Update Gemini agent tests to include structured output with thoughts and bump model version to 2.5-flash

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

@@ -28,6 +28,7 @@ from pydantic import (
     ConfigDict,
     Field,
     PrivateAttr,
+    ValidationError,
     model_validator,
 )
 from pydantic.functional_serializers import PlainSerializer
@@ -1691,24 +1692,32 @@ class Agent(BaseAgent):
         elif response_format:
             raw_output = str(output) if not isinstance(output, str) else output
             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
-                )
+                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
 
-                converter = Converter(
-                    llm=cast(BaseLLM, self.llm),
-                    text=raw_output,
-                    model=response_format,
-                    instructions=instructions,
-                )
+            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)
 
-                conversion_result = converter.to_pydantic()
-                if isinstance(conversion_result, BaseModel):
-                    formatted_result = conversion_result
-            except ConverterError:
-                pass
+                    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
         else:
             raw_output = str(output) if not isinstance(output, str) else output
 

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

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

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

@@ -1224,6 +1224,10 @@ 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),
@@ -1231,7 +1235,7 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
                 printer=PRINTER,
                 from_task=self.task,
                 from_agent=self.agent,
-                response_model=self.response_model,
+                response_model=effective_response_model,
                 executor_context=self,
                 verbose=self.agent.verbose,
             )
@@ -1319,7 +1323,7 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
                 available_functions=None,
                 from_task=self.task,
                 from_agent=self.agent,
-                response_model=self.response_model,
+                response_model=None,
                 executor_context=self,
                 verbose=self.agent.verbose,
             )

lib/crewai/src/crewai/lite_agent.py

@@ -23,6 +23,7 @@ from pydantic import (
     BaseModel,
     Field,
     PrivateAttr,
+    ValidationError,
     field_validator,
     model_validator,
 )
@@ -639,29 +640,38 @@ class LiteAgent(FlowTrackable, BaseModel):
             formatted_result = agent_finish.output
         elif active_response_format:
             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
+                formatted_result = active_response_format.model_validate_json(
+                    str(agent_finish.output)
                 )
+            except ValidationError:
+                # Direct JSON validation failed; fall back to converter-based parsing below.
+                formatted_result = None
 
-                converter = Converter(
-                    llm=self.llm,
-                    text=agent_finish.output,
-                    model=active_response_format,
-                    instructions=instructions,
-                )
+            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)
 
-                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",
+                    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",
+                        )
+
         # Calculate token usage metrics
         if isinstance(self.llm, BaseLLM):
             usage_metrics = self.llm.get_token_usage_summary()

lib/crewai/tests/agents/test_agent_executor.py

@@ -12,6 +12,7 @@ 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
@@ -108,6 +109,9 @@ class TestAgentExecutorState:
 class TestAgentExecutor:
     """Test AgentExecutor class."""
 
+    class StructuredResult(BaseModel):
+        value: str
+
     @pytest.fixture
     def mock_dependencies(self):
         """Create mock dependencies for executor."""
@@ -215,6 +219,49 @@ 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

@@ -8,18 +8,8 @@ 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}}, {"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:"]}}'
+      "additionalProperties": false}}]}], "generationConfig": {"stopSequences": ["\nObservation:"],
+      "thinkingConfig": {"include_thoughts": true}}}'
     headers:
       User-Agent:
       - X-USER-AGENT-XXX
@@ -30,13 +20,13 @@ interactions:
       connection:
       - keep-alive
       content-length:
-      - '1592'
+      - '784'
       content-type:
       - application/json
       host:
       - generativelanguage.googleapis.com
       x-goog-api-client:
-      - google-genai-sdk/1.49.0 gl-python/3.13.3
+      - google-genai-sdk/1.65.0 gl-python/3.13.3
       x-goog-api-key:
       - X-GOOG-API-KEY-XXX
     method: POST
@@ -44,27 +34,36 @@ interactions:
   response:
     body:
       string: "{\n  \"candidates\": [\n    {\n      \"content\": {\n        \"parts\":
-        [\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            \"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        \"role\": \"model\"\n      },\n      \"finishReason\":
         \"STOP\",\n      \"index\": 0,\n      \"finishMessage\": \"Model generated
         function call(s).\"\n    }\n  ],\n  \"usageMetadata\": {\n    \"promptTokenCount\":
-        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"
+        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"
     headers:
       Alt-Svc:
       - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
       Content-Type:
       - application/json; charset=UTF-8
       Date:
-      - Thu, 12 Feb 2026 22:11:14 GMT
+      - Thu, 21 May 2026 23:41:40 GMT
       Server:
       - scaffolding on HTTPServer2
       Server-Timing:
-      - gfet4t7; dur=1417
+      - gfet4t7; dur=1920
       Transfer-Encoding:
       - chunked
       Vary:
@@ -75,6 +74,8 @@ interactions:
       - X-CONTENT-TYPE-XXX
       X-Frame-Options:
       - X-FRAME-OPTIONS-XXX
+      X-Gemini-Service-Tier:
+      - standard
       X-XSS-Protection:
       - '0'
     status:
@@ -83,7 +84,7 @@ 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": "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"}],
+      {"args": {"a": 15, "b": 27}, "name": "add_numbers"}, "thoughtSignature": "CqwBAQw51sfkbjIDS7wS47oc_Bej-AYsUu5Cs-BC2Ae5NMasRmWa_u5Ct426qkpkIpgzGSNjwwfitf1gK93Abse9EGj5m1swXmPU2XSkqhMYMEXZGH1mW2U2XH8zaXHRIAx2aI0O8VbJ3sL8h1lJgbVCkvLa2RyWwY6E8FRPhQOHtrOQEQtfAUtHdJz928j6UEgS818X_7hEwuWsQhIho0frtziX30UlI7yXOeBBWw=="}],
       "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
@@ -92,18 +93,8 @@ 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}}, {"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:"]}}'
+      false}}]}], "generationConfig": {"stopSequences": ["\nObservation:"], "thinkingConfig":
+      {"include_thoughts": true}}}'
     headers:
       User-Agent:
       - X-USER-AGENT-XXX
@@ -114,13 +105,13 @@ interactions:
       connection:
       - keep-alive
       content-length:
-      - '2725'
+      - '1249'
       content-type:
       - application/json
       host:
       - generativelanguage.googleapis.com
       x-goog-api-client:
-      - google-genai-sdk/1.49.0 gl-python/3.13.3
+      - google-genai-sdk/1.65.0 gl-python/3.13.3
       x-goog-api-key:
       - X-GOOG-API-KEY-XXX
     method: POST
@@ -128,28 +119,24 @@ interactions:
   response:
     body:
       string: "{\n  \"candidates\": [\n    {\n      \"content\": {\n        \"parts\":
-        [\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
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+        `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"
     headers:
       Alt-Svc:
       - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
       Content-Type:
       - application/json; charset=UTF-8
       Date:
-      - Wed, 25 Feb 2026 20:12:47 GMT
+      - Fri, 22 May 2026 00:51:59 GMT
       Server:
       - scaffolding on HTTPServer2
       Server-Timing:
-      - gfet4t7; dur=774
+      - gfet4t7; dur=2377
       Transfer-Encoding:
       - chunked
       Vary:
@@ -189,6 +206,8 @@ 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/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-2.0-flash-001"),
+        llm=LLM(model="google/gemini-2.5-flash"),
         tools=[add_numbers],
     )