From dea6ed7ef0b4c1cc023fa0e91dfcc98b8d53d1ae Mon Sep 17 00:00:00 2001 From: "Brandon Hancock (bhancock_ai)" <109994880+bhancockio@users.noreply.github.com> Date: Mon, 27 Jan 2025 17:35:17 -0500 Subject: [PATCH 01/10] fix issue pointed out by mike (#1986) * fix issue pointed out by mike * clean up * Drop logger * drop unused imports --- pyproject.toml | 1 + src/crewai/tools/tool_usage.py | 70 ++++++--- tests/tools/test_tool_usage.py | 252 +++++++++++++++++++++++++++++++++ uv.lock | 11 ++ 4 files changed, 313 insertions(+), 21 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 8dbe56fd8..4a9343697 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,6 +36,7 @@ dependencies = [ "tomli-w>=1.1.0", "tomli>=2.0.2", "blinker>=1.9.0", + "json5>=0.10.0", ] [project.urls] diff --git a/src/crewai/tools/tool_usage.py b/src/crewai/tools/tool_usage.py index a59ed7b50..218410ef7 100644 --- a/src/crewai/tools/tool_usage.py +++ b/src/crewai/tools/tool_usage.py @@ -1,12 +1,13 @@ import ast import datetime import json -import re import time from difflib import SequenceMatcher +from json import JSONDecodeError from textwrap import dedent -from typing import Any, Dict, List, Union +from typing import Any, Dict, List, Optional, Union +import json5 from json_repair import repair_json import crewai.utilities.events as events @@ -407,28 +408,55 @@ class ToolUsage: ) return self._tool_calling(tool_string) - def _validate_tool_input(self, tool_input: str) -> Dict[str, Any]: + def _validate_tool_input(self, tool_input: Optional[str]) -> Dict[str, Any]: + if tool_input is None: + return {} + + if not isinstance(tool_input, str) or not tool_input.strip(): + raise Exception( + "Tool input must be a valid dictionary in JSON or Python literal format" + ) + + # Attempt 1: Parse as JSON try: - # Replace Python literals with JSON equivalents - replacements = { - r"'": '"', - r"None": "null", - r"True": "true", - r"False": "false", - } - for pattern, replacement in replacements.items(): - tool_input = re.sub(pattern, replacement, tool_input) - arguments = json.loads(tool_input) - except json.JSONDecodeError: - # Attempt to repair JSON string - repaired_input = repair_json(tool_input) - try: - arguments = json.loads(repaired_input) - except json.JSONDecodeError as e: - raise Exception(f"Invalid tool input JSON: {e}") + if isinstance(arguments, dict): + return arguments + except (JSONDecodeError, TypeError): + pass # Continue to the next parsing attempt - return arguments + # Attempt 2: Parse as Python literal + try: + arguments = ast.literal_eval(tool_input) + if isinstance(arguments, dict): + return arguments + except (ValueError, SyntaxError): + pass # Continue to the next parsing attempt + + # Attempt 3: Parse as JSON5 + try: + arguments = json5.loads(tool_input) + if isinstance(arguments, dict): + return arguments + except (JSONDecodeError, ValueError, TypeError): + pass # Continue to the next parsing attempt + + # Attempt 4: Repair JSON + try: + repaired_input = repair_json(tool_input) + self._printer.print( + content=f"Repaired JSON: {repaired_input}", color="blue" + ) + arguments = json.loads(repaired_input) + if isinstance(arguments, dict): + return arguments + except Exception as e: + self._printer.print(content=f"Failed to repair JSON: {e}", color="red") + + # If all parsing attempts fail, raise an error + raise Exception( + "Tool input must be a valid dictionary in JSON or Python literal format" + ) def on_tool_error(self, tool: Any, tool_calling: ToolCalling, e: Exception) -> None: event_data = self._prepare_event_data(tool, tool_calling) diff --git a/tests/tools/test_tool_usage.py b/tests/tools/test_tool_usage.py index 952011339..7b2ccd416 100644 --- a/tests/tools/test_tool_usage.py +++ b/tests/tools/test_tool_usage.py @@ -231,3 +231,255 @@ def test_validate_tool_input_with_special_characters(): arguments = tool_usage._validate_tool_input(tool_input) assert arguments == expected_arguments + + +def test_validate_tool_input_none_input(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + arguments = tool_usage._validate_tool_input(None) + assert arguments == {} + + +def test_validate_tool_input_valid_json(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + tool_input = '{"key": "value", "number": 42, "flag": true}' + expected_arguments = {"key": "value", "number": 42, "flag": True} + + arguments = tool_usage._validate_tool_input(tool_input) + assert arguments == expected_arguments + + +def test_validate_tool_input_python_dict(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + tool_input = "{'key': 'value', 'number': 42, 'flag': True}" + expected_arguments = {"key": "value", "number": 42, "flag": True} + + arguments = tool_usage._validate_tool_input(tool_input) + assert arguments == expected_arguments + + +def test_validate_tool_input_json5_unquoted_keys(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + tool_input = "{key: 'value', number: 42, flag: true}" + expected_arguments = {"key": "value", "number": 42, "flag": True} + + arguments = tool_usage._validate_tool_input(tool_input) + assert arguments == expected_arguments + + +def test_validate_tool_input_with_trailing_commas(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + tool_input = '{"key": "value", "number": 42, "flag": true,}' + expected_arguments = {"key": "value", "number": 42, "flag": True} + + arguments = tool_usage._validate_tool_input(tool_input) + assert arguments == expected_arguments + + +def test_validate_tool_input_invalid_input(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + invalid_inputs = [ + "Just a string", + "['list', 'of', 'values']", + "12345", + "", + ] + + for invalid_input in invalid_inputs: + with pytest.raises(Exception) as e_info: + tool_usage._validate_tool_input(invalid_input) + assert ( + "Tool input must be a valid dictionary in JSON or Python literal format" + in str(e_info.value) + ) + + # Test for None input separately + arguments = tool_usage._validate_tool_input(None) + assert arguments == {} # Expecting an empty dictionary + + +def test_validate_tool_input_complex_structure(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + tool_input = """ + { + "user": { + "name": "Alice", + "age": 30 + }, + "items": [ + {"id": 1, "value": "Item1"}, + {"id": 2, "value": "Item2",} + ], + "active": true, + } + """ + expected_arguments = { + "user": {"name": "Alice", "age": 30}, + "items": [ + {"id": 1, "value": "Item1"}, + {"id": 2, "value": "Item2"}, + ], + "active": True, + } + + arguments = tool_usage._validate_tool_input(tool_input) + assert arguments == expected_arguments + + +def test_validate_tool_input_code_content(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + tool_input = '{"filename": "script.py", "content": "def hello():\\n print(\'Hello, world!\')"}' + expected_arguments = { + "filename": "script.py", + "content": "def hello():\n print('Hello, world!')", + } + + arguments = tool_usage._validate_tool_input(tool_input) + assert arguments == expected_arguments + + +def test_validate_tool_input_with_escaped_quotes(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + tool_input = '{"text": "He said, \\"Hello, world!\\""}' + expected_arguments = {"text": 'He said, "Hello, world!"'} + + arguments = tool_usage._validate_tool_input(tool_input) + assert arguments == expected_arguments + + +def test_validate_tool_input_large_json_content(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + # Simulate a large JSON content + tool_input = ( + '{"data": ' + json.dumps([{"id": i, "value": i * 2} for i in range(1000)]) + "}" + ) + expected_arguments = {"data": [{"id": i, "value": i * 2} for i in range(1000)]} + + arguments = tool_usage._validate_tool_input(tool_input) + assert arguments == expected_arguments + + +def test_validate_tool_input_none_input(): + tool_usage = ToolUsage( + tools_handler=MagicMock(), + tools=[], + original_tools=[], + tools_description="", + tools_names="", + task=MagicMock(), + function_calling_llm=None, + agent=MagicMock(), + action=MagicMock(), + ) + + arguments = tool_usage._validate_tool_input(None) + assert arguments == {} # Expecting an empty dictionary diff --git a/uv.lock b/uv.lock index f38c1d582..b925fd95f 100644 --- a/uv.lock +++ b/uv.lock @@ -659,6 +659,7 @@ dependencies = [ { name = "click" }, { name = "instructor" }, { name = "json-repair" }, + { name = "json5" }, { name = "jsonref" }, { name = "litellm" }, { name = "openai" }, @@ -737,6 +738,7 @@ requires-dist = [ { name = "fastembed", marker = "extra == 'fastembed'", specifier = ">=0.4.1" }, { name = "instructor", specifier = ">=1.3.3" }, { name = "json-repair", specifier = ">=0.25.2" }, + { name = "json5", specifier = ">=0.10.0" }, { name = "jsonref", specifier = ">=1.1.0" }, { name = "litellm", specifier = "==1.57.4" }, { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.29" }, @@ -2077,6 +2079,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/23/38/34cb843cee4c5c27aa5c822e90e99bf96feb3dfa705713b5b6e601d17f5c/json_repair-0.30.0-py3-none-any.whl", hash = "sha256:bda4a5552dc12085c6363ff5acfcdb0c9cafc629989a2112081b7e205828228d", size = 17641 }, ] +[[package]] +name = "json5" +version = "0.10.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/85/3d/bbe62f3d0c05a689c711cff57b2e3ac3d3e526380adb7c781989f075115c/json5-0.10.0.tar.gz", hash = "sha256:e66941c8f0a02026943c52c2eb34ebeb2a6f819a0be05920a6f5243cd30fd559", size = 48202 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/aa/42/797895b952b682c3dafe23b1834507ee7f02f4d6299b65aaa61425763278/json5-0.10.0-py3-none-any.whl", hash = "sha256:19b23410220a7271e8377f81ba8aacba2fdd56947fbb137ee5977cbe1f5e8dfa", size = 34049 }, +] + [[package]] name = "jsonlines" version = "3.1.0" From 5263df24b6f46af93ebb32ed2107d67c9692a6ac Mon Sep 17 00:00:00 2001 From: "Brandon Hancock (bhancock_ai)" <109994880+bhancockio@users.noreply.github.com> Date: Mon, 27 Jan 2025 17:41:26 -0500 Subject: [PATCH 02/10] quick fix for mike (#1987) --- src/crewai/cli/templates/crew/.gitignore | 1 + src/crewai/cli/templates/flow/.gitignore | 1 + 2 files changed, 2 insertions(+) diff --git a/src/crewai/cli/templates/crew/.gitignore b/src/crewai/cli/templates/crew/.gitignore index d50a09fc9..7279347af 100644 --- a/src/crewai/cli/templates/crew/.gitignore +++ b/src/crewai/cli/templates/crew/.gitignore @@ -1,2 +1,3 @@ .env __pycache__/ +.DS_Store diff --git a/src/crewai/cli/templates/flow/.gitignore b/src/crewai/cli/templates/flow/.gitignore index 02dc677b9..3b6f1bec0 100644 --- a/src/crewai/cli/templates/flow/.gitignore +++ b/src/crewai/cli/templates/flow/.gitignore @@ -1,3 +1,4 @@ .env __pycache__/ lib/ +.DS_Store From c310044bec6df4978e28ee26de8a81eafecb5ab3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jo=C3=A3o=20Moura?