Add explicit type annotations for agents_config and tasks_config

Fixes #3801

This commit addresses the issue where agents_config and tasks_config
in CrewBase-decorated classes lacked explicit type annotations, making
the code un-Pythonic and reducing IDE/type checker support.

Changes:
- Added AgentsConfigDict and TasksConfigDict type aliases
- Updated load_configurations to use cast() for proper typing
- Updated CrewInstance Protocol to use typed config dictionaries
- Exported type aliases from crewai.project for user convenience
- Updated TypedDicts to support both raw YAML and processed values
- Added comprehensive tests for config loading and type annotations

The type aliases allow users to import and use proper types:
  from crewai.project import AgentConfig, AgentsConfigDict

This provides better IDE autocomplete and static type checking when
accessing self.agents_config and self.tasks_config in CrewBase classes.

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

lib/crewai-tools/pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "pytube>=15.0.0",
     "requests>=2.32.5",
     "docker>=7.1.0",
-    "crewai==1.1.0",
+    "crewai==1.2.0",
     "lancedb>=0.5.4",
     "tiktoken>=0.8.0",
     "beautifulsoup4>=4.13.4",

lib/crewai-tools/src/crewai_tools/__init__.py

@@ -287,4 +287,4 @@ __all__ = [
     "ZapierActionTools",
 ]
 
-__version__ = "1.1.0"
+__version__ = "1.2.0"

lib/crewai/pyproject.toml

@@ -49,7 +49,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.1.0",
+    "crewai-tools==1.2.0",
 ]
 embeddings = [
     "tiktoken~=0.8.0"

lib/crewai/src/crewai/__init__.py

@@ -40,7 +40,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
 
 _suppress_pydantic_deprecation_warnings()
 
-__version__ = "1.1.0"
+__version__ = "1.2.0"
 _telemetry_submitted = False
 
 

lib/crewai/src/crewai/agent.py

@@ -1186,6 +1186,15 @@ class Agent(BaseAgent):
         Returns:
             LiteAgentOutput: The result of the agent execution.
         """
+        if self.apps:
+            platform_tools = self.get_platform_tools(self.apps)
+            if platform_tools:
+                self.tools.extend(platform_tools)
+        if self.mcps:
+            mcps = self.get_mcp_tools(self.mcps)
+            if mcps:
+                self.tools.extend(mcps)
+
         lite_agent = LiteAgent(
             id=self.id,
             role=self.role,

lib/crewai/src/crewai/cli/constants.py

@@ -322,7 +322,7 @@ MODELS = {
     ],
 }
 
-DEFAULT_LLM_MODEL = "gpt-4o-mini"
+DEFAULT_LLM_MODEL = "gpt-4.1-mini"
 
 JSON_URL = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
 

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

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.1.0"
+    "crewai[tools]==1.2.0"
 ]
 
 [project.scripts]

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

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.1.0"
+    "crewai[tools]==1.2.0"
 ]
 
 [project.scripts]

lib/crewai/src/crewai/flow/flow_visualizer.py

@@ -2,7 +2,7 @@
 from __future__ import annotations
 
 import os
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
 
 from pyvis.network import Network  # type: ignore[import-untyped]
 
@@ -29,7 +29,7 @@ _printer = Printer()
 class FlowPlot:
     """Handles the creation and rendering of flow visualization diagrams."""
 
-    def __init__(self, flow: Flow) -> None:
+    def __init__(self, flow: Flow[Any]) -> None:
         """
         Initialize FlowPlot with a flow object.
 
@@ -136,7 +136,7 @@ class FlowPlot:
                 f"Unexpected error during flow visualization: {e!s}"
             ) from e
         finally:
-            self._cleanup_pyvis_lib()
+            self._cleanup_pyvis_lib(filename)
 
     def _generate_final_html(self, network_html: str) -> str:
         """
@@ -186,26 +186,33 @@ class FlowPlot:
             raise IOError(f"Failed to generate visualization HTML: {e!s}") from e
 
     @staticmethod
-    def _cleanup_pyvis_lib() -> None:
+    def _cleanup_pyvis_lib(filename: str) -> None:
         """
         Clean up the generated lib folder from pyvis.
 
