fix: broken Task Attributes table in docs (#4403)

The Guardrails row in the Task Attributes table had an unescaped pipe
character in the type column (Optional[List[Callable] | List[str]]) which
was interpreted as a column delimiter, breaking the table rendering.

Fixed by escaping the pipe with backslash and removing the extra column
from the header separator row.

Added tests to validate markdown table structure across all doc languages.

Co-Authored-By: João <joao@crewai.com>

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -65,8 +65,6 @@ body:
         - '3.10'
         - '3.11'
         - '3.12'
-        - '3.13'
-        - '3.14'
     validations:
       required: true
   - type: input

.github/codeql/codeql-config.yml

@@ -14,18 +14,13 @@ paths-ignore:
   - "lib/crewai/src/crewai/experimental/a2a/**"
 
 paths:
-  # Include GitHub Actions workflows/composite actions for CodeQL actions analysis
-  - ".github/workflows/**"
-  - ".github/actions/**"
   # Include all Python source code from workspace packages
   - "lib/crewai/src/**"
   - "lib/crewai-tools/src/**"
-  - "lib/crewai-files/src/**"
   - "lib/devtools/src/**"
   # Include tests (but exclude cassettes via paths-ignore)
   - "lib/crewai/tests/**"
   - "lib/crewai-tools/tests/**"
-  - "lib/crewai-files/tests/**"
   - "lib/devtools/tests/**"
 
 # Configure specific queries or packs if needed

.github/workflows/build-uv-cache.yml

@@ -19,7 +19,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
       - name: Checkout repository
@@ -32,10 +32,6 @@ jobs:
           python-version: ${{ matrix.python-version }}
           enable-cache: false
 
-      - name: Install system build dependencies
-        if: matrix.python-version == '3.14'
-        run: sudo apt-get update && sudo apt-get install -y libxml2-dev libxslt-dev libavformat-dev libavcodec-dev libavdevice-dev libavutil-dev libavfilter-dev libswscale-dev libswresample-dev libheif-dev
-
       - name: Install dependencies and populate cache
         run: |
           echo "Building global UV cache for Python ${{ matrix.python-version }}..."

.github/workflows/codeql.yml

@@ -69,7 +69,7 @@ jobs:
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
-      uses: github/codeql-action/init@v4
+      uses: github/codeql-action/init@v3
       with:
         languages: ${{ matrix.language }}
         build-mode: ${{ matrix.build-mode }}
@@ -98,6 +98,6 @@ jobs:
         exit 1
 
     - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v4
+      uses: github/codeql-action/analyze@v3
       with:
         category: "/language:${{matrix.language}}"

.github/workflows/linter.yml

@@ -26,15 +26,15 @@ jobs:
             ~/.cache/uv
             ~/.local/share/uv
             .venv
-          key: uv-main-py3.12-${{ hashFiles('uv.lock') }}
+          key: uv-main-py3.11-${{ hashFiles('uv.lock') }}
           restore-keys: |
-            uv-main-py3.12-
+            uv-main-py3.11-
 
       - name: Install uv
         uses: astral-sh/setup-uv@v6
         with:
           version: "0.8.4"
-          python-version: "3.12"
+          python-version: "3.11"
           enable-cache: false
 
       - name: Install dependencies
@@ -66,4 +66,4 @@ jobs:
             ~/.cache/uv
             ~/.local/share/uv
             .venv
-          key: uv-main-py3.12-${{ hashFiles('uv.lock') }}
+          key: uv-main-py3.11-${{ hashFiles('uv.lock') }}

.github/workflows/tests.yml

@@ -13,8 +13,8 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python-version: ['3.10', '3.11', '3.12', '3.13', '3.14']
-        group: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
+        python-version: ['3.10', '3.11', '3.12', '3.13']
+        group: [1, 2, 3, 4, 5, 6, 7, 8]
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
@@ -40,10 +40,6 @@ jobs:
           python-version: ${{ matrix.python-version }}
           enable-cache: false
 
-      - name: Install system build dependencies
-        if: matrix.python-version == '3.14'
-        run: sudo apt-get update && sudo apt-get install -y libxml2-dev libxslt-dev libavformat-dev libavcodec-dev libavdevice-dev libavutil-dev libavfilter-dev libswscale-dev libswresample-dev libheif-dev
-
       - name: Install the project
         run: uv sync --all-groups --all-extras
 
@@ -53,7 +49,7 @@ jobs:
           path: .test_durations_py*
           key: test-durations-py${{ matrix.python-version }}
 
-      - name: Run tests (group ${{ matrix.group }} of 16)
+      - name: Run tests (group ${{ matrix.group }} of 8)
         run: |
           PYTHON_VERSION_SAFE=$(echo "${{ matrix.python-version }}" | tr '.' '_')
           DURATION_FILE="../../.test_durations_py${PYTHON_VERSION_SAFE}"
@@ -77,17 +73,17 @@ jobs:
 
           cd lib/crewai && uv run pytest \
             -vv \
-            --splits 16 \
+            --splits 8 \
             --group ${{ matrix.group }} \
             $DURATIONS_ARG \
             --durations=10 \
             --maxfail=3
 
