fix(checkpoint): serialize type[BaseModel] fields as JSON schema

Subclass redeclarations of args_schema/response_format dropped the
parent's Annotated PlainSerializer, causing PydanticSerializationError
on model_dump(mode='json'). Replace with @field_serializer decorators
backed by a shared serialize_model_class helper:

- BaseTool: covers RecallMemoryTool, RememberTool, AskQuestionTool,
  DelegateWorkTool, AddImageTool, ReadFileTool
- BaseLLM (check_fields=False): covers LLM, Anthropic, OpenAI, Gemini,
  Bedrock
- LiteAgent.response_format
- A2AConfig / A2AClientConfig response_model

lib/crewai/src/crewai/a2a/config.py

@@ -16,6 +16,7 @@ from pydantic import (
     FilePath,
     PrivateAttr,
     SecretStr,
+    field_serializer,
     model_validator,
 )
 from typing_extensions import Self, deprecated
@@ -24,6 +25,7 @@ from crewai.a2a.auth.client_schemes import ClientAuthScheme
 from crewai.a2a.auth.server_schemes import ServerAuthScheme
 from crewai.a2a.extensions.base import ValidatedA2AExtension
 from crewai.a2a.types import ProtocolVersion, TransportType, Url
+from crewai.utilities.pydantic_schema_utils import serialize_model_class
 
 
 try:
@@ -399,6 +401,11 @@ class A2AConfig(BaseModel):
         default=None,
         description="Optional Pydantic model for structured A2A agent responses",
     )
+
+    @field_serializer("response_model", when_used="json")
+    def _serialize_response_model(self, value: Any) -> Any:
+        return serialize_model_class(value)
+
     fail_fast: bool = Field(
         default=True,
         description="If True, raise error when agent unreachable; if False, skip",
@@ -488,6 +495,11 @@ class A2AClientConfig(BaseModel):
         default=None,
         description="Optional Pydantic model for structured A2A agent responses",
     )
+
+    @field_serializer("response_model", when_used="json")
+    def _serialize_response_model(self, value: Any) -> Any:
+        return serialize_model_class(value)
+
     fail_fast: bool = Field(
         default=True,
         description="If True, raise error when agent unreachable; if False, skip",

lib/crewai/src/crewai/agent/core.py

@@ -28,7 +28,6 @@ from pydantic import (
     ConfigDict,
     Field,
     PrivateAttr,
-    ValidationError,
     model_validator,
 )
 from pydantic.functional_serializers import PlainSerializer
@@ -1110,9 +1109,14 @@ class Agent(BaseAgent):
         """
         if self.agent_executor is None:
             raise RuntimeError("Agent executor is not initialized.")
+        if not isinstance(self.llm, BaseLLM):
+            raise RuntimeError(
+                "LLM must be resolved before updating agent executor parameters."
+            )
 
         if task is not None:
             self.agent_executor.task = task
+        self.agent_executor.llm = self.llm
         self.agent_executor.tools = tools
         self.agent_executor.original_tools = raw_tools
         self.agent_executor.prompt = prompt
@@ -1412,6 +1416,11 @@ class Agent(BaseAgent):
 
         if _is_resuming_agent_executor(self.agent_executor):
             executor = self.agent_executor
+            if not isinstance(self.llm, BaseLLM):
+                raise RuntimeError(
+                    "LLM must be resolved before resuming agent executor."
+                )
+            executor.llm = self.llm
             executor.tools = parsed_tools
             executor.tools_names = get_tool_names(parsed_tools)
             executor.tools_description = render_text_description_and_args(parsed_tools)
@@ -1692,32 +1701,24 @@ class Agent(BaseAgent):
         elif response_format:
             raw_output = str(output) if not isinstance(output, str) else output
             try:
-                formatted_result = response_format.model_validate_json(raw_output)
-            except ValidationError:
-                # Direct JSON validation failed; fall back to converter-based parsing below.
-                formatted_result = None
+                model_schema = generate_model_description(response_format)
+                schema = json.dumps(model_schema, indent=2)
+                instructions = I18N_DEFAULT.slice("formatted_task_instructions").format(
+                    output_format=schema
+                )
 
-            if formatted_result is None:
-                try:
-                    model_schema = generate_model_description(response_format)
-                    schema = json.dumps(model_schema, indent=2)
-                    instructions = I18N_DEFAULT.slice(
-                        "formatted_task_instructions"
-                    ).format(output_format=schema)
+                converter = Converter(
+                    llm=cast(BaseLLM, self.llm),
+                    text=raw_output,
+                    model=response_format,
+                    instructions=instructions,
+                )
 
-                    converter = Converter(
-                        llm=cast(BaseLLM, self.llm),
-                        text=raw_output,
-                        model=response_format,
-                        instructions=instructions,
-                    )
-
-                    conversion_result = converter.to_pydantic()
-                    if isinstance(conversion_result, BaseModel):
-                        formatted_result = conversion_result
-                except ConverterError:
-                    # Conversion failure is non-fatal; raw output is preserved below.
-                    pass
+                conversion_result = converter.to_pydantic()
+                if isinstance(conversion_result, BaseModel):
+                    formatted_result = conversion_result
+            except ConverterError:
+                pass
         else:
             raw_output = str(output) if not isinstance(output, str) else output
 

lib/crewai/src/crewai/agents/crew_agent_executor.py

@@ -350,10 +350,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
 
                 enforce_rpm_limit(self.request_within_rpm_limit)
 
-                effective_response_model = (
-                    None if self.original_tools else self.response_model
-                )
-
                 answer = get_llm_response(
                     llm=cast("BaseLLM", self.llm),
                     messages=self.messages,
@@ -361,11 +357,11 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     printer=PRINTER,
                     from_task=self.task,
                     from_agent=self.agent,
-                    response_model=effective_response_model,
+                    response_model=self.response_model,
                     executor_context=self,
                     verbose=self.agent.verbose,
                 )
-                if effective_response_model is not None:
+                if self.response_model is not None:
                     try:
                         if isinstance(answer, BaseModel):
                             output_json = answer.model_dump_json()
@@ -506,7 +502,7 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     available_functions=None,
                     from_task=self.task,
                     from_agent=self.agent,
-                    response_model=None,
+                    response_model=self.response_model,
                     executor_context=self,
                     verbose=self.agent.verbose,
                 )
@@ -1165,10 +1161,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
 
                 enforce_rpm_limit(self.request_within_rpm_limit)
 
-                effective_response_model = (
-                    None if self.original_tools else self.response_model
-                )
-
                 answer = await aget_llm_response(
                     llm=cast("BaseLLM", self.llm),
                     messages=self.messages,
@@ -1176,12 +1168,12 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     printer=PRINTER,
                     from_task=self.task,
                     from_agent=self.agent,
-                    response_model=effective_response_model,
+                    response_model=self.response_model,
                     executor_context=self,
                     verbose=self.agent.verbose,
                 )
 
-                if effective_response_model is not None:
+                if self.response_model is not None:
                     try:
                         if isinstance(answer, BaseModel):
                             output_json = answer.model_dump_json()
@@ -1322,7 +1314,7 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     available_functions=None,
                     from_task=self.task,
                     from_agent=self.agent,
-                    response_model=None,
+                    response_model=self.response_model,
                     executor_context=self,
                     verbose=self.agent.verbose,
                 )

lib/crewai/src/crewai/crew.py

@@ -443,16 +443,20 @@ class Crew(FlowTrackable, BaseModel):
                 if node.event.type == "task_started" and node.event.task_id:
                     started_task_ids.add(node.event.task_id)
 
+        is_hierarchical = self.process == Process.hierarchical
         resuming_task_agent_roles: set[str] = set()
         for task in self.tasks:
-            if (
-                task.output is None
-                and task.agent is not None
-                and str(task.id) in started_task_ids
-            ):
-                resuming_task_agent_roles.add(task.agent.role)
+            if task.output is not None or str(task.id) not in started_task_ids:
+                continue
+            executing_agent = self.manager_agent if is_hierarchical else task.agent
+            if executing_agent is not None:
+                resuming_task_agent_roles.add(executing_agent.role)
 
-        for agent in self.agents:
+        candidate_agents: list[BaseAgent] = list(self.agents)
+        if self.manager_agent is not None:
+            candidate_agents.append(self.manager_agent)
+
+        for agent in candidate_agents:
             agent.crew = self
             executor = agent.agent_executor
             if (
@@ -467,7 +471,7 @@ class Crew(FlowTrackable, BaseModel):
                 agent.agent_executor = None
         for task in self.tasks:
             if task.agent is not None:
-                for agent in self.agents:
+                for agent in candidate_agents:
                     if agent.role == task.agent.role:
                         task.agent = agent
                         if agent.agent_executor is not None and task.output is None:
@@ -536,25 +540,9 @@ class Crew(FlowTrackable, BaseModel):
         if state is None:
             return
 