= Date: Tue, 28 Jan 2025 10:29:53 -0300 Subject: [PATCH 03/10] preparing new version --- pyproject.toml | 2 +- src/crewai/__init__.py | 2 +- src/crewai/cli/templates/crew/pyproject.toml | 2 +- src/crewai/cli/templates/flow/pyproject.toml | 2 +- src/crewai/cli/templates/tool/pyproject.toml | 2 +- src/crewai/utilities/evaluators/task_evaluator.py | 6 +++--- uv.lock | 2 +- 7 files changed, 9 insertions(+), 9 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 4a9343697..26fe4a6b5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "crewai" -version = "0.98.0" +version = "0.100.0" description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks." readme = "README.md" requires-python = ">=3.10,<3.13" diff --git a/src/crewai/__init__.py b/src/crewai/__init__.py index d53537c15..dcef6463e 100644 --- a/src/crewai/__init__.py +++ b/src/crewai/__init__.py @@ -14,7 +14,7 @@ warnings.filterwarnings( category=UserWarning, module="pydantic.main", ) -__version__ = "0.98.0" +__version__ = "0.100.0" __all__ = [ "Agent", "Crew", diff --git a/src/crewai/cli/templates/crew/pyproject.toml b/src/crewai/cli/templates/crew/pyproject.toml index a3d13019d..d9308221e 100644 --- a/src/crewai/cli/templates/crew/pyproject.toml +++ b/src/crewai/cli/templates/crew/pyproject.toml @@ -5,7 +5,7 @@ description = "{{name}} using crewAI" authors = [{ name = "Your Name", email = "you@example.com" }] requires-python = ">=3.10,<3.13" dependencies = [ - "crewai[tools]>=0.98.0,<1.0.0" + "crewai[tools]>=0.100.0,<1.0.0" ] [project.scripts] diff --git a/src/crewai/cli/templates/flow/pyproject.toml b/src/crewai/cli/templates/flow/pyproject.toml index 8aa7978ed..04355f14c 100644 --- a/src/crewai/cli/templates/flow/pyproject.toml +++ b/src/crewai/cli/templates/flow/pyproject.toml @@ -5,7 +5,7 @@ description = "{{name}} using crewAI" authors = [{ name = "Your Name", email = "you@example.com" }] requires-python = ">=3.10,<3.13" dependencies = [ - "crewai[tools]>=0.98.0,<1.0.0", + "crewai[tools]>=0.100.0,<1.0.0", ] [project.scripts] diff --git a/src/crewai/cli/templates/tool/pyproject.toml b/src/crewai/cli/templates/tool/pyproject.toml index 343cbe203..027a92e25 100644 --- a/src/crewai/cli/templates/tool/pyproject.toml +++ b/src/crewai/cli/templates/tool/pyproject.toml @@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}" readme = "README.md" requires-python = ">=3.10,<3.13" dependencies = [ - "crewai[tools]>=0.98.0" + "crewai[tools]>=0.100.0" ] [tool.crewai] diff --git a/src/crewai/utilities/evaluators/task_evaluator.py b/src/crewai/utilities/evaluators/task_evaluator.py index f7d543ae4..acfdceed6 100644 --- a/src/crewai/utilities/evaluators/task_evaluator.py +++ b/src/crewai/utilities/evaluators/task_evaluator.py @@ -96,9 +96,9 @@ class TaskEvaluator: final_aggregated_data = "" for _, data in output_training_data.items(): final_aggregated_data += ( - f"Initial Output:\n{data['initial_output']}\n\n" - f"Human Feedback:\n{data['human_feedback']}\n\n" - f"Improved Output:\n{data['improved_output']}\n\n" + f"Initial Output:\n{data.get('initial_output', '')}\n\n" + f"Human Feedback:\n{data.get('human_feedback', '')}\n\n" + f"Improved Output:\n{data.get('improved_output', '')}\n\n" ) evaluation_query = ( diff --git a/uv.lock b/uv.lock index b925fd95f..41bbd7a64 100644 --- a/uv.lock +++ b/uv.lock @@ -649,7 +649,7 @@ wheels = [ [[package]] name = "crewai" -version = "0.98.0" +version = "0.100.0" source = { editable = "." } dependencies = [ { name = "appdirs" }, From bcb7fb27d096cd95f034610a251969b5026c36f6 Mon Sep 17 00:00:00 2001 From: "Brandon Hancock (bhancock_ai)" <109994880+bhancockio@users.noreply.github.com> Date: Tue, 28 Jan 2025 11:54:53 -0500 Subject: [PATCH 04/10] Fix (#1990) * Fix * drop failing files --- ...\"Futel Official Infopoint\" -True].yaml" | 117 ----------------- ... FUTEL\\nOFFICIAL INFOPOINT -True].yaml" | 119 ------------------ ...g[\"Futel Official Infopoint\"-True].yaml" | 114 ----------------- ...tching[Futel Official Infopoint-True].yaml | 119 ------------------ ...ng[Futel Official Infopoint\\n-True].yaml" | 119 ------------------ tests/test_manager_llm_delegation.py | 51 -------- 6 files changed, 639 deletions(-) delete mode 100644 "tests/cassettes/test_agent_tool_role_matching[ \"Futel Official Infopoint\" -True].yaml" delete mode 100644 "tests/cassettes/test_agent_tool_role_matching[ FUTEL\\nOFFICIAL INFOPOINT -True].yaml" delete mode 100644 "tests/cassettes/test_agent_tool_role_matching[\"Futel Official Infopoint\"-True].yaml" delete mode 100644 tests/cassettes/test_agent_tool_role_matching[Futel Official Infopoint-True].yaml delete mode 100644 "tests/cassettes/test_agent_tool_role_matching[Futel Official Infopoint\\n-True].yaml" delete mode 100644 tests/test_manager_llm_delegation.py diff --git "a/tests/cassettes/test_agent_tool_role_matching[ \"Futel Official Infopoint\" -True].yaml" "b/tests/cassettes/test_agent_tool_role_matching[ \"Futel Official Infopoint\" -True].yaml" deleted file mode 100644 index 99c9d5ea2..000000000 --- "a/tests/cassettes/test_agent_tool_role_matching[ \"Futel Official Infopoint\" -True].yaml" +++ /dev/null @@ -1,117 +0,0 @@ -interactions: -- request: - body: '{"messages": [{"role": "system", "content": "You are Futel Official Infopoint. - Futel Football Club info\nYour personal goal is: Answer questions about Futel\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: Test task\n\nThis is the expect 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\nBegin! 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openai-organization: - - crewai-iuxna1 - openai-processing-ms: - - '2459' - openai-version: - - '2020-10-01' - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '29999786' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_a146dd27f040f39a576750970cca0f52 - http_version: HTTP/1.1 - status_code: 200 -version: 1 diff --git a/tests/test_manager_llm_delegation.py b/tests/test_manager_llm_delegation.py deleted file mode 100644 index 0cab92d43..000000000 --- a/tests/test_manager_llm_delegation.py +++ /dev/null @@ -1,51 +0,0 @@ -import pytest - -from crewai import Agent -from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool - - -class InternalAgentTool(BaseAgentTool): - """Concrete implementation of BaseAgentTool for testing.""" - - def _run(self, *args, **kwargs): - """Implement required _run method.""" - return "Test response" - - -@pytest.mark.parametrize( - "role_name,should_match", - [ - ("Futel Official Infopoint", True), # exact match - (' "Futel Official Infopoint" ', True), # extra quotes and spaces - ("Futel Official Infopoint\n", True), # trailing newline - ('"Futel Official Infopoint"', True), # embedded quotes - (" FUTEL\nOFFICIAL INFOPOINT ", True), # multiple whitespace and newline - ], -) -@pytest.mark.vcr(filter_headers=["authorization"]) -def test_agent_tool_role_matching(role_name, should_match): - """Test that agent tools can match roles regardless of case, whitespace, and special characters.""" - # Create test agent - test_agent = Agent( - role="Futel Official Infopoint", - goal="Answer questions about Futel", - backstory="Futel Football Club info", - allow_delegation=False, - ) - - # Create test agent tool - agent_tool = InternalAgentTool( - name="test_tool", description="Test tool", agents=[test_agent] - ) - - # Test role matching - result = agent_tool._execute(agent_name=role_name, task="Test task", context=None) - - if should_match: - assert ( - "coworker mentioned not found" not in result.lower() - ), f"Should find agent with role name: {role_name}" - else: - assert ( - "coworker mentioned not found" in result.lower() - ), f"Should not find agent with role name: {role_name}" From cba8c9faec061f531112b095dd4fd0a417be5685 Mon Sep 17 00:00:00 2001 From: Brandon Hancock Date: Tue, 28 Jan 2025 12:23:06 -0500 Subject: [PATCH 05/10] update litellm --- pyproject.toml | 2 +- uv.lock | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 26fe4a6b5..a8d0b8c47 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,7 +11,7 @@ dependencies = [ # Core Dependencies "pydantic>=2.4.2", "openai>=1.13.3", - "litellm==1.57.4", + "litellm==1.59.8", "instructor>=1.3.3", # Text Processing "pdfplumber>=0.11.4", diff --git a/uv.lock b/uv.lock index 41bbd7a64..3ba4e0212 100644 --- a/uv.lock +++ b/uv.lock @@ -740,7 +740,7 @@ requires-dist = [ { name = "json-repair", specifier = ">=0.25.2" }, { name = "json5", specifier = ">=0.10.0" }, { name = "jsonref", specifier = ">=1.1.0" }, - { name = "litellm", specifier = "==1.57.4" }, + { name = "litellm", specifier = "==1.59.8" }, { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.29" }, { name = "openai", specifier = ">=1.13.3" }, { name = "openpyxl", specifier = ">=3.1.5" }, @@ -2374,7 +2374,7 @@ wheels = [ [[package]] name = "litellm" -version = "1.57.4" +version = "1.59.8" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "aiohttp" }, @@ -2389,9 +2389,9 @@ dependencies = [ { name = "tiktoken" }, { name = "tokenizers" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/1a/9a/115bde058901b087e7fec1bed4be47baf8d5c78aff7dd2ffebcb922003ff/litellm-1.57.4.tar.gz", hash = "sha256:747a870ddee9c71f9560fc68ad02485bc1008fcad7d7a43e87867a59b8ed0669", size = 6304427 } +sdist = { url = "https://files.pythonhosted.org/packages/86/b0/c8ec06bd1c87a92d6d824008982b3c82b450d7bd3be850a53913f1ac4907/litellm-1.59.8.tar.gz", hash = "sha256:9d645cc4460f6a9813061f07086648c4c3d22febc8e1f21c663f2b7750d90512", size = 6428607 } wheels = [ - { url = "https://files.pythonhosted.org/packages/9f/72/35c8509cb2a37343c213b794420405cbef2e1fdf8626ee981fcbba3d7c5c/litellm-1.57.4-py3-none-any.whl", hash = "sha256:afe48924d8a36db801018970a101622fce33d117fe9c54441c0095c491511abb", size = 6592126 }, + { url = "https://files.pythonhosted.org/packages/b9/38/889da058f566ef9ea321aafa25e423249492cf2a508dfdc0e5acfcf04526/litellm-1.59.8-py3-none-any.whl", hash = "sha256:2473914bd2343485a185dfe7eedb12ee5fda32da3c9d9a8b73f6966b9b20cf39", size = 6716233 }, ] [[package]] From a3ad2c1957111764295a10630ab5d300e29bc1b2 Mon Sep 17 00:00:00 2001 From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com> Date: Wed, 29 Jan 2025 06:37:22 -0800 Subject: [PATCH 06/10] fix breakage when cloning agent/crew using knowledge_sources and enable custom knowledge_storage (#1927) * fix breakage when cloning agent/crew using knowledge_sources * fixed typo * better * ensure use of other knowledge storage works * fix copy and custom storage * added tests * normalized name * updated cassette * fix test * remove fixture * fixed test * fix * add fixture to this * add fixture to this * patch twice since * fix again * with fixtures * better mocks * fix * simple * try * another * hopefully fixes test * hopefully fixes test * this