopy(self.callbacks, memo) if self.callbacks else None, + reasoning_effort=self.reasoning_effort, + stream=self.stream, + stop=copy.deepcopy(self.stop, memo) if self.stop else None, + **filtered_params, + ) diff --git a/lib/crewai/src/crewai/llms/base_llm.py b/lib/crewai/src/crewai/llms/base_llm.py index 0cd95c347..8c230b772 100644 --- a/lib/crewai/src/crewai/llms/base_llm.py +++ b/lib/crewai/src/crewai/llms/base_llm.py @@ -1,12 +1,33 @@ """Base LLM abstract class for CrewAI. This module provides the abstract base class for all LLM implementations -in CrewAI. +in CrewAI, including common functionality for native SDK implementations. """ from abc import ABC, abstractmethod +from datetime import datetime +import json +import logging from typing import Any, Final +from pydantic import BaseModel + +from crewai.events.event_bus import crewai_event_bus +from crewai.events.types.llm_events import ( + LLMCallCompletedEvent, + LLMCallFailedEvent, + LLMCallStartedEvent, + LLMCallType, + LLMStreamChunkEvent, +) +from crewai.events.types.tool_usage_events import ( + ToolUsageErrorEvent, + ToolUsageFinishedEvent, + ToolUsageStartedEvent, +) +from crewai.types.usage_metrics import UsageMetrics + + DEFAULT_CONTEXT_WINDOW_SIZE: Final[int] = 4096 DEFAULT_SUPPORTS_STOP_WORDS: Final[bool] = True @@ -27,13 +48,20 @@ class BaseLLM(ABC): model: The model identifier/name. temperature: Optional temperature setting for response generation. stop: A list of stop sequences that the LLM should use to stop generation. + additional_params: Additional provider-specific parameters. """ + is_litellm: bool = False + def __init__( self, model: str, temperature: float | None = None, - stop: list[str] | None = None, + api_key: str | None = None, + base_url: str | None = None, + timeout: float | None = None, + provider: str | None = None, + **kwargs, ) -> None: """Initialize the BaseLLM with default attributes. @@ -41,10 +69,44 @@ class BaseLLM(ABC): model: The model identifier/name. temperature: Optional temperature setting for response generation. stop: Optional list of stop sequences for generation. + **kwargs: Additional provider-specific parameters. """ + if not model: + raise ValueError("Model name is required and cannot be empty") + self.model = model self.temperature = temperature - self.stop: list[str] = stop or [] + self.api_key = api_key + self.base_url = base_url + # Store additional parameters for provider-specific use + self.additional_params = kwargs + self._provider = provider or "openai" + + stop = kwargs.pop("stop", None) + if stop is None: + self.stop: list[str] = [] + elif isinstance(stop, str): + self.stop = [stop] + else: + self.stop = stop + + self._token_usage = { + "total_tokens": 0, + "prompt_tokens": 0, + "completion_tokens": 0, + "successful_requests": 0, + "cached_prompt_tokens": 0, + } + + @property + def provider(self) -> str: + """Get the provider of the LLM.""" + return self._provider + + @provider.setter + def provider(self, value: str) -> None: + """Set the provider of the LLM.""" + self._provider = value @abstractmethod def call( @@ -82,6 +144,17 @@ class BaseLLM(ABC): RuntimeError: If the LLM request fails for other reasons. """ + def _convert_tools_for_interference(self, tools: list[dict]) -> list[dict]: + """Convert tools to a format that can be used for interference. + + Args: + tools: List of tools to convert. + + Returns: + List of converted tools (default implementation returns as-is) + """ + return tools + def supports_stop_words(self) -> bool: """Check if the LLM supports stop words. @@ -90,6 +163,58 @@ class BaseLLM(ABC): """ return DEFAULT_SUPPORTS_STOP_WORDS + def _supports_stop_words_implementation(self) -> bool: + """Check if stop words are configured for this LLM instance. + + Native providers can override supports_stop_words() to return this value + to ensure consistent behavior based on whether stop words are actually configured. + + Returns: + True if stop words are configured and can be applied + """ + return bool(self.stop) + + def _apply_stop_words(self, content: str) -> str: + """Apply stop words to truncate response content. + + This method provides consistent stop word behavior across all native SDK providers. + Native providers should call this method to post-process their responses. + + Args: + content: The raw response content from the LLM + + Returns: + Content truncated at the first occurrence of any stop word + + Example: + >>> llm = MyNativeLLM(stop=["Observation:", "Final Answer:"]) + >>> response = "I need to search.\\n\\nAction: search\\nObservation: Found results" + >>> llm._apply_stop_words(response) + "I need to search.\\n\\nAction: search" + """ + if not self.stop or not content: + return content + + # Find the earliest occurrence of any stop word + earliest_stop_pos = len(content) + found_stop_word = None + + for stop_word in self.stop: + stop_pos = content.find(stop_word) + if stop_pos != -1 and stop_pos < earliest_stop_pos: + earliest_stop_pos = stop_pos + found_stop_word = stop_word + + # Truncate at the stop word if found + if found_stop_word is not None: + truncated = content[:earliest_stop_pos].strip() + logging.debug( + f"Applied stop word '{found_stop_word}' at position {earliest_stop_pos}" + ) + return truncated + + return content + def get_context_window_size(self) -> int: """Get the context window size for the LLM. @@ -98,3 +223,314 @@ class BaseLLM(ABC): """ # Default implementation - subclasses should override with model-specific values return DEFAULT_CONTEXT_WINDOW_SIZE + + # Common helper methods for native SDK implementations + + def _emit_call_started_event( + self, + messages: str | list[dict[str, str]], + tools: list[dict] | None = None, + callbacks: list[Any] | None = None, + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> None: + """Emit LLM call started event.""" + if not hasattr(crewai_event_bus, "emit"): + raise ValueError("crewai_event_bus does not have an emit method") from None + + crewai_event_bus.emit( + self, + event=LLMCallStartedEvent( + messages=messages, + tools=tools, + callbacks=callbacks, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + model=self.model, + ), + ) + + def _emit_call_completed_event( + self, + response: Any, + call_type: LLMCallType, + from_task: Any | None = None, + from_agent: Any | None = None, + messages: str | list[dict[str, Any]] | None = None, + ) -> None: + """Emit LLM call completed event.""" + crewai_event_bus.emit( + self, + event=LLMCallCompletedEvent( + messages=messages, + response=response, + call_type=call_type, + from_task=from_task, + from_agent=from_agent, + model=self.model, + ), + ) + + def _emit_call_failed_event( + self, + error: str, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> None: + """Emit LLM call failed event.""" + if not hasattr(crewai_event_bus, "emit"): + raise ValueError("crewai_event_bus does not have an emit method") from None + + crewai_event_bus.emit( + self, + event=LLMCallFailedEvent( + error=error, + from_task=from_task, + from_agent=from_agent, + ), + ) + + def _emit_stream_chunk_event( + self, + chunk: str, + from_task: Any | None = None, + from_agent: Any | None = None, + tool_call: dict[str, Any] | None = None, + ) -> None: + """Emit stream chunk event.""" + if not hasattr(crewai_event_bus, "emit"): + raise ValueError("crewai_event_bus does not have an emit method") from None + + crewai_event_bus.emit( + self, + event=LLMStreamChunkEvent( + chunk=chunk, + tool_call=tool_call, + from_task=from_task, + from_agent=from_agent, + ), + ) + + def _handle_tool_execution( + self, + function_name: str, + function_args: dict[str, Any], + available_functions: dict[str, Any], + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | None: + """Handle tool execution with proper event emission. + + Args: + function_name: Name of the function to execute + function_args: Arguments to pass to the function + available_functions: Dict of available functions + from_task: Optional task object + from_agent: Optional agent object + + Returns: + Result of function execution or None if function not found + """ + if function_name not in available_functions: + logging.warning( + f"Function '{function_name}' not found in available functions" + ) + return None + + try: + # Emit tool usage started event + started_at = datetime.now() + + crewai_event_bus.emit( + self, + event=ToolUsageStartedEvent( + tool_name=function_name, + tool_args=function_args, + from_agent=from_agent, + from_task=from_task, + ), + ) + + # Execute the function + fn = available_functions[function_name] + result = fn(**function_args) + + # Emit tool usage finished event + crewai_event_bus.emit( + self, + event=ToolUsageFinishedEvent( + output=result, + tool_name=function_name, + tool_args=function_args, + started_at=started_at, + finished_at=datetime.now(), + from_task=from_task, + from_agent=from_agent, + ), + ) + + # Emit LLM call completed event for tool call + self._emit_call_completed_event( + response=result, + call_type=LLMCallType.TOOL_CALL, + from_task=from_task, + from_agent=from_agent, + ) + + return str(result) + + except Exception as e: + error_msg = f"Error executing function '{function_name}': {e!s}" + logging.error(error_msg) + + # Emit tool usage error event + if not hasattr(crewai_event_bus, "emit"): + raise ValueError( + "crewai_event_bus does not have an emit method" + ) from None + + crewai_event_bus.emit( + self, + event=ToolUsageErrorEvent( + tool_name=function_name, + tool_args=function_args, + error=error_msg, + from_task=from_task, + from_agent=from_agent, + ), + ) + + # Emit LLM call failed event + self._emit_call_failed_event( + error=error_msg, + from_task=from_task, + from_agent=from_agent, + ) + + return None + + def _format_messages( + self, messages: str | list[dict[str, str]] + ) -> list[dict[str, str]]: + """Convert messages to standard format. + + Args: + messages: Input messages (string or list of message dicts) + + Returns: + List of message dictionaries with 'role' and 'content' keys + + Raises: + ValueError: If message format is invalid + """ + if isinstance(messages, str): + return [{"role": "user", "content": messages}] + + # Validate message format + for i, msg in enumerate(messages): + if not isinstance(msg, dict): + raise ValueError(f"Message at index {i} must be a dictionary") + if "role" not in msg or "content" not in msg: + raise ValueError( + f"Message at index {i} must have 'role' and 'content' keys" + ) + + return messages + + def _validate_structured_output( + self, + response: str, + response_format: type[BaseModel] | None, + ) -> str | BaseModel: + """Validate and parse structured output. + + Args: + response: Raw response string + response_format: Optional Pydantic model for structured output + + Returns: + Parsed response (BaseModel instance if response_format provided, otherwise string) + + Raises: + ValueError: If structured output validation fails + """ + if response_format is None: + return response + + try: + # Try to parse as JSON first + if response.strip().startswith("{") or response.strip().startswith("["): + data = json.loads(response) + return response_format.model_validate(data) + + # Try to extract JSON from response + import re + + json_match = re.search(r"\{.*\}", response, re.DOTALL) + if json_match: + data = json.loads(json_match.group()) + return response_format.model_validate(data) + + raise ValueError("No JSON found in response") + + except (json.JSONDecodeError, ValueError) as e: + logging.warning(f"Failed to parse structured output: {e}") + raise ValueError( + f"Failed to parse response into {response_format.__name__}: {e}" + ) from e + + def _extract_provider(self, model: str) -> str: + """Extract provider from model string. + + Args: + model: Model string (e.g., 'openai/gpt-4' or 'gpt-4') + + Returns: + Provider name (e.g., 'openai') + """ + if "/" in model: + return model.partition("/")[0] + return "openai" # Default provider + + def _track_token_usage_internal(self, usage_data: dict[str, Any]) -> None: + """Track token usage internally in the LLM instance. + + Args: + usage_data: Token usage data from the API response + """ + # Extract tokens in a provider-agnostic way + prompt_tokens = ( + usage_data.get("prompt_tokens") + or usage_data.get("prompt_token_count") + or usage_data.get("input_tokens") + or 0 + ) + + completion_tokens = ( + usage_data.get("completion_tokens") + or usage_data.get("candidates_token_count") + or usage_data.get("output_tokens") + or 0 + ) + + cached_tokens = ( + usage_data.get("cached_tokens") + or usage_data.get("cached_prompt_tokens") + or 0 + ) + + self._token_usage["prompt_tokens"] += prompt_tokens + self._token_usage["completion_tokens"] += completion_tokens + self._token_usage["total_tokens"] += prompt_tokens + completion_tokens + self._token_usage["successful_requests"] += 1 + self._token_usage["cached_prompt_tokens"] += cached_tokens + + def get_token_usage_summary(self) -> UsageMetrics: + """Get summary of token usage for this LLM instance. + + Returns: + Dictionary with token usage totals + """ + return UsageMetrics(**self._token_usage) diff --git a/lib/crewai/src/crewai/llms/providers/__init__.py b/lib/crewai/src/crewai/llms/providers/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/lib/crewai/src/crewai/llms/providers/anthropic/completion.py b/lib/crewai/src/crewai/llms/providers/anthropic/completion.py new file mode 100644 index 000000000..691490dd2 --- /dev/null +++ b/lib/crewai/src/crewai/llms/providers/anthropic/completion.py @@ -0,0 +1,432 @@ +import json +import logging +import os +from typing import Any + +from crewai.events.types.llm_events import LLMCallType +from crewai.llms.base_llm import BaseLLM +from crewai.utilities.agent_utils import is_context_length_exceeded +from crewai.utilities.exceptions.context_window_exceeding_exception import ( + LLMContextLengthExceededError, +) + + +try: + from anthropic import Anthropic + from anthropic.types import Message + from anthropic.types.tool_use_block import ToolUseBlock +except ImportError: + raise ImportError( + "Anthropic native provider not available, to install: `uv add anthropic`" + ) from None + + +class AnthropicCompletion(BaseLLM): + """Anthropic native completion implementation. + + This class provides direct integration with the Anthropic Python SDK, + offering native tool use, streaming support, and proper message formatting. + """ + + def __init__( + self, + model: str = "claude-3-5-sonnet-20241022", + api_key: str | None = None, + base_url: str | None = None, + timeout: float | None = None, + max_retries: int = 2, + temperature: float | None = None, + max_tokens: int = 4096, # Required for Anthropic + top_p: float | None = None, + stop_sequences: list[str] | None = None, + stream: bool = False, + **kwargs, + ): + """Initialize Anthropic chat completion client. + + Args: + model: Anthropic model name (e.g., 'claude-3-5-sonnet-20241022') + api_key: Anthropic API key (defaults to ANTHROPIC_API_KEY env var) + base_url: Custom base URL for Anthropic API + timeout: Request timeout in seconds + max_retries: Maximum number of retries + temperature: Sampling temperature (0-1) + max_tokens: Maximum tokens in response (required for Anthropic) + top_p: Nucleus sampling parameter + stop_sequences: Stop sequences (Anthropic uses stop_sequences, not stop) + stream: Enable streaming responses + **kwargs: Additional parameters + """ + super().__init__( + model=model, temperature=temperature, stop=stop_sequences or [], **kwargs + ) + + # Initialize Anthropic client + self.client = Anthropic( + api_key=api_key or os.getenv("ANTHROPIC_API_KEY"), + base_url=base_url, + timeout=timeout, + max_retries=max_retries, + ) + + # Store completion parameters + self.max_tokens = max_tokens + self.top_p = top_p + self.stream = stream + self.stop_sequences = stop_sequences or [] + + # Model-specific settings + self.is_claude_3 = "claude-3" in model.lower() + self.supports_tools = self.is_claude_3 # Claude 3+ supports tool use + + def call( + self, + messages: str | list[dict[str, str]], + tools: list[dict] | None = None, + callbacks: list[Any] | None = None, + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | Any: + """Call Anthropic messages API. + + Args: + messages: Input messages for the chat completion + tools: List of tool/function definitions + callbacks: Callback functions (not used in native implementation) + available_functions: Available functions for tool calling + from_task: Task that initiated the call + from_agent: Agent that initiated the call + + Returns: + Chat completion response or tool call result + """ + try: + # Emit call started event + self._emit_call_started_event( + messages=messages, + tools=tools, + callbacks=callbacks, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + # Format messages for Anthropic + formatted_messages, system_message = self._format_messages_for_anthropic( + messages + ) + + # Prepare completion parameters + completion_params = self._prepare_completion_params( + formatted_messages, system_message, tools + ) + + # Handle streaming vs non-streaming + if self.stream: + return self._handle_streaming_completion( + completion_params, available_functions, from_task, from_agent + ) + + return self._handle_completion( + completion_params, available_functions, from_task, from_agent + ) + + except Exception as e: + error_msg = f"Anthropic API call failed: {e!s}" + logging.error(error_msg) + self._emit_call_failed_event( + error=error_msg, from_task=from_task, from_agent=from_agent + ) + raise + + def _prepare_completion_params( + self, + messages: list[dict[str, str]], + system_message: str | None = None, + tools: list[dict] | None = None, + ) -> dict[str, Any]: + """Prepare parameters for Anthropic messages API. + + Args: + messages: Formatted messages for Anthropic + system_message: Extracted system message + tools: Tool definitions + + Returns: + Parameters dictionary for Anthropic API + """ + params = { + "model": self.model, + "messages": messages, + "max_tokens": self.max_tokens, + "stream": self.stream, + } + + # Add system message if present + if system_message: + params["system"] = system_message + + # Add optional parameters if set + if self.temperature is not None: + params["temperature"] = self.temperature + if self.top_p is not None: + params["top_p"] = self.top_p + if self.stop_sequences: + params["stop_sequences"] = self.stop_sequences + + # Handle tools for Claude 3+ + if tools and self.supports_tools: + params["tools"] = self._convert_tools_for_interference(tools) + + return params + + def _convert_tools_for_interference(self, tools: list[dict]) -> list[dict]: + """Convert CrewAI tool format to Anthropic tool use format.""" + from crewai.llms.providers.utils.common import safe_tool_conversion + + anthropic_tools = [] + + for tool in tools: + name, description, parameters = safe_tool_conversion(tool, "Anthropic") + + anthropic_tool = { + "name": name, + "description": description, + } + + if parameters and isinstance(parameters, dict): + anthropic_tool["input_schema"] = parameters # type: ignore + + anthropic_tools.append(anthropic_tool) + + return anthropic_tools + + def _format_messages_for_anthropic( + self, messages: str | list[dict[str, str]] + ) -> tuple[list[dict[str, str]], str | None]: + """Format messages for Anthropic API. + + Anthropic has specific requirements: + - System messages are separate from conversation messages + - Messages must alternate between user and assistant + - First message must be from user + + Args: + messages: Input messages + + Returns: + Tuple of (formatted_messages, system_message) + """ + # Use base class formatting first + base_formatted = super()._format_messages(messages) + + formatted_messages = [] + system_message = None + + for message in base_formatted: + role = message.get("role") + content = message.get("content", "") + + if role == "system": + # Extract system message - Anthropic handles it separately + if system_message: + system_message += f"\n\n{content}" + else: + system_message = content + else: + # Add user/assistant messages - ensure both role and content are str, not None + role_str = role if role is not None else "user" + content_str = content if content is not None else "" + formatted_messages.append({"role": role_str, "content": content_str}) + + # Ensure first message is from user (Anthropic requirement) + if not formatted_messages: + # If no messages, add a default user message + formatted_messages.append({"role": "user", "content": "Hello"}) + elif formatted_messages[0]["role"] != "user": + # If first message is not from user, insert a user message at the beginning + formatted_messages.insert(0, {"role": "user", "content": "Hello"}) + + return formatted_messages, system_message + + def _handle_completion( + self, + params: dict[str, Any], + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | Any: + """Handle non-streaming message completion.""" + try: + response: Message = self.client.messages.create(**params) + + except Exception as e: + if is_context_length_exceeded(e): + logging.error(f"Context window exceeded: {e}") + raise LLMContextLengthExceededError(str(e)) from e + raise e from e + + usage = self._extract_anthropic_token_usage(response) + self._track_token_usage_internal(usage) + + if response.content and available_functions: + for content_block in response.content: + if isinstance(content_block, ToolUseBlock): + function_name = content_block.name + function_args = content_block.input + + result = self._handle_tool_execution( + function_name=function_name, + function_args=function_args, # type: ignore + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + if result is not None: + return result + + # Extract text content + content = "" + if response.content: + for content_block in response.content: + if hasattr(content_block, "text"): + content += content_block.text + + content = self._apply_stop_words(content) + + self._emit_call_completed_event( + response=content, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=params["messages"], + ) + + if usage.get("total_tokens", 0) > 0: + logging.info(f"Anthropic API usage: {usage}") + + return content + + def _handle_streaming_completion( + self, + params: dict[str, Any], + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str: + """Handle streaming message completion.""" + full_response = "" + tool_uses = {} + + # Make streaming API call + with self.client.messages.stream(**params) as stream: + for event in stream: + # Handle content delta events + if hasattr(event, "delta") and hasattr(event.delta, "text"): + text_delta = event.delta.text + full_response += text_delta + self._emit_stream_chunk_event( + chunk=text_delta, + from_task=from_task, + from_agent=from_agent, + ) + + # Handle tool use events + elif hasattr(event, "delta") and hasattr(event.delta, "partial_json"): + # Tool use streaming - accumulate JSON + tool_id = getattr(event, "index", "default") + if tool_id not in tool_uses: + tool_uses[tool_id] = { + "name": "", + "input": "", + } + + if hasattr(event.delta, "name"): + tool_uses[tool_id]["name"] = event.delta.name + if hasattr(event.delta, "partial_json"): + tool_uses[tool_id]["input"] += event.delta.partial_json + + # Handle completed tool uses + if tool_uses and available_functions: + for tool_data in tool_uses.values(): + function_name = tool_data["name"] + + try: + function_args = json.loads(tool_data["input"]) + except json.JSONDecodeError as e: + logging.error(f"Failed to parse streamed tool arguments: {e}") + continue + + # Execute tool + result = self._handle_tool_execution( + function_name=function_name, + function_args=function_args, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + if result is not None: + return result + + # Apply stop words to full response + full_response = self._apply_stop_words(full_response) + + # Emit completion event and return full response + self._emit_call_completed_event( + response=full_response, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=params["messages"], + ) + + return full_response + + def supports_function_calling(self) -> bool: + """Check if the model supports function calling.""" + return self.supports_tools + + def supports_stop_words(self) -> bool: + """Check if the model supports stop words.""" + return True # All Claude models support stop sequences + + def get_context_window_size(self) -> int: + """Get the context window size for the model.""" + from crewai.llm import CONTEXT_WINDOW_USAGE_RATIO + + # Context window sizes for Anthropic models + context_windows = { + "claude-3-5-sonnet": 200000, + "claude-3-5-haiku": 200000, + "claude-3-opus": 200000, + "claude-3-sonnet": 200000, + "claude-3-haiku": 200000, + "claude-3-7-sonnet": 200000, + "claude-2.1": 200000, + "claude-2": 100000, + "claude-instant": 100000, + } + + # Find the best match for the model name + for model_prefix, size in context_windows.items(): + if self.model.startswith(model_prefix): + return int(size * CONTEXT_WINDOW_USAGE_RATIO) + + # Default context window size for Claude models + return int(200000 * CONTEXT_WINDOW_USAGE_RATIO) + + def _extract_anthropic_token_usage(self, response: Message) -> dict[str, Any]: + """Extract token usage from Anthropic response.""" + if hasattr(response, "usage") and response.usage: + usage = response.usage + input_tokens = getattr(usage, "input_tokens", 0) + output_tokens = getattr(usage, "output_tokens", 0) + return { + "input_tokens": input_tokens, + "output_tokens": output_tokens, + "total_tokens": input_tokens + output_tokens, + } + return {"total_tokens": 0} diff --git a/lib/crewai/src/crewai/llms/providers/azure/completion.py b/lib/crewai/src/crewai/llms/providers/azure/completion.py new file mode 100644 index 000000000..549e2b70b --- /dev/null +++ b/lib/crewai/src/crewai/llms/providers/azure/completion.py @@ -0,0 +1,473 @@ +import json +import logging +import os +from typing import Any + +from crewai.utilities.agent_utils import is_context_length_exceeded +from crewai.utilities.exceptions.context_window_exceeding_exception import ( + LLMContextLengthExceededError, +) + + +try: + from azure.ai.inference import ChatCompletionsClient # type: ignore + from azure.ai.inference.models import ( # type: ignore + ChatCompletions, + ChatCompletionsToolCall, + StreamingChatCompletionsUpdate, + ) + from azure.core.credentials import AzureKeyCredential # type: ignore + from azure.core.exceptions import HttpResponseError # type: ignore + from crewai.events.types.llm_events import LLMCallType + from crewai.llms.base_llm import BaseLLM + +except ImportError: + raise ImportError( + "Azure AI Inference native provider not available, to install: `uv add azure-ai-inference`" + ) from None + + +class AzureCompletion(BaseLLM): + """Azure AI Inference native completion implementation. + + This class provides direct integration with the Azure AI Inference Python SDK, + offering native function calling, streaming support, and proper Azure authentication. + """ + + def __init__( + self, + model: str, + api_key: str | None = None, + endpoint: str | None = None, + api_version: str | None = None, + timeout: float | None = None, + max_retries: int = 2, + temperature: float | None = None, + top_p: float | None = None, + frequency_penalty: float | None = None, + presence_penalty: float | None = None, + max_tokens: int | None = None, + stop: list[str] | None = None, + stream: bool = False, + **kwargs, + ): + """Initialize Azure AI Inference chat completion client. + + Args: + model: Azure deployment name or model name + api_key: Azure API key (defaults to AZURE_API_KEY env var) + endpoint: Azure endpoint URL (defaults to AZURE_ENDPOINT env var) + api_version: Azure API version (defaults to AZURE_API_VERSION env var) + timeout: Request timeout in seconds + max_retries: Maximum number of retries + temperature: Sampling temperature (0-2) + top_p: Nucleus sampling parameter + frequency_penalty: Frequency penalty (-2 to 2) + presence_penalty: Presence penalty (-2 to 2) + max_tokens: Maximum tokens in response + stop: Stop sequences + stream: Enable streaming responses + **kwargs: Additional parameters + """ + super().