-        # Restore crew scope and the in-progress task scope. Inner scopes
-        # (agent, llm, tool) are re-created by the executor on resume.
         stack: list[tuple[str, str]] = []
         if self._kickoff_event_id:
             stack.append((self._kickoff_event_id, "crew_kickoff_started"))
-
-        # Find the task_started event for the in-progress task (skipped on resume)
-        for task in self.tasks:
-            if task.output is None:
-                task_id_str = str(task.id)
-                for node in state.event_record.nodes.values():
-                    if (
-                        node.event.type == "task_started"
-                        and node.event.task_id == task_id_str
-                    ):
-                        stack.append((node.event.event_id, "task_started"))
-                        break
-                break
-
         restore_event_scope(tuple(stack))
 
         # Restore last_event_id and emission counter from the record

lib/crewai/src/crewai/events/event_context.py

@@ -138,6 +138,36 @@ def restore_event_scope(stack: tuple[tuple[str, str], ...]) -> None:
     _event_id_stack.set(stack)
 
 
+def resume_task_scope(task_id: str) -> bool:
+    """Push the latest recorded ``task_started`` scope for a task.
+
+    Args:
+        task_id: The task identifier to look up in the active event record.
+
+    Returns:
+        ``True`` if a prior scope was pushed; ``False`` otherwise.
+    """
+    from crewai.events.event_bus import crewai_event_bus
+
+    state = crewai_event_bus._runtime_state
+    if state is None:
+        return False
+    latest_event_id: str | None = None
+    latest_seq = -1
+    for node in list(state.event_record.nodes.values()):
+        ev = node.event
+        if ev.type != "task_started" or ev.task_id != task_id:
+            continue
+        seq = ev.emission_sequence or 0
+        if seq > latest_seq:
+            latest_seq = seq
+            latest_event_id = ev.event_id
+    if latest_event_id is None:
+        return False
+    push_event_scope(latest_event_id, "task_started")
+    return True
+
+
 def push_event_scope(event_id: str, event_type: str = "") -> None:
     """Push an event ID and type onto the scope stack."""
     config = _event_context_config.get() or _default_config

lib/crewai/src/crewai/experimental/agent_executor.py

@@ -173,8 +173,10 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
 
     executor_type: Literal["experimental"] = "experimental"
     suppress_flow_events: bool = True  # always suppress for executor
-    llm: BaseLLM = Field(exclude=True)
-    prompt: SystemPromptResult | StandardPromptResult = Field(exclude=True)
+    llm: BaseLLM | None = Field(default=None, exclude=True)
+    prompt: SystemPromptResult | StandardPromptResult | None = Field(
+        default=None, exclude=True
+    )
     max_iter: int = Field(default=25, exclude=True)
     tools: list[CrewStructuredTool] = Field(default_factory=list, exclude=True)
     tools_names: str = Field(default="", exclude=True)
@@ -1224,10 +1226,6 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
         try:
             enforce_rpm_limit(self.request_within_rpm_limit)
 
-            effective_response_model = (
-                None if self.original_tools else self.response_model
-            )
-
             answer = get_llm_response(
                 llm=self.llm,
                 messages=list(self.state.messages),
@@ -1235,7 +1233,7 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
                 printer=PRINTER,
                 from_task=self.task,
                 from_agent=self.agent,
-                response_model=effective_response_model,
+                response_model=self.response_model,
                 executor_context=self,
                 verbose=self.agent.verbose,
             )
@@ -1323,7 +1321,7 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
                 available_functions=None,
                 from_task=self.task,
                 from_agent=self.agent,
-                response_model=None,
+                response_model=self.response_model,
                 executor_context=self,
                 verbose=self.agent.verbose,
             )
@@ -2589,6 +2587,11 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
 
             self._kickoff_input = inputs.get("input", "")
 
+            if self.llm is None or self.prompt is None:
+                raise RuntimeError(
+                    "AgentExecutor.llm or .prompt is unset; the executor was "
+                    "not fully restored or initialized before execution."
+                )
             if "system" in self.prompt:
                 from crewai.llms.cache import mark_cache_breakpoint
 
@@ -2690,6 +2693,11 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
 
             self._kickoff_input = inputs.get("input", "")
 
+            if self.llm is None or self.prompt is None:
+                raise RuntimeError(
+                    "AgentExecutor.llm or .prompt is unset; the executor was "
+                    "not fully restored or initialized before execution."
+                )
             if "system" in self.prompt:
                 from crewai.llms.cache import mark_cache_breakpoint
 

lib/crewai/src/crewai/lite_agent.py

@@ -23,7 +23,7 @@ from pydantic import (
     BaseModel,
     Field,
     PrivateAttr,
-    ValidationError,
+    field_serializer,
     field_validator,
     model_validator,
 )
@@ -95,7 +95,10 @@ from crewai.utilities.guardrail import process_guardrail, serialize_guardrail_fo
 from crewai.utilities.guardrail_types import GuardrailCallable, GuardrailType
 from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.llm_utils import create_llm
-from crewai.utilities.pydantic_schema_utils import generate_model_description
+from crewai.utilities.pydantic_schema_utils import (
+    generate_model_description,
+    serialize_model_class,
+)
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.tool_utils import execute_tool_and_check_finality
 from crewai.utilities.types import LLMMessage
@@ -236,6 +239,11 @@ class LiteAgent(FlowTrackable, BaseModel):
     response_format: type[BaseModel] | None = Field(
         default=None, description="Pydantic model for structured output"
     )
+
+    @field_serializer("response_format", when_used="json")
+    def _serialize_response_format(self, value: Any) -> Any:
+        return serialize_model_class(value)
+
     verbose: bool = Field(
         default=False, description="Whether to print execution details"
     )
@@ -640,38 +648,29 @@ class LiteAgent(FlowTrackable, BaseModel):
             formatted_result = agent_finish.output
         elif active_response_format:
             try:
-                formatted_result = active_response_format.model_validate_json(
-                    str(agent_finish.output)
+                model_schema = generate_model_description(active_response_format)
+                schema = json.dumps(model_schema, indent=2)
+                instructions = I18N_DEFAULT.slice("formatted_task_instructions").format(
+                    output_format=schema
                 )
-            except ValidationError:
-                # Direct JSON validation failed; fall back to converter-based parsing below.
-                formatted_result = None
 
-            if formatted_result is None:
-                try:
-                    model_schema = generate_model_description(active_response_format)
-                    schema = json.dumps(model_schema, indent=2)
-                    instructions = I18N_DEFAULT.slice(
-                        "formatted_task_instructions"
-                    ).format(output_format=schema)
+                converter = Converter(
+                    llm=self.llm,
+                    text=agent_finish.output,
+                    model=active_response_format,
+                    instructions=instructions,
+                )
 
-                    converter = Converter(
-                        llm=self.llm,
-                        text=agent_finish.output,
-                        model=active_response_format,
-                        instructions=instructions,
+                result = converter.to_pydantic()
+                if isinstance(result, BaseModel):
+                    formatted_result = result
+            except ConverterError as e:
+                if self.verbose:
+                    PRINTER.print(
+                        content=f"Failed to parse output into response format after retries: {e.message}",
+                        color="yellow",
                     )
 
-                    result = converter.to_pydantic()
-                    if isinstance(result, BaseModel):
-                        formatted_result = result
-                except ConverterError as e:
-                    if self.verbose:
-                        PRINTER.print(
-                            content=f"Failed to parse output into response format after retries: {e.message}",
-                            color="yellow",
-                        )
-
         # Calculate token usage metrics
         if isinstance(self.llm, BaseLLM):
             usage_metrics = self.llm.get_token_usage_summary()

lib/crewai/src/crewai/llms/base_llm.py

@@ -23,6 +23,7 @@ from pydantic import (
     ConfigDict,
     Field,
     PrivateAttr,
+    field_serializer,
     model_validator,
 )
 from typing_extensions import TypedDict
@@ -42,6 +43,7 @@ from crewai.events.types.tool_usage_events import (
     ToolUsageStartedEvent,
 )
 from crewai.types.usage_metrics import UsageMetrics
+from crewai.utilities.pydantic_schema_utils import serialize_model_class
 
 
 try:
@@ -159,6 +161,10 @@ class BaseLLM(BaseModel, ABC):
     )
     additional_params: dict[str, Any] = Field(default_factory=dict)
 