         This method safely removes the temporary lib directory created by pyvis
-        during network visualization generation.
+        during network visualization generation. The lib folder is created in the
+        same directory as the output HTML file.
+
+        Parameters
+        ----------
+        filename : str
+            The output filename (without .html extension) used for the visualization.
         """
         try:
-            lib_folder = safe_path_join("lib", root=os.getcwd())
-            if os.path.exists(lib_folder) and os.path.isdir(lib_folder):
-                import shutil
+            import shutil
 
-                shutil.rmtree(lib_folder)
-        except ValueError as e:
-            _printer.print(f"Error validating lib folder path: {e}", color="red")
+            output_dir = os.path.dirname(os.path.abspath(filename)) or os.getcwd()
+            lib_folder = os.path.join(output_dir, "lib")
+            if os.path.exists(lib_folder) and os.path.isdir(lib_folder):
+                vis_js = os.path.join(lib_folder, "vis-network.min.js")
+                if os.path.exists(vis_js):
+                    shutil.rmtree(lib_folder)
         except Exception as e:
             _printer.print(f"Error cleaning up lib folder: {e}", color="red")
 
 
-def plot_flow(flow: Flow, filename: str = "flow_plot") -> None:
+def plot_flow(flow: Flow[Any], filename: str = "flow_plot") -> None:
     """
     Convenience function to create and save a flow visualization.
 

lib/crewai/src/crewai/flow/html_template_handler.py

@@ -1,5 +1,8 @@
+"""HTML template processing and generation for flow visualization diagrams."""
+
 import base64
 import re
+from typing import Any
 
 from crewai.flow.path_utils import validate_path_exists
 
@@ -7,7 +10,7 @@ from crewai.flow.path_utils import validate_path_exists
 class HTMLTemplateHandler:
     """Handles HTML template processing and generation for flow visualization diagrams."""
 
-    def __init__(self, template_path, logo_path):
+    def __init__(self, template_path: str, logo_path: str) -> None:
         """
         Initialize HTMLTemplateHandler with validated template and logo paths.
 
@@ -29,23 +32,23 @@ class HTMLTemplateHandler:
         except ValueError as e:
             raise ValueError(f"Invalid template or logo path: {e}") from e
 
-    def read_template(self):
+    def read_template(self) -> str:
         """Read and return the HTML template file contents."""
         with open(self.template_path, "r", encoding="utf-8") as f:
             return f.read()
 
-    def encode_logo(self):
+    def encode_logo(self) -> str:
         """Convert the logo SVG file to base64 encoded string."""
         with open(self.logo_path, "rb") as logo_file:
             logo_svg_data = logo_file.read()
             return base64.b64encode(logo_svg_data).decode("utf-8")
 
-    def extract_body_content(self, html):
+    def extract_body_content(self, html: str) -> str:
         """Extract and return content between body tags from HTML string."""
         match = re.search("<body.*?>(.*?)</body>", html, re.DOTALL)
         return match.group(1) if match else ""
 
-    def generate_legend_items_html(self, legend_items):
+    def generate_legend_items_html(self, legend_items: list[dict[str, Any]]) -> str:
         """Generate HTML markup for the legend items."""
         legend_items_html = ""
         for item in legend_items:
@@ -73,7 +76,9 @@ class HTMLTemplateHandler:
                 """
         return legend_items_html
 
-    def generate_final_html(self, network_body, legend_items_html, title="Flow Plot"):
+    def generate_final_html(
+        self, network_body: str, legend_items_html: str, title: str = "Flow Plot"
+    ) -> str:
         """Combine all components into final HTML document with network visualization."""
         html_template = self.read_template()
         logo_svg_base64 = self.encode_logo()

lib/crewai/src/crewai/flow/legend_generator.py

@@ -1,4 +1,23 @@
-def get_legend_items(colors):
+"""Legend generation for flow visualization diagrams."""
+
+from typing import Any
+
+from crewai.flow.config import FlowColors
+
+
+def get_legend_items(colors: FlowColors) -> list[dict[str, Any]]:
+    """Generate legend items based on flow colors.
+
+    Parameters
+    ----------
+    colors : FlowColors
+        Dictionary containing color definitions for flow elements.
+
+    Returns
+    -------
+    list[dict[str, Any]]
+        List of legend item dictionaries with labels and styling.
+    """
     return [
         {"label": "Start Method", "color": colors["start"]},
         {"label": "Method", "color": colors["method"]},
@@ -24,7 +43,19 @@ def get_legend_items(colors):
     ]
 