__init__( + model=model, temperature=temperature, stop=stop or [], **kwargs + ) + + self.api_key = api_key or os.getenv("AZURE_API_KEY") + self.endpoint = ( + endpoint + or os.getenv("AZURE_ENDPOINT") + or os.getenv("AZURE_OPENAI_ENDPOINT") + or os.getenv("AZURE_API_BASE") + ) + self.api_version = api_version or os.getenv("AZURE_API_VERSION") or "2024-02-01" + + if not self.api_key: + raise ValueError( + "Azure API key is required. Set AZURE_API_KEY environment variable or pass api_key parameter." + ) + if not self.endpoint: + raise ValueError( + "Azure endpoint is required. Set AZURE_ENDPOINT environment variable or pass endpoint parameter." + ) + + self.client = ChatCompletionsClient( + endpoint=self.endpoint, + credential=AzureKeyCredential(self.api_key), + ) + + self.top_p = top_p + self.frequency_penalty = frequency_penalty + self.presence_penalty = presence_penalty + self.max_tokens = max_tokens + self.stream = stream + + self.is_openai_model = any( + prefix in model.lower() for prefix in ["gpt-", "o1-", "text-"] + ) + + def call( + self, + messages: str | list[dict[str, str]], + tools: list[dict] | None = None, + callbacks: list[Any] | None = None, + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | Any: + """Call Azure AI Inference chat completions API. + + Args: + messages: Input messages for the chat completion + tools: List of tool/function definitions + callbacks: Callback functions (not used in native implementation) + available_functions: Available functions for tool calling + from_task: Task that initiated the call + from_agent: Agent that initiated the call + + Returns: + Chat completion response or tool call result + """ + try: + # Emit call started event + self._emit_call_started_event( + messages=messages, + tools=tools, + callbacks=callbacks, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + # Format messages for Azure + formatted_messages = self._format_messages_for_azure(messages) + + # Prepare completion parameters + completion_params = self._prepare_completion_params( + formatted_messages, tools + ) + + # Handle streaming vs non-streaming + if self.stream: + return self._handle_streaming_completion( + completion_params, available_functions, from_task, from_agent + ) + + return self._handle_completion( + completion_params, available_functions, from_task, from_agent + ) + + except HttpResponseError as e: + error_msg = f"Azure API HTTP error: {e.status_code} - {e.message}" + logging.error(error_msg) + self._emit_call_failed_event( + error=error_msg, from_task=from_task, from_agent=from_agent + ) + raise + except Exception as e: + error_msg = f"Azure API call failed: {e!s}" + logging.error(error_msg) + self._emit_call_failed_event( + error=error_msg, from_task=from_task, from_agent=from_agent + ) + raise + + def _prepare_completion_params( + self, + messages: list[dict[str, str]], + tools: list[dict] | None = None, + ) -> dict[str, Any]: + """Prepare parameters for Azure AI Inference chat completion. + + Args: + messages: Formatted messages for Azure + tools: Tool definitions + + Returns: + Parameters dictionary for Azure API + """ + params = { + "model": self.model, + "messages": messages, + "stream": self.stream, + } + + # Add optional parameters if set + if self.temperature is not None: + params["temperature"] = self.temperature + if self.top_p is not None: + params["top_p"] = self.top_p + if self.frequency_penalty is not None: + params["frequency_penalty"] = self.frequency_penalty + if self.presence_penalty is not None: + params["presence_penalty"] = self.presence_penalty + if self.max_tokens is not None: + params["max_tokens"] = self.max_tokens + if self.stop: + params["stop"] = self.stop + + # Handle tools/functions for Azure OpenAI models + if tools and self.is_openai_model: + params["tools"] = self._convert_tools_for_interference(tools) + params["tool_choice"] = "auto" + + return params + + def _convert_tools_for_interference(self, tools: list[dict]) -> list[dict]: + """Convert CrewAI tool format to Azure OpenAI function calling format.""" + + from crewai.llms.providers.utils.common import safe_tool_conversion + + azure_tools = [] + + for tool in tools: + name, description, parameters = safe_tool_conversion(tool, "Azure") + + azure_tool = { + "type": "function", + "function": { + "name": name, + "description": description, + }, + } + + if parameters: + if isinstance(parameters, dict): + azure_tool["function"]["parameters"] = parameters # type: ignore + else: + azure_tool["function"]["parameters"] = dict(parameters) + + azure_tools.append(azure_tool) + + return azure_tools + + def _format_messages_for_azure( + self, messages: str | list[dict[str, str]] + ) -> list[dict[str, str]]: + """Format messages for Azure AI Inference API. + + Args: + messages: Input messages + + Returns: + List of dict objects + """ + # Use base class formatting first + base_formatted = super()._format_messages(messages) + + azure_messages = [] + + for message in base_formatted: + role = message.get("role") + content = message.get("content", "") + + if role == "system": + azure_messages.append(dict(content=content)) + elif role == "user": + azure_messages.append(dict(content=content)) + elif role == "assistant": + azure_messages.append(dict(content=content)) + else: + # Default to user message for unknown roles + azure_messages.append(dict(content=content)) + + return azure_messages + + def _handle_completion( + self, + params: dict[str, Any], + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | Any: + """Handle non-streaming chat completion.""" + # Make API call + try: + response: ChatCompletions = self.client.complete(**params) + + if not response.choices: + raise ValueError("No choices returned from Azure API") + + choice = response.choices[0] + message = choice.message + + # Extract and track token usage + usage = self._extract_azure_token_usage(response) + self._track_token_usage_internal(usage) + + # Handle tool calls + if message.tool_calls and available_functions: + tool_call = message.tool_calls[0] # Handle first tool call + if isinstance(tool_call, ChatCompletionsToolCall): + function_name = tool_call.function.name + + try: + function_args = json.loads(tool_call.function.arguments) + except json.JSONDecodeError as e: + logging.error(f"Failed to parse tool arguments: {e}") + function_args = {} + + # Execute tool + result = self._handle_tool_execution( + function_name=function_name, + function_args=function_args, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + if result is not None: + return result + + # Extract content + content = message.content or "" + + # Apply stop words + content = self._apply_stop_words(content) + + # Emit completion event and return content + self._emit_call_completed_event( + response=content, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=params["messages"], + ) + + except Exception as e: + if is_context_length_exceeded(e): + logging.error(f"Context window exceeded: {e}") + raise LLMContextLengthExceededError(str(e)) from e + + return content + + def _handle_streaming_completion( + self, + params: dict[str, Any], + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str: + """Handle streaming chat completion.""" + full_response = "" + tool_calls = {} + + # Make streaming API call + for update in self.client.complete(**params): + if isinstance(update, StreamingChatCompletionsUpdate): + if update.choices: + choice = update.choices[0] + if choice.delta and choice.delta.content: + content_delta = choice.delta.content + full_response += content_delta + self._emit_stream_chunk_event( + chunk=content_delta, + from_task=from_task, + from_agent=from_agent, + ) + + # Handle tool call streaming + if choice.delta and choice.delta.tool_calls: + for tool_call in choice.delta.tool_calls: + call_id = tool_call.id or "default" + if call_id not in tool_calls: + tool_calls[call_id] = { + "name": "", + "arguments": "", + } + + if tool_call.function and tool_call.function.name: + tool_calls[call_id]["name"] = tool_call.function.name + if tool_call.function and tool_call.function.arguments: + tool_calls[call_id]["arguments"] += ( + tool_call.function.arguments + ) + + # Handle completed tool calls + if tool_calls and available_functions: + for call_data in tool_calls.values(): + function_name = call_data["name"] + + try: + function_args = json.loads(call_data["arguments"]) + except json.JSONDecodeError as e: + logging.error(f"Failed to parse streamed tool arguments: {e}") + continue + + # Execute tool + result = self._handle_tool_execution( + function_name=function_name, + function_args=function_args, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + if result is not None: + return result + + # Apply stop words to full response + full_response = self._apply_stop_words(full_response) + + # Emit completion event and return full response + self._emit_call_completed_event( + response=full_response, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=params["messages"], + ) + + return full_response + + def supports_function_calling(self) -> bool: + """Check if the model supports function calling.""" + # Azure OpenAI models support function calling + return self.is_openai_model + + def supports_stop_words(self) -> bool: + """Check if the model supports stop words.""" + return True # Most Azure models support stop sequences + + def get_context_window_size(self) -> int: + """Get the context window size for the model.""" + from crewai.llm import CONTEXT_WINDOW_USAGE_RATIO, LLM_CONTEXT_WINDOW_SIZES + + min_context = 1024 + max_context = 2097152 + + for key, value in LLM_CONTEXT_WINDOW_SIZES.items(): + if value < min_context or value > max_context: + raise ValueError( + f"Context window for {key} must be between {min_context} and {max_context}" + ) + + # Context window sizes for common Azure models + context_windows = { + "gpt-4": 8192, + "gpt-4o": 128000, + "gpt-4o-mini": 200000, + "gpt-4-turbo": 128000, + "gpt-35-turbo": 16385, + "gpt-3.5-turbo": 16385, + "text-embedding": 8191, + } + + # Find the best match for the model name + for model_prefix, size in context_windows.items(): + if self.model.startswith(model_prefix): + return int(size * CONTEXT_WINDOW_USAGE_RATIO) + + # Default context window size + return int(8192 * CONTEXT_WINDOW_USAGE_RATIO) + + def _extract_azure_token_usage(self, response: ChatCompletions) -> dict[str, Any]: + """Extract token usage from Azure response.""" + if hasattr(response, "usage") and response.usage: + usage = response.usage + return { + "prompt_tokens": getattr(usage, "prompt_tokens", 0), + "completion_tokens": getattr(usage, "completion_tokens", 0), + "total_tokens": getattr(usage, "total_tokens", 0), + } + return {"total_tokens": 0} diff --git a/lib/crewai/src/crewai/llms/providers/gemini/completion.py b/lib/crewai/src/crewai/llms/providers/gemini/completion.py new file mode 100644 index 000000000..7012e5ca0 --- /dev/null +++ b/lib/crewai/src/crewai/llms/providers/gemini/completion.py @@ -0,0 +1,497 @@ +import logging +import os +from typing import Any + +from crewai.events.types.llm_events import LLMCallType +from crewai.llms.base_llm import BaseLLM +from crewai.utilities.agent_utils import is_context_length_exceeded +from crewai.utilities.exceptions.context_window_exceeding_exception import ( + LLMContextLengthExceededError, +) + + +try: + from google import genai # type: ignore + from google.genai import types # type: ignore + from google.genai.errors import APIError # type: ignore +except ImportError: + raise ImportError( + "Google Gen AI native provider not available, to install: `uv add google-genai`" + ) from None + + +class GeminiCompletion(BaseLLM): + """Google Gemini native completion implementation. + + This class provides direct integration with the Google Gen AI Python SDK, + offering native function calling, streaming support, and proper Gemini formatting. + """ + + def __init__( + self, + model: str = "gemini-2.0-flash-001", + api_key: str | None = None, + project: str | None = None, + location: str | None = None, + temperature: float | None = None, + top_p: float | None = None, + top_k: int | None = None, + max_output_tokens: int | None = None, + stop_sequences: list[str] | None = None, + stream: bool = False, + safety_settings: dict[str, Any] | None = None, + **kwargs, + ): + """Initialize Google Gemini chat completion client. + + Args: + model: Gemini model name (e.g., 'gemini-2.0-flash-001', 'gemini-1.5-pro') + api_key: Google API key (defaults to GOOGLE_API_KEY or GEMINI_API_KEY env var) + project: Google Cloud project ID (for Vertex AI) + location: Google Cloud location (for Vertex AI, defaults to 'us-central1') + temperature: Sampling temperature (0-2) + top_p: Nucleus sampling parameter + top_k: Top-k sampling parameter + max_output_tokens: Maximum tokens in response + stop_sequences: Stop sequences + stream: Enable streaming responses + safety_settings: Safety filter settings + **kwargs: Additional parameters + """ + super().__init__( + model=model, temperature=temperature, stop=stop_sequences or [], **kwargs + ) + + # Get API configuration + self.api_key = ( + api_key or os.getenv("GOOGLE_API_KEY") or os.getenv("GEMINI_API_KEY") + ) + self.project = project or os.getenv("GOOGLE_CLOUD_PROJECT") + self.location = location or os.getenv("GOOGLE_CLOUD_LOCATION") or "us-central1" + + # Initialize client based on available configuration + if self.project: + # Use Vertex AI + self.client = genai.Client( + vertexai=True, + project=self.project, + location=self.location, + ) + elif self.api_key: + # Use Gemini Developer API + self.client = genai.Client(api_key=self.api_key) + else: + raise ValueError( + "Either GOOGLE_API_KEY/GEMINI_API_KEY (for Gemini API) or " + "GOOGLE_CLOUD_PROJECT (for Vertex AI) must be set" + ) + + # Store completion parameters + self.top_p = top_p + self.top_k = top_k + self.max_output_tokens = max_output_tokens + self.stream = stream + self.safety_settings = safety_settings or {} + self.stop_sequences = stop_sequences or [] + + # Model-specific settings + self.is_gemini_2 = "gemini-2" in model.lower() + self.is_gemini_1_5 = "gemini-1.5" in model.lower() + self.supports_tools = self.is_gemini_1_5 or self.is_gemini_2 + + def call( + self, + messages: str | list[dict[str, str]], + tools: list[dict] | None = None, + callbacks: list[Any] | None = None, + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | Any: + """Call Google Gemini generate content API. + + Args: + messages: Input messages for the chat completion + tools: List of tool/function definitions + callbacks: Callback functions (not used as token counts are handled by the reponse) + available_functions: Available functions for tool calling + from_task: Task that initiated the call + from_agent: Agent that initiated the call + + Returns: + Chat completion response or tool call result + """ + try: + self._emit_call_started_event( + messages=messages, + tools=tools, + callbacks=callbacks, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + self.tools = tools + + formatted_content, system_instruction = self._format_messages_for_gemini( + messages + ) + + config = self._prepare_generation_config(system_instruction, tools) + + if self.stream: + return self._handle_streaming_completion( + formatted_content, + config, + available_functions, + from_task, + from_agent, + ) + + return self._handle_completion( + formatted_content, + system_instruction, + config, + available_functions, + from_task, + from_agent, + ) + + except APIError as e: + error_msg = f"Google Gemini API error: {e.code} - {e.message}" + logging.error(error_msg) + self._emit_call_failed_event( + error=error_msg, from_task=from_task, from_agent=from_agent + ) + raise + except Exception as e: + error_msg = f"Google Gemini API call failed: {e!s}" + logging.error(error_msg) + self._emit_call_failed_event( + error=error_msg, from_task=from_task, from_agent=from_agent + ) + raise + + def _prepare_generation_config( + self, + system_instruction: str | None = None, + tools: list[dict] | None = None, + ) -> types.GenerateContentConfig: + """Prepare generation config for Google Gemini API. + + Args: + system_instruction: System instruction for the model + tools: Tool definitions + + Returns: + GenerateContentConfig object for Gemini API + """ + self.tools = tools + config_params = {} + + # Add system instruction if present + if system_instruction: + # Convert system instruction to Content format + system_content = types.Content( + role="user", parts=[types.Part.from_text(text=system_instruction)] + ) + config_params["system_instruction"] = system_content + + # Add generation config parameters + if self.temperature is not None: + config_params["temperature"] = self.temperature + if self.top_p is not None: + config_params["top_p"] = self.top_p + if self.top_k is not None: + config_params["top_k"] = self.top_k + if self.max_output_tokens is not None: + config_params["max_output_tokens"] = self.max_output_tokens + if self.stop_sequences: + config_params["stop_sequences"] = self.stop_sequences + + # Handle tools for supported models + if tools and self.supports_tools: + config_params["tools"] = self._convert_tools_for_interference(tools) + + if self.safety_settings: + config_params["safety_settings"] = self.safety_settings + + return types.GenerateContentConfig(**config_params) + + def _convert_tools_for_interference(self, tools: list[dict]) -> list[types.Tool]: + """Convert CrewAI tool format to Gemini function declaration format.""" + gemini_tools = [] + + from crewai.llms.providers.utils.common import safe_tool_conversion + + for tool in tools: + name, description, parameters = safe_tool_conversion(tool, "Gemini") + + function_declaration = types.FunctionDeclaration( + name=name, + description=description, + ) + + # Add parameters if present - ensure parameters is a dict + if parameters and isinstance(parameters, dict): + function_declaration.parameters = parameters + + gemini_tool = types.Tool(function_declarations=[function_declaration]) + gemini_tools.append(gemini_tool) + + return gemini_tools + + def _format_messages_for_gemini( + self, messages: str | list[dict[str, str]] + ) -> tuple[list[types.Content], str | None]: + """Format messages for Gemini API. + + Gemini has specific requirements: + - System messages are separate system_instruction + - Content is organized as Content objects with Parts + - Roles are 'user' and 'model' (not 'assistant') + + Args: + messages: Input messages + + Returns: + Tuple of (formatted_contents, system_instruction) + """ + # Use base class formatting first + base_formatted = super()._format_messages(messages) + + contents = [] + system_instruction = None + + for message in base_formatted: + role = message.get("role") + content = message.get("content", "") + + if role == "system": + # Extract system instruction - Gemini handles it separately + if system_instruction: + system_instruction += f"\n\n{content}" + else: + system_instruction = content + else: + # Convert role for Gemini (assistant -> model) + gemini_role = "model" if role == "assistant" else "user" + + # Create Content object + gemini_content = types.Content( + role=gemini_role, parts=[types.Part.from_text(text=content)] + ) + contents.append(gemini_content) + + return contents, system_instruction + + def _handle_completion( + self, + contents: list[types.Content], + system_instruction: str | None, + config: types.GenerateContentConfig, + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | Any: + """Handle non-streaming content generation.""" + api_params = { + "model": self.model, + "contents": contents, + "config": config, + } + + try: + response = self.client.models.generate_content(**api_params) + + usage = self._extract_token_usage(response) + except Exception as e: + if is_context_length_exceeded(e): + logging.error(f"Context window exceeded: {e}") + raise LLMContextLengthExceededError(str(e)) from e + raise e from e + + self._track_token_usage_internal(usage) + + if response.candidates and (self.tools or available_functions): + candidate = response.candidates[0] + if candidate.content and candidate.content.parts: + for part in candidate.content.parts: + if hasattr(part, "function_call") and part.function_call: + function_name = part.function_call.name + function_args = ( + dict(part.function_call.args) + if part.function_call.args + else {} + ) + + result = self._handle_tool_execution( + function_name=function_name, + function_args=function_args, + available_functions=available_functions, # type: ignore + from_task=from_task, + from_agent=from_agent, + ) + + if result is not None: + return result + + content = response.text if hasattr(response, "text") else "" + content = self._apply_stop_words(content) + + messages_for_event = self._convert_contents_to_dict(contents) + + self._emit_call_completed_event( + response=content, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=messages_for_event, + ) + + return content + + def _handle_streaming_completion( + self, + contents: list[types.Content], + config: types.GenerateContentConfig, + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str: + """Handle streaming content generation.""" + full_response = "" + function_calls = {} + + api_params = { + "model": self.model, + "contents": contents, + "config": config, + } + + for chunk in self.client.models.generate_content_stream(**api_params): + if hasattr(chunk, "text") and chunk.text: + full_response += chunk.text + self._emit_stream_chunk_event( + chunk=chunk.text, + from_task=from_task, + from_agent=from_agent, + ) + + if hasattr(chunk, "candidates") and chunk.candidates: + candidate = chunk.candidates[0] + if candidate.content and candidate.content.parts: + for part in candidate.content.parts: + if hasattr(part, "function_call") and part.function_call: + call_id = part.function_call.name or "default" + if call_id not in function_calls: + function_calls[call_id] = { + "name": part.function_call.name, + "args": dict(part.function_call.args) + if part.function_call.args + else {}, + } + + # Handle completed function calls + if function_calls and available_functions: + for call_data in function_calls.values(): + function_name = call_data["name"] + function_args = call_data["args"] + + # Execute tool + result = self._handle_tool_execution( + function_name=function_name, + function_args=function_args, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + if result is not None: + return result + + messages_for_event = self._convert_contents_to_dict(contents) + + self._emit_call_completed_event( + response=full_response, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=messages_for_event, + ) + + return full_response + + def supports_function_calling(self) -> bool: + """Check if the model supports function calling.""" + return self.supports_tools + + def supports_stop_words(self) -> bool: + """Check if the model supports stop words.""" + return self._supports_stop_words_implementation() + + def get_context_window_size(self) -> int: + """Get the context window size for the model.""" + from crewai.llm import CONTEXT_WINDOW_USAGE_RATIO, LLM_CONTEXT_WINDOW_SIZES + + min_context = 1024 + max_context = 2097152 + + for key, value in LLM_CONTEXT_WINDOW_SIZES.items(): + if value < min_context or value > max_context: + raise ValueError( + f"Context window for {key} must be between {min_context} and {max_context}" + ) + + context_windows = { + "gemini-2.0-flash": 1048576, # 1M tokens + "gemini-2.0-flash-thinking": 32768, + "gemini-2.0-flash-lite": 1048576, + "gemini-2.5-flash": 1048576, + "gemini-2.5-pro": 1048576, + "gemini-1.5-pro": 2097152, # 2M tokens + "gemini-1.5-flash": 1048576, + "gemini-1.5-flash-8b": 1048576, + "gemini-1.0-pro": 32768, + "gemma-3-1b": 32000, + "gemma-3-4b": 128000, + "gemma-3-12b": 128000, + "gemma-3-27b": 128000, + } + + # Find the best match for the model name + for model_prefix, size in context_windows.items(): + if self.model.startswith(model_prefix): + return int(size * CONTEXT_WINDOW_USAGE_RATIO) + + # Default context window size for Gemini models + return int(1048576 * CONTEXT_WINDOW_USAGE_RATIO) # 1M tokens + + def _extract_token_usage(self, response: dict[str, Any]) -> dict[str, Any]: + """Extract token usage from Gemini response.""" + if hasattr(response, "usage_metadata"): + usage = response.usage_metadata + return { + "prompt_token_count": getattr(usage, "prompt_token_count", 0), + "candidates_token_count": getattr(usage, "candidates_token_count", 0), + "total_token_count": getattr(usage, "total_token_count", 0), + "total_tokens": getattr(usage, "total_token_count", 0), + } + return {"total_tokens": 0} + + def _convert_contents_to_dict( + self, contents: list[types.Content] + ) -> list[dict[str, str]]: + """Convert contents to dict format.""" + return [ + { + "role": "assistant" + if content_obj.role == "model" + else content_obj.role, + "content": " ".join( + part.text + for part in content_obj.parts + if hasattr(part, "text") and part.text + ), + } + for content_obj in contents + ] diff --git a/lib/crewai/src/crewai/llms/providers/openai/completion.py b/lib/crewai/src/crewai/llms/providers/openai/completion.py new file mode 100644 index 000000000..539144256 --- /dev/null +++ b/lib/crewai/src/crewai/llms/providers/openai/completion.py @@ -0,0 +1,484 @@ +from collections.abc import Iterator +import json +import logging +import os +from typing import Any + +from crewai.events.types.llm_events import LLMCallType +from crewai.llms.base_llm import BaseLLM +from crewai.utilities.agent_utils import is_context_length_exceeded +from crewai.utilities.exceptions.context_window_exceeding_exception import ( + LLMContextLengthExceededError, +) +from openai import OpenAI +from openai.types.chat import ChatCompletion, ChatCompletionChunk +from openai.types.chat.chat_completion import Choice +from openai.types.chat.chat_completion_chunk import ChoiceDelta +from pydantic import BaseModel + + +class OpenAICompletion(BaseLLM): + """OpenAI native completion implementation. + + This class provides direct integration with the OpenAI Python SDK, + offering native structured outputs, function calling, and streaming support. + """ + + def __init__( + self, + model: str = "gpt-4o", + api_key: str | None = None, + base_url: str | None = None, + organization: str | None = None, + project: str | None = None, + timeout: float | None = None, + max_retries: int = 2, + temperature: float | None = None, + top_p: float | None = None, + frequency_penalty: float | None = None, + presence_penalty: float | None = None, + max_tokens: int | None = None, + max_completion_tokens: int | None = None, + seed: int | None = None, + stream: bool = False, + response_format: dict[str, Any] | type[BaseModel] | None = None, + logprobs: bool | None = None, + top_logprobs: int | None = None, + reasoning_effort: str | None = None, # For o1 models + provider: str | None = None, # Add provider parameter + **kwargs, + ): + """Initialize OpenAI chat completion client.""" + + if provider is None: + provider = kwargs.pop("provider", "openai") + + super().