+    @field_serializer("response_format", when_used="json", check_fields=False)
+    def _serialize_response_format(self, value: Any) -> Any:
+        return serialize_model_class(value)
+
     def __setattr__(self, name: str, value: Any) -> None:
         if name in ("stop", "stop_sequences"):
             if value is None:

lib/crewai/src/crewai/task.py

@@ -40,6 +40,7 @@ from crewai.agents.agent_builder.base_agent import BaseAgent, _resolve_agent
 from crewai.context import reset_current_task_id, set_current_task_id
 from crewai.core.providers.content_processor import process_content
 from crewai.events.event_bus import crewai_event_bus
+from crewai.events.event_context import resume_task_scope
 from crewai.events.types.task_events import (
     TaskCompletedEvent,
     TaskFailedEvent,
@@ -661,7 +662,10 @@ class Task(BaseModel):
             tools = tools or self.tools or []
 
             self.processed_by_agents.add(agent.role)
-            if not (agent.agent_executor and agent.agent_executor._resuming):
+            executor = agent.agent_executor
+            if not (
+                executor and executor._resuming and resume_task_scope(str(self.id))
+            ):
                 crewai_event_bus.emit(
                     self, TaskStartedEvent(context=context, task=self)
                 )
@@ -783,7 +787,10 @@ class Task(BaseModel):
             tools = tools or self.tools or []
 
             self.processed_by_agents.add(agent.role)
-            if not (agent.agent_executor and agent.agent_executor._resuming):
+            executor = agent.agent_executor
+            if not (
+                executor and executor._resuming and resume_task_scope(str(self.id))
+            ):
                 crewai_event_bus.emit(
                     self, TaskStartedEvent(context=context, task=self)
                 )

lib/crewai/src/crewai/tools/base_tool.py

@@ -8,7 +8,6 @@ from inspect import Parameter, signature
 import json
 import threading
 from typing import (
-    Annotated,
     Any,
     Generic,
     ParamSpec,
@@ -22,10 +21,10 @@ from pydantic import (
     ConfigDict,
     Field,
     GetCoreSchemaHandler,
-    PlainSerializer,
     PrivateAttr,
     computed_field,
     create_model,
+    field_serializer,
     field_validator,
 )
 from pydantic_core import CoreSchema, core_schema
@@ -145,15 +144,18 @@ class BaseTool(BaseModel, ABC):
         default_factory=list,
         description="List of environment variables used by the tool.",
     )
-    args_schema: Annotated[
-        type[PydanticBaseModel],
-        PlainSerializer(_serialize_schema, return_type=dict | None, when_used="json"),
-    ] = Field(
+    args_schema: type[PydanticBaseModel] = Field(
         default=_ArgsSchemaPlaceholder,
         validate_default=True,
         description="The schema for the arguments that the tool accepts.",
     )
 
+    @field_serializer("args_schema", when_used="json")
+    def _serialize_args_schema(
+        self, schema: type[PydanticBaseModel] | None
+    ) -> dict[str, Any] | None:
+        return _serialize_schema(schema)
+
     description_updated: bool = Field(
         default=False, description="Flag to check if the description has been updated."
     )

lib/crewai/src/crewai/utilities/pydantic_schema_utils.py

@@ -782,6 +782,20 @@ def _inline_top_level_ref(schema: dict[str, Any]) -> dict[str, Any]:
     return schema
 
 
+def serialize_model_class(value: Any) -> Any:
+    """Serialize a ``type[BaseModel]`` field value as its JSON schema.
+
+    Args:
+        value: A ``type[BaseModel]`` subclass, ``None``, or another union member.
+
+    Returns:
+        ``value.model_json_schema()`` for model classes, ``value`` otherwise.
+    """
+    if isinstance(value, type) and issubclass(value, BaseModel):
+        return value.model_json_schema()
+    return value
+
+
 def create_model_from_schema(  # type: ignore[no-any-unimported]
     json_schema: dict[str, Any],
     *,

lib/crewai/tests/agents/test_agent_executor.py

@@ -12,7 +12,6 @@ from typing import Any
 from unittest.mock import AsyncMock, Mock, patch
 
 import pytest
-from pydantic import BaseModel
 
 from crewai.agents.tools_handler import ToolsHandler as _ToolsHandler
 from crewai.agents.step_executor import StepExecutor
@@ -109,9 +108,6 @@ class TestAgentExecutorState:
 class TestAgentExecutor:
     """Test AgentExecutor class."""
 
-    class StructuredResult(BaseModel):
-        value: str
-
     @pytest.fixture
     def mock_dependencies(self):
         """Create mock dependencies for executor."""
@@ -219,49 +215,6 @@ class TestAgentExecutor:
 
         assert result == "check_iteration"
 
-    def test_call_llm_and_parse_does_not_pass_response_model_with_tools(
-        self, mock_dependencies
-    ):
-        """Structured output should not be requested during ReAct tool loops."""
-        executor = _build_executor(
-            **mock_dependencies,
-            original_tools=[Mock()],
-            response_model=self.StructuredResult,
-            callbacks=[],
-        )
-        executor.state.messages = [{"role": "user", "content": "Use a tool"}]
-
-        with patch(
-            "crewai.experimental.agent_executor.get_llm_response",
-            return_value="Thought: done\nFinal Answer: complete",
-        ) as get_llm_response_mock:
-            result = executor.call_llm_and_parse()
-
-        assert result == "parsed"
-        assert get_llm_response_mock.call_args.kwargs["response_model"] is None
-
-    def test_call_llm_native_tools_does_not_pass_response_model_with_tools(
-        self, mock_dependencies
-    ):
-        """Structured output should not be requested during native tool calls."""
-        executor = _build_executor(
-            **mock_dependencies,
-            original_tools=[Mock()],
-            response_model=self.StructuredResult,
-            callbacks=[],
-        )
-        executor._openai_tools = [{"type": "function", "function": {"name": "lookup"}}]
-        executor.state.messages = [{"role": "user", "content": "Use a tool"}]
-
-        with patch(
-            "crewai.experimental.agent_executor.get_llm_response",
-            return_value="complete",
-        ) as get_llm_response_mock:
-            result = executor.call_llm_native_tools()
-
-        assert result == "native_finished"
-        assert get_llm_response_mock.call_args.kwargs["response_model"] is None
-
     def test_finalize_success(self, mock_dependencies):
         """Test finalize with valid AgentFinish."""
         with patch.object(AgentExecutor, "_show_logs") as mock_show_logs:

lib/crewai/tests/cassettes/llms/google/test_gemini_agent_kickoff_structured_output_with_tools.yaml