 
-def generate_legend_items_html(legend_items):
+def generate_legend_items_html(legend_items: list[dict[str, Any]]) -> str:
+    """Generate HTML markup for legend items.
+
+    Parameters
+    ----------
+    legend_items : list[dict[str, Any]]
+        List of legend item dictionaries containing labels and styling.
+
+    Returns
+    -------
+    str
+        HTML string containing formatted legend items.
+    """
     legend_items_html = ""
     for item in legend_items:
         if "border" in item:

lib/crewai/src/crewai/flow/visualization_utils.py

@@ -36,28 +36,29 @@ from crewai.flow.utils import (
 from crewai.utilities.printer import Printer
 
 
-
 _printer = Printer()
 
 
 def method_calls_crew(method: Any) -> bool:
     """
-    Check if the method contains a call to `.crew()`.
+    Check if the method contains a call to `.crew()`, `.kickoff()`, or `.kickoff_async()`.
 
     Parameters
     ----------
     method : Any
-        The method to analyze for crew() calls.
+        The method to analyze for crew or agent execution calls.
 
     Returns
     -------
     bool
-        True if the method calls .crew(), False otherwise.
+        True if the method calls .crew(), .kickoff(), or .kickoff_async(), False otherwise.
 
     Notes
     -----
     Uses AST analysis to detect method calls, specifically looking for
-    attribute access of 'crew'.
+    attribute access of 'crew', 'kickoff', or 'kickoff_async'.
+    This includes both traditional Crew execution (.crew()) and Agent/LiteAgent
+    execution (.kickoff() or .kickoff_async()).
     """
     try:
         source = inspect.getsource(method)
@@ -68,14 +69,14 @@ def method_calls_crew(method: Any) -> bool:
         return False
 
     class CrewCallVisitor(ast.NodeVisitor):
-        """AST visitor to detect .crew() method calls."""
+        """AST visitor to detect .crew(), .kickoff(), or .kickoff_async() method calls."""
 
-        def __init__(self):
+        def __init__(self) -> None:
             self.found = False
 
-        def visit_Call(self, node):
+        def visit_Call(self, node: ast.Call) -> None:
             if isinstance(node.func, ast.Attribute):
-                if node.func.attr == "crew":
+                if node.func.attr in ("crew", "kickoff", "kickoff_async"):
                     self.found = True
             self.generic_visit(node)
 
@@ -113,7 +114,7 @@ def add_nodes_to_network(
     - Regular methods
     """
 
-    def human_friendly_label(method_name):
+    def human_friendly_label(method_name: str) -> str:
         return method_name.replace("_", " ").title()
 
     node_style: (

lib/crewai/src/crewai/project/__init__.py

@@ -13,11 +13,21 @@ from crewai.project.annotations import (
     task,
     tool,
 )
-from crewai.project.crew_base import CrewBase
+from crewai.project.crew_base import (
+    AgentConfig,
+    AgentsConfigDict,
+    CrewBase,
+    TaskConfig,
+    TasksConfigDict,
+)
 
 
 __all__ = [
+    "AgentConfig",
+    "AgentsConfigDict",
     "CrewBase",
+    "TaskConfig",
+    "TasksConfigDict",
     "after_kickoff",
     "agent",
     "before_kickoff",

lib/crewai/src/crewai/project/crew_base.py

@@ -52,11 +52,11 @@ class AgentConfig(TypedDict, total=False):
     allow_delegation: bool
     max_iter: int
     max_tokens: int
-    callbacks: list[str]
+    callbacks: list[str] | list[Any]
 
-    # LLM configuration
-    llm: str
-    function_calling_llm: str
+    # LLM configuration (can be string references or resolved instances)
+    llm: str | Any
+    function_calling_llm: str | Any
     use_system_prompt: bool
 