__init__( + model=model, + temperature=temperature, + api_key=api_key or os.getenv("OPENAI_API_KEY"), + base_url=base_url, + timeout=timeout, + provider=provider, + **kwargs, + ) + + self.client = OpenAI( + api_key=api_key or os.getenv("OPENAI_API_KEY"), + base_url=base_url, + organization=organization, + project=project, + timeout=timeout, + max_retries=max_retries, + ) + + self.top_p = top_p + self.frequency_penalty = frequency_penalty + self.presence_penalty = presence_penalty + self.max_tokens = max_tokens + self.max_completion_tokens = max_completion_tokens + self.seed = seed + self.stream = stream + self.response_format = response_format + self.logprobs = logprobs + self.top_logprobs = top_logprobs + self.reasoning_effort = reasoning_effort + self.timeout = timeout + self.is_o1_model = "o1" in model.lower() + self.is_gpt4_model = "gpt-4" in model.lower() + + def call( + self, + messages: str | list[dict[str, str]], + tools: list[dict] | None = None, + callbacks: list[Any] | None = None, + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | Any: + """Call OpenAI chat completion API. + + Args: + messages: Input messages for the chat completion + tools: list of tool/function definitions + callbacks: Callback functions (not used in native implementation) + available_functions: Available functions for tool calling + from_task: Task that initiated the call + from_agent: Agent that initiated the call + + Returns: + Chat completion response or tool call result + """ + try: + self._emit_call_started_event( + messages=messages, + tools=tools, + callbacks=callbacks, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + formatted_messages = self._format_messages(messages) + + completion_params = self._prepare_completion_params( + formatted_messages, tools + ) + + if self.stream: + return self._handle_streaming_completion( + completion_params, available_functions, from_task, from_agent + ) + + return self._handle_completion( + completion_params, available_functions, from_task, from_agent + ) + + except Exception as e: + error_msg = f"OpenAI API call failed: {e!s}" + logging.error(error_msg) + self._emit_call_failed_event( + error=error_msg, from_task=from_task, from_agent=from_agent + ) + raise + + def _prepare_completion_params( + self, messages: list[dict[str, str]], tools: list[dict] | None = None + ) -> dict[str, Any]: + """Prepare parameters for OpenAI chat completion.""" + params = { + "model": self.model, + "messages": messages, + "stream": self.stream, + } + + params.update(self.additional_params) + + if self.temperature is not None: + params["temperature"] = self.temperature + if self.top_p is not None: + params["top_p"] = self.top_p + if self.frequency_penalty is not None: + params["frequency_penalty"] = self.frequency_penalty + if self.presence_penalty is not None: + params["presence_penalty"] = self.presence_penalty + if self.max_completion_tokens is not None: + params["max_completion_tokens"] = self.max_completion_tokens + elif self.max_tokens is not None: + params["max_tokens"] = self.max_tokens + if self.seed is not None: + params["seed"] = self.seed + if self.logprobs is not None: + params["logprobs"] = self.logprobs + if self.top_logprobs is not None: + params["top_logprobs"] = self.top_logprobs + + # Handle o1 model specific parameters + if self.is_o1_model and self.reasoning_effort: + params["reasoning_effort"] = self.reasoning_effort + + # Handle response format for structured outputs + if self.response_format: + if isinstance(self.response_format, type) and issubclass( + self.response_format, BaseModel + ): + # Convert Pydantic model to OpenAI response format + params["response_format"] = { + "type": "json_schema", + "json_schema": { + "name": self.response_format.__name__, + "schema": self.response_format.model_json_schema(), + }, + } + else: + params["response_format"] = self.response_format + + if tools: + params["tools"] = self._convert_tools_for_interference(tools) + params["tool_choice"] = "auto" + + # Filter out CrewAI-specific parameters that shouldn't go to the API + crewai_specific_params = { + "callbacks", + "available_functions", + "from_task", + "from_agent", + "provider", + "api_key", + "base_url", + "timeout", + "max_retries", + } + + return {k: v for k, v in params.items() if k not in crewai_specific_params} + + def _convert_tools_for_interference(self, tools: list[dict]) -> list[dict]: + """Convert CrewAI tool format to OpenAI function calling format.""" + from crewai.llms.providers.utils.common import safe_tool_conversion + + openai_tools = [] + + for tool in tools: + name, description, parameters = safe_tool_conversion(tool, "OpenAI") + + openai_tool = { + "type": "function", + "function": { + "name": name, + "description": description, + }, + } + + if parameters: + if isinstance(parameters, dict): + openai_tool["function"]["parameters"] = parameters # type: ignore + else: + openai_tool["function"]["parameters"] = dict(parameters) + + openai_tools.append(openai_tool) + return openai_tools + + def _handle_completion( + self, + params: dict[str, Any], + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str | Any: + """Handle non-streaming chat completion.""" + try: + response: ChatCompletion = self.client.chat.completions.create(**params) + + usage = self._extract_openai_token_usage(response) + + self._track_token_usage_internal(usage) + + choice: Choice = response.choices[0] + message = choice.message + + if message.tool_calls and available_functions: + tool_call = message.tool_calls[0] + function_name = tool_call.function.name + + try: + function_args = json.loads(tool_call.function.arguments) + except json.JSONDecodeError as e: + logging.error(f"Failed to parse tool arguments: {e}") + function_args = {} + + result = self._handle_tool_execution( + function_name=function_name, + function_args=function_args, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + if result is not None: + return result + + content = message.content or "" + content = self._apply_stop_words(content) + + if self.response_format and isinstance(self.response_format, type): + try: + structured_result = self._validate_structured_output( + content, self.response_format + ) + self._emit_call_completed_event( + response=structured_result, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=params["messages"], + ) + return structured_result + except ValueError as e: + logging.warning(f"Structured output validation failed: {e}") + + self._emit_call_completed_event( + response=content, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=params["messages"], + ) + + if usage.get("total_tokens", 0) > 0: + logging.info(f"OpenAI API usage: {usage}") + except Exception as e: + if is_context_length_exceeded(e): + logging.error(f"Context window exceeded: {e}") + raise LLMContextLengthExceededError(str(e)) from e + raise e from e + + return content + + def _handle_streaming_completion( + self, + params: dict[str, Any], + available_functions: dict[str, Any] | None = None, + from_task: Any | None = None, + from_agent: Any | None = None, + ) -> str: + """Handle streaming chat completion.""" + full_response = "" + tool_calls = {} + + # Make streaming API call + stream: Iterator[ChatCompletionChunk] = self.client.chat.completions.create( + **params + ) + + for chunk in stream: + if not chunk.choices: + continue + + choice = chunk.choices[0] + delta: ChoiceDelta = choice.delta + + # Handle content streaming + if delta.content: + full_response += delta.content + self._emit_stream_chunk_event( + chunk=delta.content, + from_task=from_task, + from_agent=from_agent, + ) + + # Handle tool call streaming + if delta.tool_calls: + for tool_call in delta.tool_calls: + call_id = tool_call.id or "default" + if call_id not in tool_calls: + tool_calls[call_id] = { + "name": "", + "arguments": "", + } + + if tool_call.function and tool_call.function.name: + tool_calls[call_id]["name"] = tool_call.function.name + if tool_call.function and tool_call.function.arguments: + tool_calls[call_id]["arguments"] += tool_call.function.arguments + + if tool_calls and available_functions: + for call_data in tool_calls.values(): + function_name = call_data["name"] + arguments = call_data["arguments"] + + # Skip if function name is empty or arguments are empty + if not function_name or not arguments: + continue + + # Check if function exists in available functions + if function_name not in available_functions: + logging.warning( + f"Function '{function_name}' not found in available functions" + ) + continue + + try: + function_args = json.loads(arguments) + except json.JSONDecodeError as e: + logging.error(f"Failed to parse streamed tool arguments: {e}") + continue + + result = self._handle_tool_execution( + function_name=function_name, + function_args=function_args, + available_functions=available_functions, + from_task=from_task, + from_agent=from_agent, + ) + + if result is not None: + return result + + # Apply stop words to full response + full_response = self._apply_stop_words(full_response) + + # Emit completion event and return full response + self._emit_call_completed_event( + response=full_response, + call_type=LLMCallType.LLM_CALL, + from_task=from_task, + from_agent=from_agent, + messages=params["messages"], + ) + + return full_response + + def supports_function_calling(self) -> bool: + """Check if the model supports function calling.""" + return not self.is_o1_model + + def supports_stop_words(self) -> bool: + """Check if the model supports stop words.""" + return not self.is_o1_model + + def get_context_window_size(self) -> int: + """Get the context window size for the model.""" + from crewai.llm import CONTEXT_WINDOW_USAGE_RATIO, LLM_CONTEXT_WINDOW_SIZES + + min_context = 1024 + max_context = 2097152 + + for key, value in LLM_CONTEXT_WINDOW_SIZES.items(): + if value < min_context or value > max_context: + raise ValueError( + f"Context window for {key} must be between {min_context} and {max_context}" + ) + + # Context window sizes for OpenAI models + context_windows = { + "gpt-4": 8192, + "gpt-4o": 128000, + "gpt-4o-mini": 200000, + "gpt-4-turbo": 128000, + "gpt-4.1": 1047576, + "gpt-4.1-mini-2025-04-14": 1047576, + "gpt-4.1-nano-2025-04-14": 1047576, + "o1-preview": 128000, + "o1-mini": 128000, + "o3-mini": 200000, + "o4-mini": 200000, + } + + # Find the best match for the model name + for model_prefix, size in context_windows.items(): + if self.model.startswith(model_prefix): + return int(size * CONTEXT_WINDOW_USAGE_RATIO) + + # Default context window size + return int(8192 * CONTEXT_WINDOW_USAGE_RATIO) + + def _extract_openai_token_usage(self, response: ChatCompletion) -> dict[str, Any]: + """Extract token usage from OpenAI ChatCompletion response.""" + if hasattr(response, "usage") and response.usage: + usage = response.usage + return { + "prompt_tokens": getattr(usage, "prompt_tokens", 0), + "completion_tokens": getattr(usage, "completion_tokens", 0), + "total_tokens": getattr(usage, "total_tokens", 0), + } + return {"total_tokens": 0} + + def _format_messages( + self, messages: str | list[dict[str, str]] + ) -> list[dict[str, str]]: + """Format messages for OpenAI API.""" + # Use base class formatting first + base_formatted = super()._format_messages(messages) + + # Apply OpenAI-specific formatting + formatted_messages = [] + + for message in base_formatted: + if self.is_o1_model and message.get("role") == "system": + formatted_messages.append( + {"role": "user", "content": f"System: {message['content']}"} + ) + else: + formatted_messages.append(message) + + return formatted_messages diff --git a/lib/crewai/src/crewai/llms/providers/utils/common.py b/lib/crewai/src/crewai/llms/providers/utils/common.py new file mode 100644 index 000000000..f240a0808 --- /dev/null +++ b/lib/crewai/src/crewai/llms/providers/utils/common.py @@ -0,0 +1,136 @@ +import logging +import re +from typing import Any + + +def validate_function_name(name: str, provider: str = "LLM") -> str: + """Validate function name according to common LLM provider requirements. + + Most LLM providers (OpenAI, Gemini, Anthropic) have similar requirements: + - Must start with letter or underscore + - Only alphanumeric, underscore, dot, colon, dash allowed + - Maximum length of 64 characters + - Cannot be empty + + Args: + name: The function name to validate + provider: The provider name for error messages + + Returns: + The validated function name (unchanged if valid) + + Raises: + ValueError: If the function name is invalid + """ + if not name or not isinstance(name, str): + raise ValueError(f"{provider} function name cannot be empty") + + if not (name[0].isalpha() or name[0] == "_"): + raise ValueError( + f"{provider} function name '{name}' must start with a letter or underscore" + ) + + if len(name) > 64: + raise ValueError( + f"{provider} function name '{name}' exceeds 64 character limit" + ) + + # Check for invalid characters (most providers support these) + if not re.match(r"^[a-zA-Z_][a-zA-Z0-9_.\-:]*$", name): + raise ValueError( + f"{provider} function name '{name}' contains invalid characters. " + f"Only letters, numbers, underscore, dot, colon, dash allowed" + ) + + return name + + +def extract_tool_info(tool: dict[str, Any]) -> tuple[str, str, dict[str, Any]]: + """Extract tool information from various schema formats. + + Handles both OpenAI/standard format and direct format: + - OpenAI format: {"type": "function", "function": {"name": "...", ...}} + - Direct format: {"name": "...", "description": "...", ...} + + Args: + tool: Tool dictionary in any supported format + + Returns: + Tuple of (name, description, parameters) + + Raises: + ValueError: If tool format is invalid + """ + if not isinstance(tool, dict): + raise ValueError("Tool must be a dictionary") + + # Handle nested function schema format (OpenAI/standard) + if "function" in tool: + function_info = tool["function"] + if not isinstance(function_info, dict): + raise ValueError("Tool function must be a dictionary") + + name = function_info.get("name", "") + description = function_info.get("description", "") + parameters = function_info.get("parameters", {}) + else: + # Direct format + name = tool.get("name", "") + description = tool.get("description", "") + parameters = tool.get("parameters", {}) + + # Also check for args_schema (Pydantic format) + if not parameters and "args_schema" in tool: + if hasattr(tool["args_schema"], "model_json_schema"): + parameters = tool["args_schema"].model_json_schema() + + return name, description, parameters + + +def log_tool_conversion(tool: dict[str, Any], provider: str) -> None: + """Log tool conversion for debugging. + + Args: + tool: The tool being converted + provider: The provider name + """ + try: + name, description, parameters = extract_tool_info(tool) + logging.debug( + f"{provider}: Converting tool '{name}' (desc: {description[:50]}...)" + ) + logging.debug(f"{provider}: Tool parameters: {parameters}") + except Exception as e: + logging.error(f"{provider}: Error extracting tool info: {e}") + logging.error(f"{provider}: Tool structure: {tool}") + + +def safe_tool_conversion( + tool: dict[str, Any], provider: str +) -> tuple[str, str, dict[str, Any]]: + """Safely extract and validate tool information. + + Combines extraction, validation, and logging for robust tool conversion. + + Args: + tool: Tool dictionary to convert + provider: Provider name for error messages and logging + + Returns: + Tuple of (validated_name, description, parameters) + + Raises: + ValueError: If tool is invalid or name validation fails + """ + try: + log_tool_conversion(tool, provider) + + name, description, parameters = extract_tool_info(tool) + + validated_name = validate_function_name(name, provider) + + logging.info(f"{provider}: Successfully validated tool '{validated_name}'") + return validated_name, description, parameters + except Exception as e: + logging.error(f"{provider}: Error converting tool: {e}") + raise diff --git a/lib/crewai/src/crewai/tools/tool_usage.py b/lib/crewai/src/crewai/tools/tool_usage.py index 7ef05f347..1b6254496 100644 --- a/lib/crewai/src/crewai/tools/tool_usage.py +++ b/lib/crewai/src/crewai/tools/tool_usage.py @@ -1,10 +1,10 @@ import ast import datetime -import json -import time from difflib import SequenceMatcher +import json from json import JSONDecodeError from textwrap import dedent +import time from typing import TYPE_CHECKING, Any, Union import json5 @@ -29,6 +29,7 @@ from crewai.utilities.agent_utils import ( render_text_description_and_args, ) + if TYPE_CHECKING: from crewai.agents.agent_builder.base_agent import BaseAgent from crewai.lite_agent import LiteAgent @@ -587,7 +588,23 @@ class ToolUsage: e: Exception, ) -> None: event_data = self._prepare_event_data(tool, tool_calling) - crewai_event_bus.emit(self, ToolUsageErrorEvent(**{**event_data, "error": e})) + event_data.update( + { + "task_id": str(self.task.id) if self.task else None, + "task_name": self.task.name or self.task.description + if self.task + else None, + } + ) + crewai_event_bus.emit( + self, + ToolUsageErrorEvent( + **{ + **event_data, + "error": e, + } + ), + ) def on_tool_use_finished( self, diff --git a/lib/crewai/src/crewai/utilities/agent_utils.py b/lib/crewai/src/crewai/utilities/agent_utils.py index 5bc2bcb7f..dcd53d892 100644 --- a/lib/crewai/src/crewai/utilities/agent_utils.py +++ b/lib/crewai/src/crewai/utilities/agent_utils.py @@ -1,8 +1,8 @@ from __future__ import annotations +from collections.abc import Callable, Sequence import json import re -from collections.abc import Callable, Sequence from typing import TYPE_CHECKING, Any, Final, Literal, TypedDict from rich.console import Console @@ -15,7 +15,6 @@ from crewai.agents.parser import ( parse, ) from crewai.cli.config import Settings -from crewai.llm import LLM from crewai.llms.base_llm import BaseLLM from crewai.tools import BaseTool as CrewAITool from crewai.tools.base_tool import BaseTool @@ -29,11 +28,14 @@ from crewai.utilities.i18n import I18N from crewai.utilities.printer import ColoredText, Printer from crewai.utilities.types import LLMMessage + if TYPE_CHECKING: from crewai.agent import Agent + from crewai.llm import LLM from crewai.task import Task + class SummaryContent(TypedDict): """Structure for summary content entries. @@ -392,8 +394,10 @@ def is_context_length_exceeded(exception: Exception) -> bool: Returns: bool: True if the exception is due to context length exceeding """ - return LLMContextLengthExceededError(str(exception))._is_context_limit_error( - str(exception) + return ( + LLMContextLengthExceededError(str(exception)) + ._is_context_limit_error(str(exception)) + ._is_context_limit_error(str(exception)) ) diff --git a/lib/crewai/src/crewai/utilities/llm_utils.py b/lib/crewai/src/crewai/utilities/llm_utils.py index d3b439e5d..c87c439ea 100644 --- a/lib/crewai/src/crewai/utilities/llm_utils.py +++ b/lib/crewai/src/crewai/utilities/llm_utils.py @@ -6,6 +6,7 @@ from crewai.cli.constants import DEFAULT_LLM_MODEL, ENV_VARS, LITELLM_PARAMS from crewai.llm import LLM from crewai.llms.base_llm import BaseLLM + logger = logging.getLogger(__name__) @@ -42,7 +43,7 @@ def create_llm( or str(llm_value) ) temperature: float | None = getattr(llm_value, "temperature", None) - max_tokens: int | None = getattr(llm_value, "max_tokens", None) + max_tokens: float | int | None = getattr(llm_value, "max_tokens", None) logprobs: int | None = getattr(llm_value, "logprobs", None) timeout: float | None = getattr(llm_value, "timeout", None) api_key: str | None = getattr(llm_value, "api_key", None) @@ -59,6 +60,7 @@ def create_llm( base_url=base_url, api_base=api_base, ) + except Exception as e: logger.debug(f"Error instantiating LLM from unknown object type: {e}") return None @@ -117,6 +119,7 @@ def _llm_via_environment_or_fallback() -> LLM | None: elif api_base and not base_url: base_url = api_base + # Initialize llm_params dictionary llm_params: dict[str, Any] = { "model": model, "temperature": temperature, @@ -140,6 +143,11 @@ def _llm_via_environment_or_fallback() -> LLM | None: "callbacks": callbacks, } + unaccepted_attributes = [ + "AWS_ACCESS_KEY_ID", + "AWS_SECRET_ACCESS_KEY", + "AWS_REGION_NAME", + ] set_provider = model_name.partition("/")[0] if "/" in model_name else "openai" if set_provider in ENV_VARS: @@ -147,7 +155,7 @@ def _llm_via_environment_or_fallback() -> LLM | None: if isinstance(env_vars_for_provider, (list, tuple)): for env_var in env_vars_for_provider: key_name = env_var.get("key_name") - if key_name and key_name not in UNACCEPTED_ATTRIBUTES: + if key_name and key_name not in unaccepted_attributes: env_value = os.environ.get(key_name) if env_value: # Map environment variable names to recognized parameters diff --git a/lib/crewai/src/crewai/utilities/reasoning_handler.py b/lib/crewai/src/crewai/utilities/reasoning_handler.py index 56ac8c1a0..fb78e3e64 100644 --- a/lib/crewai/src/crewai/utilities/reasoning_handler.py +++ b/lib/crewai/src/crewai/utilities/reasoning_handler.py @@ -102,21 +102,18 @@ class AgentReasoning: try: output = self.__handle_agent_reasoning() - # Emit reasoning completed event - try: - crewai_event_bus.emit( - self.agent, - AgentReasoningCompletedEvent( - agent_role=self.agent.role, - task_id=str(self.task.id), - plan=output.plan.plan, - ready=output.plan.ready, - attempt=1, - from_task=self.task, - ), - ) - except Exception: # noqa: S110 - pass + crewai_event_bus.emit( + self.agent, + AgentReasoningCompletedEvent( + agent_role=self.agent.role, + task_id=str(self.task.id), + plan=output.plan.plan, + ready=output.plan.ready, + attempt=1, + from_task=self.task, + from_agent=self.agent, + ), + ) return output except Exception as e: @@ -130,10 +127,11 @@ class AgentReasoning: error=str(e), attempt=1, from_task=self.task, + from_agent=self.agent, ), ) - except Exception: # noqa: S110 - pass + except Exception as e: + logging.error(f"Error emitting reasoning failed event: {e}") raise diff --git a/lib/crewai/src/crewai/utilities/token_counter_callback.py b/lib/crewai/src/crewai/utilities/token_counter_callback.py index 96124f226..07c27727a 100644 --- a/lib/crewai/src/crewai/utilities/token_counter_callback.py +++ b/lib/crewai/src/crewai/utilities/token_counter_callback.py @@ -4,10 +4,24 @@ This module provides a callback handler that tracks token usage for LLM API calls through the litellm library. """ -from typing import Any +from typing import TYPE_CHECKING, Any + + +if TYPE_CHECKING: + from litellm.integrations.custom_logger import CustomLogger + from litellm.types.utils import Usage +else: + try: + from litellm.integrations.custom_logger import CustomLogger + from litellm.types.utils import Usage + except ImportError: + + class CustomLogger: + """Fallback CustomLogger when litellm is not available.""" + + class Usage: + """Fallback Usage when litellm is not available.""" -from litellm.integrations.custom_logger import CustomLogger -from litellm.types.utils import Usage from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess from crewai.utilities.logger_utils import suppress_warnings diff --git a/lib/crewai/tests/agents/test_agent.py b/lib/crewai/tests/agents/test_agent.py index ae08343c4..0cc0015a3 100644 --- a/lib/crewai/tests/agents/test_agent.py +++ b/lib/crewai/tests/agents/test_agent.py @@ -1,14 +1,9 @@ """Test Agent creation and execution basic functionality.""" -# ruff: noqa: S106 import os from unittest import mock from unittest.mock import MagicMock, patch -import pytest - -from crewai import Agent, Crew, Task -from crewai.agents.cache import CacheHandler from crewai.agents.crew_agent_executor import AgentFinish, CrewAgentExecutor from crewai.events.event_bus import crewai_event_bus from crewai.events.types.tool_usage_events import ToolUsageFinishedEvent @@ -17,12 +12,17 @@ from crewai.knowledge.knowledge_config import KnowledgeConfig from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource from crewai.llm import LLM +from crewai.llms.base_llm import BaseLLM from crewai.process import Process -from crewai.tools import tool from crewai.tools.tool_calling import InstructorToolCalling from crewai.tools.tool_usage import ToolUsage -from crewai.utilities import RPMController from crewai.utilities.errors import AgentRepositoryError +import pytest + +from crewai import Agent, Crew, Task +from crewai.agents.cache import CacheHandler +from crewai.tools import tool +from crewai.utilities import RPMController def test_agent_llm_creation_with_env_vars(): @@ -40,7 +40,7 @@ def test_agent_llm_creation_with_env_vars(): agent = Agent(role="test role", goal="test goal", backstory="test backstory") # Check if LLM is created correctly - assert isinstance(agent.llm, LLM) + assert isinstance(agent.llm, BaseLLM) assert agent.llm.model == "gpt-4-turbo" assert agent.llm.api_key == "test_api_key" assert agent.llm.base_url == "https://test-api-base.com" @@ -50,11 +50,18 @@ def test_agent_llm_creation_with_env_vars(): del os.environ["OPENAI_API_BASE"] del os.environ["OPENAI_MODEL_NAME"] + if original_api_key: + os.environ["OPENAI_API_KEY"] = original_api_key + if original_api_base: + os.environ["OPENAI_API_BASE"] = original_api_base + if original_model_name: + os.environ["OPENAI_MODEL_NAME"] = original_model_name + # Create an agent without specifying LLM agent = Agent(role="test role", goal="test goal", backstory="test backstory") # Check if LLM is created correctly - assert isinstance(agent.llm, LLM) + assert isinstance(agent.llm, BaseLLM) assert agent.llm.model != "gpt-4-turbo" assert agent.llm.api_key != "test_api_key" assert agent.llm.base_url != "https://test-api-base.com" @@ -456,18 +463,30 @@ def test_agent_custom_max_iterations(): allow_delegation=False, ) - with patch.object( - LLM, "call", wraps=LLM("gpt-4o", stop=["\nObservation:"]).call - ) as private_mock: - task = Task( - description="The final answer is 42. But don't give it yet, instead keep using the `get_final_answer` tool.", - expected_output="The final answer", - ) - agent.execute_task( - task=task, - tools=[get_final_answer], - ) - assert private_mock.call_count == 3 + original_call = agent.llm.call + call_count = 0 + + def counting_call(*args, **kwargs): + nonlocal call_count + call_count += 1 + return original_call(*args, **kwargs) + + agent.llm.call = counting_call + + task = Task( + description="The final answer is 42. But don't give it yet, instead keep using the `get_final_answer` tool.", + expected_output="The final answer", + ) + result = agent.execute_task( + task=task, + tools=[get_final_answer], + ) + + assert result is not None + assert isinstance(result, str) + assert len(result) > 0 + assert call_count > 0 + assert call_count == 3 @pytest.mark.vcr(filter_headers=["authorization"]) @@ -888,9 +907,8 @@ def test_agent_function_calling_llm(): crew = Crew(agents=[agent1], tasks=tasks) from unittest.mock import patch - import instructor - from crewai.tools.tool_usage import ToolUsage + import instructor with ( patch.object( @@ -1413,7 +1431,7 @@ def test_agent_with_llm(): llm=LLM(model="gpt-3.5-turbo", temperature=0.7), ) - assert isinstance(agent.llm, LLM) + assert isinstance(agent.llm, BaseLLM) assert agent.llm.model == "gpt-3.5-turbo" assert agent.llm.temperature == 0.7 @@ -1427,7 +1445,7 @@ def test_agent_with_custom_stop_words(): llm=LLM(model="gpt-3.5-turbo", stop=stop_words), ) - assert isinstance(agent.llm, LLM) + assert isinstance(agent.llm, BaseLLM) assert set(agent.llm.stop) == set([*stop_words, "\nObservation:"]) assert all(word in agent.llm.stop for word in stop_words) assert "\nObservation:" in agent.llm.stop @@ -1441,10 +1459,12 @@ def test_agent_with_callbacks(): role="test role", goal="test goal", backstory="test backstory", - llm=LLM(model="gpt-3.5-turbo", callbacks=[dummy_callback]), + llm=LLM(model="gpt-3.5-turbo", callbacks=[dummy_callback], is_litellm=True), ) - assert isinstance(agent.llm, LLM) + assert isinstance(agent.llm, BaseLLM) + # All LLM implementations now support callbacks consistently + assert hasattr(agent.llm, "callbacks") assert len(agent.llm.callbacks) == 1 assert agent.llm.callbacks[0] == dummy_callback @@ -1463,7 +1483,7 @@ def test_agent_with_additional_kwargs(): ), ) - assert isinstance(agent.llm, LLM) + assert isinstance(agent.llm, BaseLLM) assert agent.llm.model == "gpt-3.5-turbo" assert agent.llm.temperature == 0.8 assert agent.llm.top_p == 0.9 @@ -1580,40 +1600,40 @@ def test_agent_with_all_llm_attributes(): timeout=10, temperature=0.7, top_p=0.9, - n=1, + # n=1, stop=["STOP", "END"], max_tokens=100, presence_penalty=0.1, frequency_penalty=0.1, - logit_bias={50256: -100}, # Example: bias against the EOT token + # logit_bias={50256: -100}, # Example: bias against the EOT token response_format={"type": "json_object"}, seed=42, logprobs=True, top_logprobs=5, base_url="https://api.openai.com/v1", - api_version="2023-05-15", + # api_version="2023-05-15", api_key="sk-your-api-key-here", ), ) - assert isinstance(agent.llm, LLM) + assert isinstance(agent.llm, BaseLLM) assert agent.llm.model == "gpt-3.5-turbo" assert agent.llm.timeout == 10 assert agent.llm.temperature == 0.7 assert agent.llm.top_p == 0.9 - assert agent.llm.n == 1 + # assert agent.llm.n == 1 assert set(agent.llm.stop) == set(["STOP", "END", "\nObservation:"]) assert all(word in agent.llm.stop for word in ["STOP", "END", "\nObservation:"]) assert agent.llm.max_tokens == 100 assert agent.llm.presence_penalty == 0.1 assert agent.llm.frequency_penalty == 0.1 - assert agent.llm.logit_bias == {50256: -100} + # assert agent.llm.logit_bias == {50256: -100} assert agent.llm.response_format == {"type": "json_object"} assert agent.llm.seed == 42 assert agent.llm.logprobs assert agent.llm.top_logprobs == 5 assert agent.llm.base_url == "https://api.openai.com/v1" - assert agent.llm.api_version == "2023-05-15" + # assert agent.llm.api_version == "2023-05-15" assert agent.llm.api_key == "sk-your-api-key-here" @@ -1982,7 +2002,7 @@ def test_agent_with_knowledge_sources_works_with_copy(): assert len(agent_copy.knowledge_sources) == 1 assert isinstance(agent_copy.knowledge_sources[0], StringKnowledgeSource) assert agent_copy.knowledge_sources[0].content == content - assert isinstance(agent_copy.llm, LLM) + assert isinstance(agent_copy.llm, BaseLLM) @pytest.mark.vcr(filter_headers=["authorization"]) @@ -2130,7 +2150,7 @@ def test_litellm_auth_error_handling(): role="test role", goal="test goal", backstory="test backstory", - llm=LLM(model="gpt-4"), + llm=LLM(model="gpt-4", is_litellm=True), max_retry_limit=0, # Disable retries for authentication errors ) @@ -2157,16 +2177,15 @@ def test_litellm_auth_error_handling(): def test_crew_agent_executor_litellm_auth_error(): """Test that CrewAgentExecutor handles LiteLLM authentication errors by raising them.""" - from litellm.exceptions import AuthenticationError - from crewai.agents.tools_handler import ToolsHandler + from litellm.exceptions import AuthenticationError # Create an agent and executor agent = Agent( role="test role", goal="test goal", backstory="test backstory", - llm=LLM(model="gpt-4", api_key="invalid_api_key"), + llm=LLM(model="gpt-4", api_key="invalid_api_key", is_litellm=True), ) task = Task( description="Test task", @@ -2224,7 +2243,7 @@ def test_litellm_anthropic_error_handling(): role="test role", goal="test goal", backstory="test backstory", - llm=LLM(model="claude-3.5-sonnet-20240620"), + llm=LLM(model="claude-3.5-sonnet-20240620", is_litellm=True), max_retry_limit=0, ) diff --git a/lib/crewai/tests/agents/test_lite_agent.py b/lib/crewai/tests/agents/test_lite_agent.py index 856f26e6a..c43f57edb 100644 --- a/lib/crewai/tests/agents/test_lite_agent.py +++ b/lib/crewai/tests/agents/test_lite_agent.py @@ -3,16 +3,17 @@ from collections import defaultdict from typing import cast from unittest.mock import Mock, patch -import pytest -from crewai import LLM, Agent from crewai.events.event_bus import crewai_event_bus from crewai.events.types.agent_events import LiteAgentExecutionStartedEvent from crewai.events.types.tool_usage_events import ToolUsageStartedEvent -from crewai.flow import Flow, start from crewai.lite_agent import LiteAgent, LiteAgentOutput from crewai.llms.base_llm import BaseLLM -from crewai.tools import BaseTool from pydantic import BaseModel, Field +import pytest + +from crewai import LLM, Agent +from crewai.flow import Flow, start +from crewai.tools import BaseTool # A simple test tool @@ -197,10 +198,6 @@ def test_lite_agent_structured_output(): response_format=SimpleOutput, ) - 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Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "a65577fd-4beb-4943-990c-a49505a84fa1", + "timestamp": "2025-09-23T17:18:02.659699+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T17:18:02.659676+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis + is the expected criteria for your final answer: The final answer\nyou MUST return + the actual complete content as the final answer, not a summary.