-      - name: Run tool tests (group ${{ matrix.group }} of 16)
+      - name: Run tool tests (group ${{ matrix.group }} of 8)
         run: |
           cd lib/crewai-tools && uv run pytest \
             -vv \
-            --splits 16 \
+            --splits 8 \
             --group ${{ matrix.group }} \
             --durations=10 \
             --maxfail=3

.github/workflows/type-checker.yml

@@ -12,7 +12,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
       - name: Checkout code
@@ -39,10 +39,6 @@ jobs:
           python-version: ${{ matrix.python-version }}
           enable-cache: false
 
-      - name: Install system build dependencies
-        if: matrix.python-version == '3.14'
-        run: sudo apt-get update && sudo apt-get install -y libxml2-dev libxslt-dev libavformat-dev libavcodec-dev libavdevice-dev libavutil-dev libavfilter-dev libswscale-dev libswresample-dev libheif-dev
-
       - name: Install dependencies
         run: uv sync --all-groups --all-extras
 

.github/workflows/update-test-durations.yml

@@ -16,11 +16,11 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.10', '3.11', '3.12', '3.13', '3.14']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
     env:
       OPENAI_API_KEY: fake-api-key
       PYTHONUNBUFFERED: 1
-
+    
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
@@ -44,10 +44,6 @@ jobs:
           python-version: ${{ matrix.python-version }}
           enable-cache: false
 
-      - name: Install system build dependencies
-        if: matrix.python-version == '3.14'
-        run: sudo apt-get update && sudo apt-get install -y libxml2-dev libxslt-dev libavformat-dev libavcodec-dev libavdevice-dev libavutil-dev libavfilter-dev libswscale-dev libswresample-dev libheif-dev
-
       - name: Install the project
         run: uv sync --all-groups --all-extras
 
@@ -72,4 +68,4 @@ jobs:
             ~/.cache/uv
             ~/.local/share/uv
             .venv
-          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
+          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}

docs/en/concepts/tasks.mdx

@@ -45,26 +45,26 @@ crew = Crew(
 
 ## Task Attributes
 
-| Attribute                              | Parameters              | Type                        | Description                                                                                                     |
-| :------------------------------------- | :---------------------- | :-------------------------- | :-------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- |
-| **Description**                        | `description`           | `str`                       | A clear, concise statement of what the task entails.                                                            |
-| **Expected Output**                    | `expected_output`       | `str`                       | A detailed description of what the task's completion looks like.                                                |
-| **Name** _(optional)_                  | `name`                  | `Optional[str]`             | A name identifier for the task.                                                                                 |
-| **Agent** _(optional)_                 | `agent`                 | `Optional[BaseAgent]`       | The agent responsible for executing the task.                                                                   |
-| **Tools** _(optional)_                 | `tools`                 | `List[BaseTool]`            | The tools/resources the agent is limited to use for this task.                                                  |
-| **Context** _(optional)_               | `context`               | `Optional[List["Task"]]`    | Other tasks whose outputs will be used as context for this task.                                                |
-| **Async Execution** _(optional)_       | `async_execution`       | `Optional[bool]`            | Whether the task should be executed asynchronously. Defaults to False.                                          |
-| **Human Input** _(optional)_           | `human_input`           | `Optional[bool]`            | Whether the task should have a human review the final answer of the agent. Defaults to False.                   |
-| **Markdown** _(optional)_              | `markdown`              | `Optional[bool]`            | Whether the task should instruct the agent to return the final answer formatted in Markdown. Defaults to False. |
-| **Config** _(optional)_                | `config`                | `Optional[Dict[str, Any]]`  | Task-specific configuration parameters.                                                                         |
-| **Output File** _(optional)_           | `output_file`           | `Optional[str]`             | File path for storing the task output.                                                                          |
-| **Create Directory** _(optional)_      | `create_directory`      | `Optional[bool]`            | Whether to create the directory for output_file if it doesn't exist. Defaults to True.                          |
-| **Output JSON** _(optional)_           | `output_json`           | `Optional[Type[BaseModel]]` | A Pydantic model to structure the JSON output.                                                                  |
-| **Output Pydantic** _(optional)_       | `output_pydantic`       | `Optional[Type[BaseModel]]` | A Pydantic model for task output.                                                                               |
-| **Callback** _(optional)_              | `callback`              | `Optional[Any]`             | Function/object to be executed after task completion.                                                           |
-| **Guardrail** _(optional)_             | `guardrail`             | `Optional[Callable]`        | Function to validate task output before proceeding to next task.                                                |
-| **Guardrails** _(optional)_            | `guardrails`            | `Optional[List[Callable]    | List[str]]`                                                                                                     | List of guardrails to validate task output before proceeding to next task. |
-| **Guardrail Max Retries** _(optional)_ | `guardrail_max_retries` | `Optional[int]`             | Maximum number of retries when guardrail validation fails. Defaults to 3.                                       |
+| Attribute                              | Parameters              | Type                                    | Description                                                                                                     |
+| :------------------------------------- | :---------------------- | :-------------------------------------- | :-------------------------------------------------------------------------------------------------------------- |
+| **Description**                        | `description`           | `str`                                   | A clear, concise statement of what the task entails.                                                            |
+| **Expected Output**                    | `expected_output`       | `str`                                   | A detailed description of what the task's completion looks like.                                                |
+| **Name** _(optional)_                  | `name`                  | `Optional[str]`                         | A name identifier for the task.                                                                                 |
+| **Agent** _(optional)_                 | `agent`                 | `Optional[BaseAgent]`                   | The agent responsible for executing the task.                                                                   |
+| **Tools** _(optional)_                 | `tools`                 | `List[BaseTool]`                        | The tools/resources the agent is limited to use for this task.                                                  |
+| **Context** _(optional)_               | `context`               | `Optional[List["Task"]]`                | Other tasks whose outputs will be used as context for this task.                                                |
+| **Async Execution** _(optional)_       | `async_execution`       | `Optional[bool]`                        | Whether the task should be executed asynchronously. Defaults to False.                                          |
+| **Human Input** _(optional)_           | `human_input`           | `Optional[bool]`                        | Whether the task should have a human review the final answer of the agent. Defaults to False.                   |
+| **Markdown** _(optional)_              | `markdown`              | `Optional[bool]`                        | Whether the task should instruct the agent to return the final answer formatted in Markdown. Defaults to False. |
+| **Config** _(optional)_                | `config`                | `Optional[Dict[str, Any]]`              | Task-specific configuration parameters.                                                                         |
+| **Output File** _(optional)_           | `output_file`           | `Optional[str]`                         | File path for storing the task output.                                                                          |
+| **Create Directory** _(optional)_      | `create_directory`      | `Optional[bool]`                        | Whether to create the directory for output_file if it doesn't exist. Defaults to True.                          |
+| **Output JSON** _(optional)_           | `output_json`           | `Optional[Type[BaseModel]]`             | A Pydantic model to structure the JSON output.                                                                  |
+| **Output Pydantic** _(optional)_       | `output_pydantic`       | `Optional[Type[BaseModel]]`             | A Pydantic model for task output.                                                                               |
+| **Callback** _(optional)_              | `callback`              | `Optional[Any]`                         | Function/object to be executed after task completion.                                                           |
+| **Guardrail** _(optional)_             | `guardrail`             | `Optional[Callable]`                    | Function to validate task output before proceeding to next task.                                                |
+| **Guardrails** _(optional)_            | `guardrails`            | `Optional[List[Callable] \| List[str]]` | List of guardrails to validate task output before proceeding to next task.                                      |
+| **Guardrail Max Retries** _(optional)_ | `guardrail_max_retries` | `Optional[int]`                         | Maximum number of retries when guardrail validation fails. Defaults to 3.                                       |
 