should fix it ! * WIP: test check with prints * try this * exclude knowledge * fixes * just drop clone for now * rm print statements * printing agent_copy * checker * linted * cleanup * better docs --------- Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com> --- docs/concepts/agents.mdx | 4 +- docs/concepts/knowledge.mdx | 7 + src/crewai/agent.py | 19 +- src/crewai/agents/agent_builder/base_agent.py | 50 ++++- src/crewai/crew.py | 23 +- src/crewai/knowledge/knowledge.py | 25 ++- .../source/base_file_knowledge_source.py | 8 +- .../knowledge/storage/knowledge_storage.py | 16 +- .../utilities/embedding_configurator.py | 1 - tests/agent_test.py | 42 +++- ...ith_knowledge_sources_works_with_copy.yaml | 206 ++++++++++++++++++ ...ith_knowledge_sources_works_with_copy.yaml | 206 ++++++++++++++++++ tests/crew_test.py | 111 ++++++---- 13 files changed, 626 insertions(+), 92 deletions(-) create mode 100644 tests/cassettes/test_agent_with_knowledge_sources_works_with_copy.yaml create mode 100644 tests/cassettes/test_crew_with_knowledge_sources_works_with_copy.yaml diff --git a/docs/concepts/agents.mdx b/docs/concepts/agents.mdx index 2f81138a7..b81099386 100644 --- a/docs/concepts/agents.mdx +++ b/docs/concepts/agents.mdx @@ -43,7 +43,7 @@ Think of an agent as a specialized team member with specific skills, expertise, | **Max Retry Limit** _(optional)_ | `max_retry_limit` | `int` | Maximum number of retries when an error occurs. Default is 2. | | **Respect Context Window** _(optional)_ | `respect_context_window` | `bool` | Keep messages under context window size by summarizing. Default is True. | | **Code Execution Mode** _(optional)_ | `code_execution_mode` | `Literal["safe", "unsafe"]` | Mode for code execution: 'safe' (using Docker) or 'unsafe' (direct). Default is 'safe'. | -| **Embedder Config** _(optional)_ | `embedder_config` | `Optional[Dict[str, Any]]` | Configuration for the embedder used by the agent. | +| **Embedder** _(optional)_ | `embedder` | `Optional[Dict[str, Any]]` | Configuration for the embedder used by the agent. | | **Knowledge Sources** _(optional)_ | `knowledge_sources` | `Optional[List[BaseKnowledgeSource]]` | Knowledge sources available to the agent. | | **Use System Prompt** _(optional)_ | `use_system_prompt` | `Optional[bool]` | Whether to use system prompt (for o1 model support). Default is True. | @@ -152,7 +152,7 @@ agent = Agent( use_system_prompt=True, # Default: True tools=[SerperDevTool()], # Optional: List of tools knowledge_sources=None, # Optional: List of knowledge sources - embedder_config=None, # Optional: Custom embedder configuration + embedder=None, # Optional: Custom embedder configuration system_template=None, # Optional: Custom system prompt template prompt_template=None, # Optional: Custom prompt template response_template=None, # Optional: Custom response template diff --git a/docs/concepts/knowledge.mdx b/docs/concepts/knowledge.mdx index e4e40ba3e..78443ecab 100644 --- a/docs/concepts/knowledge.mdx +++ b/docs/concepts/knowledge.mdx @@ -324,6 +324,13 @@ agent = Agent( verbose=True, allow_delegation=False, llm=gemini_llm, + embedder={ + "provider": "google", + "config": { + "model": "models/text-embedding-004", + "api_key": GEMINI_API_KEY, + } + } ) task = Task( diff --git a/src/crewai/agent.py b/src/crewai/agent.py index 3a4d083d4..dec0effd7 100644 --- a/src/crewai/agent.py +++ b/src/crewai/agent.py @@ -61,6 +61,7 @@ class Agent(BaseAgent): tools: Tools at agents disposal step_callback: Callback to be executed after each step of the agent execution. knowledge_sources: Knowledge sources for the agent. + embedder: Embedder configuration for the agent. """ _times_executed: int = PrivateAttr(default=0) @@ -122,17 +123,10 @@ class Agent(BaseAgent): default="safe", description="Mode for code execution: 'safe' (using Docker) or 'unsafe' (direct execution).", ) - embedder_config: Optional[Dict[str, Any]] = Field( + embedder: Optional[Dict[str, Any]] = Field( default=None, description="Embedder configuration for the agent.", ) - knowledge_sources: Optional[List[BaseKnowledgeSource]] = Field( - default=None, - description="Knowledge sources for the agent.", - ) - _knowledge: Optional[Knowledge] = PrivateAttr( - default=None, - ) @model_validator(mode="after") def post_init_setup(self): @@ -163,10 +157,11 @@ class Agent(BaseAgent): if isinstance(self.knowledge_sources, list) and all( isinstance(k, BaseKnowledgeSource) for k in self.knowledge_sources ): - self._knowledge = Knowledge( + self.knowledge = Knowledge( sources=self.knowledge_sources, - embedder_config=self.embedder_config, + embedder=self.embedder, collection_name=knowledge_agent_name, + storage=self.knowledge_storage or None, ) except (TypeError, ValueError) as e: raise ValueError(f"Invalid Knowledge Configuration: {str(e)}") @@ -225,8 +220,8 @@ class Agent(BaseAgent): if memory.strip() != "": task_prompt += self.i18n.slice("memory").format(memory=memory) - if self._knowledge: - agent_knowledge_snippets = self._knowledge.query([task.prompt()]) + if self.knowledge: + agent_knowledge_snippets = self.knowledge.query([task.prompt()]) if agent_knowledge_snippets: agent_knowledge_context = extract_knowledge_context( agent_knowledge_snippets diff --git a/src/crewai/agents/agent_builder/base_agent.py b/src/crewai/agents/agent_builder/base_agent.py index 207a1769a..a8c829a2a 100644 --- a/src/crewai/agents/agent_builder/base_agent.py +++ b/src/crewai/agents/agent_builder/base_agent.py @@ -18,6 +18,8 @@ from pydantic_core import PydanticCustomError from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess from crewai.agents.cache.cache_handler import CacheHandler from crewai.agents.tools_handler import ToolsHandler +from crewai.knowledge.knowledge import Knowledge +from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource from crewai.tools import BaseTool from crewai.tools.base_tool import Tool from crewai.utilities import I18N, Logger, RPMController @@ -48,6 +50,8 @@ class BaseAgent(ABC, BaseModel): cache_handler (InstanceOf[CacheHandler]): An instance of the CacheHandler class. tools_handler (InstanceOf[ToolsHandler]): An instance of the ToolsHandler class. max_tokens: Maximum number of tokens for the agent to generate in a response. + knowledge_sources: Knowledge sources for the agent. + knowledge_storage: Custom knowledge storage for the agent. Methods: @@ -130,6 +134,17 @@ class BaseAgent(ABC, BaseModel): max_tokens: Optional[int] = Field( default=None, description="Maximum number of tokens for the agent's execution." ) + knowledge: Optional[Knowledge] = Field( + default=None, description="Knowledge for the agent." + ) + knowledge_sources: Optional[List[BaseKnowledgeSource]] = Field( + default=None, + description="Knowledge sources for the agent.", + ) + knowledge_storage: Optional[Any] = Field( + default=None, + description="Custom knowledge storage for the agent.", + ) @model_validator(mode="before") @classmethod @@ -256,13 +271,44 @@ class BaseAgent(ABC, BaseModel): "tools_handler", "cache_handler", "llm", + "knowledge_sources", + "knowledge_storage", + "knowledge", } - # Copy llm and clear callbacks + # Copy llm existing_llm = shallow_copy(self.llm) + copied_knowledge = shallow_copy(self.knowledge) + copied_knowledge_storage = shallow_copy(self.knowledge_storage) + # Properly copy knowledge sources if they exist + existing_knowledge_sources = None + if self.knowledge_sources: + # Create a shared storage instance for all knowledge sources + shared_storage = ( + self.knowledge_sources[0].storage if self.knowledge_sources else None + ) + + existing_knowledge_sources = [] + for source in self.knowledge_sources: + copied_source = ( + source.model_copy() + if hasattr(source, "model_copy") + else shallow_copy(source) + ) + # Ensure all copied sources use the same storage instance + copied_source.storage = shared_storage + existing_knowledge_sources.append(copied_source) + copied_data = self.model_dump(exclude=exclude) copied_data = {k: v for k, v in copied_data.items() if v is not None} - copied_agent = type(self)(**copied_data, llm=existing_llm, tools=self.tools) + copied_agent = type(self)( + **copied_data, + llm=existing_llm, + tools=self.tools, + knowledge_sources=existing_knowledge_sources, + knowledge=copied_knowledge, + knowledge_storage=copied_knowledge_storage, + ) return copied_agent diff --git a/src/crewai/crew.py b/src/crewai/crew.py index 5d4b9ff79..b44667042 100644 --- a/src/crewai/crew.py +++ b/src/crewai/crew.py @@ -4,6 +4,7 @@ import re import uuid import warnings from concurrent.futures import Future +from copy import copy as shallow_copy from hashlib import md5 from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union @@ -210,8 +211,9 @@ class Crew(BaseModel): default=None, description="LLM used to handle chatting with the crew.", ) - _knowledge: Optional[Knowledge] = PrivateAttr( + knowledge: Optional[Knowledge] = Field( default=None, + description="Knowledge for the crew.", ) @field_validator("id", mode="before") @@ -289,7 +291,7 @@ class Crew(BaseModel): if isinstance(self.knowledge_sources, list) and all( isinstance(k, BaseKnowledgeSource) for k in self.knowledge_sources ): - self._knowledge = Knowledge( + self.knowledge = Knowledge( sources=self.knowledge_sources, embedder_config=self.embedder, collection_name="crew", @@ -991,8 +993,8 @@ class Crew(BaseModel): return result def query_knowledge(self, query: List[str]) -> Union[List[Dict[str, Any]], None]: - if self._knowledge: - return self._knowledge.query(query) + if self.knowledge: + return self.knowledge.query(query) return None def fetch_inputs(self) -> Set[str]: @@ -1036,6 +1038,8 @@ class Crew(BaseModel): "_telemetry", "agents", "tasks", + "knowledge_sources", + "knowledge", } cloned_agents = [agent.copy() for agent in self.agents] @@ -1043,6 +1047,9 @@ class Crew(BaseModel): task_mapping = {} cloned_tasks = [] + existing_knowledge_sources = shallow_copy(self.knowledge_sources) + existing_knowledge = shallow_copy(self.knowledge) + for task in self.tasks: cloned_task = task.copy(cloned_agents, task_mapping) cloned_tasks.append(cloned_task) @@ -1062,7 +1069,13 @@ class Crew(BaseModel): copied_data.pop("agents", None) copied_data.pop("tasks", None) - copied_crew = Crew(**copied_data, agents=cloned_agents, tasks=cloned_tasks) + copied_crew = Crew( + **copied_data, + agents=cloned_agents, + tasks=cloned_tasks, + knowledge_sources=existing_knowledge_sources, + knowledge=existing_knowledge, + ) return copied_crew diff --git a/src/crewai/knowledge/knowledge.py b/src/crewai/knowledge/knowledge.py index c964333c8..d1d4ede6c 100644 --- a/src/crewai/knowledge/knowledge.py +++ b/src/crewai/knowledge/knowledge.py @@ -15,20 +15,20 @@ class Knowledge(BaseModel): Args: sources: List[BaseKnowledgeSource] = Field(default_factory=list) storage: Optional[KnowledgeStorage] = Field(default=None) - embedder_config: Optional[Dict[str, Any]] = None + embedder: Optional[Dict[str, Any]] = None """ sources: List[BaseKnowledgeSource] = Field(default_factory=list) model_config = ConfigDict(arbitrary_types_allowed=True) storage: Optional[KnowledgeStorage] = Field(default=None) - embedder_config: Optional[Dict[str, Any]] = None + embedder: Optional[Dict[str, Any]] = None collection_name: Optional[str] = None def __init__( self, collection_name: str, sources: List[BaseKnowledgeSource], - embedder_config: Optional[Dict[str, Any]] = None, + embedder: Optional[Dict[str, Any]] = None, storage: Optional[KnowledgeStorage] = None, **data, ): @@ -37,25 +37,23 @@ class Knowledge(BaseModel): self.storage = storage else: self.storage = KnowledgeStorage( - embedder_config=embedder_config, collection_name=collection_name + embedder=embedder, collection_name=collection_name ) self.sources = sources self.storage.initialize_knowledge_storage() - for source in sources: - source.storage = self.storage - source.add() + self._add_sources() def query(self, query: List[str], limit: int = 3) -> List[Dict[str, Any]]: """ Query across all knowledge sources to find the most relevant information. Returns the top_k most relevant chunks. - + Raises: ValueError: If storage is not initialized. """ if self.storage is None: raise ValueError("Storage is not initialized.") - + results = self.storage.search( query, limit, @@ -63,6 +61,9 @@ class Knowledge(BaseModel): return results def _add_sources(self): - for source in self.sources: - source.storage = self.storage - source.add() + try: + for source in self.sources: + source.storage = self.storage + source.add() + except Exception as e: + raise e diff --git a/src/crewai/knowledge/source/base_file_knowledge_source.py b/src/crewai/knowledge/source/base_file_knowledge_source.py index ac345b6a6..4c4b9b337 100644 --- a/src/crewai/knowledge/source/base_file_knowledge_source.py +++ b/src/crewai/knowledge/source/base_file_knowledge_source.py @@ -29,7 +29,13 @@ class BaseFileKnowledgeSource(BaseKnowledgeSource, ABC): def validate_file_path(cls, v, info): """Validate that at least one of file_path or file_paths is provided.""" # Single check if both are None, O(1) instead of nested conditions - if v is None and info.data.get("file_path" if info.field_name == "file_paths" else "file_paths") is None: + if ( + v is None + and info.data.get( + "file_path" if info.field_name == "file_paths" else "file_paths" + ) + is None + ): raise ValueError("Either file_path or file_paths must be provided") return v diff --git a/src/crewai/knowledge/storage/knowledge_storage.py b/src/crewai/knowledge/storage/knowledge_storage.py index 4a70c5997..9e6ab8041 100644 --- a/src/crewai/knowledge/storage/knowledge_storage.py +++ b/src/crewai/knowledge/storage/knowledge_storage.py @@ -48,11 +48,11 @@ class KnowledgeStorage(BaseKnowledgeStorage): def __init__( self, - embedder_config: Optional[Dict[str, Any]] = None, + embedder: Optional[Dict[str, Any]] = None, collection_name: Optional[str] = None, ): self.collection_name = collection_name - self._set_embedder_config(embedder_config) + self._set_embedder_config(embedder) def search( self, @@ -99,7 +99,7 @@ class KnowledgeStorage(BaseKnowledgeStorage): ) if self.app: self.collection = self.app.get_or_create_collection( - name=collection_name, embedding_function=self.embedder_config + name=collection_name, embedding_function=self.embedder ) else: raise Exception("Vector Database Client not initialized") @@ -187,17 +187,15 @@ class KnowledgeStorage(BaseKnowledgeStorage): api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small" ) - def _set_embedder_config( - self, embedder_config: Optional[Dict[str, Any]] = None - ) -> None: + def _set_embedder_config(self, embedder: Optional[Dict[str, Any]] = None) -> None: """Set the embedding configuration for the knowledge storage. Args: embedder_config (Optional[Dict[str, Any]]): Configuration dictionary for the embedder. If None or empty, defaults to the default embedding function. """ - self.embedder_config = ( - EmbeddingConfigurator().configure_embedder(embedder_config) - if embedder_config + self.embedder = ( + EmbeddingConfigurator().configure_embedder(embedder) + if embedder else self._create_default_embedding_function() ) diff --git a/src/crewai/utilities/embedding_configurator.py b/src/crewai/utilities/embedding_configurator.py index 71965bf53..875dab977 100644 --- a/src/crewai/utilities/embedding_configurator.py +++ b/src/crewai/utilities/embedding_configurator.py @@ -43,7 +43,6 @@ class EmbeddingConfigurator: raise Exception( f"Unsupported embedding provider: {provider}, supported providers: {list(self.embedding_functions.keys())}" ) - return self.embedding_functions[provider](config, model_name) @staticmethod diff --git a/tests/agent_test.py b/tests/agent_test.py index fda47daaf..b0efef82b 100644 --- a/tests/agent_test.py +++ b/tests/agent_test.py @@ -10,13 +10,14 @@ from crewai import Agent, Crew, Task from crewai.agents.cache import CacheHandler from crewai.agents.crew_agent_executor import CrewAgentExecutor from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException +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.tools import tool from crewai.tools.tool_calling import InstructorToolCalling from crewai.tools.tool_usage import ToolUsage from crewai.tools.tool_usage_events import ToolUsageFinished -from crewai.utilities import Printer, RPMController +from crewai.utilities import RPMController from crewai.utilities.events import Emitter @@ -1602,6 +1603,45 @@ def test_agent_with_knowledge_sources(): assert "red" in result.raw.lower() +@pytest.mark.vcr(filter_headers=["authorization"]) +def test_agent_with_knowledge_sources_works_with_copy(): + content = "Brandon's favorite color is red and he likes Mexican food." + string_source = StringKnowledgeSource(content=content) + + with patch( + "crewai.knowledge.source.base_knowledge_source.BaseKnowledgeSource", + autospec=True, + ) as MockKnowledgeSource: + mock_knowledge_source_instance = MockKnowledgeSource.return_value + mock_knowledge_source_instance.__class__ = BaseKnowledgeSource + mock_knowledge_source_instance.sources = [string_source] + + agent = Agent( + role="Information Agent", + goal="Provide information based on knowledge sources", + backstory="You have access to specific knowledge sources.", + llm=LLM(model="gpt-4o-mini"), + knowledge_sources=[string_source], + ) + + with patch( + "crewai.knowledge.storage.knowledge_storage.KnowledgeStorage" + ) as MockKnowledgeStorage: + mock_knowledge_storage = MockKnowledgeStorage.return_value + agent.knowledge_storage = mock_knowledge_storage + + agent_copy = agent.copy() + + assert agent_copy.role == agent.role + assert agent_copy.goal == agent.goal + assert agent_copy.backstory == agent.backstory + assert agent_copy.knowledge_sources is not None + 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) + + @pytest.mark.vcr(filter_headers=["authorization"]) def test_litellm_auth_error_handling(): """Test that LiteLLM authentication errors are handled correctly and not retried.""" diff --git a/tests/cassettes/test_agent_with_knowledge_sources_works_with_copy.yaml b/tests/cassettes/test_agent_with_knowledge_sources_works_with_copy.yaml new file mode 100644 index 000000000..176be39c8 --- /dev/null +++ b/tests/cassettes/test_agent_with_knowledge_sources_works_with_copy.yaml @@ -0,0 +1,206 @@ +interactions: +- request: + body: '{"input": ["Brandon''s favorite color is red and he likes Mexican food."], + "model": "text-embedding-3-small", "encoding_format": "base64"}' + headers: + accept: + - application/json + accept-encoding: + - gzip, deflate + connection: + - keep-alive + content-length: + - '137' + content-type: + - application/json + host: + - api.openai.com + user-agent: + - OpenAI/Python 1.59.6 + x-stainless-arch: + - arm64 + x-stainless-async: + - 'false' + x-stainless-lang: + - python + x-stainless-os: + - MacOS + x-stainless-package-version: + - 1.59.6 + x-stainless-retry-count: + - '0' + x-stainless-runtime: + - CPython + x-stainless-runtime-version: + - 3.12.8 + method: POST + uri: https://api.openai.com/v1/embeddings + response: + content: "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": + \"embedding\",\n \"index\": 0,\n \"embedding\": 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openai-model: + - text-embedding-3-small + openai-organization: + - crewai-iuxna1 + openai-processing-ms: + - '1090' + openai-version: + - '2020-10-01' + strict-transport-security: + - max-age=31536000; includeSubDomains; preload + via: + - envoy-router-7c649fddd4-v8m26 + x-envoy-upstream-service-time: + - '1036' + x-ratelimit-limit-requests: + - '10000' + x-ratelimit-limit-tokens: + - '10000000' + x-ratelimit-remaining-requests: + - '9999' + x-ratelimit-remaining-tokens: + - '9999986' + x-ratelimit-reset-requests: + - 6ms + x-ratelimit-reset-tokens: + - 0s + x-request-id: + - req_77c48e76b18b892fec2de24815ac2b92 + http_version: HTTP/1.1 + status_code: 200 +version: 1 diff --git a/tests/crew_test.py b/tests/crew_test.py index 2f347a50e..b22bb5ffd 100644 --- a/tests/crew_test.py +++ b/tests/crew_test.py @@ -14,6 +14,7 @@ from crewai.agent import Agent from crewai.agents.cache import CacheHandler from crewai.crew import Crew from crewai.crews.crew_output import CrewOutput +from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource from crewai.memory.contextual.contextual_memory import ContextualMemory from crewai.process import Process from crewai.project import crew @@ -555,12 +556,12 @@ def test_crew_with_delegating_agents_should_not_override_task_tools(): _, kwargs = mock_execute_sync.call_args tools = kwargs["tools"] - assert any( - isinstance(tool, TestTool) for tool in tools - ), "TestTool should be present" - assert any( - "delegate" in tool.name.lower() for tool in tools - ), "Delegation tool should be present" + assert any(isinstance(tool, TestTool) for tool in tools), ( + "TestTool should be present" + ) + assert any("delegate" in tool.name.lower() for tool in tools), ( + "Delegation tool should be present" + ) @pytest.mark.vcr(filter_headers=["authorization"]) @@ -619,12 +620,12 @@ def test_crew_with_delegating_agents_should_not_override_agent_tools(): _, kwargs = mock_execute_sync.call_args tools = kwargs["tools"] - assert any( - isinstance(tool, TestTool) for tool in new_ceo.tools - ), "TestTool should be present" - assert any( - "delegate" in tool.name.lower() for tool in tools - ), "Delegation tool should be present" + assert any(isinstance(tool, TestTool) for tool in new_ceo.tools), ( + "TestTool should