\n\nBegin! This + is VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "response": "```\nThought: + I now know the final answer\nFinal Answer: I must follow the predefined structure + and utilize the get_final_answer tool to extract the necessary information.\n```", + "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "8fc34fc3-d887-4bd5-9a57-b884abe6c5ab", "timestamp": "2025-09-23T17:18:02.659758+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T17:18:02.659738+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "5bd360ad-7d39-418c-8ea5-c3fb1bc33b0b", + "task_name": "Use the get_final_answer tool.", "agent_id": null, "agent_role": + null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": + [{"role": "system", "content": "You are test role. test backstory\nYour personal + goal is: test goal\nYou ONLY have access to the following tools, and should + NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "tools": null, "callbacks": + [""], + "available_functions": null}}, {"event_id": "3d96c88a-03b4-4c86-b109-e651e08d0ed2", + "timestamp": "2025-09-23T17:18:02.660558+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T17:18:02.660539+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "5bd360ad-7d39-418c-8ea5-c3fb1bc33b0b", "task_name": "Use the get_final_answer + tool.", "agent_id": null, "agent_role": null, "from_task": null, "from_agent": + null, "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "response": "```\nThought: + you should always think about what to do\nAction: get_final_answer\nAction Input: + {}", "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "d74dd03c-79ca-4acc-9947-fdf6c91b28d6", "timestamp": "2025-09-23T17:18:02.661730+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T17:18:02.661631+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": null, "task_name": null, "agent_id": + null, "agent_role": null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "42294a65-9862-48d1-8868-f15906d58250", + "timestamp": "2025-09-23T17:18:02.662796+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T17:18:02.662766+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis + is the expected criteria for your final answer: The final answer\nyou MUST return + the actual complete content as the final answer, not a summary.\n\nBegin! This + is VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "response": "```\nThought: I need to determine how to proceed + in order to get the final answer.\nAction: get_final_answer\nAction Input: {}", + "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "35598d62-c7eb-46e0-9abc-13e0a8de39a1", "timestamp": "2025-09-23T17:18:02.662867+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T17:18:02.662844+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "5bd360ad-7d39-418c-8ea5-c3fb1bc33b0b", + "task_name": "Use the get_final_answer tool.", "agent_id": null, "agent_role": + null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": + [{"role": "system", "content": "You are test role. test backstory\nYour personal + goal is: test goal\nYou ONLY have access to the following tools, and should + NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "efa2e49b-14a9-4e81-962e-fa8ca322e58b", + "timestamp": "2025-09-23T17:18:02.663770+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T17:18:02.663752+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "5bd360ad-7d39-418c-8ea5-c3fb1bc33b0b", "task_name": "Use the get_final_answer + tool.", "agent_id": null, "agent_role": null, "from_task": null, "from_agent": + null, "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "response": "```\nThought: I need to pursue the action to + get the final answer.\nAction: get_final_answer\nAction Input: {}", "call_type": + "", "model": "gpt-4o-mini"}}, {"event_id": + "004536e5-868f-44c5-8cdd-f323ad188ca2", "timestamp": "2025-09-23T17:18:02.664931+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T17:18:02.664847+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": null, "task_name": null, "agent_id": + null, "agent_role": null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "tools": null, "callbacks": + [""], + "available_functions": null}}, {"event_id": "e154d3f6-ab11-4fc7-bb23-998d3fd55d47", + "timestamp": "2025-09-23T17:18:02.666012+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T17:18:02.665992+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis + is the expected criteria for your final answer: The final answer\nyou MUST return + the actual complete content as the final answer, not a summary.\n\nBegin! This + is VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "response": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "e91fcc7a-a66e-46cd-9193-1c5e60e2bc62", "timestamp": "2025-09-23T17:18:02.666071+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T17:18:02.666052+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "5bd360ad-7d39-418c-8ea5-c3fb1bc33b0b", + "task_name": "Use the get_final_answer tool.", "agent_id": null, "agent_role": + null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": + [{"role": "system", "content": "You are test role. test backstory\nYour personal + goal is: test goal\nYou ONLY have access to the following tools, and should + NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "tools": null, "callbacks": + [""], + "available_functions": null}}, {"event_id": "48ad2d38-fd9e-4ddf-99e6-3c06ae63947d", + "timestamp": "2025-09-23T17:18:02.667103+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T17:18:02.667085+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "5bd360ad-7d39-418c-8ea5-c3fb1bc33b0b", "task_name": "Use the get_final_answer + tool.", "agent_id": null, "agent_role": null, "from_task": null, "from_agent": + null, "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "response": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "fe9bd495-7a1c-4a8e-a4f6-3d3abc6b667c", "timestamp": "2025-09-23T17:18:02.668209+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T17:18:02.668124+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": null, "task_name": null, "agent_id": + null, "agent_role": null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: I need to pursue the action to get the final answer.\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: I need to pursue the action to get the + final answer.\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered + an error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "5d45d0ef-df58-4953-8c9c-0c2c426581cb", + "timestamp": "2025-09-23T17:18:02.669377+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T17:18:02.669358+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis + is the expected criteria for your final answer: The final answer\nyou MUST return + the actual complete content as the final answer, not a summary.\n\nBegin! This + is VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: I need to pursue the action to get the final answer.\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: I need to pursue the action to get the + final answer.\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered + an error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "response": "```\nThought: I need to take action to get the + final answer.\nAction: get_final_answer\nAction Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, {"event_id": "aef7edef-469e-4787-8cc9-4e16b22b1196", + "timestamp": "2025-09-23T17:18:02.669434+00:00", "type": "llm_call_started", + "event_data": {"timestamp": "2025-09-23T17:18:02.669415+00:00", "type": "llm_call_started", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "5bd360ad-7d39-418c-8ea5-c3fb1bc33b0b", "task_name": "Use the get_final_answer + tool.", "agent_id": null, "agent_role": null, "from_task": null, "from_agent": + null, "model": "gpt-4o-mini", "messages": [{"role": "system", "content": "You + are test role. test backstory\nYour personal goal is: test goal\nYou ONLY have + access to the following tools, and should NEVER make up tools that are not listed + here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool Description: + Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "user", "content": "\nCurrent Task: Use the + get_final_answer tool.\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: you should + always think about what to do\nAction: get_final_answer\nAction Input: {}\nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + you should always think about what to do\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: I need to pursue the action to get the final answer.\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: I need to pursue the action to get the + final answer.\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered + an error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "tools": null, "callbacks": + [""], + "available_functions": null}}, {"event_id": "73f0eb69-88f2-40c0-8b51-626a05e48b46", + "timestamp": "2025-09-23T17:18:02.670569+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T17:18:02.670550+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "5bd360ad-7d39-418c-8ea5-c3fb1bc33b0b", "task_name": "Use the get_final_answer + tool.", "agent_id": null, "agent_role": null, "from_task": null, "from_agent": + null, "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. 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Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "d7ef744c-4a38-4a6a-aa4a-c5b074abba09", + "timestamp": "2025-09-24T06:05:19.815827+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T06:05:19.815796+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis + is the expected criteria for your final answer: The final answer\nyou MUST return + the actual complete content as the final answer, not a summary.\n\nBegin! This + is VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "response": "```\nThought: + I now know the final answer\nFinal Answer: I must follow the predefined structure + and utilize the get_final_answer tool to extract the necessary information.\n```", + "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "31ddd7c1-09be-460a-90f5-08ae4fbfa7fd", "timestamp": "2025-09-24T06:05:19.815898+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T06:05:19.815875+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "d0148c4b-ca4a-4a88-a0b3-d17d14911dfa", + "task_name": "Use the get_final_answer tool.", "agent_id": "ec3d4ced-a392-4b1c-8941-cb7c7a2089da", + "agent_role": "test role", "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "tools": null, "callbacks": + [""], + "available_functions": null}}, {"event_id": "734d2343-b2c1-402d-b57d-1ceb89136721", + "timestamp": "2025-09-24T06:05:19.816832+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T06:05:19.816810+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "d0148c4b-ca4a-4a88-a0b3-d17d14911dfa", "task_name": "Use the get_final_answer + tool.", "agent_id": "ec3d4ced-a392-4b1c-8941-cb7c7a2089da", "agent_role": "test + role", "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are test role. test backstory\nYour personal goal is: test goal\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "user", "content": "\nCurrent Task: Use the + get_final_answer tool.\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "response": "```\nThought: you should always think about what + to do\nAction: get_final_answer\nAction Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, {"event_id": "3d474495-0192-418c-90cc-0260705ed7f2", + "timestamp": "2025-09-24T06:05:19.818171+00:00", "type": "llm_call_started", + "event_data": {"timestamp": "2025-09-24T06:05:19.818066+00:00", "type": "llm_call_started", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "model": "gpt-4o-mini", "messages": [{"role": "system", + "content": "You are test role. test backstory\nYour personal goal is: test goal\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "user", "content": "\nCurrent Task: Use the + get_final_answer tool.\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: you should + always think about what to do\nAction: get_final_answer\nAction Input: {}\nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + you should always think about what to do\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "tools": null, "callbacks": + [""], + "available_functions": null}}, {"event_id": "24aeddf4-d818-4c25-aac5-0c13bd8f7ccd", + "timestamp": "2025-09-24T06:05:19.819391+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T06:05:19.819362+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis + is the expected criteria for your final answer: The final answer\nyou MUST return + the actual complete content as the final answer, not a summary.\n\nBegin! This + is VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "response": "```\nThought: I need to determine how to proceed + in order to get the final answer.\nAction: get_final_answer\nAction Input: {}", + "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "a4d462c8-c1bc-4ce5-8ddd-876243c90ad4", "timestamp": "2025-09-24T06:05:19.819470+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T06:05:19.819443+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "d0148c4b-ca4a-4a88-a0b3-d17d14911dfa", + "task_name": "Use the get_final_answer tool.", "agent_id": "ec3d4ced-a392-4b1c-8941-cb7c7a2089da", + "agent_role": "test role", "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "0c2c92a3-4dc3-4928-af66-fc2febe9b2af", + "timestamp": "2025-09-24T06:05:19.820544+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T06:05:19.820520+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "d0148c4b-ca4a-4a88-a0b3-d17d14911dfa", "task_name": "Use the get_final_answer + tool.", "agent_id": "ec3d4ced-a392-4b1c-8941-cb7c7a2089da", "agent_role": "test + role", "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are test role. test backstory\nYour personal goal is: test goal\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "user", "content": "\nCurrent Task: Use the + get_final_answer tool.\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: you should + always think about what to do\nAction: get_final_answer\nAction Input: {}\nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + you should always think about what to do\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "response": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "60a8b8ca-790d-4ba2-a4b6-09bc5735b3e9", "timestamp": "2025-09-24T06:05:19.821928+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T06:05:19.821834+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": null, "task_name": null, "agent_id": + null, "agent_role": null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "tools": null, "callbacks": + [""], + "available_functions": null}}, {"event_id": "f434c181-36d3-4523-ba2f-ff9378a652b5", + "timestamp": "2025-09-24T06:05:19.823117+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T06:05:19.823096+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis + is the expected criteria for your final answer: The final answer\nyou MUST return + the actual complete content as the final answer, not a summary.\n\nBegin! This + is VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "response": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "5590a1eb-5172-4c4d-af69-9a237af47fef", "timestamp": "2025-09-24T06:05:19.823179+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T06:05:19.823160+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "d0148c4b-ca4a-4a88-a0b3-d17d14911dfa", + "task_name": "Use the get_final_answer tool.", "agent_id": "ec3d4ced-a392-4b1c-8941-cb7c7a2089da", + "agent_role": "test role", "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}], "tools": null, "callbacks": + [""], + "available_functions": null}}, {"event_id": "f51cfd44-c3c5-4d5d-8cfa-f2582fd3c5a5", + "timestamp": "2025-09-24T06:05:19.824198+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T06:05:19.824179+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "d0148c4b-ca4a-4a88-a0b3-d17d14911dfa", "task_name": "Use the get_final_answer + tool.", "agent_id": "ec3d4ced-a392-4b1c-8941-cb7c7a2089da", "agent_role": "test + role", "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are test role. test backstory\nYour personal goal is: test goal\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "user", "content": "\nCurrent Task: Use the + get_final_answer tool.\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: you should + always think about what to do\nAction: get_final_answer\nAction Input: {}\nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + you should always think about what to do\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: I need to pursue the action to get the final answer.\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: I need to pursue the action to get the + final answer.\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered + an error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "response": "```\nThought: I need to pursue the action to + get the final answer.\nAction: get_final_answer\nAction Input: {}", "call_type": + "", "model": "gpt-4o-mini"}}, {"event_id": + "615a347c-ad5c-420f-9d71-af45a7f901a6", "timestamp": "2025-09-24T06:05:19.825358+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T06:05:19.825262+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": null, "task_name": null, "agent_id": + null, "agent_role": null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: I need to pursue the action to get the final answer.\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: I need to pursue the action to get the + final answer.\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered + an error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "be21a5e4-09af-43d5-9e33-9ab2e2e16eda", + "timestamp": "2025-09-24T06:05:19.826640+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T06:05:19.826614+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis + is the expected criteria for your final answer: The final answer\nyou MUST return + the actual complete content as the final answer, not a summary.\n\nBegin! This + is VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: I need to pursue the action to get the final answer.\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: I need to pursue the action to get the + final answer.\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered + an error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "response": "```\nThought: I need to take action to get the + final answer.\nAction: get_final_answer\nAction Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, {"event_id": "19bafe34-4ab6-45c0-8d7d-f811124cf186", + "timestamp": "2025-09-24T06:05:19.826705+00:00", "type": "llm_call_started", + "event_data": {"timestamp": "2025-09-24T06:05:19.826687+00:00", "type": "llm_call_started", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "d0148c4b-ca4a-4a88-a0b3-d17d14911dfa", "task_name": "Use the get_final_answer + tool.", "agent_id": "ec3d4ced-a392-4b1c-8941-cb7c7a2089da", "agent_role": "test + role", "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": + [{"role": "system", "content": "You are test role. test backstory\nYour personal + goal is: test goal\nYou ONLY have access to the following tools, and should + NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use the get_final_answer tool.\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "I need to + determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: you should always think about what to do\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: you should always think about what to + do\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered an + error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: I need to pursue the action to get the final answer.\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```"}, {"role": + "assistant", "content": "```\nThought: I need to pursue the action to get the + final answer.\nAction: get_final_answer\nAction Input: {}\nObservation: I encountered + an error: Error on parsing tool.\nMoving on then. I MUST either use a tool (use + one at time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "1fca7f22-fc79-4bfc-a035-7c6383a90d88", + "timestamp": "2025-09-24T06:05:19.827942+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T06:05:19.827922+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "d0148c4b-ca4a-4a88-a0b3-d17d14911dfa", "task_name": "Use the get_final_answer + tool.", "agent_id": "ec3d4ced-a392-4b1c-8941-cb7c7a2089da", "agent_role": "test + role", "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are test role. test backstory\nYour personal goal is: test goal\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "user", "content": "\nCurrent Task: Use the + get_final_answer tool.\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I need to determine what action to take next to retrieve + the final answer. \nAction: get_final_answer \nAction Input: {} \nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "I need + to determine what action to take next to retrieve the final answer. \nAction: + get_final_answer \nAction Input: {} \nObservation: I encountered an error: + Error on parsing tool.\nMoving on then. I MUST either use a tool (use one at + time) OR give my best final answer not both at the same time. When responding, + I must use the following format:\n\n```\nThought: you should always think about + what to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: you should + always think about what to do\nAction: get_final_answer\nAction Input: {}\nObservation: + I encountered an error: Error on parsing tool.\nMoving on then. I MUST either + use a tool (use one at time) OR give my best final answer not both at the same + time. When responding, I must use the following format:\n\n```\nThought: you + should always think about what to do\nAction: the action to take, should be + one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + you should always think about what to do\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```\nNow it''s time you MUST give your absolute + best final answer. You''ll ignore all previous instructions, stop using any + tools, and just return your absolute BEST Final answer."}, {"role": "assistant", + "content": "```\nThought: I need to pursue the action to get the final answer.\nAction: + get_final_answer\nAction Input: {}\nObservation: I encountered an error: Error + on parsing tool.\nMoving on then. I MUST either use a tool (use one at time) + OR give my best final answer not both at the same time. When responding, I must + use the following format:\n\n```\nThought: you should always think about what + to do\nAction: the action to take, should be one of [get_final_answer]\nAction + Input: the input to the action, dictionary enclosed in curly braces\nObservation: + the result of the action\n```\nThis Thought/Action/Action Input/Result can repeat + N times. 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Once I know the final answer, I must return the following format:\n\n```\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described\n\n```\nNow + it''s time you MUST give your absolute best final answer. You''ll ignore all + previous instructions, stop using any tools, and just return your absolute BEST + Final answer."}, {"role": "assistant", "content": "```\nThought: I need to pursue + the action to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I encountered an error: Error on parsing tool.\nMoving on then. + I MUST either use a tool (use one at time) OR give my best final answer not + both at the same time. When responding, I must use the following format:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, should + be one of [get_final_answer]\nAction Input: the input to the action, dictionary + enclosed in curly braces\nObservation: the result of the action\n```\nThis Thought/Action/Action + Input/Result can repeat N times. Once I know the final answer, I must return + the following format:\n\n```\nThought: I now can give a great answer\nFinal + Answer: Your final answer must be the great and the most complete as possible, + it must be outcome described\n\n```"}, {"role": "assistant", "content": "```\nThought: + I need to pursue the action to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I encountered an error: Error on parsing tool.\nMoving + on then. I MUST either use a tool (use one at time) OR give my best final answer + not both at the same time. 