 <Note type="warning" title="Deprecated: max_retries">
   The task attribute `max_retries` is deprecated and will be removed in v1.0.0.

lib/crewai-files/pyproject.toml

@@ -6,7 +6,7 @@ readme = "README.md"
 authors = [
     { name = "Greyson LaLonde", email = "greyson@crewai.com" }
 ]
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.10, <3.14"
 dependencies = [
     "Pillow~=10.4.0",
     "pypdf~=4.0.0",

lib/crewai-tools/pyproject.toml

@@ -6,7 +6,7 @@ readme = "README.md"
 authors = [
     { name = "João Moura", email = "joaomdmoura@gmail.com" },
 ]
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.10, <3.14"
 dependencies = [
     "lancedb~=0.5.4",
     "pytube~=15.0.0",
@@ -118,7 +118,7 @@ rag = [
     "lxml>=5.3.0,<5.4.0",  # Pin to avoid etree import issues in 5.4.0
 ]
 xml = [
-    "unstructured[local-inference, all-docs]>=0.17.2,<0.18.31"
+    "unstructured[local-inference, all-docs]>=0.17.2"
 ]
 oxylabs = [
     "oxylabs==2.0.0"

lib/crewai-tools/tests/tools/brave_search_tool_test.py

@@ -33,11 +33,8 @@ def test_brave_tool_search(mock_get, brave_tool):
     mock_get.return_value.json.return_value = mock_response
 
     result = brave_tool.run(query="test")
-    data = json.loads(result)
-    assert isinstance(data, list)
-    assert len(data) >= 1
-    assert data[0]["title"] == "Test Title"
-    assert data[0]["url"] == "http://test.com"
+    assert "Test Title" in result
+    assert "http://test.com" in result
 
 
 @patch("requests.get")

lib/crewai/pyproject.toml

@@ -6,7 +6,7 @@ readme = "README.md"
 authors = [
     { name = "Joao Moura", email = "joao@crewai.com" }
 ]
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.10, <3.14"
 dependencies = [
     # Core Dependencies
     "pydantic~=2.11.9",
@@ -14,7 +14,7 @@ dependencies = [
     "instructor>=1.3.3",
     # Text Processing
     "pdfplumber~=0.11.4",
-    "regex~=2026.1.15",
+    "regex~=2024.9.11",
     # Telemetry and Monitoring
     "opentelemetry-api~=1.34.0",
     "opentelemetry-sdk~=1.34.0",
@@ -36,7 +36,7 @@ dependencies = [
     "json5~=0.10.0",
     "portalocker~=2.7.0",
     "pydantic-settings~=2.10.1",
-    "mcp~=1.26.0",
+    "mcp~=1.23.1",
     "uv~=0.9.13",
     "aiosqlite~=0.21.0",
 ]