@@ -8,8 +8,18 @@ interactions:
       [{"description": "Add two numbers together and return the sum.", "name": "add_numbers",
       "parameters_json_schema": {"properties": {"a": {"title": "A", "type": "integer"},
       "b": {"title": "B", "type": "integer"}}, "required": ["a", "b"], "type": "object",
-      "additionalProperties": false}}]}], "generationConfig": {"stopSequences": ["\nObservation:"],
-      "thinkingConfig": {"include_thoughts": true}}}'
+      "additionalProperties": false}}, {"description": "Use this tool to provide your
+      final structured response. Call this tool when you have gathered all necessary
+      information and are ready to provide the final answer in the required format.",
+      "name": "structured_output", "parameters_json_schema": {"description": "Structured
+      output for calculation results.", "properties": {"operation": {"description":
+      "The mathematical operation performed", "title": "Operation", "type": "string"},
+      "result": {"description": "The result of the calculation", "title": "Result",
+      "type": "integer"}, "explanation": {"description": "Brief explanation of the
+      calculation", "title": "Explanation", "type": "string"}}, "required": ["operation",
+      "result", "explanation"], "title": "CalculationResult", "type": "object", "additionalProperties":
+      false, "propertyOrdering": ["operation", "result", "explanation"]}}]}], "generationConfig":
+      {"stopSequences": ["\nObservation:"]}}'
     headers:
       User-Agent:
       - X-USER-AGENT-XXX
@@ -20,13 +30,13 @@ interactions:
       connection:
       - keep-alive
       content-length:
-      - '784'
+      - '1592'
       content-type:
       - application/json
       host:
       - generativelanguage.googleapis.com
       x-goog-api-client:
-      - google-genai-sdk/1.65.0 gl-python/3.13.3
+      - google-genai-sdk/1.49.0 gl-python/3.13.3
       x-goog-api-key:
       - X-GOOG-API-KEY-XXX
     method: POST
@@ -34,36 +44,27 @@ interactions:
   response:
     body:
       string: "{\n  \"candidates\": [\n    {\n      \"content\": {\n        \"parts\":
-        [\n          {\n            \"text\": \"Okay, here's my thought process on
-        tackling this simple addition problem:\\n\\n**Calculating 15 + 27**\\n\\nRight,
-        so I need to calculate 15 plus 27. It's a straightforward arithmetic operation,
-        and I know I have a dedicated tool for that \u2013 the `add_numbers` function.
-        No need to reinvent the wheel, I should use the appropriate tool in my toolbox.\\n\\nTo
-        use the tool effectively, I need to provide the correct inputs. In this case,
-        I'll set `a` equal to 15, and `b` equal to 27. That should be a piece of cake
-        for the function. Now I just need to call it!\\n\",\n            \"thought\":
-        true\n          },\n          {\n            \"functionCall\": {\n              \"name\":
-        \"add_numbers\",\n              \"args\": {\n                \"a\": 15,\n
-        \               \"b\": 27\n              }\n            },\n            \"thoughtSignature\":
-        \"CqwBAQw51sfkbjIDS7wS47oc/Bej+AYsUu5Cs+BC2Ae5NMasRmWa/u5Ct426qkpkIpgzGSNjwwfitf1gK93Abse9EGj5m1swXmPU2XSkqhMYMEXZGH1mW2U2XH8zaXHRIAx2aI0O8VbJ3sL8h1lJgbVCkvLa2RyWwY6E8FRPhQOHtrOQEQtfAUtHdJz928j6UEgS818X/7hEwuWsQhIho0frtziX30UlI7yXOeBBWw==\"\n
+        [\n          {\n            \"functionCall\": {\n              \"name\": \"add_numbers\",\n
+        \             \"args\": {\n                \"a\": 15,\n                \"b\":
+        27\n              }\n            },\n            \"thoughtSignature\": \"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\"\n
         \         }\n        ],\n        \"role\": \"model\"\n      },\n      \"finishReason\":
         \"STOP\",\n      \"index\": 0,\n      \"finishMessage\": \"Model generated
         function call(s).\"\n    }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\":
-        104,\n    \"candidatesTokenCount\": 22,\n    \"totalTokenCount\": 173,\n    \"promptTokensDetails\":
-        [\n      {\n        \"modality\": \"TEXT\",\n        \"tokenCount\": 104\n
-        \     }\n    ],\n    \"thoughtsTokenCount\": 47,\n    \"serviceTier\": \"standard\"\n
-        \ },\n  \"modelVersion\": \"gemini-2.5-flash\",\n  \"responseId\": \"MpgPapmwO_vN-sAPvrWJmA0\"\n}\n"
+        202,\n    \"candidatesTokenCount\": 22,\n    \"totalTokenCount\": 403,\n    \"promptTokensDetails\":
+        [\n      {\n        \"modality\": \"TEXT\",\n        \"tokenCount\": 202\n
+        \     }\n    ],\n    \"thoughtsTokenCount\": 179\n  },\n  \"modelVersion\":
+        \"gemini-2.5-flash\",\n  \"responseId\": \"AlCOadrrK7aVjMcPksrU-A0\"\n}\n"
     headers:
       Alt-Svc:
       - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
       Content-Type:
       - application/json; charset=UTF-8
       Date:
-      - Thu, 21 May 2026 23:41:40 GMT
+      - Thu, 12 Feb 2026 22:11:14 GMT
       Server:
       - scaffolding on HTTPServer2
       Server-Timing:
-      - gfet4t7; dur=1920
+      - gfet4t7; dur=1417
       Transfer-Encoding:
       - chunked
       Vary:
@@ -74,8 +75,6 @@ interactions:
       - X-CONTENT-TYPE-XXX
       X-Frame-Options:
       - X-FRAME-OPTIONS-XXX
-      X-Gemini-Service-Tier:
-      - standard
       X-XSS-Protection:
       - '0'
     status:
@@ -84,7 +83,7 @@ interactions:
 - request:
     body: '{"contents": [{"parts": [{"text": "\nCurrent Task: Calculate 15 + 27 using
       your add_numbers tool. Report the result."}], "role": "user"}, {"parts": [{"functionCall":
-      {"args": {"a": 15, "b": 27}, "name": "add_numbers"}, "thoughtSignature": "CqwBAQw51sfkbjIDS7wS47oc_Bej-AYsUu5Cs-BC2Ae5NMasRmWa_u5Ct426qkpkIpgzGSNjwwfitf1gK93Abse9EGj5m1swXmPU2XSkqhMYMEXZGH1mW2U2XH8zaXHRIAx2aI0O8VbJ3sL8h1lJgbVCkvLa2RyWwY6E8FRPhQOHtrOQEQtfAUtHdJz928j6UEgS818X_7hEwuWsQhIho0frtziX30UlI7yXOeBBWw=="}],
+      {"args": {"a": 15, "b": 27}, "name": "add_numbers"}, "thoughtSignature": "CqMFAb4-9vtoEAola3khZd5LD4cccGlQsdVI9cPJGQBURT0qF5Xqp8o1L7oGN4s5trQpk7NPhKe1CYDMXDJueC7zM_zGlcy2daSJAeuTd9pxAbtndEXCGjM_9Nt8QRpvaDV3Ff2bkKSn_JCOJdzsN5m6G5C6BMRGVt8bZyRHelwu7tjCNYiMEvFqVoQIWN6d-CWKkHnbSwOlSUTDXJEcWvUwP82Ou7s68l2k7XNbDWCY5Tt8LUdPgeqjfH15JoEgZUbPxbVKA0ykRln1svfpvQ4Vm3Hn7PL3voWZWGzP5uLnH6JF2M8H6TokSDYZETvlDo5bK1Cx9IzrdUgHkku6gNbct_e53CPEUgqSKbY1VhsLAXAHieT4PKqeMQ4B-7gyCLXHeL6TOGjqSVGBBOQLtF9yCbKbkXa5pPu3-DnPhoOeH7jEPb-bqIWv6rxERErbKhu0IlP-UNBRAAj-wXNDZxQvLnlrlXrLtWllO9wFshr1DzgDgNZSRsPQeVQq2L0bL-KRobCXAfjMpH_8bhxdTI3sgsCtU3-dKwV5Z8Fg6e5oRyBAss8AE2CmYtdnYpt-iss9IT8NlSpI2DcdmVErEFNsebVcSwnr-9YXoESh4O1i8er9lX59hKTBdYXdP2GJ63cq9cSOalzx_doKxA2FzP3QhdV-H11LiUQzsQCXHqv0D-D290z1QoPhpsHEd7b_1EoW7D_2rub4acV8tpUcG2oe_Mj1kzYQoiEwZkgM56JoUs--5-5tWBMW68e4y1AmkyhDTCDkiNIa4noE6AOdNsLjL_-EHvcNFRmayFXXiUShIcMT0WQ9xNriWQP_dbhd6F5K7BKSajdB1391OYeHVmSEzzXYxjnUWXd-jqORQcsiPNIVRQkZI7ZGl6-4exmZsfrKzbFy"}],
       "role": "model"}, {"parts": [{"functionResponse": {"name": "add_numbers", "response":
       {"result": 42}}}], "role": "user"}], "systemInstruction": {"parts": [{"text":
       "You are Calculator. You are a calculator assistant that uses tools to compute
@@ -93,8 +92,18 @@ interactions:
       numbers together and return the sum.", "name": "add_numbers", "parameters_json_schema":
       {"properties": {"a": {"title": "A", "type": "integer"}, "b": {"title": "B",
       "type": "integer"}}, "required": ["a", "b"], "type": "object", "additionalProperties":
-      false}}]}], "generationConfig": {"stopSequences": ["\nObservation:"], "thinkingConfig":
-      {"include_thoughts": true}}}'
+      false}}, {"description": "Use this tool to provide your final structured response.
+      Call this tool when you have gathered all necessary information and are ready
+      to provide the final answer in the required format.", "name": "structured_output",
+      "parameters_json_schema": {"description": "Structured output for calculation
+      results.", "properties": {"operation": {"description": "The mathematical operation
+      performed", "title": "Operation", "type": "string"}, "result": {"description":