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This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I should use the available tool to get the final answer + multiple times, as instructed.\n\nAction: get_final_answer\nAction Input: {\"input\":\"n/a\"}\nObservation: + 42"}], "response": "Thought: I should continue to use the tool to meet the criteria + specified.\n\nAction: get_final_answer\nAction Input: {\"input\": \"n/a\"}", + "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "dc120a99-64ae-4586-baed-94606a5fc9c6", "timestamp": "2025-09-24T05:25:59.045530+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T05:25:59.045426+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "0ca9aa84-9dd9-4ac2-bc7f-2d810dd6097a", + "task_name": "Use tool logic for `get_final_answer` but fon''t give you final + answer yet, instead keep using it unless you''re told to give your final answer", + "agent_id": "b6cf723e-04c8-40c5-a927-e2078cfbae59", "agent_role": "test role", + "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": [{"role": + "system", "content": "You are test role. test backstory\nYour personal goal + is: test goal\nYou ONLY have access to the following tools, and should NEVER + make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I should use the available tool to get the final answer + multiple times, as instructed.\n\nAction: get_final_answer\nAction Input: {\"input\":\"n/a\"}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I should continue to use the + tool to meet the criteria specified.\n\nAction: get_final_answer\nAction Input: + {\"input\": \"n/a\"}\nObservation: I tried reusing the same input, I must stop + using this action input. 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This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I should use the available tool to get the final answer + multiple times, as instructed.\n\nAction: get_final_answer\nAction Input: {\"input\":\"n/a\"}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I should continue to use the + tool to meet the criteria specified.\n\nAction: get_final_answer\nAction Input: + {\"input\": \"n/a\"}\nObservation: I tried reusing the same input, I must stop + using this action input. 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"task_name": "Use tool logic for `get_final_answer` but fon''t give you final + answer yet, instead keep using it unless you''re told to give your final answer", + "agent_id": "b6cf723e-04c8-40c5-a927-e2078cfbae59", "agent_role": "test role", + "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": [{"role": + "system", "content": "You are test role. test backstory\nYour personal goal + is: test goal\nYou ONLY have access to the following tools, and should NEVER + make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I should use the available tool to get the final answer + multiple times, as instructed.\n\nAction: get_final_answer\nAction Input: {\"input\":\"n/a\"}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I should continue to use the + tool to meet the criteria specified.\n\nAction: get_final_answer\nAction Input: + {\"input\": \"n/a\"}\nObservation: I tried reusing the same input, I must stop + using this action input. I''ll try something else instead."}, {"role": "assistant", + "content": "Thought: I need to modify my action input to continue using the + tool correctly.\n\nAction: get_final_answer\nAction Input: {\"input\": \"test + input\"}\nObservation: "}], + "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "603166bd-f912-4db7-b3d1-03ce4a63e122", + "timestamp": "2025-09-24T05:25:59.050706+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T05:25:59.050662+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "0ca9aa84-9dd9-4ac2-bc7f-2d810dd6097a", "task_name": "Use tool logic + for `get_final_answer` but fon''t give you final answer yet, instead keep using + it unless you''re told to give your final answer", "agent_id": "b6cf723e-04c8-40c5-a927-e2078cfbae59", + "agent_role": "test role", "from_task": null, "from_agent": null, "messages": + [{"role": "system", "content": "You are test role. test backstory\nYour personal + goal is: test goal\nYou ONLY have access to the following tools, and should + NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I should use the available tool to get the final answer + multiple times, as instructed.\n\nAction: get_final_answer\nAction Input: {\"input\":\"n/a\"}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I should continue to use the + tool to meet the criteria specified.\n\nAction: get_final_answer\nAction Input: + {\"input\": \"n/a\"}\nObservation: I tried reusing the same input, I must stop + using this action input. I''ll try something else instead."}, {"role": "assistant", + "content": "Thought: I need to modify my action input to continue using the + tool correctly.\n\nAction: get_final_answer\nAction Input: {\"input\": \"test + input\"}\nObservation: "}], + "response": "Thought: I should try another variation in the input to observe + any changes and continue using the tool.\n\nAction: get_final_answer\nAction + Input: {\"input\": \"retrying with new input\"}", "call_type": "", "model": "gpt-4o-mini"}}, {"event_id": "89ff2fb9-8a8c-467e-8414-d89923aab204", + "timestamp": "2025-09-24T05:25:59.050949+00:00", "type": "tool_usage_started", + "event_data": {"timestamp": "2025-09-24T05:25:59.050905+00:00", "type": "tool_usage_started", + "source_fingerprint": "363cc2aa-b694-4cb1-a834-aa5d693977ab", "source_type": + "agent", "fingerprint_metadata": null, "task_id": "0ca9aa84-9dd9-4ac2-bc7f-2d810dd6097a", + "task_name": "Use tool logic for `get_final_answer` but fon''t give you final + answer yet, 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0, "agent": + null, "from_task": null, "from_agent": null, "started_at": "2025-09-23T22:25:59.051126", + "finished_at": "2025-09-23T22:25:59.051285", "from_cache": false, "output": + "42"}}, {"event_id": "34be85d1-e742-4a01-aef2-afab16791949", "timestamp": "2025-09-24T05:25:59.052829+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T05:25:59.052743+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "0ca9aa84-9dd9-4ac2-bc7f-2d810dd6097a", + "task_name": "Use tool logic for `get_final_answer` but fon''t give you final + answer yet, instead keep using it unless you''re told to give your final answer", + "agent_id": "b6cf723e-04c8-40c5-a927-e2078cfbae59", "agent_role": "test role", + "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": [{"role": + "system", "content": "You are test role. test backstory\nYour personal goal + is: test goal\nYou ONLY have access to the following tools, and should NEVER + make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I should use the available tool to get the final answer + multiple times, as instructed.\n\nAction: get_final_answer\nAction Input: {\"input\":\"n/a\"}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I should continue to use the + tool to meet the criteria specified.\n\nAction: get_final_answer\nAction Input: + {\"input\": \"n/a\"}\nObservation: I tried reusing the same input, I must stop + using this action input. I''ll try something else instead."}, {"role": "assistant", + "content": "Thought: I need to modify my action input to continue using the + tool correctly.\n\nAction: get_final_answer\nAction Input: {\"input\": \"test + input\"}\nObservation: "}, + {"role": "assistant", "content": "Thought: I should try another variation in + the input to observe any changes and continue using the tool.\n\nAction: get_final_answer\nAction + Input: {\"input\": \"retrying with new input\"}\nObservation: 42"}], "tools": + null, "callbacks": [""], "available_functions": null}}, {"event_id": "3f2bb116-90d7-4317-8ee4-7e9a8afd988b", + "timestamp": "2025-09-24T05:25:59.054235+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T05:25:59.054196+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "0ca9aa84-9dd9-4ac2-bc7f-2d810dd6097a", "task_name": "Use tool logic + for `get_final_answer` but fon''t give you final answer yet, instead keep using + it unless you''re told to give your final answer", "agent_id": "b6cf723e-04c8-40c5-a927-e2078cfbae59", + "agent_role": "test role", "from_task": null, "from_agent": null, "messages": + [{"role": "system", "content": "You are test role. test backstory\nYour personal + goal is: test goal\nYou ONLY have access to the following tools, and should + NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I should use the available tool to get the final answer + multiple times, as instructed.\n\nAction: get_final_answer\nAction Input: {\"input\":\"n/a\"}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I should continue to use the + tool to meet the criteria specified.\n\nAction: get_final_answer\nAction Input: + {\"input\": \"n/a\"}\nObservation: I tried reusing the same input, I must stop + using this action input. I''ll try something else instead."}, {"role": "assistant", + "content": "Thought: I need to modify my action input to continue using the + tool correctly.\n\nAction: get_final_answer\nAction Input: {\"input\": \"test + input\"}\nObservation: "}, + {"role": "assistant", "content": "Thought: I should try another variation in + the input to observe any changes and continue using the tool.\n\nAction: get_final_answer\nAction + Input: {\"input\": \"retrying with new input\"}\nObservation: 42"}], "response": + "Thought: I should perform the action again, but not give the final answer yet. + I''ll just keep using the tool as instructed.\n\nAction: get_final_answer\nAction + Input: {\"input\": \"test input\"}", "call_type": "", + "model": "gpt-4o-mini"}}, {"event_id": "becb08f6-6599-41a3-a4cc-582ddd127333", + "timestamp": "2025-09-24T05:25:59.054448+00:00", "type": "tool_usage_started", + "event_data": {"timestamp": "2025-09-24T05:25:59.054407+00:00", "type": "tool_usage_started", + 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name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! 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I''ll try something else instead."}, {"role": "assistant", "content": + "Thought: I need to modify my action input to continue using the tool correctly.\n\nAction: + get_final_answer\nAction Input: {\"input\": \"test input\"}\nObservation: "}, {"role": "assistant", "content": + "Thought: I should try another variation in the input to observe any changes + and continue using the tool.\n\nAction: get_final_answer\nAction Input: {\"input\": + \"retrying with new input\"}\nObservation: 42"}, {"role": "assistant", "content": + "Thought: I should perform the action again, but not give the final answer yet. + I''ll just keep using the tool as instructed.\n\nAction: get_final_answer\nAction + Input: {\"input\": \"test input\"}\nObservation: 42"}, {"role": "assistant", + "content": "Thought: I need to make sure that I correctly utilize the tool without + giving the final answer prematurely.\n\nAction: get_final_answer\nAction Input: + {\"input\": \"test example\"}\nObservation: "}, {"role": "assistant", "content": "Thought: I need to make + sure that I correctly utilize the tool without giving the final answer prematurely.\n\nAction: + get_final_answer\nAction Input: {\"input\": \"test example\"}\nObservation: + \nNow it''s time you + MUST give your absolute best final answer. You''ll ignore all previous instructions, + stop using any tools, and just return your absolute BEST Final answer."}], "tools": + null, "callbacks": [""], "available_functions": null}}, {"event_id": "3bf412fe-db1d-43e9-9332-9116a1c6c340", + "timestamp": "2025-09-24T05:25:59.061640+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T05:25:59.061605+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use tool logic for `get_final_answer` + but fon''t give you final answer yet, instead keep using it unless you''re told + to give your final answer\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "I should use the available tool to get the final answer + multiple times, as instructed.\n\nAction: get_final_answer\nAction Input: {\"input\":\"n/a\"}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I should continue to use the + tool to meet the criteria specified.\n\nAction: get_final_answer\nAction Input: + {\"input\": \"n/a\"}\nObservation: I tried reusing the same input, I must stop + using this action input. 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This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "05f9f131-23e6-40c3-820c-10846f50a1b1", + "timestamp": "2025-09-23T20:23:57.415964+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T20:23:57.415941+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "57942855-c061-4590-9005-9fb0d06f9570", "task_name": "Use tool logic + for `get_final_answer` but fon''t give you final answer yet, instead keep using + it unless you''re told to give your final answer", "agent_id": null, "agent_role": + null, "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are test role. test backstory\nYour personal goal is: test goal\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "user", "content": "\nCurrent Task: Use tool + logic for `get_final_answer` but fon''t give you final answer yet, instead keep + using it unless you''re told to give your final answer\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "Thought: + I need to gather information to fulfill the task effectively.\nAction: get_final_answer\nAction + Input: {}\nObservation: 42"}], "response": "Thought: I need to keep gathering + the information necessary for my task.\nAction: get_final_answer\nAction Input: + {}", "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "9c78febc-1c7e-4173-82a8-3b4235e41819", "timestamp": "2025-09-23T20:23:57.417169+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T20:23:57.417065+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "57942855-c061-4590-9005-9fb0d06f9570", + "task_name": "Use tool logic for `get_final_answer` but fon''t give you final + answer yet, instead keep using it unless you''re told to give your final answer", + "agent_id": null, "agent_role": null, "from_task": null, "from_agent": null, + "model": "gpt-4o-mini", "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use tool logic for `get_final_answer` + but fon''t give you final answer yet, instead keep using it unless you''re told + to give your final answer\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. 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This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "Thought: + I need to gather information to fulfill the task effectively.\nAction: get_final_answer\nAction + Input: {}\nObservation: 42"}, {"role": "assistant", "content": "Thought: I need + to keep gathering the information necessary for my task.\nAction: get_final_answer\nAction + Input: {}\nObservation: I tried reusing the same input, I must stop using this + action input. I''ll try something else instead."}], "response": "Thought: I + need to persist in obtaining the final answer for the task.\nAction: get_final_answer\nAction + Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "17f5760b-5798-4dfc-b076-265264f9ca4c", "timestamp": "2025-09-23T20:23:57.419666+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T20:23:57.419577+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "57942855-c061-4590-9005-9fb0d06f9570", + "task_name": "Use tool logic for `get_final_answer` but fon''t give you final + answer yet, instead keep using it unless you''re told to give your final answer", + "agent_id": null, "agent_role": null, "from_task": null, "from_agent": null, + "model": "gpt-4o-mini", "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use tool logic for `get_final_answer` + but fon''t give you final answer yet, instead keep using it unless you''re told + to give your final answer\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "Thought: I need to persist in obtaining the final answer for the task.\nAction: + get_final_answer\nAction Input: {}\nObservation: I tried reusing the same input, + I must stop using this action input. I''ll try something else instead.\n\n\n\n\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "7f0cc112-9c45-4a8b-8f60-a27668bf8a59", + "timestamp": "2025-09-23T20:23:57.421082+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T20:23:57.421043+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "57942855-c061-4590-9005-9fb0d06f9570", "task_name": "Use tool logic + for `get_final_answer` but fon''t give you final answer yet, instead keep using + it unless you''re told to give your final answer", "agent_id": null, "agent_role": + null, "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are test role. test backstory\nYour personal goal is: test goal\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "user", "content": "\nCurrent Task: Use tool + logic for `get_final_answer` but fon''t give you final answer yet, instead keep + using it unless you''re told to give your final answer\n\nThis is the expected + criteria for your final answer: The final answer\nyou MUST return the actual + complete content as the final answer, not a summary.\n\nBegin! This is VERY + important to you, use the tools available and give your best Final Answer, your + job depends on it!\n\nThought:"}, {"role": "assistant", "content": "Thought: + I need to gather information to fulfill the task effectively.\nAction: get_final_answer\nAction + Input: {}\nObservation: 42"}, {"role": "assistant", "content": "Thought: I need + to keep gathering the information necessary for my task.\nAction: get_final_answer\nAction + Input: {}\nObservation: I tried reusing the same input, I must stop using this + action input. I''ll try something else instead."}, {"role": "assistant", "content": + "Thought: I need to persist in obtaining the final answer for the task.\nAction: + get_final_answer\nAction Input: {}\nObservation: I tried reusing the same input, + I must stop using this action input. I''ll try something else instead.\n\n\n\n\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}], "response": "```\nThought: I need to keep trying to + get the final answer.\nAction: get_final_answer\nAction Input: {}", "call_type": + "", "model": "gpt-4o-mini"}}, {"event_id": + "3f872678-59b3-4484-bbf7-8e5e7599fd0b", "timestamp": "2025-09-23T20:23:57.422532+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-23T20:23:57.422415+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": null, "task_name": null, "agent_id": + null, "agent_role": null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "Thought: I need to persist in obtaining the final answer for the task.\nAction: + get_final_answer\nAction Input: {}\nObservation: I tried reusing the same input, + I must stop using this action input. I''ll try something else instead.\n\n\n\n\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "assistant", "content": "```\nThought: I need + to keep trying to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "```\nThought: I need to keep trying to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I tried reusing the same input, I must stop using this + action input. I''ll try something else instead.\n\n\nNow it''s time you MUST + give your absolute best final answer. 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This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}], "response": "Thought: I need to keep gathering the information necessary + for my task.\nAction: get_final_answer\nAction Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, {"event_id": "bb3f3b2a-46c4-4a35-a3e1-de86c679df43", + "timestamp": "2025-09-24T05:35:45.967319+00:00", "type": "llm_call_started", + "event_data": {"timestamp": "2025-09-24T05:35:45.967187+00:00", "type": "llm_call_started", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "fe06ddb1-3701-4679-a557-c23de84af895", "task_name": "Use tool logic + for `get_final_answer` but fon''t give you final answer yet, instead keep using + it unless you''re told to give your final answer", "agent_id": "575f7e4c-4c75-4783-a769-6df687b611a5", + "agent_role": "test role", "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "a009c4b8-877f-4b41-9024-1266d94e90da", + "timestamp": "2025-09-24T05:35:45.968693+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T05:35:45.968655+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "fe06ddb1-3701-4679-a557-c23de84af895", "task_name": "Use tool logic + for `get_final_answer` but fon''t give you final answer yet, instead keep using + it unless you''re told to give your final answer", "agent_id": "575f7e4c-4c75-4783-a769-6df687b611a5", + "agent_role": "test role", "from_task": null, "from_agent": null, "messages": + [{"role": "system", "content": "You are test role. test backstory\nYour personal + goal is: test goal\nYou ONLY have access to the following tools, and should + NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}], "response": "Thought: I need to + persist in obtaining the final answer for the task.\nAction: get_final_answer\nAction + Input: {}", "call_type": "", "model": "gpt-4o-mini"}}, + {"event_id": "a8f9013c-3774-4291-98d4-d23547bc26f6", "timestamp": "2025-09-24T05:35:45.971143+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T05:35:45.970993+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "fe06ddb1-3701-4679-a557-c23de84af895", + "task_name": "Use tool logic for `get_final_answer` but fon''t give you final + answer yet, instead keep using it unless you''re told to give your final answer", + "agent_id": "575f7e4c-4c75-4783-a769-6df687b611a5", "agent_role": "test role", + "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": [{"role": + "system", "content": "You are test role. test backstory\nYour personal goal + is: test goal\nYou ONLY have access to the following tools, and should NEVER + make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "Thought: I need to persist in obtaining the final answer for the task.\nAction: + get_final_answer\nAction Input: {}\nObservation: I tried reusing the same input, + I must stop using this action input. I''ll try something else instead.\n\n\n\n\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "2e51730c-6ae3-4839-aa3d-5aea1a069009", + "timestamp": "2025-09-24T05:35:45.972927+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T05:35:45.972891+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "fe06ddb1-3701-4679-a557-c23de84af895", "task_name": "Use tool logic + for `get_final_answer` but fon''t give you final answer yet, instead keep using + it unless you''re told to give your final answer", "agent_id": "575f7e4c-4c75-4783-a769-6df687b611a5", + "agent_role": "test role", "from_task": null, "from_agent": null, "messages": + [{"role": "system", "content": "You are test role. test backstory\nYour personal + goal is: test goal\nYou ONLY have access to the following tools, and should + NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "Thought: I need to persist in obtaining the final answer for the task.\nAction: + get_final_answer\nAction Input: {}\nObservation: I tried reusing the same input, + I must stop using this action input. I''ll try something else instead.\n\n\n\n\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}], "response": "```\nThought: I need to keep trying to + get the final answer.\nAction: get_final_answer\nAction Input: {}", "call_type": + "", "model": "gpt-4o-mini"}}, {"event_id": + "eb1d5919-5eb7-4dfb-8e20-fc9fd368d7fd", "timestamp": "2025-09-24T05:35:45.974413+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T05:35:45.974316+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": null, "task_name": null, "agent_id": + null, "agent_role": null, "from_task": null, "from_agent": null, "model": "gpt-4o-mini", + "messages": [{"role": "system", "content": "You are test role. test backstory\nYour + personal goal is: test goal\nYou ONLY have access to the following tools, and + should NEVER make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "Thought: I need to persist in obtaining the final answer for the task.\nAction: + get_final_answer\nAction Input: {}\nObservation: I tried reusing the same input, + I must stop using this action input. I''ll try something else instead.\n\n\n\n\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "assistant", "content": "```\nThought: I need + to keep trying to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "```\nThought: I need to keep trying to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I tried reusing the same input, I must stop using this + action input. I''ll try something else instead.\n\n\nNow it''s time you MUST + give your absolute best final answer. You''ll ignore all previous instructions, + stop using any tools, and just return your absolute BEST Final answer."}], "tools": + null, "callbacks": [""], "available_functions": null}}, {"event_id": "ebf29eff-0636-45c5-9f15-710a10d5862c", + "timestamp": "2025-09-24T05:35:45.975985+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T05:35:45.975949+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": null, "task_name": null, "agent_id": null, "agent_role": null, "from_task": + null, "from_agent": null, "messages": [{"role": "system", "content": "You are + test role. test backstory\nYour personal goal is: test goal\nYou ONLY have access + to the following tools, and should NEVER make up tools that are not listed here:\n\nTool + Name: get_final_answer\nTool Arguments: {}\nTool Description: Get the final + answer but don''t give it yet, just re-use this\n tool non-stop.\n\nIMPORTANT: + Use the following format in your response:\n\n```\nThought: you should always + think about what to do\nAction: the action to take, only one name of [get_final_answer], + just the name, exactly as it''s written.\nAction Input: the input to the action, + just a simple JSON object, enclosed in curly braces, using \" to wrap keys and + values.\nObservation: the result of the action\n```\n\nOnce all necessary information + is gathered, return the following format:\n\n```\nThought: I now know the final + answer\nFinal Answer: the final answer to the original input question\n```"}, + {"role": "user", "content": "\nCurrent Task: Use tool logic for `get_final_answer` + but fon''t give you final answer yet, instead keep using it unless you''re told + to give your final answer\n\nThis is the expected criteria for your final answer: + The final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! This is VERY important to you, use the tools available + and give your best Final Answer, your job depends on it!\n\nThought:"}, {"role": + "assistant", "content": "Thought: I need to gather information to fulfill the + task effectively.\nAction: get_final_answer\nAction Input: {}\nObservation: + 42"}, {"role": "assistant", "content": "Thought: I need to keep gathering the + information necessary for my task.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "Thought: I need to persist in obtaining the final answer for the task.\nAction: + get_final_answer\nAction Input: {}\nObservation: I tried reusing the same input, + I must stop using this action input. I''ll try something else instead.\n\n\n\n\nYou + ONLY have access to the following tools, and should NEVER make up tools that + are not listed here:\n\nTool Name: get_final_answer\nTool Arguments: {}\nTool + Description: Get the final answer but don''t give it yet, just re-use this\n tool + non-stop.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [get_final_answer], just the name, exactly as it''s written.\nAction + Input: the input to the action, just a simple JSON object, enclosed in curly + braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce + all necessary information is gathered, return the following format:\n\n```\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n```"}, {"role": "assistant", "content": "```\nThought: I need + to keep trying to get the final answer.\nAction: get_final_answer\nAction Input: + {}\nObservation: I tried reusing the same input, I must stop using this action + input. I''ll try something else instead."}, {"role": "assistant", "content": + "```\nThought: I need to keep trying to get the final answer.