lib/crewai/src/crewai/cli/templates/crew/pyproject.toml

@@ -3,7 +3,7 @@ name = "{{folder_name}}"
 version = "0.1.0"
 description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.10,<3.14"
 dependencies = [
     "crewai[tools]==1.9.3"
 ]

lib/crewai/src/crewai/cli/templates/flow/pyproject.toml

@@ -3,7 +3,7 @@ name = "{{folder_name}}"
 version = "0.1.0"
 description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.10,<3.14"
 dependencies = [
     "crewai[tools]==1.9.3"
 ]

lib/crewai/src/crewai/cli/templates/tool/pyproject.toml

@@ -3,9 +3,9 @@ name = "{{folder_name}}"
 version = "0.1.0"
 description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.9.3"
+    "crewai[tools]>=0.203.1"
 ]
 
 [tool.crewai]

lib/crewai/src/crewai/crew.py

@@ -187,7 +187,6 @@ class Crew(FlowTrackable, BaseModel):
     _task_output_handler: TaskOutputStorageHandler = PrivateAttr(
         default_factory=TaskOutputStorageHandler
     )
-    _kickoff_event_id: str | None = PrivateAttr(default=None)
 
     name: str | None = Field(default="crew")
     cache: bool = Field(default=True)
@@ -760,11 +759,7 @@ class Crew(FlowTrackable, BaseModel):
         except Exception as e:
             crewai_event_bus.emit(
                 self,
-                CrewKickoffFailedEvent(
-                    error=str(e),
-                    crew_name=self.name,
-                    started_event_id=self._kickoff_event_id,
-                ),
+                CrewKickoffFailedEvent(error=str(e), crew_name=self.name),
             )
             raise
         finally:
@@ -954,11 +949,7 @@ class Crew(FlowTrackable, BaseModel):
         except Exception as e:
             crewai_event_bus.emit(
                 self,
-                CrewKickoffFailedEvent(
-                    error=str(e),
-                    crew_name=self.name,
-                    started_event_id=self._kickoff_event_id,
-                ),
+                CrewKickoffFailedEvent(error=str(e), crew_name=self.name),
             )
             raise
         finally:
@@ -1533,7 +1524,6 @@ class Crew(FlowTrackable, BaseModel):
                 crew_name=self.name,
                 output=final_task_output,
                 total_tokens=self.token_usage.total_tokens,
-                started_event_id=self._kickoff_event_id,
             ),
         )
 

lib/crewai/src/crewai/crews/utils.py

@@ -265,9 +265,10 @@ def prepare_kickoff(
             normalized = {}
         normalized = before_callback(normalized)
 
-    started_event = CrewKickoffStartedEvent(crew_name=crew.name, inputs=normalized)
-    crew._kickoff_event_id = started_event.event_id
-    future = crewai_event_bus.emit(crew, started_event)
+    future = crewai_event_bus.emit(
+        crew,
+        CrewKickoffStartedEvent(crew_name=crew.name, inputs=normalized),
+    )
     if future is not None:
         try:
             future.result()

lib/crewai/src/crewai/llms/providers/openai/completion.py

@@ -1696,99 +1696,6 @@ class OpenAICompletion(BaseLLM):
 
         return content
 
-    def _finalize_streaming_response(
-        self,
-        full_response: str,
-        tool_calls: dict[int, dict[str, Any]],
-        usage_data: dict[str, int],
-        params: dict[str, Any],
-        available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
-        from_agent: Any | None = None,
-    ) -> str | list[dict[str, Any]]:
-        """Finalize a streaming response with usage tracking, tool call handling, and events.
-
-        Args:
-            full_response: The accumulated text response from the stream.
-            tool_calls: Accumulated tool calls from the stream, keyed by index.
-            usage_data: Token usage data from the stream.
-            params: The completion parameters containing messages.
-            available_functions: Available functions for tool calling.
-            from_task: Task that initiated the call.
-            from_agent: Agent that initiated the call.
-
-        Returns:
-            Tool calls list when tools were invoked without available_functions,
-            tool execution result when available_functions is provided,
-            or the text response string.
-        """
-        self._track_token_usage_internal(usage_data)
-
-        if tool_calls and not available_functions:
-            tool_calls_list = [
-                {
-                    "id": call_data["id"],
-                    "type": "function",
-                    "function": {
-                        "name": call_data["name"],
-                        "arguments": call_data["arguments"],
-                    },
-                    "index": call_data["index"],
-                }
-                for call_data in tool_calls.values()
-            ]
-            self._emit_call_completed_event(
-                response=tool_calls_list,
-                call_type=LLMCallType.TOOL_CALL,
-                from_task=from_task,
-                from_agent=from_agent,
-                messages=params["messages"],
-            )
-            return tool_calls_list
-
-        if tool_calls and available_functions:
-            for call_data in tool_calls.values():
-                function_name = call_data["name"]
-                arguments = call_data["arguments"]
-
-                if not function_name or not arguments:
-                    continue
-
-                if function_name not in available_functions:
-                    logging.warning(
-                        f"Function '{function_name}' not found in available functions"
-                    )
-                    continue
-
-                try:
-                    function_args = json.loads(arguments)
-                except json.JSONDecodeError as e:
-                    logging.error(f"Failed to parse streamed tool arguments: {e}")
-                    continue
-
-                result = self._handle_tool_execution(
-                    function_name=function_name,
-                    function_args=function_args,
-                    available_functions=available_functions,
-                    from_task=from_task,
-                    from_agent=from_agent,
-                )
-
-                if result is not None:
-                    return result
-
-        full_response = self._apply_stop_words(full_response)
-
-        self._emit_call_completed_event(
-            response=full_response,
-            call_type=LLMCallType.LLM_CALL,
-            from_task=from_task,
-            from_agent=from_agent,
-            messages=params["messages"],
-        )
-
-        return full_response
-
     def _handle_streaming_completion(
         self,
         params: dict[str, Any],
@@ -1796,7 +1703,7 @@ class OpenAICompletion(BaseLLM):
         from_task: Any | None = None,
         from_agent: Any | None = None,
         response_model: type[BaseModel] | None = None,
-    ) -> str | list[dict[str, Any]] | BaseModel:
+    ) -> str | BaseModel:
         """Handle streaming chat completion."""
         full_response = ""
         tool_calls: dict[int, dict[str, Any]] = {}
@@ -1913,20 +1820,54 @@ class OpenAICompletion(BaseLLM):
                         response_id=response_id_stream,
                     )
 