+      "The result of the calculation", "title": "Result", "type": "integer"}, "explanation":
+      {"description": "Brief explanation of the calculation", "title": "Explanation",
+      "type": "string"}}, "required": ["operation", "result", "explanation"], "title":
+      "CalculationResult", "type": "object", "additionalProperties": false, "propertyOrdering":
+      ["operation", "result", "explanation"]}}]}], "generationConfig": {"stopSequences":
+      ["\nObservation:"]}}'
     headers:
       User-Agent:
       - X-USER-AGENT-XXX
@@ -105,13 +114,13 @@ interactions:
       connection:
       - keep-alive
       content-length:
-      - '1249'
+      - '2725'
       content-type:
       - application/json
       host:
       - generativelanguage.googleapis.com
       x-goog-api-client:
-      - google-genai-sdk/1.65.0 gl-python/3.13.3
+      - google-genai-sdk/1.49.0 gl-python/3.13.3
       x-goog-api-key:
       - X-GOOG-API-KEY-XXX
     method: POST
@@ -119,24 +128,28 @@ interactions:
   response:
     body:
       string: "{\n  \"candidates\": [\n    {\n      \"content\": {\n        \"parts\":
-        [\n          {\n            \"text\": \"The sum of 15 and 27 is 42.\"\n          }\n
-        \       ],\n        \"role\": \"model\"\n      },\n      \"finishReason\":
-        \"STOP\",\n      \"index\": 0\n    }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\":
-        142,\n    \"candidatesTokenCount\": 15,\n    \"totalTokenCount\": 157,\n    \"promptTokensDetails\":
-        [\n      {\n        \"modality\": \"TEXT\",\n        \"tokenCount\": 142\n
-        \     }\n    ],\n    \"serviceTier\": \"standard\"\n  },\n  \"modelVersion\":
-        \"gemini-2.5-flash\",\n  \"responseId\": \"NZgPasTKBf3F-sAP4Lu48Ak\"\n}\n"
+        [\n          {\n            \"functionCall\": {\n              \"name\": \"structured_output\",\n
+        \             \"args\": {\n                \"result\": 42,\n                \"explanation\":
+        \"The sum of 15 and 27 is 42.\",\n                \"operation\": \"Addition\"\n
+        \             }\n            },\n            \"thoughtSignature\": \"CtYCAb4+9vsKJoVFV1W8ORKk+Likt7GS9CuzuE53V9sbS2gFuiEjJ7ghBqWDG2UrgyRYFjPl6EalXUBnEbEq9rZNYGY27VpcweI1tv6p+477bgz1pmZnL0nfAcrp4nuphL+Ij0nXZQoo5cF4Gk29RQSNy49VRn3eP9eUW0hG7EpkPmfJiUSSDuaQENHN1UBBnFS9QUC+Fw+unnQ10B57fauyiXWNrBUkE2PYqgj5vELa5lVMtk5beh4ydWNnZ04t8gvQniCJ38EWWQr8VAXrSqE156oCBMwkFaFM7huPWHZk53n/HAG/VsQgPayf045STWKWjBzp6uTiwH9pYtoI1LBah3uxVbJRKOzH7HI4U0cHsffQqIIUn8cW4SP1UK/nvAivU1l0p6Bot8KIVJ5vqoF+o2oDmTuZv0HkDo5+UvXRqfsO5AylpUdM+JMGaXVAA7oZNqVPQybw\"\n
+        \         }\n        ],\n        \"role\": \"model\"\n      },\n      \"finishReason\":
+        \"STOP\",\n      \"index\": 0,\n      \"finishMessage\": \"Model generated
+        function call(s).\"\n    }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\":
+        240,\n    \"candidatesTokenCount\": 39,\n    \"totalTokenCount\": 357,\n    \"promptTokensDetails\":
+        [\n      {\n        \"modality\": \"TEXT\",\n        \"tokenCount\": 240\n
+        \     }\n    ],\n    \"thoughtsTokenCount\": 78\n  },\n  \"modelVersion\":
+        \"gemini-2.5-flash\",\n  \"responseId\": \"A1COaaWbKvKGjMcPsN-EkAs\"\n}\n"
     headers:
       Alt-Svc:
       - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
       Content-Type:
       - application/json; charset=UTF-8
       Date:
-      - Thu, 21 May 2026 23:41:41 GMT
+      - Thu, 12 Feb 2026 22:11:15 GMT
       Server:
       - scaffolding on HTTPServer2
       Server-Timing:
-      - gfet4t7; dur=750
+      - gfet4t7; dur=906
       Transfer-Encoding:
       - chunked
       Vary:
@@ -147,107 +160,6 @@ interactions:
       - X-CONTENT-TYPE-XXX
       X-Frame-Options:
       - X-FRAME-OPTIONS-XXX
-      X-Gemini-Service-Tier:
-      - standard
-      X-XSS-Protection:
-      - '0'
-    status:
-      code: 200
-      message: OK
-- request:
-    body: '{"contents": [{"parts": [{"text": "The sum of 15 and 27 is 42."}], "role":
-      "user"}], "systemInstruction": {"parts": [{"text": "Format your final answer
-      according to the following OpenAPI schema: {\n  \"type\": \"json_schema\",\n  \"json_schema\":
-      {\n    \"name\": \"CalculationResult\",\n    \"strict\": true,\n    \"schema\":
-      {\n      \"description\": \"Structured output for calculation results.\",\n      \"properties\":
-      {\n        \"operation\": {\n          \"description\": \"The mathematical operation
-      performed\",\n          \"title\": \"Operation\",\n          \"type\": \"string\"\n        },\n        \"result\":
-      {\n          \"description\": \"The result of the calculation\",\n          \"title\":
-      \"Result\",\n          \"type\": \"integer\"\n        },\n        \"explanation\":
-      {\n          \"description\": \"Brief explanation of the calculation\",\n          \"title\":
-      \"Explanation\",\n          \"type\": \"string\"\n        }\n      },\n      \"required\":
-      [\n        \"operation\",\n        \"result\",\n        \"explanation\"\n      ],\n      \"title\":
-      \"CalculationResult\",\n      \"type\": \"object\",\n      \"additionalProperties\":
-      false\n    }\n  }\n}\n\nIMPORTANT: Preserve the original content exactly as-is.
-      Do NOT rewrite, paraphrase, or modify the meaning of the content. Only structure
-      it to match the schema format.\n\nDo not include the OpenAPI schema in the final
-      output. Ensure the final output does not include any code block markers like
-      ```json or ```python."}], "role": "user"}, "generationConfig": {"responseMimeType":
-      "application/json", "responseJsonSchema": {"description": "Structured output
-      for calculation results.", "properties": {"operation": {"description": "The
-      mathematical operation performed", "title": "Operation", "type": "string"},
-      "result": {"description": "The result of the calculation", "title": "Result",
-      "type": "integer"}, "explanation": {"description": "Brief explanation of the
-      calculation", "title": "Explanation", "type": "string"}}, "required": ["operation",
-      "result", "explanation"], "title": "CalculationResult", "type": "object", "additionalProperties":
-      false, "propertyOrdering": ["operation", "result", "explanation"]}, "thinkingConfig":
-      {"include_thoughts": true}}}'
-    headers:
-      User-Agent:
-      - X-USER-AGENT-XXX
-      accept:
-      - '*/*'
-      accept-encoding:
-      - ACCEPT-ENCODING-XXX
-      connection:
-      - keep-alive
-      content-length:
-      - '2247'
-      content-type:
-      - application/json
-      host:
-      - generativelanguage.googleapis.com
-      x-goog-api-client:
-      - google-genai-sdk/1.65.0 gl-python/3.13.3
-      x-goog-api-key:
-      - X-GOOG-API-KEY-XXX
-    method: POST
-    uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent
-  response:
-    body:
-      string: "{\n  \"candidates\": [\n    {\n      \"content\": {\n        \"parts\":
-        [\n          {\n            \"text\": \"**Analyzing the User's Statement**\\n\\nOkay,
-        so the user has given me the statement: \\\"The sum of 15 and 27 is 42.\\\"
-        My task is to break this down into a structured JSON object according to the
-        `CalculationResult` schema I'm working with. This is straightforward; let's
-        extract the key pieces:\\n\\nFirst, the **operation**: The word \\\"sum\\\"
-        is a clear indicator that we're dealing with addition. No ambiguity there.\\n\\nNext,
-        the **result**: The statement explicitly tells us that the result \\\"is 42\\\".
-        That's a direct, easily extracted value.\\n\\nFinally, the **explanation**:
-        I can use the entire original statement, \\\"The sum of 15 and 27 is 42.\\\",
-        as the explanation. It's concise and perfectly encapsulates the context of
-        the calculation.\\n\",\n            \"thought\": true\n          },\n          {\n
-        \           \"text\": \"{\\\"operation\\\":\\\"addition\\\",\\\"result\\\":42,\\\"explanation\\\":\\\"The
-        sum of 15 and 27 is 42.\\\"}\"\n          }\n        ],\n        \"role\":