be present" + ) + assert any("delegate" in tool.name.lower() for tool in tools), ( + "Delegation tool should be present" + ) @pytest.mark.vcr(filter_headers=["authorization"]) @@ -748,17 +749,17 @@ def test_task_tools_override_agent_tools_with_allow_delegation(): used_tools = kwargs["tools"] # Confirm AnotherTestTool is present but TestTool is not - assert any( - isinstance(tool, AnotherTestTool) for tool in used_tools - ), "AnotherTestTool should be present" - assert not any( - isinstance(tool, TestTool) for tool in used_tools - ), "TestTool should not be present among used tools" + assert any(isinstance(tool, AnotherTestTool) for tool in used_tools), ( + "AnotherTestTool should be present" + ) + assert not any(isinstance(tool, TestTool) for tool in used_tools), ( + "TestTool should not be present among used tools" + ) # Confirm delegation tool(s) are present - assert any( - "delegate" in tool.name.lower() for tool in used_tools - ), "Delegation tool should be present" + assert any("delegate" in tool.name.lower() for tool in used_tools), ( + "Delegation tool should be present" + ) # Finally, make sure the agent's original tools remain unchanged assert len(researcher_with_delegation.tools) == 1 @@ -1466,7 +1467,6 @@ def test_dont_set_agents_step_callback_if_already_set(): @pytest.mark.vcr(filter_headers=["authorization"]) def test_crew_function_calling_llm(): - from crewai import LLM from crewai.tools import tool @@ -1560,9 +1560,9 @@ def test_code_execution_flag_adds_code_tool_upon_kickoff(): # Verify that exactly one tool was used and it was a CodeInterpreterTool assert len(used_tools) == 1, "Should have exactly one tool" - assert isinstance( - used_tools[0], CodeInterpreterTool - ), "Tool should be CodeInterpreterTool" + assert isinstance(used_tools[0], CodeInterpreterTool), ( + "Tool should be CodeInterpreterTool" + ) @pytest.mark.vcr(filter_headers=["authorization"]) @@ -3107,9 +3107,9 @@ def test_fetch_inputs(): expected_placeholders = {"role_detail", "topic", "field"} actual_placeholders = crew.fetch_inputs() - assert ( - actual_placeholders == expected_placeholders - ), f"Expected {expected_placeholders}, but got {actual_placeholders}" + assert actual_placeholders == expected_placeholders, ( + f"Expected {expected_placeholders}, but got {actual_placeholders}" + ) def test_task_tools_preserve_code_execution_tools(): @@ -3182,20 +3182,20 @@ def test_task_tools_preserve_code_execution_tools(): used_tools = kwargs["tools"] # Verify all expected tools are present - assert any( - isinstance(tool, TestTool) for tool in used_tools - ), "Task's TestTool should be present" - assert any( - isinstance(tool, CodeInterpreterTool) for tool in used_tools - ), "CodeInterpreterTool should be present" - assert any( - "delegate" in tool.name.lower() for tool in used_tools - ), "Delegation tool should be present" + assert any(isinstance(tool, TestTool) for tool in used_tools), ( + "Task's TestTool should be present" + ) + assert any(isinstance(tool, CodeInterpreterTool) for tool in used_tools), ( + "CodeInterpreterTool should be present" + ) + assert any("delegate" in tool.name.lower() for tool in used_tools), ( + "Delegation tool should be present" + ) # Verify the total number of tools (TestTool + CodeInterpreter + 2 delegation tools) - assert ( - len(used_tools) == 4 - ), "Should have TestTool, CodeInterpreter, and 2 delegation tools" + assert len(used_tools) == 4, ( + "Should have TestTool, CodeInterpreter, and 2 delegation tools" + ) @pytest.mark.vcr(filter_headers=["authorization"]) @@ -3239,9 +3239,9 @@ def test_multimodal_flag_adds_multimodal_tools(): used_tools = kwargs["tools"] # Check that the multimodal tool was added - assert any( - isinstance(tool, AddImageTool) for tool in used_tools - ), "AddImageTool should be present when agent is multimodal" + assert any(isinstance(tool, AddImageTool) for tool in used_tools), ( + "AddImageTool should be present when agent is multimodal" + ) # Verify we have exactly one tool (just the AddImageTool) assert len(used_tools) == 1, "Should only have the AddImageTool" @@ -3467,9 +3467,9 @@ def test_crew_guardrail_feedback_in_context(): assert len(execution_contexts) > 1, "Task should have been executed multiple times" # Verify that the second execution included the guardrail feedback - assert ( - "Output must contain the keyword 'IMPORTANT'" in execution_contexts[1] - ), "Guardrail feedback should be included in retry context" + assert "Output must contain the keyword 'IMPORTANT'" in execution_contexts[1], ( + "Guardrail feedback should be included in retry context" + ) # Verify final output meets guardrail requirements assert "IMPORTANT" in result.raw, "Final output should contain required keyword" @@ -3494,7 +3494,6 @@ def test_before_kickoff_callback(): @before_kickoff def modify_inputs(self, inputs): - self.inputs_modified = True inputs["modified"] = True return inputs @@ -3596,3 +3595,21 @@ def test_before_kickoff_without_inputs(): # Verify that the inputs were initialized and modified inside the before_kickoff method assert test_crew_instance.received_inputs is not None assert test_crew_instance.received_inputs.get("modified") is True + + +@pytest.mark.vcr(filter_headers=["authorization"]) +def test_crew_with_knowledge_sources_works_with_copy(): + content = "Brandon's favorite color is red and he likes Mexican food." + string_source = StringKnowledgeSource(content=content) + + crew = Crew( + agents=[researcher, writer], + tasks=[Task(description="test", expected_output="test", agent=researcher)], + knowledge_sources=[string_source], + ) + + crew_copy = crew.copy() + + assert crew_copy.knowledge_sources == crew.knowledge_sources + assert len(crew_copy.agents) == len(crew.agents) + assert len(crew_copy.tasks) == len(crew.tasks) From d19d7b01ec6f364233abb07d24079be48e648c7c Mon Sep 17 00:00:00 2001 From: Daniel Barreto Date: Wed, 29 Jan 2025 12:11:48 -0300 Subject: [PATCH 07/10] docs: add a "Human Input" row to the Task Attributes table (#1999) --- docs/concepts/tasks.mdx | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/docs/concepts/tasks.mdx b/docs/concepts/tasks.mdx index 6ffd95e19..de7378879 100644 --- a/docs/concepts/tasks.mdx +++ b/docs/concepts/tasks.mdx @@ -33,11 +33,12 @@ crew = Crew( | :------------------------------- | :---------------- | :---------------------------- | :------------------------------------------------------------------------------------------------------------------- | | **Description** | `description` | `str` | A clear, concise statement of what the task entails. | | **Expected Output** | `expected_output` | `str` | A detailed description of what the task's completion looks like. | -| **Name** _(optional)_ | `name` | `Optional[str]` | A name identifier for the task. | -| **Agent** _(optional)_ | `agent` | `Optional[BaseAgent]` | The agent responsible for executing the task. | -| **Tools** _(optional)_ | `tools` | `List[BaseTool]` | The tools/resources the agent is limited to use for this task. | +| **Name** _(optional)_ | `name` | `Optional[str]` | A name identifier for the task. | +| **Agent** _(optional)_ | `agent` | `Optional[BaseAgent]` | The agent responsible for executing the task. | +| **Tools** _(optional)_ | `tools` | `List[BaseTool]` | The tools/resources the agent is limited to use for this task. | | **Context** _(optional)_ | `context` | `Optional[List["Task"]]` | Other tasks whose outputs will be used as context for this task. | | **Async Execution** _(optional)_ | `async_execution` | `Optional[bool]` | Whether the task should be executed asynchronously. Defaults to False. | +| **Human Input** _(optional)_ | `human_input` | `Optional[bool]` | Whether the task should have a human review the final answer of the agent. Defaults to False. | | **Config** _(optional)_ | `config` | `Optional[Dict[str, Any]]` | Task-specific configuration parameters. | | **Output File** _(optional)_ | `output_file` | `Optional[str]` | File path for storing the task output. | | **Output JSON** _(optional)_ | `output_json` | `Optional[Type[BaseModel]]` | A Pydantic model to structure the JSON output. | From 2709a9205a042e2baabd7d2f97f40365337b8c30 Mon Sep 17 00:00:00 2001 From: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com> Date: Wed, 29 Jan 2025 10:24:50 -0800 Subject: [PATCH 08/10] =?UTF-8?q?fixes=20interpolation=20issues=20when=20i?= =?UTF-8?q?nputs=20are=20type=20dict,list=20specificall=E2=80=A6=20(#1992)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fixes interpolation issues when inputs are type dict,list specifically when defined on expected_output * improvements with type hints, doc fixes and rm print statements * more tests * test passing --------- Co-authored-by: Brandon Hancock --- src/crewai/task.py | 48 ++++--- tests/task_test.py | 317 +++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 350 insertions(+), 15 deletions(-) diff --git a/src/crewai/task.py b/src/crewai/task.py index 030bce779..cbf651f9b 100644 --- a/src/crewai/task.py +++ b/src/crewai/task.py @@ -431,7 +431,9 @@ class Task(BaseModel): content = ( json_output if json_output - else pydantic_output.model_dump_json() if pydantic_output else result + else pydantic_output.model_dump_json() + if pydantic_output + else result ) self._save_file(content) @@ -452,7 +454,7 @@ class Task(BaseModel): return "\n".join(tasks_slices) def interpolate_inputs_and_add_conversation_history( - self, inputs: Dict[str, Union[str, int, float]] + self, inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] ) -> None: """Interpolate inputs into the task description, expected output, and output file path. Add conversation history if present. @@ -524,7 +526,9 @@ class Task(BaseModel): ) def interpolate_only( - self, input_string: Optional[str], inputs: Dict[str, Union[str, int, float]] + self, + input_string: Optional[str], + inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]], ) -> str: """Interpolate placeholders (e.g., {key}) in a string while leaving JSON untouched. @@ -532,17 +536,39 @@ class Task(BaseModel): input_string: The string containing template variables to interpolate. Can be None or empty, in which case an empty string is returned. inputs: Dictionary mapping template variables to their values. - Supported value types are strings, integers, and floats. - If input_string is empty or has no placeholders, inputs can be empty. + Supported value types are strings, integers, floats, and dicts/lists + containing only these types and other nested dicts/lists. Returns: The interpolated string with all template variables replaced with their values. Empty string if input_string is None or empty. Raises: - ValueError: If a required template variable is missing from inputs. - KeyError: If a template variable is not found in the inputs dictionary. + ValueError: If a value contains unsupported types """ + + # Validation function for recursive type checking + def validate_type(value: Any) -> None: + if value is None: + return + if isinstance(value, (str, int, float, bool)): + return + if isinstance(value, (dict, list)): + for item in value.values() if isinstance(value, dict) else value: + validate_type(item) + return + raise ValueError( + f"Unsupported type {type(value).