-        result = self._finalize_streaming_response(
-            full_response=full_response,
-            tool_calls=tool_calls,
-            usage_data=usage_data,
-            params=params,
-            available_functions=available_functions,
+        self._track_token_usage_internal(usage_data)
+
+        if tool_calls and available_functions:
+            for call_data in tool_calls.values():
+                function_name = call_data["name"]
+                arguments = call_data["arguments"]
+
+                # Skip if function name is empty or arguments are empty
+                if not function_name or not arguments:
+                    continue
+
+                # Check if function exists in available functions
+                if function_name not in available_functions:
+                    logging.warning(
+                        f"Function '{function_name}' not found in available functions"
+                    )
+                    continue
+
+                try:
+                    function_args = json.loads(arguments)
+                except json.JSONDecodeError as e:
+                    logging.error(f"Failed to parse streamed tool arguments: {e}")
+                    continue
+
+                result = self._handle_tool_execution(
+                    function_name=function_name,
+                    function_args=function_args,
+                    available_functions=available_functions,
+                    from_task=from_task,
+                    from_agent=from_agent,
+                )
+
+                if result is not None:
+                    return result
+
+        full_response = self._apply_stop_words(full_response)
+
+        self._emit_call_completed_event(
+            response=full_response,
+            call_type=LLMCallType.LLM_CALL,
             from_task=from_task,
             from_agent=from_agent,
+            messages=params["messages"],
+        )
+
+        return self._invoke_after_llm_call_hooks(
+            params["messages"], full_response, from_agent
         )
-        if isinstance(result, str):
-            return self._invoke_after_llm_call_hooks(
-                params["messages"], result, from_agent
-            )
-        return result
 
     async def _ahandle_completion(
         self,
@@ -2075,7 +2016,7 @@ class OpenAICompletion(BaseLLM):
         from_task: Any | None = None,
         from_agent: Any | None = None,
         response_model: type[BaseModel] | None = None,
-    ) -> str | list[dict[str, Any]] | BaseModel:
+    ) -> str | BaseModel:
         """Handle async streaming chat completion."""
         full_response = ""
         tool_calls: dict[int, dict[str, Any]] = {}
@@ -2201,16 +2142,51 @@ class OpenAICompletion(BaseLLM):
                         response_id=response_id_stream,
                     )
 
-        return self._finalize_streaming_response(
-            full_response=full_response,
-            tool_calls=tool_calls,
-            usage_data=usage_data,
-            params=params,
-            available_functions=available_functions,
+        self._track_token_usage_internal(usage_data)
+
+        if tool_calls and available_functions:
+            for call_data in tool_calls.values():
+                function_name = call_data["name"]
+                arguments = call_data["arguments"]
+
+                if not function_name or not arguments:
+                    continue
+
+                if function_name not in available_functions:
+                    logging.warning(
+                        f"Function '{function_name}' not found in available functions"
+                    )
+                    continue
+
+                try:
+                    function_args = json.loads(arguments)
+                except json.JSONDecodeError as e:
+                    logging.error(f"Failed to parse streamed tool arguments: {e}")
+                    continue
+
+                result = self._handle_tool_execution(
+                    function_name=function_name,
+                    function_args=function_args,
+                    available_functions=available_functions,
+                    from_task=from_task,
+                    from_agent=from_agent,
+                )
+
+                if result is not None:
+                    return result
+
+        full_response = self._apply_stop_words(full_response)
+
+        self._emit_call_completed_event(
+            response=full_response,
+            call_type=LLMCallType.LLM_CALL,
             from_task=from_task,
             from_agent=from_agent,
+            messages=params["messages"],
         )
 