-        \"model\"\n      },\n      \"finishReason\": \"STOP\",\n      \"index\": 0\n
-        \   }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\": 321,\n    \"candidatesTokenCount\":
-        28,\n    \"totalTokenCount\": 480,\n    \"promptTokensDetails\": [\n      {\n
-        \       \"modality\": \"TEXT\",\n        \"tokenCount\": 321\n      }\n    ],\n
-        \   \"thoughtsTokenCount\": 131,\n    \"serviceTier\": \"standard\"\n  },\n
-        \ \"modelVersion\": \"gemini-2.5-flash\",\n  \"responseId\": \"NZgPasDuKf2VjMcPwc6D4Ak\"\n}\n"
-    headers:
-      Alt-Svc:
-      - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
-      Content-Type:
-      - application/json; charset=UTF-8
-      Date:
-      - Thu, 21 May 2026 23:41:44 GMT
-      Server:
-      - scaffolding on HTTPServer2
-      Server-Timing:
-      - gfet4t7; dur=2425
-      Transfer-Encoding:
-      - chunked
-      Vary:
-      - Origin
-      - X-Origin
-      - Referer
-      X-Content-Type-Options:
-      - X-CONTENT-TYPE-XXX
-      X-Frame-Options:
-      - X-FRAME-OPTIONS-XXX
-      X-Gemini-Service-Tier:
-      - standard
       X-XSS-Protection:
       - '0'
     status:

lib/crewai/tests/cassettes/llms/google/test_gemini_crew_structured_output_with_tools.yaml

@@ -23,8 +23,17 @@ interactions:
       numbers together and return the sum.", "name": "add_numbers", "parameters_json_schema":
       {"properties": {"a": {"title": "A", "type": "integer"}, "b": {"title": "B",
       "type": "integer"}}, "required": ["a", "b"], "type": "object", "additionalProperties":
-      false}}]}], "generationConfig": {"stopSequences": ["\nObservation:"], "thinkingConfig":
-      {"include_thoughts": true}}}'
+      false}}, {"description": "Use this tool to provide your final structured response.
+      Call this tool when you have gathered all necessary information and are ready
+      to provide the final answer in the required format.", "name": "structured_output",
+      "parameters_json_schema": {"properties": {"operation": {"description": "The
+      mathematical operation performed", "title": "Operation", "type": "string"},
+      "result": {"description": "The result of the calculation", "title": "Result",
+      "type": "integer"}, "explanation": {"description": "Brief explanation of the
+      calculation", "title": "Explanation", "type": "string"}}, "required": ["operation",
+      "result", "explanation"], "title": "CalculationResult", "type": "object", "additionalProperties":
+      false, "propertyOrdering": ["operation", "result", "explanation"]}}]}], "generationConfig":
+      {"stopSequences": ["\nObservation:"]}}'
     headers:
       User-Agent:
       - X-USER-AGENT-XXX
@@ -35,67 +44,41 @@ interactions:
       connection:
       - keep-alive
       content-length:
-      - '2016'
+      - '2763'
       content-type:
       - application/json
       host:
       - generativelanguage.googleapis.com
       x-goog-api-client:
-      - google-genai-sdk/1.65.0 gl-python/3.13.3
+      - google-genai-sdk/1.49.0 gl-python/3.13.12
       x-goog-api-key:
       - X-GOOG-API-KEY-XXX
     method: POST
-    uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent
+    uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent
   response:
     body:
       string: "{\n  \"candidates\": [\n    {\n      \"content\": {\n        \"parts\":
-        [\n          {\n            \"text\": \"**My Calculation Process**\\n\\nAlright,
-        the user wants me to compute 15 + 27. Simple enough. I have a tool specifically
-        designed for this: `add_numbers(a: int, b: int)`. This is ideal; I'll utilize
-        that.\\n\\nSo, first step: I need to call the `add_numbers` tool. The inputs
-        are straightforward: `a` should be 15 and `b` should be 27. I'll execute that
-        call immediately.\\n\\nOnce I have the result \u2013 the sum \u2013 in hand,
-        I need to format the output. The user is specific about the structure; it
-        needs to be a JSON object conforming to that OpenAPI schema. Specifically,
-        the JSON should include: an \\\"operation\\\" field set to \\\"Addition\\\",
-        a \\\"result\\\" field populated with the calculated sum, and an \\\"explanation\\\"
-        field giving some context, which should be \\\"Added 15 and 27 together.\\\"\\n\\nTherefore,
-        my workflow is: call the tool with the provided numbers, get the sum, and
-        then construct the final JSON object in the required format.\\n\",\n            \"thought\":
-        true\n          },\n          {\n            \"text\": \"**My Reasoning for
-        Calculating 15 + 27**\\n\\nOkay, the user wants me to compute 15 plus 27.
-        No problem; that's straightforward. I've got a dedicated `add_numbers` tool
-        for this, which is exactly the right approach. Let's see...I need to call
-        that tool, providing `a=15` and `b=27` as input parameters. Once I receive
-        the sum, I can move on to formatting the result.\\n\\nNow, the important part:
-        the output needs to be a JSON object, specifically structured as dictated
-        by the OpenAPI schema. I need to make sure I include the \\\"operation\\\",
-        \\\"result\\\", and \\\"explanation\\\" fields. \\\"operation\\\" will be
-        \\\"Addition\\\", the \\\"result\\\" will naturally be the sum I get from
-        the tool, and the \\\"explanation\\\" will simply be \\\"Added 15 and 27 together.\\\"
-        That should cover everything, and the user should get a perfectly formatted
-        response.\\n\",\n            \"thought\": true\n          },\n          {\n
-        \           \"functionCall\": {\n              \"name\": \"add_numbers\",\n
+        [\n          {\n            \"functionCall\": {\n              \"name\": \"add_numbers\",\n
         \             \"args\": {\n                \"a\": 15,\n                \"b\":
-        27\n              }\n            },\n            \"thoughtSignature\": \"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\"\n
-        \         }\n        ],\n        \"role\": \"model\"\n      },\n      \"finishReason\":
-        \"STOP\",\n      \"index\": 0,\n      \"finishMessage\": \"Model generated
-        function call(s).\"\n    }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\":
-        383,\n    \"candidatesTokenCount\": 22,\n    \"totalTokenCount\": 658,\n    \"promptTokensDetails\":
-        [\n      {\n        \"modality\": \"TEXT\",\n        \"tokenCount\": 383\n
-        \     }\n    ],\n    \"thoughtsTokenCount\": 253,\n    \"serviceTier\": \"standard\"\n
-        \ },\n  \"modelVersion\": \"gemini-2.5-flash\",\n  \"responseId\": \"qagPas37Ba2R-8YPzYzI8AY\"\n}\n"
+        27\n              }\n            }\n          }\n        ],\n        \"role\":
+        \"model\"\n      },\n      \"finishReason\": \"STOP\",\n      \"avgLogprobs\":
+        4.3579145442760951e-06\n    }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\":
+        377,\n    \"candidatesTokenCount\": 7,\n    \"totalTokenCount\": 384,\n    \"promptTokensDetails\":
+        [\n      {\n        \"modality\": \"TEXT\",\n        \"tokenCount\": 377\n
+        \     }\n    ],\n    \"candidatesTokensDetails\": [\n      {\n        \"modality\":
+        \"TEXT\",\n        \"tokenCount\": 7\n      }\n    ]\n  },\n  \"modelVersion\":
+        \"gemini-2.0-flash-001\",\n  \"responseId\": \"vVefaYDSOouXjMcPicLCsQY\"\n}\n"
     headers:
       Alt-Svc:
       - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
       Content-Type:
       - application/json; charset=UTF-8
       Date:
-      - Fri, 22 May 2026 00:51:56 GMT
+      - Wed, 25 Feb 2026 20:12:46 GMT
       Server:
       - scaffolding on HTTPServer2
       Server-Timing:
-      - gfet4t7; dur=3892
+      - gfet4t7; dur=718
       Transfer-Encoding:
       - chunked
       Vary:
@@ -106,8 +89,6 @@ interactions:
       - X-CONTENT-TYPE-XXX
       X-Frame-Options:
       - X-FRAME-OPTIONS-XXX
-      X-Gemini-Service-Tier:
-      - standard
       X-XSS-Protection:
       - '0'
     status:
@@ -131,17 +112,27 @@ interactions:
       the schema format.\n\nDo not include the OpenAPI schema in the final output.
       Ensure the final output does not include any code block markers like ```json
       or ```python."}], "role": "user"}, {"parts": [{"functionCall": {"args": {"a":
-      15, "b": 27}, "name": "add_numbers"}, "thoughtSignature": "CtkGAQw51sf8m1RivBZ7Zp-ZkaqxDdZzSlzepmvlCKak9gl6edIuej_pHxR5dg3qZf89XmHvQ6HigZyzqHcYbSvcRHVGbpNkTr62FC0g10oK5ZEp_r1otLIcgXoVgyFGguJPe_NsfWSX3Uc7ZaYgV0Q2MHBsjUmEHicPH0Pj4Xmbe2I1pK_9DPrzSQqZW3duhLBlBIF9RwZUiltPH6mK-k71l8bN_ebsbbZM18FMXf0wg_7lf3OjvY2wdLDNUD_F2M7T8yfi7NelPWorjIuTGOVWlVRsdGW0QEzuVoyYY7OfbBJC-XsmTumYt-vqgIR3jcQZlA5_3yJdj3e_3mrNmzGt-8VvkjUnu3pz0IUkq2SoTG0-6Y_ajsUI0YA_BFiAXHjrRhH1Nx3ihGWT7E7VzpU_E1ZPFMJIOPLRSpRv8G6ITnjZGthozTZtKLgoHCF7kx4Ni8eVdOh2Us6kY7tYpVabM1dmw0gextEEt-fBMoI-qZGkXdL1YW6SEtQBHh3BGKX8khcrqNvqPZDFzSG0iieMJq7abbEYAIc8zRkeGlWEdX6ES6e-njnFN7JX0Nc32GzOjmpgx9gRhYe-wKonqBQ9RwLLNK-lFuflLTrU3D8jMiPCJyvoRsjdjEc-2JtHXo14ibOVXvZ6oYCHsTEB7f-90_qzcrITESyDBD_rmiT_SqgitBa44MZE9CZ9Ml-BW0xd9FfCy4oLy8w4vszVFDw9Eotr4pEzdCeDeWjMn35taJnWf6jUeF0z_0iyHjbi7XRubJXxI2YuKQ-HRCKX1RFaJWLhmxO4JNBDBqfYZqsO_FefqxjWi2pRzE8U_Upp8Tv_hy1FoN9Abs8W6lPoqgOyEiOcpVkM-u0CgUbf87I1X2EiPpuJF4D9dHlEJqumiPqIGazSLnrjW1qqbM5UpQQuPoTC7q-G092CEnNJBIwrufddZPDfD9rqINpmMa-7OswldKViVaCWR3VsgrSXJj7lVRntCyE2atWxTvtQVnR_JLDdyc98CAUChtAPnC4K_K3OVI4jffQQsHmfeOnTyg0n2VnZ6Yhgo0lMdE4IfMrNOWOuNvHodeHisD2yXjvTCgScO8B3s-EJTvenHMert3nRgjNRmFZ0cRNSjbTeG0UlB9s7Uy0uyrn5ODkKIgEMOdbH9yJU53jInG9boFeMXb1qif47Pc72taZkl6ZaMK4="}],
-      "role": "model"}, {"parts": [{"functionResponse": {"name": "add_numbers", "response":
-      {"result": 42}}}], "role": "user"}], "systemInstruction": {"parts": [{"text":
-      "You are Calculator. You are a calculator assistant that uses tools to compute
-      results.\nYour personal goal is: Perform calculations using available tools"}],
-      "role": "user"}, "tools": [{"functionDeclarations": [{"description": "Add two
-      numbers together and return the sum.", "name": "add_numbers", "parameters_json_schema":
-      {"properties": {"a": {"title": "A", "type": "integer"}, "b": {"title": "B",
-      "type": "integer"}}, "required": ["a", "b"], "type": "object", "additionalProperties":
-      false}}]}], "generationConfig": {"stopSequences": ["\nObservation:"], "thinkingConfig":
-      {"include_thoughts": true}}}'
+      15, "b": 27}, "name": "add_numbers"}}], "role": "model"}, {"parts": [{"functionResponse":
+      {"name": "add_numbers", "response": {"result": 42}}}], "role": "user"}, {"parts":
+      [{"text": "Analyze the tool result. If requirements are met, provide the Final
+      Answer. Otherwise, call the next tool. Deliver only the answer without meta-commentary."}],
+      "role": "user"}], "systemInstruction": {"parts": [{"text": "You are Calculator.
+      You are a calculator assistant that uses tools to compute results.\nYour personal
+      goal is: Perform calculations using available tools"}], "role": "user"}, "tools":
+      [{"functionDeclarations": [{"description": "Add two numbers together and return
+      the sum.", "name": "add_numbers", "parameters_json_schema": {"properties": {"a":
+      {"title": "A", "type": "integer"}, "b": {"title": "B", "type": "integer"}},
+      "required": ["a", "b"], "type": "object", "additionalProperties": false}}, {"description":
+      "Use this tool to provide your final structured response. Call this tool when
+      you have gathered all necessary information and are ready to provide the final
+      answer in the required format.", "name": "structured_output", "parameters_json_schema":
+      {"properties": {"operation": {"description": "The mathematical operation performed",
+      "title": "Operation", "type": "string"}, "result": {"description": "The result
+      of the calculation", "title": "Result", "type": "integer"}, "explanation": {"description":
+      "Brief explanation of the calculation", "title": "Explanation", "type": "string"}},
+      "required": ["operation", "result", "explanation"], "title": "CalculationResult",
+      "type": "object", "additionalProperties": false, "propertyOrdering": ["operation",
+      "result", "explanation"]}}]}], "generationConfig": {"stopSequences": ["\nObservation:"]}}'
     headers:
       User-Agent:
       - X-USER-AGENT-XXX
@@ -152,50 +143,42 @@ interactions:
       connection:
       - keep-alive
       content-length:
-      - '3441'
+      - '3166'
       content-type:
       - application/json
       host:
       - generativelanguage.googleapis.com
       x-goog-api-client:
-      - google-genai-sdk/1.65.0 gl-python/3.13.3
+      - google-genai-sdk/1.49.0 gl-python/3.13.12
       x-goog-api-key:
       - X-GOOG-API-KEY-XXX
     method: POST
-    uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent
+    uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent
   response:
     body:
       string: "{\n  \"candidates\": [\n    {\n      \"content\": {\n        \"parts\":
-        [\n          {\n            \"text\": \"**My Calculation and OpenAPI Formatting**\\n\\nOkay,
-        so I've just crunched the numbers, 15 plus 27, and the answer, as expected,
-        is 42. Now comes the formatting, the part I truly appreciate. It's time to
-        translate this into the precise structure that the OpenAPI schema dictates.\\n\\nLet's
-        see\u2026 I need to populate three key fields: `operation`, `result`, and
-        `explanation`. This is straightforward. For `operation`, I'll enter \\\"Addition,\\\"
-        because, well, that's what I did! For `result`, the answer I painstakingly
-        produced, 42. And for `explanation`, a concise note, \\\"Added 15 and 27 together.\\\"
-        Perfect. That should do the trick. Now I can move on to the next task.\\n\",\n
-        \           \"thought\": true\n          },\n          {\n            \"text\":
-        \"{\\n  \\\"operation\\\": \\\"Addition\\\",\\n  \\\"result\\\": 42,\\n  \\\"explanation\\\":
-        \\\"Added 15 and 27 together.\\\"\\n}\",\n            \"thoughtSignature\":
-        \"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\"\n
-        \         }\n        ],\n        \"role\": \"model\"\n      },\n      \"finishReason\":
-        \"STOP\",\n      \"index\": 0\n    }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\":
-        421,\n    \"candidatesTokenCount\": 36,\n    \"totalTokenCount\": 560,\n    \"promptTokensDetails\":
-        [\n      {\n        \"modality\": \"TEXT\",\n        \"tokenCount\": 421\n
-        \     }\n    ],\n    \"thoughtsTokenCount\": 103,\n    \"serviceTier\": \"standard\"\n
-        \ },\n  \"modelVersion\": \"gemini-2.5-flash\",\n  \"responseId\": \"ragPaseeA6nT_uMP653cmAc\"\n}\n"
+        [\n          {\n            \"functionCall\": {\n              \"name\": \"structured_output\",\n
+        \             \"args\": {\n                \"result\": 42,\n                \"explanation\":
+        \"15 + 27 = 42\",\n                \"operation\": \"addition\"\n              }\n
+        \           }\n          }\n        ],\n        \"role\": \"model\"\n      },\n
+        \     \"finishReason\": \"STOP\",\n      \"avgLogprobs\": -0.07498827245500353\n
+        \   }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\": 421,\n    \"candidatesTokenCount\":
+        18,\n    \"totalTokenCount\": 439,\n    \"promptTokensDetails\": [\n      {\n
+        \       \"modality\": \"TEXT\",\n        \"tokenCount\": 421\n      }\n    ],\n
+        \   \"candidatesTokensDetails\": [\n      {\n        \"modality\": \"TEXT\",\n
+        \       \"tokenCount\": 18\n      }\n    ]\n  },\n  \"modelVersion\": \"gemini-2.0-flash-001\",\n
+        \ \"responseId\": \"vlefac7bJb6TjMcPzYWh0Ag\"\n}\n"
     headers:
       Alt-Svc:
       - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
       Content-Type:
       - application/json; charset=UTF-8
       Date:
-      - Fri, 22 May 2026 00:51:59 GMT
+      - Wed, 25 Feb 2026 20:12:47 GMT
       Server:
       - scaffolding on HTTPServer2
       Server-Timing:
-      - gfet4t7; dur=2377