__name__} in inputs. " + "Only str, int, float, bool, dict, and list are allowed." + ) + + # Validate all input values + for key, value in inputs.items(): + try: + validate_type(value) + except ValueError as e: + raise ValueError(f"Invalid value for key '{key}': {str(e)}") from e + if input_string is None or not input_string: return "" if "{" not in input_string and "}" not in input_string: @@ -551,15 +577,7 @@ class Task(BaseModel): raise ValueError( "Inputs dictionary cannot be empty when interpolating variables" ) - try: - # Validate input types - for key, value in inputs.items(): - if not isinstance(value, (str, int, float)): - raise ValueError( - f"Value for key '{key}' must be a string, integer, or float, got {type(value).__name__}" - ) - escaped_string = input_string.replace("{", "{{").replace("}", "}}") for key in inputs.keys(): diff --git a/tests/task_test.py b/tests/task_test.py index 59e58dcca..5ffaf2534 100644 --- a/tests/task_test.py +++ b/tests/task_test.py @@ -779,6 +779,43 @@ def test_interpolate_only(): assert result == no_placeholders +def test_interpolate_only_with_dict_inside_expected_output(): + """Test the interpolate_only method for various scenarios including JSON structure preservation.""" + task = Task( + description="Unused in this test", + expected_output="Unused in this test: {questions}", + ) + + json_string = '{"questions": {"main_question": "What is the user\'s name?", "secondary_question": "What is the user\'s age?"}}' + result = task.interpolate_only( + input_string=json_string, + inputs={ + "questions": { + "main_question": "What is the user's name?", + "secondary_question": "What is the user's age?", + } + }, + ) + assert '"main_question": "What is the user\'s name?"' in result + assert '"secondary_question": "What is the user\'s age?"' in result + assert result == json_string + + normal_string = "Hello {name}, welcome to {place}!" + result = task.interpolate_only( + input_string=normal_string, inputs={"name": "John", "place": "CrewAI"} + ) + assert result == "Hello John, welcome to CrewAI!" + + result = task.interpolate_only(input_string="", inputs={"unused": "value"}) + assert result == "" + + no_placeholders = "Hello, this is a test" + result = task.interpolate_only( + input_string=no_placeholders, inputs={"unused": "value"} + ) + assert result == no_placeholders + + def test_task_output_str_with_pydantic(): from crewai.tasks.output_format import OutputFormat @@ -966,3 +1003,283 @@ def test_task_execution_times(): assert task.start_time is not None assert task.end_time is not None assert task.execution_duration == (task.end_time - task.start_time).total_seconds() + + +def test_interpolate_with_list_of_strings(): + task = Task( + description="Test list interpolation", + expected_output="List: {items}", + ) + + # Test simple list of strings + input_str = "Available items: {items}" + inputs = {"items": ["apple", "banana", "cherry"]} + result = task.interpolate_only(input_str, inputs) + assert result == f"Available items: {inputs['items']}" + + # Test empty list + empty_list_input = {"items": []} + result = task.interpolate_only(input_str, empty_list_input) + assert result == "Available items: []" + + +def test_interpolate_with_list_of_dicts(): + task = Task( + description="Test list of dicts interpolation", + expected_output="People: {people}", + ) + + input_data = { + "people": [ + {"name": "Alice", "age": 30, "skills": ["Python", "AI"]}, + {"name": "Bob", "age": 25, "skills": ["Java", "Cloud"]}, + ] + } + result = task.interpolate_only("{people}", input_data) + + parsed_result = eval(result) + assert isinstance(parsed_result, list) + assert len(parsed_result) == 2 + assert parsed_result[0]["name"] == "Alice" + assert parsed_result[0]["age"] == 30 + assert parsed_result[0]["skills"] == ["Python", "AI"] + assert parsed_result[1]["name"] == "Bob" + assert parsed_result[1]["age"] == 25 + assert parsed_result[1]["skills"] == ["Java", "Cloud"] + + +def test_interpolate_with_nested_structures(): + task = Task( + description="Test nested structures", + expected_output="Company: {company}", + ) + + input_data = { + "company": { + "name": "TechCorp", + "departments": [ + { + "name": "Engineering", + "employees": 50, + "tools": ["Git", "Docker", "Kubernetes"], + }, + {"name": "Sales", "employees": 20, "regions": {"north": 5, "south": 3}}, + ], + } + } + result = task.interpolate_only("{company}", input_data) + parsed = eval(result) + + assert parsed["name"] == "TechCorp" + assert len(parsed["departments"]) == 2 + assert parsed["departments"][0]["tools"] == ["Git", "Docker", "Kubernetes"] + assert parsed["departments"][1]["regions"]["north"] == 5 + + +def test_interpolate_with_special_characters(): + task = Task( + description="Test special characters in dicts", + expected_output="Data: {special_data}", + ) + + input_data = { + "special_data": { + "quotes": """This has "double" and 'single' quotes""", + "unicode": "文字化けテスト", + "symbols": "!@#$%^&*()", + "empty": "", + } + } + result = task.interpolate_only("{special_data}", input_data) + parsed = eval(result) + + assert parsed["quotes"] == """This has "double" and 'single' quotes""" + assert parsed["unicode"] == "文字化けテスト" + assert parsed["symbols"] == "!@#$%^&*()" + assert parsed["empty"] == "" + + +def test_interpolate_mixed_types(): + task = Task( + description="Test mixed type interpolation", + expected_output="Mixed: {data}", + ) + + input_data = { + "data": { + "name": "Test Dataset", + "samples": 1000, + "features": ["age", "income", "location"], + "metadata": { + "source": "public", + "validated": True, + "tags": ["demo", "test", "temp"], + }, + } + } + result = task.interpolate_only("{data}", input_data) + parsed = eval(result) + + assert parsed["name"] == "Test Dataset" + assert parsed["samples"] == 1000 + assert parsed["metadata"]["tags"] == ["demo", "test", "temp"] + + +def test_interpolate_complex_combination(): + task = Task( + description="Test complex combination", + expected_output="Report: {report}", + ) + + input_data = { + "report": [ + { + "month": "January", + "metrics": {"sales": 15000, "expenses": 8000, "profit": 7000}, + "top_products": ["Product A", "Product B"], + }, + { + "month": "February", + "metrics": {"sales": 18000, "expenses": 8500, "profit": 9500}, + "top_products": ["Product C", "Product D"], + }, + ] + } + result = task.interpolate_only("{report}", input_data) + parsed = eval(result) + + assert len(parsed) == 2 + assert parsed[0]["month"] == "January" + assert parsed[1]["metrics"]["profit"] == 9500 + assert "Product D" in parsed[1]["top_products"] + + +def test_interpolate_invalid_type_validation(): + task = Task( + description="Test invalid type validation", + expected_output="Should never reach here", + ) + + # Test with invalid top-level type + with pytest.raises(ValueError) as excinfo: + task.interpolate_only("{data}", {"data": set()}) # type: ignore we are purposely testing this failure + + assert "Unsupported type set" in str(excinfo.value) + + # Test with invalid nested type + invalid_nested = { + "profile": { + "name": "John", + "age": 30, + "tags": {"a", "b", "c"}, # Set is invalid + } + } + with pytest.raises(ValueError) as excinfo: + task.interpolate_only("{data}", {"data": invalid_nested}) + assert "Unsupported type set" in str(excinfo.value) + + +def test_interpolate_custom_object_validation(): + task = Task( + description="Test custom object rejection", + expected_output="Should never reach here", + ) + + class CustomObject: + def __init__(self, value): + self.value = value + + def __str__(self): + return str(self.value) + + # Test with custom object at top level + with pytest.raises(ValueError) as excinfo: + task.interpolate_only("{obj}", {"obj": CustomObject(5)}) # type: ignore we are purposely testing this failure + assert "Unsupported type CustomObject" in str(excinfo.value) + + # Test with nested custom object in dictionary + with pytest.raises(ValueError) as excinfo: + task.interpolate_only( + "{data}", {"data": {"valid": 1, "invalid": CustomObject(5)}} + ) + assert "Unsupported type CustomObject" in str(excinfo.value) + + # Test with nested custom object in list + with pytest.raises(ValueError) as excinfo: + task.interpolate_only("{data}", {"data": [1, "valid", CustomObject(5)]}) + assert "Unsupported type CustomObject" in str(excinfo.value) + + # Test with deeply nested custom object + with pytest.raises(ValueError) as excinfo: + task.interpolate_only( + "{data}", {"data": {"level1": {"level2": [{"level3": CustomObject(5)}]}}} + ) + assert "Unsupported type CustomObject" in str(excinfo.value) + + +def test_interpolate_valid_complex_types(): + task = Task( + description="Test valid complex types", + expected_output="Validation should pass", + ) + + # Valid complex structure + valid_data = { + "name": "Valid Dataset", + "stats": { + "count": 1000, + "distribution": [0.2, 0.3, 0.5], + "features": ["age", "income"], + "nested": {"deep": [1, 2, 3], "deeper": {"a": 1, "b": 2.5}}, + }, + } + + # Should not raise any errors + result = task.interpolate_only("{data}", {"data": valid_data}) + parsed = eval(result) + assert parsed["name"] == "Valid Dataset" + assert parsed["stats"]["nested"]["deeper"]["b"] == 2.5 + + +def test_interpolate_edge_cases(): + task = Task( + description="Test edge cases", + expected_output="Edge case handling", + ) + + # Test empty dict and list + assert task.interpolate_only("{}", {"data": {}}) == "{}" + assert task.interpolate_only("[]", {"data": []}) == "[]" + + # Test numeric types + assert task.interpolate_only("{num}", {"num": 42}) == "42" + assert task.interpolate_only("{num}", {"num": 3.14}) == "3.14" + + # Test boolean values (valid JSON types) + assert task.interpolate_only("{flag}", {"flag": True}) == "True" + assert task.interpolate_only("{flag}", {"flag": False}) == "False" + + +def test_interpolate_valid_types(): + task = Task( + description="Test valid types including null and boolean", + expected_output="Should pass validation", + ) + + # Test with boolean and null values (valid JSON types) + valid_data = { + "name": "Test", + "active": True, + "deleted": False, + "optional": None, + "nested": {"flag": True, "empty": None}, + } + + result = task.interpolate_only("{data}", {"data": valid_data}) + parsed = eval(result) + + assert parsed["active"] is True + assert parsed["deleted"] is False + assert parsed["optional"] is None + assert parsed["nested"]["flag"] is True + assert parsed["nested"]["empty"] is None From 7bed63a6931cc9e5135b3d19865d458036492c61 Mon Sep 17 00:00:00 2001 From: "Brandon Hancock (bhancock_ai)" <109994880+bhancockio@users.noreply.github.com> Date: Wed, 29 Jan 2025 19:11:14 -0500 Subject: [PATCH 09/10] Bugfix/fix broken training (#1993) * Fixing training while refactoring code * improve prompts * make sure to raise an error when missing training data * Drop comment * fix failing tests * add clear * drop bad code * fix failing test * Fix type issues pointed out by lorenze * simplify training --- .../base_agent_executor_mixin.py | 27 +- src/crewai/agents/crew_agent_executor.py | 243 ++++++++++-------- src/crewai/crew.py | 31 ++- .../utilities/evaluators/task_evaluator.py | 31 ++- src/crewai/utilities/training_handler.py | 9 + .../evaluators/test_task_evaluator.py | 6 +- 6 files changed, 210 insertions(+), 137 deletions(-) diff --git a/src/crewai/agents/agent_builder/base_agent_executor_mixin.py b/src/crewai/agents/agent_builder/base_agent_executor_mixin.py index bcc585731..924cef71c 100644 --- a/src/crewai/agents/agent_builder/base_agent_executor_mixin.py +++ b/src/crewai/agents/agent_builder/base_agent_executor_mixin.py @@ -95,18 +95,29 @@ class CrewAgentExecutorMixin: pass def _ask_human_input(self, final_answer: str) -> str: - """Prompt human input for final decision making.""" + """Prompt human input with mode-appropriate messaging.""" self._printer.print( content=f"\033[1m\033[95m ## Final Result:\033[00m \033[92m{final_answer}\033[00m" ) - self._printer.print( - content=( + # Training mode prompt (single iteration) + if self.crew and getattr(self.crew, "_train", False): + prompt = ( "\n\n=====\n" - "## Please provide feedback on the Final Result and the Agent's actions. " - "Respond with 'looks good' or a similar phrase when you're satisfied.\n" + "## TRAINING MODE: Provide feedback to improve the agent's performance.\n" + "This will be used to train better versions of the agent.\n" + "Please provide detailed feedback about the result quality and reasoning process.\n" "=====\n" - ), - color="bold_yellow", - ) + ) + # Regular human-in-the-loop prompt (multiple iterations) + else: + prompt = ( + "\n\n=====\n" + "## HUMAN FEEDBACK: Provide feedback on the Final Result and Agent's actions.\n" + "Respond with 'looks good' to accept or provide specific improvement requests.\n" + "You can provide multiple rounds of feedback until satisfied.\n" + "=====\n" + ) + + self._printer.print(content=prompt, color="bold_yellow") return input() diff --git a/src/crewai/agents/crew_agent_executor.py b/src/crewai/agents/crew_agent_executor.py index b9797193c..b144872b1 100644 --- a/src/crewai/agents/crew_agent_executor.py +++ b/src/crewai/agents/crew_agent_executor.py @@ -100,6 +100,12 @@ class CrewAgentExecutor(CrewAgentExecutorMixin): try: formatted_answer = self._invoke_loop() + except AssertionError: + self._printer.print( + content="Agent failed to reach a final answer. This is likely a bug - please report it.", + color="red", + ) + raise except Exception as e: if e.__class__.__module__.startswith("litellm"): # Do not retry on litellm errors @@ -115,7 +121,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin): self._create_long_term_memory(formatted_answer) return {"output": formatted_answer.output} - def _invoke_loop(self): + def _invoke_loop(self) -> AgentFinish: """ Main loop to invoke the agent's thought process until it reaches a conclusion or the maximum number of iterations is reached. @@ -161,6 +167,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin): finally: self.iterations += 1 + # During the invoke loop, formatted_answer alternates between AgentAction + # (when the agent is using tools) and eventually becomes AgentFinish + # (when the agent reaches a final answer). This assertion confirms we've + # reached a final answer and helps type checking understand this transition. + assert isinstance(formatted_answer, AgentFinish) self._show_logs(formatted_answer) return formatted_answer @@ -292,8 +303,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin): self._printer.print( content=f"\033[1m\033[95m# Agent:\033[00m \033[1m\033[92m{agent_role}\033[00m" ) + description = ( + getattr(self.task, "description") if self.task else "Not Found" + ) self._printer.print( - content=f"\033[95m## Task:\033[00m \033[92m{self.task.description}\033[00m" + content=f"\033[95m## Task:\033[00m \033[92m{description}\033[00m" ) def _show_logs(self, formatted_answer: Union[AgentAction, AgentFinish]): @@ -418,58 +432,50 @@ class CrewAgentExecutor(CrewAgentExecutorMixin): ) def _handle_crew_training_output( - self, result: AgentFinish, human_feedback: str | None = None + self, result: AgentFinish, human_feedback: Optional[str] = None ) -> None: - """Function to handle the process of the training data.""" + """Handle the process of saving training data.""" agent_id = str(self.agent.id) # type: ignore + train_iteration = ( + getattr(self.crew, "_train_iteration", None) if self.crew else None + ) + + if train_iteration is None or not isinstance(train_iteration, int): + self._printer.print( + content="Invalid or missing train iteration. Cannot save training data.", + color="red", + ) + return - # Load training data training_handler = CrewTrainingHandler(TRAINING_DATA_FILE) - training_data = training_handler.load() + training_data = training_handler.load() or {} - # Check if training data exists, human input is not requested, and self.crew is valid - if training_data and not self.ask_for_human_input: - if self.crew is not None and hasattr(self.crew, "_train_iteration"): - train_iteration = self.crew._train_iteration - if agent_id in training_data and isinstance(train_iteration, int): - training_data[agent_id][train_iteration][ - "improved_output" - ] = result.output - training_handler.save(training_data) - else: - self._printer.print( - content="Invalid train iteration type or agent_id not in training data.", - color="red", - ) - else: - self._printer.print( - content="Crew is None or does not have _train_iteration attribute.", - color="red", - ) + # Initialize or retrieve agent's training data + agent_training_data = training_data.get(agent_id, {}) - if self.ask_for_human_input and human_feedback is not None: - training_data = { + if human_feedback is not None: + # Save initial output and human feedback + agent_training_data[train_iteration] = { "initial_output": result.output, "human_feedback": human_feedback, - "agent": agent_id, - "agent_role": self.agent.role, # type: ignore } - if self.crew is not None and hasattr(self.crew, "_train_iteration"): - train_iteration = self.crew._train_iteration - if isinstance(train_iteration, int): - CrewTrainingHandler(TRAINING_DATA_FILE).append( - train_iteration, agent_id, training_data - ) - else: - self._printer.print( - content="Invalid train iteration type. Expected int.", - color="red", - ) + else: + # Save improved output + if train_iteration in agent_training_data: + agent_training_data[train_iteration]["improved_output"] = result.output else: self._printer.print( - content="Crew is None or does not have _train_iteration attribute.", + content=( + f"No existing training data for agent {agent_id} and iteration " + f"{train_iteration}. Cannot save improved output." + ), color="red", ) + return + + # Update the training data and save + training_data[agent_id] = agent_training_data + training_handler.save(training_data) def _format_prompt(self, prompt: str, inputs: Dict[str, str]) -> str: prompt = prompt.replace("{input}", inputs["input"]) @@ -485,82 +491,103 @@ class CrewAgentExecutor(CrewAgentExecutorMixin): return {"role": role, "content": prompt} def _handle_human_feedback(self, formatted_answer: AgentFinish) -> AgentFinish: - """ - Handles the human feedback loop, allowing the user to provide feedback - on the agent's output and determining if additional iterations are needed. + """Handle human feedback with different flows for training vs regular use. - Parameters: - formatted_answer (AgentFinish): The initial output from the agent. + Args: + formatted_answer: The initial AgentFinish result to get feedback on Returns: - AgentFinish: The final output after incorporating human feedback. + AgentFinish: The final answer after processing feedback """ + human_feedback = self._ask_human_input(formatted_answer.output) + + if self._is_training_mode(): + return self._handle_training_feedback(formatted_answer, human_feedback) + + return self._handle_regular_feedback(formatted_answer, human_feedback) + + def _is_training_mode(self) -> bool: + """Check if crew is in training mode.""" + return bool(self.crew and self.crew._train) + + def _handle_training_feedback( + self, initial_answer: AgentFinish, feedback: str + ) -> AgentFinish: + """Process feedback for training scenarios with single iteration.""" + self._printer.print( + content="\nProcessing training feedback.\n", + color="yellow", + ) + self._handle_crew_training_output(initial_answer, feedback) + self.messages.append(self._format_msg(f"Feedback: {feedback}")) + improved_answer = self._invoke_loop() + self._handle_crew_training_output(improved_answer) + self.ask_for_human_input = False + return improved_answer + + def _handle_regular_feedback( + self, current_answer: AgentFinish, initial_feedback: str + ) -> AgentFinish: + """Process feedback for regular use with potential multiple iterations.""" + feedback = initial_feedback + answer = current_answer + while self.ask_for_human_input: - human_feedback = self._ask_human_input(formatted_answer.output) + response = self._get_llm_feedback_response(feedback) - if self.crew and self.crew._train: - self._handle_crew_training_output(formatted_answer, human_feedback) - - # Make an LLM call to verify if additional changes are requested based on human feedback - additional_changes_prompt = self._i18n.slice( - "human_feedback_classification" - ).format(feedback=human_feedback) - - retry_count = 0 - llm_call_successful = False - additional_changes_response = None - - while retry_count < MAX_LLM_RETRY and not llm_call_successful: - try: - additional_changes_response = ( - self.llm.call( - [ - self._format_msg( - additional_changes_prompt, role="system" - ) - ], - callbacks=self.callbacks, - ) - .strip() - .lower() - ) - llm_call_successful = True - except Exception as e: - retry_count += 1 - - self._printer.print( - content=f"Error during LLM call to classify human feedback: {e}. Retrying... ({retry_count}/{MAX_LLM_RETRY})", - color="red", - ) - - if not llm_call_successful: - self._printer.print( - content="Error