+        return full_response
+
     def supports_function_calling(self) -> bool:
         """Check if the model supports function calling."""
         return not self.is_o1_model

lib/crewai/tests/cli/deploy/test_deploy_main.py

@@ -230,7 +230,7 @@ class TestDeployCommand(unittest.TestCase):
         [project]
         name = "test_project"
         version = "0.1.0"
-        requires-python = ">=3.10,<3.15"
+        requires-python = ">=3.10,<3.14"
         dependencies = ["crewai"]
         """,
     )
@@ -249,7 +249,7 @@ class TestDeployCommand(unittest.TestCase):
     [project]
     name = "test_project"
     version = "0.1.0"
-    requires-python = ">=3.10,<3.15"
+    requires-python = ">=3.10,<3.14"
     dependencies = ["crewai"]
     """,
     )

lib/crewai/tests/llms/openai/test_openai.py

@@ -1,7 +1,6 @@
 import os
 import sys
 import types
-from typing import Any
 from unittest.mock import patch, MagicMock
 import openai
 import pytest
@@ -1579,167 +1578,3 @@ def test_openai_structured_output_preserves_json_with_stop_word_patterns():
     assert "Action:" in result.action_taken
     assert "Observation:" in result.observation_result
     assert "Final Answer:" in result.final_answer
-
-
-def test_openai_streaming_returns_tool_calls_without_available_functions():
-    """Test that streaming returns tool calls list when available_functions is None.
-
-    This mirrors the non-streaming path where tool_calls are returned for
-    the executor to handle. Reproduces the bug where streaming with tool
-    calls would return empty text instead of tool_calls when
-    available_functions was not provided (as the crew executor does).
-    """
-    llm = LLM(model="openai/gpt-4o-mini", stream=True)
-
-    mock_chunk_1 = MagicMock()
-    mock_chunk_1.choices = [MagicMock()]
-    mock_chunk_1.choices[0].delta = MagicMock()
-    mock_chunk_1.choices[0].delta.content = None
-    mock_chunk_1.choices[0].delta.tool_calls = [MagicMock()]
-    mock_chunk_1.choices[0].delta.tool_calls[0].index = 0
-    mock_chunk_1.choices[0].delta.tool_calls[0].id = "call_abc123"
-    mock_chunk_1.choices[0].delta.tool_calls[0].function = MagicMock()
-    mock_chunk_1.choices[0].delta.tool_calls[0].function.name = "calculator"
-    mock_chunk_1.choices[0].delta.tool_calls[0].function.arguments = '{"expr'
-    mock_chunk_1.choices[0].finish_reason = None
-    mock_chunk_1.usage = None
-    mock_chunk_1.id = "chatcmpl-1"
-
-    mock_chunk_2 = MagicMock()
-    mock_chunk_2.choices = [MagicMock()]
-    mock_chunk_2.choices[0].delta = MagicMock()
-    mock_chunk_2.choices[0].delta.content = None
-    mock_chunk_2.choices[0].delta.tool_calls = [MagicMock()]
-    mock_chunk_2.choices[0].delta.tool_calls[0].index = 0
-    mock_chunk_2.choices[0].delta.tool_calls[0].id = None
-    mock_chunk_2.choices[0].delta.tool_calls[0].function = MagicMock()
-    mock_chunk_2.choices[0].delta.tool_calls[0].function.name = None
-    mock_chunk_2.choices[0].delta.tool_calls[0].function.arguments = 'ession": "1+1"}'
-    mock_chunk_2.choices[0].finish_reason = None
-    mock_chunk_2.usage = None
-    mock_chunk_2.id = "chatcmpl-1"
-
-    mock_chunk_3 = MagicMock()
-    mock_chunk_3.choices = [MagicMock()]
-    mock_chunk_3.choices[0].delta = MagicMock()
-    mock_chunk_3.choices[0].delta.content = None
-    mock_chunk_3.choices[0].delta.tool_calls = None
-    mock_chunk_3.choices[0].finish_reason = "tool_calls"
-    mock_chunk_3.usage = MagicMock()
-    mock_chunk_3.usage.prompt_tokens = 10
-    mock_chunk_3.usage.completion_tokens = 5
-    mock_chunk_3.id = "chatcmpl-1"
-
-    with patch.object(
-        llm.client.chat.completions, "create", return_value=iter([mock_chunk_1, mock_chunk_2, mock_chunk_3])
-    ):
-        result = llm.call(
-            messages=[{"role": "user", "content": "Calculate 1+1"}],
-            tools=[{
-                "type": "function",
-                "function": {
-                    "name": "calculator",
-                    "description": "Calculate expression",
-                    "parameters": {"type": "object", "properties": {"expression": {"type": "string"}}},
-                },
-            }],
-            available_functions=None,
-        )