+      - gfet4t7; dur=774
       Transfer-Encoding:
       - chunked
       Vary:
@@ -206,8 +189,6 @@ interactions:
       - X-CONTENT-TYPE-XXX
       X-Frame-Options:
       - X-FRAME-OPTIONS-XXX
-      X-Gemini-Service-Tier:
-      - standard
       X-XSS-Protection:
       - '0'
     status:

lib/crewai/tests/events/test_event_context.py

@@ -11,6 +11,7 @@ from crewai.events.event_context import (
     MismatchBehavior,
     StackDepthExceededError,
     _event_context_config,
+    _event_id_stack,
     EventContextConfig,
     get_current_parent_id,
     get_enclosing_parent_id,
@@ -21,6 +22,7 @@ from crewai.events.event_context import (
     pop_event_scope,
     push_event_scope,
     reset_last_event_id,
+    resume_task_scope,
     set_last_event_id,
     set_triggering_event_id,
     triggered_by_scope,
@@ -180,6 +182,91 @@ class TestTriggeredByScope:
         assert get_triggering_event_id() is None
 
 
+class TestResumeTaskScope:
+    """Tests for the checkpoint-resume scope helper."""
+
+    @pytest.fixture(autouse=True)
+    def _reset_stack(self) -> None:
+        _event_id_stack.set(())
+
+    def _bind_runtime_state(self, *event_dicts: dict[str, object]):
+        from crewai.events import crewai_event_bus
+        from crewai.events.types.task_events import TaskStartedEvent
+        from crewai.state.event_record import EventRecord
+        from crewai.state.runtime import RuntimeState
+
+        record = EventRecord()
+        for spec in event_dicts:
+            ev = TaskStartedEvent(context=None, task=None)
+            ev.task_id = spec["task_id"]  # type: ignore[assignment]
+            ev.event_id = spec["event_id"]  # type: ignore[assignment]
+            ev.emission_sequence = spec["emission_sequence"]  # type: ignore[assignment]
+            record.add(ev)
+        state = RuntimeState(root=[])
+        state._event_record = record
+
+        previous = crewai_event_bus._runtime_state
+        crewai_event_bus._runtime_state = state
+        return crewai_event_bus, previous
+
+    def test_returns_false_when_no_runtime_state(self) -> None:
+        from crewai.events import crewai_event_bus
+
+        previous = crewai_event_bus._runtime_state
+        crewai_event_bus._runtime_state = None
+        try:
+            assert resume_task_scope("any-task") is False
+            assert _event_id_stack.get() == ()
+        finally:
+            crewai_event_bus._runtime_state = previous
+
+    def test_returns_false_when_no_matching_event(self) -> None:
+        bus, previous = self._bind_runtime_state(
+            {"task_id": "other", "event_id": "e1", "emission_sequence": 1},
+        )
+        try:
+            assert resume_task_scope("missing") is False
+            assert _event_id_stack.get() == ()
+        finally:
+            bus._runtime_state = previous
+
+    def test_pushes_latest_event_for_task(self) -> None:
+        bus, previous = self._bind_runtime_state(
+            {"task_id": "t1", "event_id": "e1", "emission_sequence": 1},
+            {"task_id": "t1", "event_id": "e2", "emission_sequence": 5},
+            {"task_id": "t1", "event_id": "e3", "emission_sequence": 3},
+            {"task_id": "t2", "event_id": "x1", "emission_sequence": 9},
+        )
+        try:
+            assert resume_task_scope("t1") is True
+            assert _event_id_stack.get() == (("e2", "task_started"),)
+        finally:
+            bus._runtime_state = previous
+
+    def test_pairs_cleanly_with_task_completed(self) -> None:
+        """The pushed scope must be popped by a matching task_completed."""
+        from crewai.events import crewai_event_bus
+        from crewai.events.types.task_events import TaskCompletedEvent
+        from crewai.tasks.task_output import TaskOutput
+
+        push_event_scope("kickoff-1", "crew_kickoff_started")
+        bus, previous = self._bind_runtime_state(
+            {"task_id": "t1", "event_id": "started-1", "emission_sequence": 1},
+        )
+        try:
+            assert resume_task_scope("t1") is True
+            output = TaskOutput(description="d", raw="r", agent="a")
+            completed = TaskCompletedEvent(output=output, task=None)
+            completed.task_id = "t1"
+            crewai_event_bus.emit(None, completed)
+            crewai_event_bus.flush()
+            assert _event_id_stack.get() == (("kickoff-1", "crew_kickoff_started"),)
+            assert completed.started_event_id == "started-1"
+        finally:
+            bus._runtime_state = previous
+            _event_id_stack.set(())
+
+
 def test_agent_scope_preserved_after_tool_error_event() -> None:
     from crewai.events import crewai_event_bus
     from crewai.events.types.tool_usage_events import (

lib/crewai/tests/llms/google/test_google.py

@@ -1025,7 +1025,7 @@ def test_gemini_crew_structured_output_with_tools():
         role="Calculator",
         goal="Perform calculations using available tools",
         backstory="You are a calculator assistant that uses tools to compute results.",
-        llm=LLM(model="google/gemini-2.5-flash"),
+        llm=LLM(model="google/gemini-2.0-flash-001"),
         tools=[add_numbers],
     )
 

pyproject.toml

@@ -189,6 +189,7 @@ exclude-newer = "3 days"
 # authlib <1.6.11 has GHSA-jj8c-mmj3-mmgv (CSRF bypass in cache-based state storage).
 # pip <26.1.1 has GHSA-58qw-9mgm-455v (archive handling); OSV considers 26.1.1 unaffected.
 # paramiko <5.0.0 has GHSA-r374-rxx8-8654 (SHA-1 in rsakey.py); OSV considers 5.0.0 unaffected. Transitive via composio-core.
+# starlette <1.0.1 has PYSEC-2026-161 (missing Host header validation poisons request.url.path, bypassing path-based auth). Transitive via fastapi.
 # litellm 1.83.8+ hard-pins openai==2.24.0, missing openai.types.responses used by crewai;
 # override to >=2.30.0 (the version litellm 1.83.7 used) until upstream relaxes the pin.
 override-dependencies = [
@@ -209,6 +210,7 @@ override-dependencies = [
     "authlib>=1.6.11",
     "pip>=26.1.1",
     "paramiko>=5.0.0",
+    "starlette>=1.0.1",
 ]
 
 [tool.uv.workspace]

uv.lock

@@ -13,9 +13,12 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-05-17T14:20:01.778505Z"
+exclude-newer = "2026-05-19T15:27:50.647689Z"
 exclude-newer-span = "P3D"
 
+[options.exclude-newer-package]
+starlette = "2026-05-22T16:00:00Z"
+
 [manifest]
 members = [
     "crewai",
@@ -40,6 +43,7 @@ overrides = [
     { name = "pypdf", specifier = ">=6.10.2,<7" },
     { name = "python-multipart", specifier = ">=0.0.27,<1" },
     { name = "rich", specifier = ">=13.7.1" },
+    { name = "starlette", specifier = ">=1.0.1" },
     { name = "transformers", marker = "python_full_version >= '3.10'", specifier = ">=5.4.0" },
     { name = "urllib3", specifier = ">=2.7.0" },
     { name = "uv", specifier = ">=0.11.6,<1" },
@@ -8528,15 +8532,15 @@ wheels = [
 
 [[package]]
 name = "starlette"
-version = "1.0.0"
+version = "1.0.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "anyio" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/81/69/17425771797c36cded50b7fe44e850315d039f28b15901ab44839e70b593/starlette-1.0.0.tar.gz", hash = "sha256:6a4beaf1f81bb472fd19ea9b918b50dc3a77a6f2e190a12954b25e6ed5eea149", size = 2655289, upload-time = "2026-03-22T18:29:46.779Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/08/a3/84e821cc54b4ab50ae6dbc6ac3800a651b65ec35f045cc73785380654057/starlette-1.0.1.tar.gz", hash = "sha256:512399c5f1de7fac99c88572212ded9ddeddef2fb32afa82d724000e88b38f4f", size = 2659596, upload-time = "2026-05-21T21:58:58.433Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0b/c9/584bc9651441b4ba60cc4d557d8a547b5aff901af35bda3a4ee30c819b82/starlette-1.0.0-py3-none-any.whl", hash = "sha256:d3ec55e0bb321692d275455ddfd3df75fff145d009685eb40dc91fc66b03d38b", size = 72651, upload-time = "2026-03-22T18:29:45.111Z" },
+    { url = "https://files.pythonhosted.org/packages/ec/e1/b2df4bc09a1e51ff664c1e17018a4274b42e5e9352e4a478ea540512dc88/starlette-1.0.1-py3-none-any.whl", hash = "sha256:7c0e69b2ee1c848bd54669d908500117a3ee13de603a21427e5c6fc1adf98dcd", size = 72802, upload-time = "2026-05-21T21:58:56.551Z" },
 ]
 
 [[package]]