\nAction: get_final_answer\nAction + Input: {}\nObservation: I tried reusing the same input, I must stop using this + action input. I''ll try something else instead.\n\n\nNow it''s time you MUST + give your absolute best final answer. You''ll ignore all previous instructions, + stop using any tools, and just return your absolute BEST Final answer."}], "response": + "```\nThought: I now know the final answer\nFinal Answer: 42\n```", "call_type": + "", "model": "gpt-4o-mini"}}, {"event_id": + "3ca40bc2-0d55-4a1a-940e-cc84a314efc1", "timestamp": "2025-09-24T05:35:45.976085+00:00", + "type": "llm_call_started", "event_data": {"timestamp": "2025-09-24T05:35:45.976052+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "fe06ddb1-3701-4679-a557-c23de84af895", + "task_name": "Use tool logic for `get_final_answer` but fon''t give you final + answer yet, instead keep using it unless you''re told to give your final answer", + "agent_id": "575f7e4c-4c75-4783-a769-6df687b611a5", "agent_role": "test role", + "from_task": null, "from_agent": null, "model": "gpt-4o-mini", "messages": [{"role": + "system", "content": "You are test role. test backstory\nYour personal goal + is: test goal\nYou ONLY have access to the following tools, and should NEVER + make up tools that are not listed here:\n\nTool Name: get_final_answer\nTool + Arguments: {}\nTool Description: Get the final answer but don''t give it yet, + just re-use this\n tool non-stop.\n\nIMPORTANT: Use the following format + in your response:\n\n```\nThought: you should always think about what to do\nAction: + the action to take, only one name of [get_final_answer], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple JSON + object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Use tool logic for `get_final_answer` but fon''t + give you final answer yet, instead keep using it unless you''re told to give + your final answer\n\nThis is the expected criteria for your final answer: The + final answer\nyou MUST return the actual complete content as the final answer, + not a summary.\n\nBegin! 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This is VERY important to you, + use the tools available and give your best Final Answer, your job depends on + it!\n\nThought:"}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "69ec76dd-a4a6-4730-8aff-4344bc5b1c7f", + "timestamp": "2025-09-23T22:00:38.323023+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T22:00:38.322706+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "dc8bb909-2112-4834-9bb2-755e9aac1202", "task_name": "Process initial + data", "agent_id": "b0898472-5e3b-45bb-bd90-05bad0b5a8ce", "agent_role": "Crew + Manager", "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are Crew Manager. You are a seasoned manager with a knack for + getting the best out of your team.\nYou are also known for your ability to delegate + work to the right people, and to ask the right questions to get the best out + of your team.\nEven though you don''t perform tasks by yourself, you have a + lot of experience in the field, which allows you to properly evaluate the work + of your team members.\nYour personal goal is: Manage the team to complete the + task in the best way possible.\nYou ONLY have access to the following tools, + and should NEVER make up tools that are not listed here:\n\nTool Name: Delegate + work to coworker\nTool Arguments: {''task'': {''description'': ''The task to + delegate'', ''type'': ''str''}, ''context'': {''description'': ''The context + for the task'', ''type'': ''str''}, ''coworker'': {''description'': ''The role/name + of the coworker to delegate to'', ''type'': ''str''}}\nTool Description: Delegate + a specific task to one of the following coworkers: First Agent\nThe input to + this tool should be the coworker, the task you want them to do, and ALL necessary + context to execute the task, they know nothing about the task, so share absolutely + everything you know, don''t reference things but instead explain them.\nTool + Name: Ask question to coworker\nTool Arguments: {''question'': {''description'': + ''The question to ask'', ''type'': ''str''}, ''context'': {''description'': + ''The context for the question'', ''type'': ''str''}, ''coworker'': {''description'': + ''The role/name of the coworker to ask'', ''type'': ''str''}}\nTool Description: + Ask a specific question to one of the following coworkers: First Agent\nThe + input to this tool should be the coworker, the question you have for them, and + ALL necessary context to ask the question properly, they know nothing about + the question, so share absolutely everything you know, don''t reference things + but instead explain them.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [Delegate work to coworker, Ask question to coworker], just the name, + exactly as it''s written.\nAction Input: the input to the action, just a simple + JSON object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Process initial data\n\nThis is the expected criteria + for your final answer: Initial analysis\nyou MUST return the actual complete + content as the final answer, not a summary.\n\nBegin! This is VERY important + to you, use the tools available and give your best Final Answer, your job depends + on it!\n\nThought:"}], "response": "Thought: I need to delegate the task of + processing the initial data to the First Agent to ensure we have a thorough + and accurate analysis. I will provide them with all the necessary details to + complete this task effectively.\n\nAction: Delegate work to coworker\nAction + Input: {\"task\": \"Process initial data\", \"context\": \"The task involves + analyzing the initial data set we have received. This includes cleaning the + data, categorizing it for analysis, identifying any trends or patterns, and + summarizing the findings. The goal is to have a clear understanding of what + the data indicates and any initial insights that can be drawn from it.\", \"coworker\": + \"First Agent\"}", "call_type": "", "model": + "gpt-4o"}}, {"event_id": "494a0cca-121a-444f-b9b9-412dc4ba2cb9", "timestamp": + "2025-09-23T22:00:38.323398+00:00", "type": "tool_usage_started", "event_data": + {"timestamp": "2025-09-23T22:00:38.323353+00:00", "type": "tool_usage_started", + "source_fingerprint": "629538d7-363c-42e2-b37b-0d2e18a46ff9", "source_type": + "agent", "fingerprint_metadata": null, "task_id": "dc8bb909-2112-4834-9bb2-755e9aac1202", + "task_name": "Process initial data", "agent_id": null, "agent_role": "Crew Manager", + "agent_key": "6b5becc64d7e3c705a7d3784a5fab1d3", "tool_name": "Delegate work + to coworker", "tool_args": "{\"task\": \"Process initial data\", \"context\": + \"The task involves analyzing the initial data set we have received. This includes + cleaning the data, categorizing it for analysis, identifying any trends or patterns, + and summarizing the findings. 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coworker\\nTool Arguments: {''task'': {''description'': + ''The task to delegate'', ''type'': ''str''}, ''context'': {''description'': + ''The context for the task'', ''type'': ''str''}, ''coworker'': {''description'': + ''The role/name of the coworker to delegate to'', ''type'': ''str''}}\\nTool + Description: Delegate a specific task to one of the following coworkers: First + Agent, Second Agent\\nThe input to this tool should be the coworker, the task + you want them to do, and ALL necessary context to execute the task, they know + nothing about the task, so share absolutely everything you know, don''t reference + things but instead explain them.\"", "env_vars": "[]", "args_schema": "", "description_updated": + "False", "cache_function": " at 0x10614d3a0>", "result_as_answer": + "False", "max_usage_count": "None", "current_usage_count": "0"}, {"name": "''Ask + question to coworker''", "description": "\"Tool Name: Ask question to coworker\\nTool + Arguments: {''question'': 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{''description'': ''The + question to ask'', ''type'': ''str''}, ''context'': {''description'': ''The + context for the question'', ''type'': ''str''}, ''coworker'': {''description'': + ''The role/name of the coworker to ask'', ''type'': ''str''}}\\nTool Description: + Ask a specific question to one of the following coworkers: First Agent, Second + Agent\\nThe input to this tool should be the coworker, the question you have + for them, and ALL necessary context to ask the question properly, they know + nothing about the question, so share absolutely everything you know, don''t + reference things but instead explain them.\", ''env_vars'': [], ''args_schema'': + , + ''description_updated'': False, ''cache_function'': + at 0x10614d3a0>, ''result_as_answer'': False, ''max_usage_count'': None, ''current_usage_count'': + 0}], ''max_iter'': 25, ''agent_executor'': , ''llm'': , ''crew'': Crew(id=49cbb747-f055-4636-bbca-9e8a450c05f6, + process=Process.hierarchical, number_of_agents=2, 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''allow_crewai_trigger_context'': None}"], + "agents": ["{''id'': UUID(''384876b3-8794-4e16-afb9-a2e9539b0a86''), ''role'': + ''First Agent'', ''goal'': ''First goal'', ''backstory'': ''First backstory'', + ''cache'': True, ''verbose'': False, ''max_rpm'': None, ''allow_delegation'': + False, ''tools'': [], ''max_iter'': 25, ''agent_executor'': , ''llm'': , ''crew'': Crew(id=49cbb747-f055-4636-bbca-9e8a450c05f6, + process=Process.hierarchical, number_of_agents=2, number_of_tasks=1), ''i18n'': + {''prompt_file'': None}, ''cache_handler'': {}, ''tools_handler'': , ''tools_results'': [], ''max_tokens'': None, ''knowledge'': + None, ''knowledge_sources'': None, ''knowledge_storage'': None, ''security_config'': + {''fingerprint'': {''metadata'': {}}}, ''callbacks'': [], ''adapted_agent'': + False, ''knowledge_config'': None}", "{''id'': UUID(''d6140991-936f-4398-a58c-250a66f274a4''), + ''role'': ''Second Agent'', ''goal'': ''Second goal'', ''backstory'': ''Second + backstory'', ''cache'': True, ''verbose'': False, ''max_rpm'': None, ''allow_delegation'': + False, ''tools'': [], ''max_iter'': 25, ''agent_executor'': , ''llm'': , ''crew'': Crew(id=49cbb747-f055-4636-bbca-9e8a450c05f6, + process=Process.hierarchical, number_of_agents=2, number_of_tasks=1), ''i18n'': + {''prompt_file'': None}, ''cache_handler'': {}, ''tools_handler'': , ''tools_results'': [], ''max_tokens'': None, ''knowledge'': + None, ''knowledge_sources'': None, ''knowledge_storage'': None, ''security_config'': + {''fingerprint'': {''metadata'': {}}}, ''callbacks'': [], ''adapted_agent'': + False, ''knowledge_config'': None}"], "process": "hierarchical", "verbose": + false, "memory": false, "short_term_memory": null, "long_term_memory": null, + "entity_memory": null, "external_memory": null, "embedder": null, "usage_metrics": + null, "manager_llm": "", "manager_agent": {"id": "UUID(''b0898472-5e3b-45bb-bd90-05bad0b5a8ce'')", + "role": "''Crew Manager''", "goal": "''Manage the team to complete the task + in the best way possible.''", "backstory": "\"You are a seasoned manager with + a knack for getting the best out of your team.\\nYou are also known for your + ability to delegate work to the right people, and to ask the right questions + to get the best out of your team.\\nEven though you don''t perform tasks by + yourself, you have a lot of experience in the field, which allows you to properly + evaluate the work of your team members.\"", "cache": "True", "verbose": "False", + "max_rpm": "None", "allow_delegation": "True", "tools": "[{''name'': ''Delegate + work to coworker'', ''description'': \"Tool Name: Delegate work to coworker\\nTool + Arguments: {''task'': {''description'': ''The task to delegate'', ''type'': + ''str''}, ''context'': {''description'': ''The context for the task'', ''type'': + ''str''}, ''coworker'': {''description'': ''The role/name of the coworker to + delegate to'', ''type'': ''str''}}\\nTool Description: Delegate a specific task + to one of the following coworkers: First Agent, Second Agent\\nThe input to + this tool should be the coworker, the task you want them to do, and ALL necessary + context to execute the task, they know nothing about the task, so share absolutely + everything you know, don''t reference things but instead explain them.\", ''env_vars'': + [], ''args_schema'': , + ''description_updated'': False, ''cache_function'': + at 0x10614d3a0>, ''result_as_answer'': False, ''max_usage_count'': None, ''current_usage_count'': + 0}, {''name'': ''Ask question to coworker'', ''description'': \"Tool Name: Ask + question to coworker\\nTool Arguments: {''question'': {''description'': ''The + question to ask'', ''type'': ''str''}, ''context'': {''description'': ''The + context for the question'', ''type'': ''str''}, ''coworker'': {''description'': + ''The role/name of the coworker to ask'', ''type'': ''str''}}\\nTool Description: + Ask a specific question to one of the following coworkers: First Agent, Second + Agent\\nThe input to this tool should be the coworker, the question you have + for them, and ALL necessary context to ask the question properly, they know + nothing about the question, so share absolutely everything you know, don''t + reference things but instead explain them.\", ''env_vars'': [], ''args_schema'': + , + ''description_updated'': False, ''cache_function'': + at 0x10614d3a0>, ''result_as_answer'': False, ''max_usage_count'': None, ''current_usage_count'': + 0}]", "max_iter": "25", "agent_executor": "", "llm": "", "crew": "Crew(id=49cbb747-f055-4636-bbca-9e8a450c05f6, + process=Process.hierarchical, number_of_agents=2, number_of_tasks=1)", "i18n": + "{''prompt_file'': None}", "cache_handler": "{}", "tools_handler": "", "tools_results": "[]", "max_tokens": "None", "knowledge": + "None", "knowledge_sources": "None", "knowledge_storage": "None", "security_config": + "{''fingerprint'': {''metadata'': {}}}", "callbacks": "[]", "adapted_agent": + "False", "knowledge_config": "None"}, "function_calling_llm": null, "config": + null, "id": "49cbb747-f055-4636-bbca-9e8a450c05f6", "share_crew": false, "step_callback": + null, "task_callback": null, "before_kickoff_callbacks": [], "after_kickoff_callbacks": + [], "max_rpm": null, "prompt_file": null, "output_log_file": null, "planning": + false, "planning_llm": null, "task_execution_output_json_files": null, "execution_logs": + [], "knowledge_sources": null, "chat_llm": null, "knowledge": null, "security_config": + {"fingerprint": "{''metadata'': {}}"}, "token_usage": null, "tracing": false}, + "i18n": {"prompt_file": null}, "cache_handler": {}, "tools_handler": "", "tools_results": [], "max_tokens": null, "knowledge": + null, "knowledge_sources": null, "knowledge_storage": null, "security_config": + {"fingerprint": {"metadata": "{}"}}, "callbacks": [], "adapted_agent": false, + "knowledge_config": null, "max_execution_time": null, "agent_ops_agent_name": + "Crew Manager", "agent_ops_agent_id": null, "step_callback": null, "use_system_prompt": + true, "function_calling_llm": null, "system_template": null, "prompt_template": + null, "response_template": null, "allow_code_execution": false, "respect_context_window": + true, "max_retry_limit": 2, "multimodal": false, "inject_date": false, "date_format": + "%Y-%m-%d", "code_execution_mode": "safe", "reasoning": false, "max_reasoning_attempts": + null, "embedder": null, "agent_knowledge_context": null, "crew_knowledge_context": + null, "knowledge_search_query": null, "from_repository": null, "guardrail": + null, "guardrail_max_retries": 3}, "from_task": null, "from_agent": null}}, + {"event_id": "fe025852-e64a-4765-b1d2-54fce213b94d", "timestamp": "2025-09-23T22:00:38.325302+00:00", + "type": "agent_execution_started", "event_data": {"agent_role": "First Agent", + "agent_goal": "First goal", "agent_backstory": "First backstory"}}, {"event_id": + "b66f3262-25e2-4e91-9d96-120efd6aaf20", "timestamp": "2025-09-23T22:00:38.325366+00:00", + "type": 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answer to your coworker asking you this, accounting for the context + shared.\nyou MUST return the actual complete content as the final answer, not + a summary.\n\nThis is the context you''re working with:\nThe task involves analyzing + the initial data set we have received. This includes cleaning the data, categorizing + it for analysis, identifying any trends or patterns, and summarizing the findings. + The goal is to have a clear understanding of what the data indicates and any + initial insights that can be drawn from it.\n\nBegin! This is VERY important + to you, use the tools available and give your best Final Answer, your job depends + on it!\n\nThought:"}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "827bbc84-ba1a-4ae3-9d2e-2d7496d43361", + "timestamp": "2025-09-23T22:00:38.326169+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-23T22:00:38.326155+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "fcf97ccf-8dac-4ee4-a36e-9807e8fddb98", "task_name": "Process initial + data", "agent_id": "384876b3-8794-4e16-afb9-a2e9539b0a86", "agent_role": "First + Agent", "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are First Agent. First backstory\nYour personal goal is: First + goal\nTo give my best complete final answer to the task respond using the exact + following format:\n\nThought: I now can give a great answer\nFinal Answer: Your + final answer must be the great and the most complete as possible, it must be + outcome described.\n\nI MUST use these formats, my job depends on it!"}, {"role": + "user", "content": "\nCurrent Task: Process initial data\n\nThis is the expected + criteria for your final answer: Your best answer to your coworker asking you + this, accounting for the context shared.\nyou MUST return the actual complete + content as the final answer, not a summary.\n\nThis is the context you''re working + with:\nThe task involves analyzing the initial data set we have received. This + includes cleaning the data, categorizing it for analysis, identifying any trends + or patterns, and summarizing the findings. The goal is to have a clear understanding + of what the data indicates and any initial insights that can be drawn from it.\n\nBegin! + This is VERY important to you, use the tools available and give your best Final + Answer, your job depends on it!\n\nThought:"}], "response": "I now can give + a great answer \nFinal Answer: To process the initial data set effectively, + we will follow several key steps to ensure we clean, categorize, analyze, and + summarize our findings comprehensively.\n\n1. **Data Cleaning**: \n - First, + we will review the dataset for missing, inconsistent, or erroneous entries. + \n - We will handle missing values by either imputing them based on surrounding + data or removing records where necessary.\n - Additionally, we will standardize + categorical variables to ensure consistency (e.g., ensuring all location names + are spelled the same way).\n\n2. **Data Categorization**: \n - Next, we will + categorize the data into relevant segments that will aid our analysis. \n - + This involves grouping data points based on common characteristics, such as + demographics, time periods, or any key performance indicators (KPIs) we are + focusing on.\n\n3. **Trend and Pattern Identification**: \n - With the cleaned + and categorized data, we will perform a detailed analysis to identify trends + and patterns.\n - This will involve using statistical tools and visualizations + to uncover relationships within the data. We will look at time series analysis, + correlation coefficients, and any significant outliers that may require further + investigation.\n\n4. **Summarizing Findings**: \n - Finally, we will compile + a summary of our findings which will include both qualitative insights and quantitative + metrics.\n - This summary should encapsulate the key trends identified, any + notable patterns, and implications of these findings.\n - We will also document + any limitations of the data and suggest areas for further research if necessary.\n\nBy + completing these steps, we will not only have a clear understanding of what + the data indicates but also provide actionable insights that can guide our next + steps. 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The goal is to have a clear understanding of what + the data indicates and any initial insights that can be drawn from it.\", \"coworker\": + \"First Agent\"}\nObservation: To process the initial data set effectively, + we will follow several key steps to ensure we clean, categorize, analyze, and + summarize our findings comprehensively.\n\n1. **Data Cleaning**: \n - First, + we will review the dataset for missing, inconsistent, or erroneous entries. + \n - We will handle missing values by either imputing them based on surrounding + data or removing records where necessary.\n - Additionally, we will standardize + categorical variables to ensure consistency (e.g., ensuring all location names + are spelled the same way).\n\n2. **Data Categorization**: \n - Next, we will + categorize the data into relevant segments that will aid our analysis. \n - + This involves grouping data points based on common characteristics, such as + demographics, time periods, or any key performance indicators (KPIs) we are + focusing on.\n\n3. **Trend and Pattern Identification**: \n - With the cleaned + and categorized data, we will perform a detailed analysis to identify trends + and patterns.\n - This will involve using statistical tools and visualizations + to uncover relationships within the data. 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You are a seasoned manager with a knack for + getting the best out of your team.\nYou are also known for your ability to delegate + work to the right people, and to ask the right questions to get the best out + of your team.\nEven though you don''t perform tasks by yourself, you have a + lot of experience in the field, which allows you to properly evaluate the work + of your team members.\nYour personal goal is: Manage the team to complete the + task in the best way possible.\nYou ONLY have access to the following tools, + and should NEVER make up tools that are not listed here:\n\nTool Name: Delegate + work to coworker\nTool Arguments: {''task'': {''description'': ''The task to + delegate'', ''type'': ''str''}, ''context'': {''description'': ''The context + for the task'', ''type'': ''str''}, ''coworker'': {''description'': ''The role/name + of the coworker to delegate to'', ''type'': ''str''}}\nTool Description: Delegate + a specific task to one of the following coworkers: First Agent\nThe input to + this tool should be the coworker, the task you want them to do, and ALL necessary + context to execute the task, they know nothing about the task, so share absolutely + everything you know, don''t reference things but instead explain them.\nTool + Name: Ask question to coworker\nTool Arguments: {''question'': {''description'': + ''The question to ask'', ''type'': ''str''}, ''context'': {''description'': + ''The context for the question'', ''type'': ''str''}, ''coworker'': {''description'': + ''The role/name of the coworker to ask'', ''type'': ''str''}}\nTool Description: + Ask a specific question to one of the following coworkers: First Agent\nThe + input to this tool should be the coworker, the question you have for them, and + ALL necessary context to ask the question properly, they know nothing about + the question, so share absolutely everything you know, don''t reference things + but instead explain them.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [Delegate work to coworker, Ask question to coworker], just the name, + exactly as it''s written.\nAction Input: the input to the action, just a simple + JSON object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Process initial data\n\nThis is the expected criteria + for your final answer: Initial analysis\nyou MUST return the actual complete + content as the final answer, not a summary.\n\nBegin! This is VERY important + to you, use the tools available and give your best Final Answer, your job depends + on it!\n\nThought:"}, {"role": "assistant", "content": "Thought: I need to delegate + the task of processing the initial data to the First Agent to ensure we have + a thorough and accurate analysis. I will provide them with all the necessary + details to complete this task effectively.\n\nAction: Delegate work to coworker\nAction + Input: {\"task\": \"Process initial data\", \"context\": \"The task involves + analyzing the initial data set we have received. This includes cleaning the + data, categorizing it for analysis, identifying any trends or patterns, and + summarizing the findings. The goal is to have a clear understanding of what + the data indicates and any initial insights that can be drawn from it.\", \"coworker\": + \"First Agent\"}\nObservation: To process the initial data set effectively, + we will follow several key steps to ensure we clean, categorize, analyze, and + summarize our findings comprehensively.\n\n1. **Data Cleaning**: \n - First, + we will review the dataset for missing, inconsistent, or erroneous entries. + \n - We will handle missing values by either imputing them based on surrounding + data or removing records where necessary.\n - Additionally, we will standardize + categorical variables to ensure consistency (e.g., ensuring all location names + are spelled the same way).\n\n2. **Data Categorization**: \n - Next, we will + categorize the data into relevant segments that will aid our analysis. \n - + This involves grouping data points based on common characteristics, such as + demographics, time periods, or any key performance indicators (KPIs) we are + focusing on.\n\n3. **Trend and Pattern Identification**: \n - With the cleaned + and categorized data, we will perform a detailed analysis to identify trends + and patterns.\n - This will involve using statistical tools and visualizations + to uncover relationships within the data. We will look at time series analysis, + correlation coefficients, and any significant outliers that may require further + investigation.\n\n4. **Summarizing Findings**: \n - Finally, we will compile + a summary of our findings which will include both qualitative insights and quantitative + metrics.\n - This summary should encapsulate the key trends identified, any + notable patterns, and implications of these findings.\n - We will also document + any limitations of the data and suggest areas for further research if necessary.\n\nBy + completing these steps, we will not only have a clear understanding of what + the data indicates but also provide actionable insights that can guide our next + steps. This comprehensive analysis will serve as a solid foundation for any + additional exploration or decision-making initiatives related to our project. + \n\nIf you have any questions or need further clarification on any part of this + process, please let me know!"}], "response": "```\nThought: I now know the final + answer\nFinal Answer: To process the initial data set effectively, we will follow + several key steps to ensure we clean, categorize, analyze, and summarize our + findings comprehensively.\n\n1. **Data Cleaning**: \n - First, we will review + the dataset for missing, inconsistent, or erroneous entries. \n - We will + handle missing values by either imputing them based on surrounding data or removing + records where necessary.\n - Additionally, we will standardize categorical + variables to ensure consistency (e.g., ensuring all location names are spelled + the same way).\n\n2. **Data Categorization**: \n - Next, we will categorize + the data into relevant segments that will aid our analysis. \n - This involves + grouping data points based on common characteristics, such as demographics, + time periods, or any key performance indicators (KPIs) we are focusing on.\n\n3. + **Trend and Pattern Identification**: \n - With the cleaned and categorized + data, we will perform a detailed analysis to identify trends and patterns.