-
-    assert isinstance(result, list), f"Expected list of tool calls, got {type(result)}: {result}"
-    assert len(result) == 1
-    assert result[0]["function"]["name"] == "calculator"
-    assert result[0]["function"]["arguments"] == '{"expression": "1+1"}'
-    assert result[0]["id"] == "call_abc123"
-    assert result[0]["type"] == "function"
-
-
-@pytest.mark.asyncio
-async def test_openai_async_streaming_returns_tool_calls_without_available_functions():
-    """Test that async streaming returns tool calls list when available_functions is None.
-
-    Same as the sync test but for the async path (_ahandle_streaming_completion).
-    """
-    llm = LLM(model="openai/gpt-4o-mini", stream=True)
-
-    mock_chunk_1 = MagicMock()
-    mock_chunk_1.choices = [MagicMock()]
-    mock_chunk_1.choices[0].delta = MagicMock()
-    mock_chunk_1.choices[0].delta.content = None
-    mock_chunk_1.choices[0].delta.tool_calls = [MagicMock()]
-    mock_chunk_1.choices[0].delta.tool_calls[0].index = 0
-    mock_chunk_1.choices[0].delta.tool_calls[0].id = "call_abc123"
-    mock_chunk_1.choices[0].delta.tool_calls[0].function = MagicMock()
-    mock_chunk_1.choices[0].delta.tool_calls[0].function.name = "calculator"
-    mock_chunk_1.choices[0].delta.tool_calls[0].function.arguments = '{"expr'
-    mock_chunk_1.choices[0].finish_reason = None
-    mock_chunk_1.usage = None
-    mock_chunk_1.id = "chatcmpl-1"
-
-    mock_chunk_2 = MagicMock()
-    mock_chunk_2.choices = [MagicMock()]
-    mock_chunk_2.choices[0].delta = MagicMock()
-    mock_chunk_2.choices[0].delta.content = None
-    mock_chunk_2.choices[0].delta.tool_calls = [MagicMock()]
-    mock_chunk_2.choices[0].delta.tool_calls[0].index = 0
-    mock_chunk_2.choices[0].delta.tool_calls[0].id = None
-    mock_chunk_2.choices[0].delta.tool_calls[0].function = MagicMock()
-    mock_chunk_2.choices[0].delta.tool_calls[0].function.name = None
-    mock_chunk_2.choices[0].delta.tool_calls[0].function.arguments = 'ession": "1+1"}'
-    mock_chunk_2.choices[0].finish_reason = None
-    mock_chunk_2.usage = None
-    mock_chunk_2.id = "chatcmpl-1"
-
-    mock_chunk_3 = MagicMock()
-    mock_chunk_3.choices = [MagicMock()]
-    mock_chunk_3.choices[0].delta = MagicMock()
-    mock_chunk_3.choices[0].delta.content = None
-    mock_chunk_3.choices[0].delta.tool_calls = None
-    mock_chunk_3.choices[0].finish_reason = "tool_calls"
-    mock_chunk_3.usage = MagicMock()
-    mock_chunk_3.usage.prompt_tokens = 10
-    mock_chunk_3.usage.completion_tokens = 5
-    mock_chunk_3.id = "chatcmpl-1"
-
-    class MockAsyncStream:
-        """Async iterator that mimics OpenAI's async streaming response."""
-
-        def __init__(self, chunks: list[Any]) -> None:
-            self._chunks = chunks
-            self._index = 0
-
-        def __aiter__(self) -> "MockAsyncStream":
-            return self
-
-        async def __anext__(self) -> Any:
-            if self._index >= len(self._chunks):
-                raise StopAsyncIteration
-            chunk = self._chunks[self._index]
-            self._index += 1
-            return chunk
-
-    async def mock_create(**kwargs: Any) -> MockAsyncStream:
-        return MockAsyncStream([mock_chunk_1, mock_chunk_2, mock_chunk_3])
-
-    with patch.object(
-        llm.async_client.chat.completions, "create", side_effect=mock_create
-    ):
-        result = await llm.acall(
-            messages=[{"role": "user", "content": "Calculate 1+1"}],
-            tools=[{
-                "type": "function",
-                "function": {
-                    "name": "calculator",
-                    "description": "Calculate expression",
-                    "parameters": {"type": "object", "properties": {"expression": {"type": "string"}}},
-                },
-            }],
-            available_functions=None,
-        )
-
-    assert isinstance(result, list), f"Expected list of tool calls, got {type(result)}: {result}"
-    assert len(result) == 1
-    assert result[0]["function"]["name"] == "calculator"
-    assert result[0]["function"]["arguments"] == '{"expression": "1+1"}'
-    assert result[0]["id"] == "call_abc123"
-    assert result[0]["type"] == "function"