     # Template configuration
@@ -66,7 +66,7 @@ class AgentConfig(TypedDict, total=False):
 
     # Tools and handlers (can be string references or instances)
     tools: list[str] | list[BaseTool]
-    step_callback: str
+    step_callback: str | Any
     cache_handler: str | CacheHandler
 
     # Code execution
@@ -111,18 +111,18 @@ class TaskConfig(TypedDict, total=False):
     description: str
     expected_output: str
 
-    # Agent and context
-    agent: str
-    context: list[str]
+    # Agent and context (can be string references or resolved instances)
+    agent: str | Any
+    context: list[str] | list[Any]
 
     # Tools and callbacks (can be string references or instances)
     tools: list[str] | list[BaseTool]
-    callback: str
-    callbacks: list[str]
+    callback: str | Any
+    callbacks: list[str] | list[Any]
 
-    # Output configuration
-    output_json: str
-    output_pydantic: str
+    # Output configuration (can be string references or resolved class wrappers)
+    output_json: str | Any
+    output_pydantic: str | Any
     output_file: str
     create_directory: bool
 
@@ -139,6 +139,10 @@ class TaskConfig(TypedDict, total=False):
     allow_crewai_trigger_context: bool
 
 
+AgentsConfigDict = dict[str, AgentConfig]
+TasksConfigDict = dict[str, TaskConfig]
+
+
 load_dotenv()
 
 CallableT = TypeVar("CallableT", bound=Callable[..., Any])
@@ -378,8 +382,14 @@ def load_configurations(self: CrewInstance) -> None:
     Args:
         self: Crew instance with configuration paths.
     """
-    self.agents_config = self._load_config(self.original_agents_config_path, "agent")
-    self.tasks_config = self._load_config(self.original_tasks_config_path, "task")
+    self.agents_config = cast(
+        AgentsConfigDict,
+        self._load_config(self.original_agents_config_path, "agent"),
+    )
+    self.tasks_config = cast(
+        TasksConfigDict,
+        self._load_config(self.original_tasks_config_path, "task"),
+    )
 
 
 def load_yaml(config_path: Path) -> dict[str, Any]:

lib/crewai/src/crewai/project/wrappers.py

@@ -22,6 +22,12 @@ from typing_extensions import Self
 if TYPE_CHECKING:
     from crewai import Agent, Crew, Task
     from crewai.crews.crew_output import CrewOutput
+    from crewai.project.crew_base import (
+        AgentConfig,
+        AgentsConfigDict,
+        TaskConfig,
+        TasksConfigDict,
+    )
     from crewai.tools import BaseTool
 
 
@@ -75,8 +81,8 @@ class CrewInstance(Protocol):
     base_directory: Path
     original_agents_config_path: str
     original_tasks_config_path: str
-    agents_config: dict[str, Any]
-    tasks_config: dict[str, Any]
+    agents_config: AgentsConfigDict
+    tasks_config: TasksConfigDict
     mcp_server_params: Any
     mcp_connect_timeout: int
 
@@ -90,7 +96,7 @@ class CrewInstance(Protocol):
     def _map_agent_variables(
         self,
         agent_name: str,
-        agent_info: dict[str, Any],
+        agent_info: AgentConfig,
         llms: dict[str, Callable[..., Any]],
         tool_functions: dict[str, Callable[..., Any]],
         cache_handler_functions: dict[str, Callable[..., Any]],
@@ -99,7 +105,7 @@ class CrewInstance(Protocol):
     def _map_task_variables(
         self,
         task_name: str,
-        task_info: dict[str, Any],
+        task_info: TaskConfig,
         agents: dict[str, Callable[..., Any]],
         tasks: dict[str, Callable[..., Any]],
         output_json_functions: dict[str, Callable[..., Any]],

lib/crewai/src/crewai/utilities/agent_utils.py

@@ -419,7 +419,7 @@ def handle_context_length(
         i18n: I18N instance for messages
 