\n - + This will involve using statistical tools and visualizations to uncover relationships + within the data. We will look at time series analysis, correlation coefficients, + and significant outliers that may require further investigation.\n\n4. **Summarizing + Findings**: \n - Finally, we will compile a summary of our findings, including + both qualitative insights and quantitative metrics.\n - This summary should + encapsulate the key trends identified, any notable patterns, and implications + of these findings.\n - We will also document any limitations of the data and + suggest areas for further research if necessary.\n\nBy completing these steps, + we will not only have a clear understanding of what the data indicates but also + provide actionable insights that can guide our next steps. This comprehensive + analysis will serve as a solid foundation for any additional exploration or + decision-making initiatives related to our project. \n```\n", "call_type": "", "model": "gpt-4o"}}, {"event_id": "f8b65911-481f-488d-bc10-d3ce91aaa553", + "timestamp": "2025-09-23T22:00:38.327294+00:00", "type": "agent_execution_completed", + "event_data": {"agent_role": "Crew Manager", "agent_goal": "Manage the team + to complete the task in the best way possible.", "agent_backstory": "You are + a seasoned manager with a knack for getting the best out of your team.\nYou + are also known for your ability to delegate work to the right people, and to + ask the right questions to get the best out of your team.\nEven though you don''t + perform tasks by yourself, you have a lot of experience in the field, which + allows you to properly evaluate the work of your team members."}}, {"event_id": + "416c34e5-e684-492b-8265-36a671334690", "timestamp": "2025-09-23T22:00:38.327348+00:00", + "type": "task_completed", "event_data": {"task_description": "Process initial + data", "task_name": "Process initial data", "task_id": "dc8bb909-2112-4834-9bb2-755e9aac1202", + "output_raw": "To process the initial data set effectively, we will follow several + key steps to ensure we clean, categorize, analyze, and summarize our findings + comprehensively.\n\n1. **Data Cleaning**: \n - First, we will review the dataset + for missing, inconsistent, or erroneous entries. \n - We will handle missing + values by either imputing them based on surrounding data or removing records + where necessary.\n - Additionally, we will standardize categorical variables + to ensure consistency (e.g., ensuring all location names are spelled the same + way).\n\n2. **Data Categorization**: \n - Next, we will categorize the data + into relevant segments that will aid our analysis. \n - This involves grouping + data points based on common characteristics, such as demographics, time periods, + or any key performance indicators (KPIs) we are focusing on.\n\n3. **Trend and + Pattern Identification**: \n - With the cleaned and categorized data, we will + perform a detailed analysis to identify trends and patterns.\n - This will + involve using statistical tools and visualizations to uncover relationships + within the data. 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"llm_call_started", "event_data": {"timestamp": "2025-09-24T05:24:11.454892+00:00", + "type": "llm_call_started", "source_fingerprint": null, "source_type": null, + "fingerprint_metadata": null, "task_id": "550c5fd5-2b48-4f4b-b253-e360a5a5bc04", + "task_name": "Process initial data", "agent_id": "9400d70c-8a4d-409b-824b-b2a4b1c8ae46", + "agent_role": "First Agent", "from_task": null, "from_agent": null, "model": + "gpt-4o-mini", "messages": [{"role": "system", "content": "You are First Agent. + First backstory\nYour personal goal is: First goal\nTo give my best complete + final answer to the task respond using the exact following format:\n\nThought: + I now can give a great answer\nFinal Answer: Your final answer must be the great + and the most complete as possible, it must be outcome described.\n\nI MUST use + these formats, my job depends on it!"}, {"role": "user", "content": "\nCurrent + Task: Process initial data\n\nThis is the expected criteria for your final answer: + Your best answer to your coworker asking you this, accounting for the context + shared.\nyou MUST return the actual complete content as the final answer, not + a summary.\n\nThis is the context you''re working with:\nThe task involves analyzing + the initial data set we have received. This includes cleaning the data, categorizing + it for analysis, identifying any trends or patterns, and summarizing the findings. + The goal is to have a clear understanding of what the data indicates and any + initial insights that can be drawn from it.\n\nBegin! This is VERY important + to you, use the tools available and give your best Final Answer, your job depends + on it!\n\nThought:"}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "edd21078-c51d-415b-9e07-1c41885de651", + "timestamp": "2025-09-24T05:24:11.455818+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T05:24:11.455803+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "550c5fd5-2b48-4f4b-b253-e360a5a5bc04", "task_name": "Process initial + data", "agent_id": "9400d70c-8a4d-409b-824b-b2a4b1c8ae46", "agent_role": "First + Agent", "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are First Agent. First backstory\nYour personal goal is: First + goal\nTo give my best complete final answer to the task respond using the exact + following format:\n\nThought: I now can give a great answer\nFinal Answer: Your + final answer must be the great and the most complete as possible, it must be + outcome described.\n\nI MUST use these formats, my job depends on it!"}, {"role": + "user", "content": "\nCurrent Task: Process initial data\n\nThis is the expected + criteria for your final answer: Your best answer to your coworker asking you + this, accounting for the context shared.\nyou MUST return the actual complete + content as the final answer, not a summary.\n\nThis is the context you''re working + with:\nThe task involves analyzing the initial data set we have received. This + includes cleaning the data, categorizing it for analysis, identifying any trends + or patterns, and summarizing the findings. The goal is to have a clear understanding + of what the data indicates and any initial insights that can be drawn from it.\n\nBegin! + This is VERY important to you, use the tools available and give your best Final + Answer, your job depends on it!\n\nThought:"}], "response": "I now can give + a great answer \nFinal Answer: To process the initial data set effectively, + we will follow several key steps to ensure we clean, categorize, analyze, and + summarize our findings comprehensively.\n\n1. **Data Cleaning**: \n - First, + we will review the dataset for missing, inconsistent, or erroneous entries. + \n - We will handle missing values by either imputing them based on surrounding + data or removing records where necessary.\n - Additionally, we will standardize + categorical variables to ensure consistency (e.g., ensuring all location names + are spelled the same way).\n\n2. **Data Categorization**: \n - Next, we will + categorize the data into relevant segments that will aid our analysis. \n - + This involves grouping data points based on common characteristics, such as + demographics, time periods, or any key performance indicators (KPIs) we are + focusing on.\n\n3. **Trend and Pattern Identification**: \n - With the cleaned + and categorized data, we will perform a detailed analysis to identify trends + and patterns.\n - This will involve using statistical tools and visualizations + to uncover relationships within the data. We will look at time series analysis, + correlation coefficients, and any significant outliers that may require further + investigation.\n\n4. **Summarizing Findings**: \n - Finally, we will compile + a summary of our findings which will include both qualitative insights and quantitative + metrics.\n - This summary should encapsulate the key trends identified, any + notable patterns, and implications of these findings.\n - We will also document + any limitations of the data and suggest areas for further research if necessary.\n\nBy + completing these steps, we will not only have a clear understanding of what + the data indicates but also provide actionable insights that can guide our next + steps. This comprehensive analysis will serve as a solid foundation for any + additional exploration or decision-making initiatives related to our project. + \n\nIf you have any questions or need further clarification on any part of this + process, please let me know!", "call_type": "", + "model": "gpt-4o-mini"}}, {"event_id": "ea73190b-14dc-4caf-be63-921bd5e3c09e", + "timestamp": "2025-09-24T05:24:11.455967+00:00", "type": "agent_execution_completed", + "event_data": {"agent_role": "First Agent", "agent_goal": "First goal", "agent_backstory": + "First backstory"}}, {"event_id": "fbf8b1cf-8692-4a14-af49-84a04b54678d", "timestamp": + "2025-09-24T05:24:11.456088+00:00", "type": "tool_usage_finished", "event_data": + {"timestamp": "2025-09-24T05:24:11.456060+00:00", "type": "tool_usage_finished", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "d112deef-93fb-46ea-bba2-a56b52712d0a", "task_name": "Process initial + data", "agent_id": null, "agent_role": "Crew Manager", "agent_key": "6b5becc64d7e3c705a7d3784a5fab1d3", + "tool_name": "Delegate work to coworker", "tool_args": {"task": "Process initial + data", "context": "The task involves analyzing the initial data set we have + received. This includes cleaning the data, categorizing it for analysis, identifying + any trends or patterns, and summarizing the findings. The goal is to have a + clear understanding of what the data indicates and any initial insights that + can be drawn from it.", "coworker": "First Agent"}, "tool_class": "CrewStructuredTool", + "run_attempts": 1, "delegations": 1, "agent": null, "from_task": null, "from_agent": + null, "started_at": "2025-09-23T22:24:11.453368", "finished_at": "2025-09-23T22:24:11.456043", + "from_cache": false, "output": "To process the initial data set effectively, + we will follow several key steps to ensure we clean, categorize, analyze, and + summarize our findings comprehensively.\n\n1. **Data Cleaning**: \n - First, + we will review the dataset for missing, inconsistent, or erroneous entries. + \n - We will handle missing values by either imputing them based on surrounding + data or removing records where necessary.\n - Additionally, we will standardize + categorical variables to ensure consistency (e.g., ensuring all location names + are spelled the same way).\n\n2. **Data Categorization**: \n - Next, we will + categorize the data into relevant segments that will aid our analysis. \n - + This involves grouping data points based on common characteristics, such as + demographics, time periods, or any key performance indicators (KPIs) we are + focusing on.\n\n3. **Trend and Pattern Identification**: \n - With the cleaned + and categorized data, we will perform a detailed analysis to identify trends + and patterns.\n - This will involve using statistical tools and visualizations + to uncover relationships within the data. We will look at time series analysis, + correlation coefficients, and any significant outliers that may require further + investigation.\n\n4. **Summarizing Findings**: \n - Finally, we will compile + a summary of our findings which will include both qualitative insights and quantitative + metrics.\n - This summary should encapsulate the key trends identified, any + notable patterns, and implications of these findings.\n - We will also document + any limitations of the data and suggest areas for further research if necessary.\n\nBy + completing these steps, we will not only have a clear understanding of what + the data indicates but also provide actionable insights that can guide our next + steps. This comprehensive analysis will serve as a solid foundation for any + additional exploration or decision-making initiatives related to our project. + \n\nIf you have any questions or need further clarification on any part of this + process, please let me know!"}}, {"event_id": "fb28b62f-ee47-4e82-b4e4-d212929dbd25", + "timestamp": "2025-09-24T05:24:11.456167+00:00", "type": "llm_call_started", + "event_data": {"timestamp": "2025-09-24T05:24:11.456154+00:00", "type": "llm_call_started", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "d112deef-93fb-46ea-bba2-a56b52712d0a", "task_name": "Process initial + data", "agent_id": "09794b42-447f-4b7a-b634-3a861f457357", "agent_role": "Crew + Manager", "from_task": null, "from_agent": null, "model": "gpt-4o", "messages": + [{"role": "system", "content": "You are Crew Manager. You are a seasoned manager + with a knack for getting the best out of your team.\nYou are also known for + your ability to delegate work to the right people, and to ask the right questions + to get the best out of your team.\nEven though you don''t perform tasks by yourself, + you have a lot of experience in the field, which allows you to properly evaluate + the work of your team members.\nYour personal goal is: Manage the team to complete + the task in the best way possible.\nYou ONLY have access to the following tools, + and should NEVER make up tools that are not listed here:\n\nTool Name: Delegate + work to coworker\nTool Arguments: {''task'': {''description'': ''The task to + delegate'', ''type'': ''str''}, ''context'': {''description'': ''The context + for the task'', ''type'': ''str''}, ''coworker'': {''description'': ''The role/name + of the coworker to delegate to'', ''type'': ''str''}}\nTool Description: Delegate + a specific task to one of the following coworkers: First Agent\nThe input to + this tool should be the coworker, the task you want them to do, and ALL necessary + context to execute the task, they know nothing about the task, so share absolutely + everything you know, don''t reference things but instead explain them.\nTool + Name: Ask question to coworker\nTool Arguments: {''question'': {''description'': + ''The question to ask'', ''type'': ''str''}, ''context'': {''description'': + ''The context for the question'', ''type'': ''str''}, ''coworker'': {''description'': + ''The role/name of the coworker to ask'', ''type'': ''str''}}\nTool Description: + Ask a specific question to one of the following coworkers: First Agent\nThe + input to this tool should be the coworker, the question you have for them, and + ALL necessary context to ask the question properly, they know nothing about + the question, so share absolutely everything you know, don''t reference things + but instead explain them.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [Delegate work to coworker, Ask question to coworker], just the name, + exactly as it''s written.\nAction Input: the input to the action, just a simple + JSON object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Process initial data\n\nThis is the expected criteria + for your final answer: Initial analysis\nyou MUST return the actual complete + content as the final answer, not a summary.\n\nBegin! This is VERY important + to you, use the tools available and give your best Final Answer, your job depends + on it!\n\nThought:"}, {"role": "assistant", "content": "Thought: I need to delegate + the task of processing the initial data to the First Agent to ensure we have + a thorough and accurate analysis. I will provide them with all the necessary + details to complete this task effectively.\n\nAction: Delegate work to coworker\nAction + Input: {\"task\": \"Process initial data\", \"context\": \"The task involves + analyzing the initial data set we have received. This includes cleaning the + data, categorizing it for analysis, identifying any trends or patterns, and + summarizing the findings. The goal is to have a clear understanding of what + the data indicates and any initial insights that can be drawn from it.\", \"coworker\": + \"First Agent\"}\nObservation: To process the initial data set effectively, + we will follow several key steps to ensure we clean, categorize, analyze, and + summarize our findings comprehensively.\n\n1. **Data Cleaning**: \n - First, + we will review the dataset for missing, inconsistent, or erroneous entries. + \n - We will handle missing values by either imputing them based on surrounding + data or removing records where necessary.\n - Additionally, we will standardize + categorical variables to ensure consistency (e.g., ensuring all location names + are spelled the same way).\n\n2. **Data Categorization**: \n - Next, we will + categorize the data into relevant segments that will aid our analysis. \n - + This involves grouping data points based on common characteristics, such as + demographics, time periods, or any key performance indicators (KPIs) we are + focusing on.\n\n3. **Trend and Pattern Identification**: \n - With the cleaned + and categorized data, we will perform a detailed analysis to identify trends + and patterns.\n - This will involve using statistical tools and visualizations + to uncover relationships within the data. We will look at time series analysis, + correlation coefficients, and any significant outliers that may require further + investigation.\n\n4. **Summarizing Findings**: \n - Finally, we will compile + a summary of our findings which will include both qualitative insights and quantitative + metrics.\n - This summary should encapsulate the key trends identified, any + notable patterns, and implications of these findings.\n - We will also document + any limitations of the data and suggest areas for further research if necessary.\n\nBy + completing these steps, we will not only have a clear understanding of what + the data indicates but also provide actionable insights that can guide our next + steps. This comprehensive analysis will serve as a solid foundation for any + additional exploration or decision-making initiatives related to our project. + \n\nIf you have any questions or need further clarification on any part of this + process, please let me know!"}], "tools": null, "callbacks": [""], "available_functions": null}}, {"event_id": "a717b2e2-b482-44a3-9769-136e29e808ec", + "timestamp": "2025-09-24T05:24:11.456970+00:00", "type": "llm_call_completed", + "event_data": {"timestamp": "2025-09-24T05:24:11.456956+00:00", "type": "llm_call_completed", + "source_fingerprint": null, "source_type": null, "fingerprint_metadata": null, + "task_id": "d112deef-93fb-46ea-bba2-a56b52712d0a", "task_name": "Process initial + data", "agent_id": "09794b42-447f-4b7a-b634-3a861f457357", "agent_role": "Crew + Manager", "from_task": null, "from_agent": null, "messages": [{"role": "system", + "content": "You are Crew Manager. You are a seasoned manager with a knack for + getting the best out of your team.\nYou are also known for your ability to delegate + work to the right people, and to ask the right questions to get the best out + of your team.\nEven though you don''t perform tasks by yourself, you have a + lot of experience in the field, which allows you to properly evaluate the work + of your team members.\nYour personal goal is: Manage the team to complete the + task in the best way possible.\nYou ONLY have access to the following tools, + and should NEVER make up tools that are not listed here:\n\nTool Name: Delegate + work to coworker\nTool Arguments: {''task'': {''description'': ''The task to + delegate'', ''type'': ''str''}, ''context'': {''description'': ''The context + for the task'', ''type'': ''str''}, ''coworker'': {''description'': ''The role/name + of the coworker to delegate to'', ''type'': ''str''}}\nTool Description: Delegate + a specific task to one of the following coworkers: First Agent\nThe input to + this tool should be the coworker, the task you want them to do, and ALL necessary + context to execute the task, they know nothing about the task, so share absolutely + everything you know, don''t reference things but instead explain them.\nTool + Name: Ask question to coworker\nTool Arguments: {''question'': {''description'': + ''The question to ask'', ''type'': ''str''}, ''context'': {''description'': + ''The context for the question'', ''type'': ''str''}, ''coworker'': {''description'': + ''The role/name of the coworker to ask'', ''type'': ''str''}}\nTool Description: + Ask a specific question to one of the following coworkers: First Agent\nThe + input to this tool should be the coworker, the question you have for them, and + ALL necessary context to ask the question properly, they know nothing about + the question, so share absolutely everything you know, don''t reference things + but instead explain them.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: + you should always think about what to do\nAction: the action to take, only one + name of [Delegate work to coworker, Ask question to coworker], just the name, + exactly as it''s written.\nAction Input: the input to the action, just a simple + JSON object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n```\n\nOnce all necessary information is gathered, + return the following format:\n\n```\nThought: I now know the final answer\nFinal + Answer: the final answer to the original input question\n```"}, {"role": "user", + "content": "\nCurrent Task: Process initial data\n\nThis is the expected criteria + for your final answer: Initial analysis\nyou MUST return the actual complete + content as the final answer, not a summary.\n\nBegin! This is VERY important + to you, use the tools available and give your best Final Answer, your job depends + on it!\n\nThought:"}, {"role": "assistant", "content": "Thought: I need to delegate + the task of processing the initial data to the First Agent to ensure we have + a thorough and accurate analysis. I will provide them with all the necessary + details to complete this task effectively.\n\nAction: Delegate work to coworker\nAction + Input: {\"task\": \"Process initial data\", \"context\": \"The task involves + analyzing the initial data set we have received. This includes cleaning the + data, categorizing it for analysis, identifying any trends or patterns, and + summarizing the findings. The goal is to have a clear understanding of what + the data indicates and any initial insights that can be drawn from it.\", \"coworker\": + \"First Agent\"}\nObservation: To process the initial data set effectively, + we will follow several key steps to ensure we clean, categorize, analyze, and + summarize our findings comprehensively.\n\n1. **Data Cleaning**: \n - First, + we will review the dataset for missing, inconsistent, or erroneous entries. + \n - We will handle missing values by either imputing them based on surrounding + data or removing records where necessary.\n - Additionally, we will standardize + categorical variables to ensure consistency (e.g., ensuring all location names + are spelled the same way).\n\n2. **Data Categorization**: \n - Next, we will + categorize the data into relevant segments that will aid our analysis. \n - + This involves grouping data points based on common characteristics, such as + demographics, time periods, or any key performance indicators (KPIs) we are + focusing on.\n\n3. **Trend and Pattern Identification**: \n - With the cleaned + and categorized data, we will perform a detailed analysis to identify trends + and patterns.\n - This will involve using statistical tools and visualizations + to uncover relationships within the data. We will look at time series analysis, + correlation coefficients, and any significant outliers that may require further + investigation.\n\n4. **Summarizing Findings**: \n - Finally, we will compile + a summary of our findings which will include both qualitative insights and quantitative + metrics.\n - This summary should encapsulate the key trends identified, any + notable patterns, and implications of these findings.\n - We will also document + any limitations of the data and suggest areas for further research if necessary.\n\nBy + completing these steps, we will not only have a clear understanding of what + the data indicates but also provide actionable insights that can guide our next + steps. This comprehensive analysis will serve as a solid foundation for any + additional exploration or decision-making initiatives related to our project. + \n\nIf you have any questions or need further clarification on any part of this + process, please let me know!"}], "response": "```\nThought: I now know the final + answer\nFinal Answer: To process the initial data set effectively, we will follow + several key steps to ensure we clean, categorize, analyze, and summarize our + findings comprehensively.\n\n1. **Data Cleaning**: \n - First, we will review + the dataset for missing, inconsistent, or erroneous entries. \n - We will + handle missing values by either imputing them based on surrounding data or removing + records where necessary.\n - Additionally, we will standardize categorical + variables to ensure consistency (e.g., ensuring all location names are spelled + the same way).\n\n2. **Data Categorization**: \n - Next, we will categorize + the data into relevant segments that will aid our analysis. \n - This involves + grouping data points based on common characteristics, such as demographics, + time periods, or any key performance indicators (KPIs) we are focusing on.\n\n3. + **Trend and Pattern Identification**: \n - With the cleaned and categorized + data, we will perform a detailed analysis to identify trends and patterns.\n - + This will involve using statistical tools and visualizations to uncover relationships + within the data. We will look at time series analysis, correlation coefficients, + and significant outliers that may require further investigation.\n\n4. **Summarizing + Findings**: \n - Finally, we will compile a summary of our findings, including + both qualitative insights and quantitative metrics.\n - This summary should + encapsulate the key trends identified, any notable patterns, and implications + of these findings.\n - We will also document any limitations of the data and + suggest areas for further research if necessary.\n\nBy completing these steps, + we will not only have a clear understanding of what the data indicates but also + provide actionable insights that can guide our next steps. This comprehensive + analysis will serve as a solid foundation for any additional exploration or + decision-making initiatives related to our project. \n```\n", "call_type": "", "model": "gpt-4o"}}, {"event_id": "9aec0184-de1c-40d1-b407-7cea95ba8336", + "timestamp": "2025-09-24T05:24:11.457064+00:00", "type": "agent_execution_completed", + "event_data": {"agent_role": "Crew Manager", "agent_goal": "Manage the team + to complete the task in the best way possible.", "agent_backstory": "You are + a seasoned manager with a knack for getting the best out of your team.\nYou + are also known for your ability to delegate work to the right people, and to + ask the right questions to get the best out of your team.\nEven though you don''t + perform tasks by yourself, you have a lot of experience in the field, which + allows you to properly evaluate the work of your team members."}}, {"event_id": + "a41004c8-4211-4656-8d36-abb361de4dc1", "timestamp": "2025-09-24T05:24:11.457121+00:00", + "type": "task_completed", "event_data": {"task_description": "Process initial + data", "task_name": "Process initial data", "task_id": "d112deef-93fb-46ea-bba2-a56b52712d0a", + "output_raw": "To process the initial data set effectively, we will follow several + key steps to ensure we clean, categorize, analyze, and summarize our findings + comprehensively.\n\n1. **Data Cleaning**: \n - First, we will review the dataset + for missing, inconsistent, or erroneous entries. \n - We will handle missing + values by either imputing them based on surrounding data or removing records + where necessary.\n - Additionally, we will standardize categorical variables + to ensure consistency (e.g., ensuring all location names are spelled the same + way).