lib/crewai/tests/test_docs_table_formatting.py

@@ -0,0 +1,155 @@
+"""Tests to validate markdown table formatting in documentation files.
+
+These tests ensure that markdown tables in the documentation are well-formed
+and render correctly. Specifically, they check that:
+- All rows have the same number of columns as the header
+- Pipe characters inside table cells are properly escaped
+- Separator rows match the header column count
+"""
+
+from __future__ import annotations
+
+import re
+from pathlib import Path
+
+import pytest
+
+DOCS_DIR = Path(__file__).resolve().parents[3] / "docs"
+
+DOCS_TABLE_FILES = [
+    "en/concepts/tasks.mdx",
+    "pt-BR/concepts/tasks.mdx",
+    "ko/concepts/tasks.mdx",
+]
+
+
+def _split_table_row(line: str) -> list[str]:
+    """Split a markdown table row on unescaped pipe characters.
+
+    Escaped pipes (``\\|``) are preserved as literal ``|`` inside cells.
+    """
+    cells = re.split(r"(?<!\\)\|", line)
+    return [cell.replace("\\|", "|").strip() for cell in cells]
+
+
+def _parse_markdown_tables(content: str) -> list[tuple[int, list[list[str]]]]:
+    """Parse all markdown tables from content.
+
+    Returns a list of (start_line_number, table_rows) tuples.
+    Each table_rows is a list of rows, where each row is a list of cell values.
+    """
+    lines = content.split("\n")
+    tables: list[tuple[int, list[list[str]]]] = []
+    current_table: list[list[str]] = []
+    table_start = 0
+
+    for i, line in enumerate(lines):
+        stripped = line.strip()
+        if stripped.startswith("|") and stripped.endswith("|"):
+            if not current_table:
+                table_start = i + 1
+            cells = _split_table_row(stripped)
+            cells = cells[1:-1]
+            current_table.append(cells)
+        else:
+            if current_table:
+                tables.append((table_start, current_table))
+                current_table = []
+
+    if current_table:
+        tables.append((table_start, current_table))
+
+    return tables
+
+
+def _is_separator_row(cells: list[str]) -> bool:
+    """Check if a row is a table separator (e.g., | :--- | :--- |)."""
+    return all(re.match(r"^:?-+:?$", cell.strip()) for cell in cells if cell.strip())
+
+
+@pytest.mark.parametrize("doc_path", DOCS_TABLE_FILES)
+def test_markdown_tables_have_consistent_columns(doc_path: str) -> None:
+    """Verify all rows in each markdown table have the same number of columns."""
+    full_path = DOCS_DIR / doc_path
+    if not full_path.exists():
+        pytest.skip(f"Doc file not found: {full_path}")
+
+    content = full_path.read_text(encoding="utf-8")
+    tables = _parse_markdown_tables(content)
+
+    for table_start, rows in tables:
+        if len(rows) < 2:
+            continue
+        header_col_count = len(rows[0])
+        for row_idx, row in enumerate(rows[1:], start=1):
+            assert len(row) == header_col_count, (
+                f"Table at line {table_start} in {doc_path}: "
+                f"row {row_idx + 1} has {len(row)} columns, expected {header_col_count}. "
+                f"Row content: {'|'.join(row)}"
+            )
+
+
+@pytest.mark.parametrize("doc_path", DOCS_TABLE_FILES)
+def test_task_attributes_table_has_no_unescaped_pipes_in_cells(doc_path: str) -> None:
+    """Verify the Task Attributes table doesn't have unescaped pipe chars in cells.
+
+    The '|' character is the column delimiter in markdown tables. If a type
+    annotation like `List[Callable] | List[str]` contains an unescaped pipe,
+    it will be interpreted as a column separator and break the table layout.
+    """
+    full_path = DOCS_DIR / doc_path
+    if not full_path.exists():
+        pytest.skip(f"Doc file not found: {full_path}")
+
+    content = full_path.read_text(encoding="utf-8")
+    lines = content.split("\n")
+
+    in_task_attrs = False
+    for i, line in enumerate(lines):
+        if "## Task Attributes" in line or "## Atributos da Tarefa" in line:
+            in_task_attrs = True
+            continue
+
+        if in_task_attrs and line.startswith("##"):
+            break
+
+        if in_task_attrs and line.strip().startswith("|") and line.strip().endswith("|"):
+            stripped = line.strip()
+            cells = stripped.split("|")
+            cells = cells[1:-1]
+
+            if _is_separator_row(cells):
+                continue
+
+            for cell_idx, cell in enumerate(cells):
+                unescaped_pipes = re.findall(r"(?<!\\)\|", cell)
+                assert not unescaped_pipes, (
+                    f"Line {i + 1} in {doc_path}, cell {cell_idx + 1}: "
+                    f"found unescaped pipe character in cell content: '{cell.strip()}'. "
+                    f"Use '\\|' to escape pipe characters inside table cells."
+                )
+
+
+@pytest.mark.parametrize("doc_path", DOCS_TABLE_FILES)
+def test_task_attributes_table_separator_matches_header(doc_path: str) -> None:
+    """Verify the separator row has the same number of columns as the header."""
+    full_path = DOCS_DIR / doc_path
+    if not full_path.exists():
+        pytest.skip(f"Doc file not found: {full_path}")
+
+    content = full_path.read_text(encoding="utf-8")
+    tables = _parse_markdown_tables(content)
+
+    for table_start, rows in tables:
+        if len(rows) < 2:
+            continue
+
+        header = rows[0]
+        separator = rows[1]
+
+        if _is_separator_row(separator):
+            assert len(separator) == len(header), (
+                f"Table at line {table_start} in {doc_path}: "
+                f"separator has {len(separator)} columns but header has {len(header)}. "
+                f"This usually means the header or separator row has extra '|' delimiters."
+            )

lib/devtools/pyproject.toml

@@ -6,7 +6,7 @@ readme = "README.md"
 authors = [
     { name = "Greyson R. LaLonde", email = "greyson@crewai.com" },
 ]
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.10, <3.14"
 classifiers = ["Private :: Do Not Upload"]
 private = true
 dependencies = [

pyproject.toml

@@ -1,7 +1,7 @@
 name = "crewai-workspace"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.10,<3.14"
 authors = [
     { name = "Joao Moura", email = "joao@crewai.com" }
 ]
@@ -143,11 +143,6 @@ python_classes = "Test*"
 python_functions = "test_*"
 
 
-[tool.uv]
-constraint-dependencies = [
-    "onnxruntime<1.24; python_version < '3.11'",
-]
-
 [tool.uv.workspace]
 members = [
     "lib/crewai",