     Raises:
-        LLMContextLengthExceededError: If context length is exceeded and user opts not to summarize
+        SystemExit: If context length is exceeded and user opts not to summarize
     """
     if respect_context_window:
         printer.print(
@@ -432,7 +432,7 @@ def handle_context_length(
             content="Context length exceeded. Consider using smaller text or RAG tools from crewai_tools.",
             color="red",
         )
-        raise LLMContextLengthExceededError(
+        raise SystemExit(
             "Context length exceeded and user opted not to summarize. Consider using smaller text or RAG tools from crewai_tools."
         )
 

lib/crewai/src/crewai/utilities/llm_utils.py

@@ -29,8 +29,8 @@ def create_llm(
         try:
             return LLM(model=llm_value)
         except Exception as e:
-            logger.debug(f"Failed to instantiate LLM with model='{llm_value}': {e}")
-            return None
+            logger.error(f"Error instantiating LLM from string: {e}")
+            raise e
 
     if llm_value is None:
         return _llm_via_environment_or_fallback()
@@ -62,8 +62,8 @@ def create_llm(
         )
 
     except Exception as e:
-        logger.debug(f"Error instantiating LLM from unknown object type: {e}")
-        return None
+        logger.error(f"Error instantiating LLM from unknown object type: {e}")
+        raise e
 
 
 UNACCEPTED_ATTRIBUTES: Final[list[str]] = [
@@ -176,10 +176,10 @@ def _llm_via_environment_or_fallback() -> LLM | None:
     try:
         return LLM(**llm_params)
     except Exception as e:
-        logger.debug(
+        logger.error(
             f"Error instantiating LLM from environment/fallback: {type(e).__name__}: {e}"
         )
-        return None
+        raise e
 
 
 def _normalize_key_name(key_name: str) -> str:

lib/crewai/tests/agents/test_agent.py

@@ -6,6 +6,7 @@ from unittest import mock
 from unittest.mock import MagicMock, patch
 
 from crewai.agents.crew_agent_executor import AgentFinish, CrewAgentExecutor
+from crewai.cli.constants import DEFAULT_LLM_MODEL
 from crewai.events.event_bus import crewai_event_bus
 from crewai.events.types.tool_usage_events import ToolUsageFinishedEvent
 from crewai.knowledge.knowledge import Knowledge
@@ -18,9 +19,6 @@ from crewai.process import Process
 from crewai.tools.tool_calling import InstructorToolCalling
 from crewai.tools.tool_usage import ToolUsage
 from crewai.utilities.errors import AgentRepositoryError
-from crewai.utilities.exceptions.context_window_exceeding_exception import (
-    LLMContextLengthExceededError,
-)
 import pytest
 
 from crewai import Agent, Crew, Task
@@ -138,7 +136,7 @@ def test_agent_with_missing_response_template():
 
 def test_agent_default_values():
     agent = Agent(role="test role", goal="test goal", backstory="test backstory")
-    assert agent.llm.model == "gpt-4o-mini"
+    assert agent.llm.model == DEFAULT_LLM_MODEL
     assert agent.allow_delegation is False
 
 
@@ -228,7 +226,7 @@ def test_logging_tool_usage():
         verbose=True,
     )
 
-    assert agent.llm.model == "gpt-4o-mini"
+    assert agent.llm.model == DEFAULT_LLM_MODEL
     assert agent.tools_handler.last_used_tool is None
     task = Task(
         description="What is 3 times 4?",