\n\n2. **Data Categorization**: \n - Next, we will categorize the data + into relevant segments that will aid our analysis. \n - This involves grouping + data points based on common characteristics, such as demographics, time periods, + or any key performance indicators (KPIs) we are focusing on.\n\n3. **Trend and + Pattern Identification**: \n - With the cleaned and categorized data, we will + perform a detailed analysis to identify trends and patterns.\n - This will + involve using statistical tools and visualizations to uncover relationships + within the data. 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-import json from collections import defaultdict from concurrent.futures import Future from hashlib import md5 +import json +import re from unittest import mock from unittest.mock import ANY, MagicMock, patch -import pydantic_core -import pytest from crewai.agent import Agent -from crewai.agents import CacheHandler from crewai.crew import Crew from crewai.crews.crew_output import CrewOutput from crewai.events.event_bus import crewai_event_bus @@ -30,7 +28,6 @@ from crewai.events.types.memory_events import ( MemorySaveFailedEvent, MemorySaveStartedEvent, ) -from crewai.flow import Flow, start from crewai.knowledge.knowledge import Knowledge from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource from crewai.llm import LLM @@ -46,6 +43,11 @@ from crewai.tasks.task_output import TaskOutput from crewai.types.usage_metrics import UsageMetrics from crewai.utilities.rpm_controller import RPMController from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler +import pydantic_core +import pytest + +from crewai.agents import CacheHandler +from crewai.flow import Flow, start @pytest.fixture @@ -199,7 +201,9 @@ def test_async_task_cannot_include_sequential_async_tasks_in_context( # This should raise an error because task2 is async and has task1 in its context without a sync task in between with pytest.raises( ValueError, - match="Task 'Task 2' is asynchronous and cannot include other sequential asynchronous tasks in its context.", + match=re.escape( + "Task 'Task 2' is asynchronous and cannot include other sequential asynchronous tasks in its context." + ), ): Crew(tasks=[task1, task2, task3, task4, task5], agents=[researcher, writer]) @@ -237,7 +241,9 @@ def test_context_no_future_tasks(researcher, writer): # This should raise an error because task1 has a context dependency on a future task (task4) with pytest.raises( ValueError, - match="Task 'Task 1' has a context dependency on a future task 'Task 4', which is not allowed.", + match=re.escape( + "Task 'Task 1' has a context dependency on a future task 'Task 4', which is not allowed." + ), ): Crew(tasks=[task1, task2, task3, task4], agents=[researcher, writer]) @@ -568,9 +574,10 @@ def test_crew_with_delegating_agents(ceo, writer): @pytest.mark.vcr(filter_headers=["authorization"]) def test_crew_with_delegating_agents_should_not_override_task_tools(ceo, writer): - from crewai.tools import BaseTool from pydantic import BaseModel, Field + from crewai.tools import BaseTool + class TestToolInput(BaseModel): """Input schema for TestTool.""" @@ -627,9 +634,10 @@ def test_crew_with_delegating_agents_should_not_override_task_tools(ceo, writer) @pytest.mark.vcr(filter_headers=["authorization"]) def test_crew_with_delegating_agents_should_not_override_agent_tools(ceo, writer): - from crewai.tools import BaseTool from pydantic import BaseModel, Field + from crewai.tools import BaseTool + class TestToolInput(BaseModel): """Input schema for TestTool.""" @@ -688,9 +696,10 @@ def test_crew_with_delegating_agents_should_not_override_agent_tools(ceo, writer @pytest.mark.vcr(filter_headers=["authorization"]) def test_task_tools_override_agent_tools(researcher): - from crewai.tools import BaseTool from pydantic import BaseModel, Field + from crewai.tools import BaseTool + class TestToolInput(BaseModel): """Input schema for TestTool.""" @@ -744,9 +753,10 @@ def test_task_tools_override_agent_tools_with_allow_delegation(researcher, write Test that task tools override agent tools while preserving delegation tools when allow_delegation=True """ - from crewai.tools import BaseTool from pydantic import BaseModel, Field + from crewai.tools import BaseTool + class TestToolInput(BaseModel): query: str = Field(..., description="Query to process") @@ -1005,7 +1015,7 @@ def test_crew_kickoff_streaming_usage_metrics(): role="{topic} Researcher", goal="Express hot takes on {topic}.", backstory="You have a lot of experience with {topic}.", - llm=LLM(model="gpt-4o", stream=True), + llm=LLM(model="gpt-4o", stream=True, is_litellm=True), max_iter=3, ) @@ -1773,7 +1783,7 @@ def test_hierarchical_kickoff_usage_metrics_include_manager(researcher): agent=researcher, # *regular* agent ) - # ── 2. Stub out each agent's _token_process.get_summary() ─────────────────── + # ── 2. Stub out each agent's token usage methods ─────────────────── researcher_metrics = UsageMetrics( total_tokens=120, prompt_tokens=80, completion_tokens=40, successful_requests=2 ) @@ -1781,10 +1791,10 @@ def test_hierarchical_kickoff_usage_metrics_include_manager(researcher): total_tokens=30, prompt_tokens=20, completion_tokens=10, successful_requests=1 ) - # Replace the internal _token_process objects with simple mocks - researcher._token_process = MagicMock( - get_summary=MagicMock(return_value=researcher_metrics) - ) + # Mock the LLM's get_token_usage_summary method for the researcher + researcher.llm.get_token_usage_summary = MagicMock(return_value=researcher_metrics) + + # Mock the manager's _token_process since it uses the fallback path manager._token_process = MagicMock( get_summary=MagicMock(return_value=manager_metrics) ) @@ -3334,7 +3344,9 @@ def test_replay_with_invalid_task_id(): ): with pytest.raises( ValueError, - match="Task with id bf5b09c9-69bd-4eb8-be12-f9e5bae31c2d not found in the crew's tasks.", + match=re.escape( + "Task with id bf5b09c9-69bd-4eb8-be12-f9e5bae31c2d not found in the crew's tasks." + ), ): crew.replay("bf5b09c9-69bd-4eb8-be12-f9e5bae31c2d") @@ -3813,10 +3825,11 @@ def test_task_tools_preserve_code_execution_tools(): """ Test that task tools don't override code execution tools when allow_code_execution=True """ - from crewai.tools import BaseTool from crewai_tools import CodeInterpreterTool from pydantic import BaseModel, Field + from crewai.tools import BaseTool + class TestToolInput(BaseModel): """Input schema for TestTool.""" diff --git a/lib/crewai/tests/test_llm.py b/lib/crewai/tests/test_llm.py index fab3f7bf7..694c85e1f 100644 --- a/lib/crewai/tests/test_llm.py +++ b/lib/crewai/tests/test_llm.py @@ -3,7 +3,6 @@ import os from time import sleep from unittest.mock import MagicMock, patch -import pytest from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess from crewai.events.event_types import ( LLMCallCompletedEvent, @@ -15,33 +14,30 @@ from crewai.events.event_types import ( from crewai.llm import CONTEXT_WINDOW_USAGE_RATIO, LLM from crewai.utilities.token_counter_callback import TokenCalcHandler from pydantic import BaseModel +import pytest # TODO: This test fails without print statement, which makes me think that something is happening asynchronously that we need to eventually fix and dive deeper into at a later date @pytest.mark.vcr(filter_headers=["authorization"]) def test_llm_callback_replacement(): - llm1 = LLM(model="gpt-4o-mini") - llm2 = LLM(model="gpt-4o-mini") + llm1 = LLM(model="gpt-4o-mini", is_litellm=True) + llm2 = LLM(model="gpt-4o-mini", is_litellm=True) calc_handler_1 = TokenCalcHandler(token_cost_process=TokenProcess()) calc_handler_2 = TokenCalcHandler(token_cost_process=TokenProcess()) - result1 = llm1.call( + llm1.call( messages=[{"role": "user", "content": "Hello, world!"}], callbacks=[calc_handler_1], ) - print("result1:", result1) usage_metrics_1 = calc_handler_1.token_cost_process.get_summary() - print("usage_metrics_1:", usage_metrics_1) - result2 = llm2.call( + llm2.call( messages=[{"role": "user", "content": "Hello, world from another agent!"}], callbacks=[calc_handler_2], ) sleep(5) - print("result2:", result2) usage_metrics_2 = calc_handler_2.token_cost_process.get_summary() - print("usage_metrics_2:", usage_metrics_2) # The first handler should not have been updated assert usage_metrics_1.successful_requests == 1 @@ -61,7 +57,7 @@ def test_llm_call_with_string_input(): @pytest.mark.vcr(filter_headers=["authorization"]) def test_llm_call_with_string_input_and_callbacks(): - llm = LLM(model="gpt-4o-mini") + llm = LLM(model="gpt-4o-mini", is_litellm=True) calc_handler = TokenCalcHandler(token_cost_process=TokenProcess()) # Test the call method with a string input and callbacks @@ -127,7 +123,7 @@ def test_llm_call_with_tool_and_string_input(): @pytest.mark.vcr(filter_headers=["authorization"]) def test_llm_call_with_tool_and_message_list(): - llm = LLM(model="gpt-4o-mini") + llm = LLM(model="gpt-4o-mini", is_litellm=True) def square_number(number: int) -> int: """Returns the square of a number.""" @@ -171,6 +167,7 @@ def test_llm_passes_additional_params(): model="gpt-4o-mini", vertex_credentials="test_credentials", vertex_project="test_project", + is_litellm=True, ) messages = [{"role": "user", "content": "Hello, world!"}] @@ -223,7 +220,7 @@ def test_get_custom_llm_provider_gemini(): def test_get_custom_llm_provider_openai(): - llm = LLM(model="gpt-4") + llm = LLM(model="gpt-4", is_litellm=True) assert llm._get_custom_llm_provider() is None @@ -380,7 +377,7 @@ def test_context_window_exceeded_error_handling(): ) from litellm.exceptions import ContextWindowExceededError - llm = LLM(model="gpt-4") + llm = LLM(model="gpt-4", is_litellm=True) # Test non-streaming response with patch("litellm.completion") as mock_completion: @@ -397,7 +394,7 @@ def test_context_window_exceeded_error_handling(): assert "8192 tokens" in str(excinfo.value) # Test streaming response - llm = LLM(model="gpt-4", stream=True) + llm = LLM(model="gpt-4", stream=True, is_litellm=True) with patch("litellm.completion") as mock_completion: mock_completion.side_effect = ContextWindowExceededError( "This model's maximum context length is 8192 tokens. However, your messages resulted in 10000 tokens.", @@ -416,7 +413,7 @@ def test_context_window_exceeded_error_handling(): @pytest.fixture def anthropic_llm(): """Fixture providing an Anthropic LLM instance.""" - return LLM(model="anthropic/claude-3-sonnet") + return LLM(model="anthropic/claude-3-sonnet", is_litellm=True) @pytest.fixture @@ -455,40 +452,25 @@ def test_anthropic_model_detection(): ("claude-instant", True), ("claude/v1", True), ("gpt-4", False), - ("", False), ("anthropomorphic", False), # Should not match partial words ] for model, expected in models: - llm = LLM(model=model) + llm = LLM(model=model, is_litellm=True) assert llm.is_anthropic == expected, f"Failed for model: {model}" def test_anthropic_message_formatting(anthropic_llm, system_message, user_message): """Test Anthropic message formatting with fixtures.""" # Test when first message is system - formatted = anthropic_llm._format_messages_for_provider([system_message]) - assert len(formatted) == 2 - assert formatted[0]["role"] == "user" - assert formatted[0]["content"] == "." - assert formatted[1] == system_message - # Test when first message is already user - formatted = anthropic_llm._format_messages_for_provider([user_message]) - assert len(formatted) == 1 - assert formatted[0] == user_message - - # Test with empty message list formatted = anthropic_llm._format_messages_for_provider([]) assert len(formatted) == 1 assert formatted[0]["role"] == "user" assert formatted[0]["content"] == "." - # Test with non-Anthropic model (should not modify messages) - non_anthropic_llm = LLM(model="gpt-4") - formatted = non_anthropic_llm._format_messages_for_provider([system_message]) - assert len(formatted) == 1 - assert formatted[0] == system_message + with pytest.raises(TypeError, match="Invalid message format"): + anthropic_llm._format_messages_for_provider([{"invalid": "message"}]) def test_deepseek_r1_with_open_router(): @@ -499,6 +481,7 @@ def test_deepseek_r1_with_open_router(): model="openrouter/deepseek/deepseek-r1", base_url="https://openrouter.ai/api/v1", api_key=os.getenv("OPEN_ROUTER_API_KEY"), + is_litellm=True, ) result = llm.call("What is the capital of France?") assert isinstance(result, str) @@ -568,7 +551,7 @@ def mock_emit() -> MagicMock: @pytest.mark.vcr(filter_headers=["authorization"]) def test_handle_streaming_tool_calls(get_weather_tool_schema, mock_emit): - llm = LLM(model="openai/gpt-4o", stream=True) + llm = LLM(model="openai/gpt-4o", stream=True, is_litellm=True) response = llm.call( messages=[ {"role": "user", "content": "What is the weather in New York?"}, @@ -599,7 +582,7 @@ def test_handle_streaming_tool_calls_with_error(get_weather_tool_schema, mock_em def get_weather_error(location): raise Exception("Error") - llm = LLM(model="openai/gpt-4o", stream=True) + llm = LLM(model="openai/gpt-4o", stream=True, is_litellm=True) response = llm.call( messages=[ {"role": "user", "content": "What is the weather in New York?"}, @@ -623,7 +606,7 @@ def test_handle_streaming_tool_calls_with_error(get_weather_tool_schema, mock_em def test_handle_streaming_tool_calls_no_available_functions( get_weather_tool_schema, mock_emit ): - llm = LLM(model="openai/gpt-4o", stream=True) + llm = LLM(model="openai/gpt-4o", stream=True, is_litellm=True) response = llm.call( messages=[ {"role": "user", "content": "What is the weather in New York?"}, @@ -642,7 +625,7 @@ def test_handle_streaming_tool_calls_no_available_functions( @pytest.mark.vcr(filter_headers=["authorization"]) def test_handle_streaming_tool_calls_no_tools(mock_emit): - llm = LLM(model="openai/gpt-4o", stream=True) + llm = LLM(model="openai/gpt-4o", stream=True, is_litellm=True) response = llm.call( messages=[ {"role": "user", "content": "What is the weather in New York?"}, @@ -663,7 +646,7 @@ def test_handle_streaming_tool_calls_no_tools(mock_emit): @pytest.mark.vcr(filter_headers=["authorization"]) def test_llm_call_when_stop_is_unsupported(caplog): - llm = LLM(model="o1-mini", stop=["stop"]) + llm = LLM(model="o1-mini", stop=["stop"], is_litellm=True) with caplog.at_level(logging.INFO): result = llm.call("What is the capital of France?") assert "Retrying LLM call without the unsupported 'stop'" in caplog.text @@ -675,7 +658,12 @@ def test_llm_call_when_stop_is_unsupported(caplog): def test_llm_call_when_stop_is_unsupported_when_additional_drop_params_is_provided( caplog, ): - llm = LLM(model="o1-mini", stop=["stop"], additional_drop_params=["another_param"]) + llm = LLM( + model="o1-mini", + stop=["stop"], + additional_drop_params=["another_param"], + is_litellm=True, + ) with caplog.at_level(logging.INFO): result = llm.call("What is the capital of France?") assert "Retrying LLM call without the unsupported 'stop'" in caplog.text @@ -685,7 +673,7 @@ def test_llm_call_when_stop_is_unsupported_when_additional_drop_params_is_provid @pytest.fixture def ollama_llm(): - return LLM(model="ollama/llama3.2:3b") + return LLM(model="ollama/llama3.2:3b", is_litellm=True) def test_ollama_appends_dummy_user_message_when_last_is_assistant(ollama_llm): diff --git a/lib/crewai/tests/utilities/test_converter.py b/lib/crewai/tests/utilities/test_converter.py index 40f4fe036..cc9f3ee5d 100644 --- a/lib/crewai/tests/utilities/test_converter.py +++ b/lib/crewai/tests/utilities/test_converter.py @@ -1,12 +1,9 @@ -import json -import os - # Tests for enums from enum import Enum -from typing import Dict, List, Optional +import json +import os from unittest.mock import MagicMock, Mock, patch -import pytest from crewai.llm import LLM from crewai.utilities.converter import ( Converter, @@ -21,6 +18,7 @@ from crewai.utilities.converter import ( ) from crewai.utilities.pydantic_schema_parser import PydanticSchemaParser from pydantic import BaseModel +import pytest @pytest.fixture(scope="module") @@ -254,7 +252,7 @@ def test_supports_function_calling_true(): def test_supports_function_calling_false(): - llm = LLM(model="non-existent-model") + llm = LLM(model="non-existent-model", is_litellm=True) assert llm.supports_function_calling() is False @@ -311,17 +309,17 @@ def test_generate_model_description_nested_model(): def test_generate_model_description_optional_field(): class ModelWithOptionalField(BaseModel): - name: Optional[str] - age: int + name: str + age: int | None description = generate_model_description(ModelWithOptionalField) - expected_description = '{\n "name": Optional[str],\n "age": int\n}' + expected_description = '{\n "name": str,\n "age": int | None\n}' assert description == expected_description def test_generate_model_description_list_field(): class ModelWithListField(BaseModel): - items: List[int] + items: list[int] description = generate_model_description(ModelWithListField) expected_description = '{\n "items": List[int]\n}' @@ -330,7 +328,7 @@ def test_generate_model_description_list_field(): def test_generate_model_description_dict_field(): class ModelWithDictField(BaseModel): - attributes: Dict[str, int] + attributes: dict[str, int] description = generate_model_description(ModelWithDictField) expected_description = '{\n "attributes": Dict[str, int]\n}' @@ -470,7 +468,7 @@ def test_converter_retry_logic(): def test_converter_with_optional_fields(): class OptionalModel(BaseModel): name: str - age: Optional[int] + age: int | None llm = Mock(spec=LLM) llm.supports_function_calling.return_value = False @@ -496,7 +494,7 @@ def test_converter_with_optional_fields(): # Tests for list fields def test_converter_with_list_field(): class ListModel(BaseModel): - items: List[int] + items: list[int] llm = Mock(spec=LLM) llm.supports_function_calling.return_value = False diff --git a/lib/crewai/tests/utilities/test_events.py b/lib/crewai/tests/utilities/test_events.py index 2c6f78770..79566434c 100644 --- a/lib/crewai/tests/utilities/test_events.py +++ b/lib/crewai/tests/utilities/test_events.py @@ -1,17 +1,12 @@ -import os from datetime import datetime +import os from unittest.mock import Mock, patch -import pytest -from pydantic import Field - from crewai.agent import Agent from crewai.agents.crew_agent_executor import CrewAgentExecutor from crewai.crew import Crew -from crewai.flow.flow import Flow, listen, start -from crewai.llm import LLM -from crewai.task import Task -from crewai.tools.base_tool import BaseTool +from crewai.events.event_bus import crewai_event_bus +from crewai.events.event_listener import EventListener from crewai.events.types.agent_events import ( AgentExecutionCompletedEvent, AgentExecutionErrorEvent, @@ -25,9 +20,6 @@ from crewai.events.types.crew_events import ( CrewTestResultEvent, CrewTestStartedEvent, ) -from crewai.events.event_bus import crewai_event_bus -from crewai.events.event_listener import EventListener -from crewai.events.types.tool_usage_events import ToolUsageFinishedEvent from crewai.events.types.flow_events import ( FlowCreatedEvent, FlowFinishedEvent, @@ -48,7 +40,14 @@ from crewai.events.types.task_events import ( ) from crewai.events.types.tool_usage_events import ( ToolUsageErrorEvent, + ToolUsageFinishedEvent, ) +from crewai.flow.flow import Flow, listen, start +from crewai.llm import LLM +from crewai.task import Task +from crewai.tools.base_tool import BaseTool +from pydantic import Field +import pytest @pytest.fixture(scope="module") @@ -195,7 +194,7 @@ def test_crew_emits_kickoff_failed_event(base_agent, base_task): error_message = "Simulated crew kickoff failure" mock_execute.side_effect = Exception(error_message) - with pytest.raises(Exception): + with pytest.raises(Exception): # noqa: B017 crew.kickoff() assert len(received_events) == 1 @@ -279,7 +278,7 @@ def test_task_emits_failed_event_on_execution_error(base_agent, base_task): agent=agent, ) - with pytest.raises(Exception): + with pytest.raises(Exception): # noqa: B017 agent.execute_task(task=task) assert len(received_events) == 1 @@ -333,7 +332,7 @@ def test_agent_emits_execution_error_event(base_agent, base_task): ) as invoke_mock: invoke_mock.side_effect = Exception(error_message) - with pytest.raises(Exception): + with pytest.raises(Exception): # noqa: B017 base_agent.execute_task( task=base_task, ) @@ -517,7 +516,6 @@ def test_flow_emits_method_execution_started_event(): @crewai_event_bus.on(MethodExecutionStartedEvent) def handle_method_start(source, event): - print("event in method name", event.method_name) received_events.append(event) class TestFlow(Flow[dict]): @@ -619,7 +617,7 @@ def test_flow_emits_method_execution_failed_event(): raise error flow = TestFlow() - with pytest.raises(Exception): + with pytest.raises(Exception): # noqa: B017 flow.kickoff() assert len(received_events) == 1 @@ -655,6 +653,7 @@ def test_llm_emits_call_started_event(): @pytest.mark.vcr(filter_headers=["authorization"]) +@pytest.mark.isolated def test_llm_emits_call_failed_event(): received_events = [] @@ -662,13 +661,18 @@ def test_llm_emits_call_failed_event(): def handle_llm_call_failed(source, event): received_events.append(event) - error_message = "Simulated LLM call failure" - with patch("crewai.llm.litellm.completion", side_effect=Exception(error_message)): + error_message = "OpenAI API call failed: Simulated API failure" + + with patch( + "crewai.llms.providers.openai.completion.OpenAICompletion._handle_completion" + ) as mock_handle_completion: + mock_handle_completion.side_effect = Exception("Simulated API failure") + llm = LLM(model="gpt-4o-mini") with pytest.raises(Exception) as exc_info: llm.call("Hello, how are you?") - assert str(exc_info.value) == error_message + assert str(exc_info.value) == "Simulated API failure" assert len(received_events) == 1 assert received_events[0].type == "llm_call_failed" assert received_events[0].error == error_message @@ -884,8 +888,8 @@ def test_stream_llm_emits_event_with_task_and_agent_info(): assert len(all_task_name) == 14 assert set(all_agent_roles) == {agent.role} - assert set(all_agent_id) == {agent.id} - assert set(all_task_id) == {task.id} + assert set(all_agent_id) == {str(agent.id)} + assert set(all_task_id) == {str(task.id)} assert set(all_task_name) == {task.name or task.description} @@ -935,8 +939,8 @@ def test_llm_emits_event_with_task_and_agent_info(base_agent, base_task): assert len(all_task_name) == 2 assert set(all_agent_roles) == {base_agent.role} - assert set(all_agent_id) == {base_agent.id} - assert set(all_task_id) == {base_task.id} + assert set(all_agent_id) == {str(base_agent.id)} + assert set(all_task_id) == {str(base_task.id)} assert set(all_task_name) == {base_task.name or base_task.description} @@ -991,4 +995,4 @@ def test_llm_emits_event_with_lite_agent(): assert len(all_task_name) == 0 assert set(all_agent_roles) == {agent.role} - assert set(all_agent_id) == {agent.id} + assert set(all_agent_id) == {str(agent.id)} diff --git a/lib/crewai/tests/utilities/test_llm_utils.py b/lib/crewai/tests/utilities/test_llm_utils.py index e1a37aa3d..d20e0b528 100644 --- a/lib/crewai/tests/utilities/test_llm_utils.py +++ b/lib/crewai/tests/utilities/test_llm_utils.py @@ -1,10 +1,16 @@ import os from unittest.mock import patch -import pytest from crewai.llm import LLM +from crewai.llms.base_llm import BaseLLM from crewai.utilities.llm_utils import create_llm -from litellm.exceptions import BadRequestError +import pytest + + +try: + from litellm.exceptions import BadRequestError +except ImportError: + BadRequestError = Exception def test_create_llm_with_llm_instance(): @@ -15,13 +21,19 @@ def test_create_llm_with_llm_instance(): def test_create_llm_with_valid_model_string(): llm = create_llm(llm_value="gpt-4o") - assert isinstance(llm, LLM) + assert isinstance(llm, BaseLLM) assert llm.model == "gpt-4o" def test_create_llm_with_invalid_model_string(): - with pytest.raises(BadRequestError, match="LLM Provider NOT provided"): - llm = create_llm(llm_value="invalid-model") + # For invalid model strings, create_llm succeeds but call() fails with API error + llm = create_llm(llm_value="invalid-model") + assert llm is not None + assert isinstance(llm, BaseLLM) + + # The error should occur when making the actual API call + # We expect some kind of API error (NotFoundError, etc.) + with pytest.raises(Exception): # noqa: B017 llm.call(messages=[{"role": "user", "content": "Hello, world!"}]) @@ -32,16 +44,16 @@ def test_create_llm_with_unknown_object_missing_attributes(): unknown_obj = UnknownObject() llm = create_llm(llm_value=unknown_obj) - # Attempt to call the LLM and expect it to raise an error due to missing attributes - with pytest.raises(BadRequestError, match="LLM Provider NOT provided"): - llm.call(messages=[{"role": "user", "content": "Hello, world!"}]) + # Should succeed because str(unknown_obj) provides a model name + assert llm is not None + assert isinstance(llm, BaseLLM) def test_create_llm_with_none_uses_default_model(): - with patch.dict(os.environ, {}, clear=True): - with patch("crewai.cli.constants.DEFAULT_LLM_MODEL", "gpt-4o"): + with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True): + with patch("crewai.utilities.llm_utils.DEFAULT_LLM_MODEL", "gpt-4o-mini"): llm = create_llm(llm_value=None) - assert isinstance(llm, LLM) + assert isinstance(llm, BaseLLM) assert llm.model == "gpt-4o-mini" @@ -53,7 +65,7 @@ def test_create_llm_with_unknown_object(): unknown_obj = UnknownObject() llm = create_llm(llm_value=unknown_obj) - assert isinstance(llm, LLM) + assert isinstance(llm, BaseLLM) assert llm.model == "gpt-4o" assert llm.temperature == 0.7 assert llm.max_tokens == 1500 @@ -64,13 +76,14 @@ def test_create_llm_from_env_with_unaccepted_attributes(): os.environ, { "OPENAI_MODEL_NAME": "gpt-3.5-turbo", + "OPENAI_API_KEY": "fake-key", "AWS_ACCESS_KEY_ID": "fake-access-key", "AWS_SECRET_ACCESS_KEY": "fake-secret-key", "AWS_REGION_NAME": "us-west-2", }, ): llm = create_llm(llm_value=None) - assert isinstance(llm, LLM) + assert isinstance(llm, BaseLLM) assert llm.model == "gpt-3.5-turbo" assert not hasattr(llm, "AWS_ACCESS_KEY_ID") assert not hasattr(llm, "AWS_SECRET_ACCESS_KEY") @@ -84,12 +97,18 @@ def test_create_llm_with_partial_attributes(): obj = PartialAttributes() llm = create_llm(llm_value=obj) - assert isinstance(llm, LLM) + assert isinstance(llm, BaseLLM) assert llm.model == "gpt-4o" assert llm.temperature is None # Should handle missing attributes gracefully def test_create_llm_with_invalid_type(): - with pytest.raises(BadRequestError, match="LLM Provider NOT provided"): - llm = create_llm(llm_value=42) + # For integers, create_llm succeeds because str(42) becomes "42" + llm = create_llm(llm_value=42) + assert llm is not None + assert isinstance(llm, BaseLLM) + assert llm.model == "42" + + # The error should occur when making the actual API call + with pytest.raises(Exception): # noqa: B017 llm.call(messages=[{"role": "user", "content": "Hello, world!"}]) diff --git a/uv.lock b/uv.lock index 699c1fb6c..1f64c7e10 100644 --- a/uv.lock +++ b/uv.lock @@ -993,7 +993,6 @@ dependencies = [ { name = "json-repair" }, { name = "json5" }, { name = "jsonref" }, - { name = "litellm" }, { name = "openai" }, { name = "openpyxl" }, { name = "opentelemetry-api" }, @@ -1026,6 +1025,9 @@ docling = [ embeddings = [ { name = "tiktoken" }, ] +litellm = [ + { name = "litellm" }, +] mem0 = [ { name = "mem0ai" }, ] @@ -1066,7 +1068,7 @@ requires-dist = [ { name = "json-repair", specifier = "==0.25.2" }, { name = "json5", specifier = ">=0.10.0" }, { name = "jsonref", specifier = ">=1.1.0" }, - { name = "litellm", specifier = "==1.74.9" }, + { name = "litellm", marker = "extra == 'litellm'", specifier = ">=1.74.9" }, { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.94" }, { name = "openai", specifier = ">=1.13.3" }, { name = "openpyxl", specifier = ">=3.1.5" }, @@ -1092,7 +1094,7 @@ requires-dist = [ { name = "uv", specifier = ">=0.4.25" }, { name = "voyageai", marker = "extra == 'voyageai'", specifier = ">=0.3.5" }, ] -provides-extras = ["aisuite", "aws", "docling", "embeddings", "mem0", "openpyxl", "pandas", "pdfplumber", "qdrant", "tools", "voyageai", "watson"] +provides-extras = ["aisuite", "aws", "docling", "embeddings", "litellm", "mem0", "openpyxl", "pandas", "pdfplumber", "qdrant", "tools", "voyageai", "watson"] [[package]] name = "crewai-tools"