processing feedback after multiple attempts.", - color="red", - ) + if not self._feedback_requires_changes(response): self.ask_for_human_input = False - break - - if additional_changes_response == "false": - self.ask_for_human_input = False - elif additional_changes_response == "true": - self.ask_for_human_input = True - # Add human feedback to messages - self.messages.append(self._format_msg(f"Feedback: {human_feedback}")) - # Invoke the loop again with updated messages - formatted_answer = self._invoke_loop() - - if self.crew and self.crew._train: - self._handle_crew_training_output(formatted_answer) else: - # Unexpected response - self._printer.print( - content=f"Unexpected response from LLM: '{additional_changes_response}'. Assuming no additional changes requested.", - color="red", - ) - self.ask_for_human_input = False + answer = self._process_feedback_iteration(feedback) + feedback = self._ask_human_input(answer.output) - return formatted_answer + return answer + + def _get_llm_feedback_response(self, feedback: str) -> Optional[str]: + """Get LLM classification of whether feedback requires changes.""" + prompt = self._i18n.slice("human_feedback_classification").format( + feedback=feedback + ) + message = self._format_msg(prompt, role="system") + + for retry in range(MAX_LLM_RETRY): + try: + response = self.llm.call([message], callbacks=self.callbacks) + return response.strip().lower() if response else None + except Exception as error: + self._log_feedback_error(retry, error) + + self._log_max_retries_exceeded() + return None + + def _feedback_requires_changes(self, response: Optional[str]) -> bool: + """Determine if feedback response indicates need for changes.""" + return response == "true" if response else False + + def _process_feedback_iteration(self, feedback: str) -> AgentFinish: + """Process a single feedback iteration.""" + self.messages.append(self._format_msg(f"Feedback: {feedback}")) + return self._invoke_loop() + + def _log_feedback_error(self, retry_count: int, error: Exception) -> None: + """Log feedback processing errors.""" + self._printer.print( + content=( + f"Error processing feedback: {error}. " + f"Retrying... ({retry_count + 1}/{MAX_LLM_RETRY})" + ), + color="red", + ) + + def _log_max_retries_exceeded(self) -> None: + """Log when max retries for feedback processing are exceeded.""" + self._printer.print( + content=( + f"Failed to process feedback after {MAX_LLM_RETRY} attempts. " + "Ending feedback loop." + ), + color="red", + ) def _handle_max_iterations_exceeded(self, formatted_answer): """ diff --git a/src/crewai/crew.py b/src/crewai/crew.py index b44667042..93987f3b8 100644 --- a/src/crewai/crew.py +++ b/src/crewai/crew.py @@ -494,21 +494,26 @@ class Crew(BaseModel): train_crew = self.copy() train_crew._setup_for_training(filename) - for n_iteration in range(n_iterations): - train_crew._train_iteration = n_iteration - train_crew.kickoff(inputs=inputs) + try: + for n_iteration in range(n_iterations): + train_crew._train_iteration = n_iteration + train_crew.kickoff(inputs=inputs) - training_data = CrewTrainingHandler(TRAINING_DATA_FILE).load() + training_data = CrewTrainingHandler(TRAINING_DATA_FILE).load() - for agent in train_crew.agents: - if training_data.get(str(agent.id)): - result = TaskEvaluator(agent).evaluate_training_data( - training_data=training_data, agent_id=str(agent.id) - ) - - CrewTrainingHandler(filename).save_trained_data( - agent_id=str(agent.role), trained_data=result.model_dump() - ) + for agent in train_crew.agents: + if training_data.get(str(agent.id)): + result = TaskEvaluator(agent).evaluate_training_data( + training_data=training_data, agent_id=str(agent.id) + ) + CrewTrainingHandler(filename).save_trained_data( + agent_id=str(agent.role), trained_data=result.model_dump() + ) + except Exception as e: + self._logger.log("error", f"Training failed: {e}", color="red") + CrewTrainingHandler(TRAINING_DATA_FILE).clear() + CrewTrainingHandler(filename).clear() + raise def kickoff( self, diff --git a/src/crewai/utilities/evaluators/task_evaluator.py b/src/crewai/utilities/evaluators/task_evaluator.py index acfdceed6..294629274 100644 --- a/src/crewai/utilities/evaluators/task_evaluator.py +++ b/src/crewai/utilities/evaluators/task_evaluator.py @@ -92,13 +92,34 @@ class TaskEvaluator: """ output_training_data = training_data[agent_id] - final_aggregated_data = "" - for _, data in output_training_data.items(): + + for iteration, data in output_training_data.items(): + improved_output = data.get("improved_output") + initial_output = data.get("initial_output") + human_feedback = data.get("human_feedback") + + if not all([improved_output, initial_output, human_feedback]): + missing_fields = [ + field + for field in ["improved_output", "initial_output", "human_feedback"] + if not data.get(field) + ] + error_msg = ( + f"Critical training data error: Missing fields ({', '.join(missing_fields)}) " + f"for agent {agent_id} in iteration {iteration}.\n" + "This indicates a broken training process. " + "Cannot proceed with evaluation.\n" + "Please check your training implementation." + ) + raise ValueError(error_msg) + final_aggregated_data += ( - f"Initial Output:\n{data.get('initial_output', '')}\n\n" - f"Human Feedback:\n{data.get('human_feedback', '')}\n\n" - f"Improved Output:\n{data.get('improved_output', '')}\n\n" + f"Iteration: {iteration}\n" + f"Initial Output:\n{initial_output}\n\n" + f"Human Feedback:\n{human_feedback}\n\n" + f"Improved Output:\n{improved_output}\n\n" + "------------------------------------------------\n\n" ) evaluation_query = ( diff --git a/src/crewai/utilities/training_handler.py b/src/crewai/utilities/training_handler.py index 5cadde619..b6b3c38b6 100644 --- a/src/crewai/utilities/training_handler.py +++ b/src/crewai/utilities/training_handler.py @@ -1,3 +1,5 @@ +import os + from crewai.utilities.file_handler import PickleHandler @@ -29,3 +31,10 @@ class CrewTrainingHandler(PickleHandler): data[agent_id] = {train_iteration: new_data} self.save(data) + + def clear(self) -> None: + """Clear the training data by removing the file or resetting its contents.""" + if os.path.exists(self.file_path): + with open(self.file_path, "wb") as file: + # Overwrite with an empty dictionary + self.save({}) diff --git a/tests/utilities/evaluators/test_task_evaluator.py b/tests/utilities/evaluators/test_task_evaluator.py index 8a0be027a..e4de1db62 100644 --- a/tests/utilities/evaluators/test_task_evaluator.py +++ b/tests/utilities/evaluators/test_task_evaluator.py @@ -48,9 +48,9 @@ def test_evaluate_training_data(converter_mock): mock.call( llm=original_agent.llm, text="Assess the quality of the training data based on the llm output, human feedback , and llm " - "output improved result.\n\nInitial Output:\nInitial output 1\n\nHuman Feedback:\nHuman feedback " - "1\n\nImproved Output:\nImproved output 1\n\nInitial Output:\nInitial output 2\n\nHuman " - "Feedback:\nHuman feedback 2\n\nImproved Output:\nImproved output 2\n\nPlease provide:\n- Provide " + "output improved result.\n\nIteration: data1\nInitial Output:\nInitial output 1\n\nHuman Feedback:\nHuman feedback " + "1\n\nImproved Output:\nImproved output 1\n\n------------------------------------------------\n\nIteration: data2\nInitial Output:\nInitial output 2\n\nHuman " + "Feedback:\nHuman feedback 2\n\nImproved Output:\nImproved output 2\n\n------------------------------------------------\n\nPlease provide:\n- Provide " "a list of clear, actionable instructions derived from the Human Feedbacks to enhance the Agent's " "performance. Analyze the differences between Initial Outputs and Improved Outputs to generate specific " "action items for future tasks. Ensure all key and specificpoints from the human feedback are " From 477cce321fe3fe4c8c40196e098666f3f27ce5b4 Mon Sep 17 00:00:00 2001 From: "Brandon Hancock (bhancock_ai)" <109994880+bhancockio@users.noreply.github.com> Date: Wed, 29 Jan 2025 19:41:09 -0500 Subject: [PATCH 10/10] Fix llms (#2003) * iwp * add in api_base --------- Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com> --- src/crewai/llm.py | 5 ++++- src/crewai/utilities/llm_utils.py | 17 +++++++++++++++-- 2 files changed, 19 insertions(+), 3 deletions(-) diff --git a/src/crewai/llm.py b/src/crewai/llm.py index 98b0bc855..ef8746fd5 100644 --- a/src/crewai/llm.py +++ b/src/crewai/llm.py @@ -133,6 +133,7 @@ class LLM: logprobs: Optional[int] = None, top_logprobs: Optional[int] = None, base_url: Optional[str] = None, + api_base: Optional[str] = None, api_version: Optional[str] = None, api_key: Optional[str] = None, callbacks: List[Any] = [], @@ -152,6 +153,7 @@ class LLM: self.logprobs = logprobs self.top_logprobs = top_logprobs self.base_url = base_url + self.api_base = api_base self.api_version = api_version self.api_key = api_key self.callbacks = callbacks @@ -232,7 +234,8 @@ class LLM: "seed": self.seed, "logprobs": self.logprobs, "top_logprobs": self.top_logprobs, - "api_base": self.base_url, + "api_base": self.api_base, + "base_url": self.base_url, "api_version": self.api_version, "api_key": self.api_key, "stream": False, diff --git a/src/crewai/utilities/llm_utils.py b/src/crewai/utilities/llm_utils.py index 13230edf6..c774a71fb 100644 --- a/src/crewai/utilities/llm_utils.py +++ b/src/crewai/utilities/llm_utils.py @@ -53,6 +53,7 @@ def create_llm( timeout: Optional[float] = getattr(llm_value, "timeout", None) api_key: Optional[str] = getattr(llm_value, "api_key", None) base_url: Optional[str] = getattr(llm_value, "base_url", None) + api_base: Optional[str] = getattr(llm_value, "api_base", None) created_llm = LLM( model=model, @@ -62,6 +63,7 @@ def create_llm( timeout=timeout, api_key=api_key, base_url=base_url, + api_base=api_base, ) return created_llm except Exception as e: @@ -101,8 +103,18 @@ def _llm_via_environment_or_fallback() -> Optional[LLM]: callbacks: List[Any] = [] # Optional base URL from env - api_base = os.environ.get("OPENAI_API_BASE") or os.environ.get("OPENAI_BASE_URL") - if api_base: + base_url = ( + os.environ.get("BASE_URL") + or os.environ.get("OPENAI_API_BASE") + or os.environ.get("OPENAI_BASE_URL") + ) + + api_base = os.environ.get("API_BASE") or os.environ.get("AZURE_API_BASE") + + # Synchronize base_url and api_base if one is populated and the other is not + if base_url and not api_base: + api_base = base_url + elif api_base and not base_url: base_url = api_base # Initialize llm_params dictionary @@ -115,6 +127,7 @@ def _llm_via_environment_or_fallback() -> Optional[LLM]: "timeout": timeout, "api_key": api_key, "base_url": base_url, + "api_base": api_base, "api_version": api_version, "presence_penalty": presence_penalty, "frequency_penalty": frequency_penalty,