lib/crewai/tests/agents/test_lite_agent.py

@@ -591,3 +591,81 @@ def test_lite_agent_with_invalid_llm():
                 llm="invalid-model",
             )
         assert "Expected LLM instance of type BaseLLM" in str(exc_info.value)
+
+
+@patch.dict("os.environ", {"CREWAI_PLATFORM_INTEGRATION_TOKEN": "test_token"})
+@patch("crewai_tools.tools.crewai_platform_tools.crewai_platform_tool_builder.requests.get")
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_kickoff_with_platform_tools(mock_get):
+    """Test that Agent.kickoff() properly integrates platform tools with LiteAgent"""
+    mock_response = Mock()
+    mock_response.raise_for_status.return_value = None
+    mock_response.json.return_value = {
+        "actions": {
+            "github": [
+                {
+                    "name": "create_issue",
+                    "description": "Create a GitHub issue",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "title": {"type": "string", "description": "Issue title"},
+                            "body": {"type": "string", "description": "Issue body"},
+                        },
+                        "required": ["title"],
+                    },
+                }
+            ]
+        }
+    }
+    mock_get.return_value = mock_response
+
+    agent = Agent(
+        role="Test Agent",
+        goal="Test goal",
+        backstory="Test backstory",
+        llm=LLM(model="gpt-3.5-turbo"),
+        apps=["github"],
+        verbose=True
+    )
+
+    result = agent.kickoff("Create a GitHub issue")
+
+    assert isinstance(result, LiteAgentOutput)
+    assert result.raw is not None
+
+
+@patch.dict("os.environ", {"EXA_API_KEY": "test_exa_key"})
+@patch("crewai.agent.Agent._get_external_mcp_tools")
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_kickoff_with_mcp_tools(mock_get_mcp_tools):
+    """Test that Agent.kickoff() properly integrates MCP tools with LiteAgent"""
+    # Setup mock MCP tools - create a proper BaseTool instance
+    class MockMCPTool(BaseTool):
+        name: str = "exa_search"
+        description: str = "Search the web using Exa"
+
+        def _run(self, query: str) -> str:
+            return f"Mock search results for: {query}"
+
+    mock_get_mcp_tools.return_value = [MockMCPTool()]
+
+    # Create agent with MCP servers
+    agent = Agent(
+        role="Test Agent",
+        goal="Test goal",
+        backstory="Test backstory",
+        llm=LLM(model="gpt-3.5-turbo"),
+        mcps=["https://mcp.exa.ai/mcp?api_key=test_exa_key&profile=research"],
+        verbose=True
+    )
+
+    # Execute kickoff
+    result = agent.kickoff("Search for information about AI")
+
+    # Verify the result is a LiteAgentOutput
+    assert isinstance(result, LiteAgentOutput)
+    assert result.raw is not None
+
+    # Verify MCP tools were retrieved
+    mock_get_mcp_tools.assert_called_once_with("https://mcp.exa.ai/mcp?api_key=test_exa_key&profile=research")

lib/crewai/tests/cassettes/test_agent_kickoff_with_mcp_tools.yaml

@@ -0,0 +1,244 @@
+interactions:
+- request:
+    body: '{"messages": [{"role": "system", "content": "You are Test Agent. Test backstory\nYour
+      personal goal is: Test goal\n\nYou ONLY have access to the following tools,
+      and should NEVER make up tools that are not listed here:\n\nTool Name: exa_search\nTool
+      Arguments: {''query'': {''description'': None, ''type'': ''str''}}\nTool Description:
+      Search the web using Exa\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought:
+      you should always think about what to do\nAction: the action to take, only one
+      name of [exa_search], just the name, exactly as it''s written.\nAction Input:
+      the input to the action, just a simple JSON object, enclosed in curly braces,
+      using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce
+      all necessary information is gathered, return the following format:\n\n```\nThought:
+      I now know the final answer\nFinal Answer: the final answer to the original
+      input question\n```"}, {"role": "user", "content": "Search for information about
+      AI"}], "model": "gpt-3.5-turbo", "stream": false}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate
+      connection:
+      - keep-alive
+      content-length:
+      - '1038'
+      content-type:
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lib/crewai/tests/cassettes/test_agent_kickoff_with_platform_tools.yaml

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+      Arguments: {''title'': {''description'': ''Issue title'', ''type'': ''str''},
+      ''body'': {''description'': ''Issue body'', ''type'': ''Union[str, NoneType]''}}\nTool
+      Description: Create a GitHub issue\nDetailed Parameter Structure:\nObject with
+      properties:\n  - title: Issue title (required)\n  - body: Issue body (optional)\n\nIMPORTANT:
+      Use the following format in your response:\n\n```\nThought: you should always
+      think about what to do\nAction: the action to take, only one name of [create_issue],
+      just the name, exactly as it''s written.\nAction Input: the input to the action,
+      just a simple JSON object, enclosed in curly braces, using \" to wrap keys and
+      values.\nObservation: the result of the action\n```\n\nOnce all necessary information
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lib/crewai/tests/project/test_crew_base_configs.py

@@ -0,0 +1,193 @@
+"""Tests for CrewBase configuration type annotations."""
+
+from pathlib import Path
+
+import pytest
+
+from crewai.project import AgentConfig, AgentsConfigDict, CrewBase, TaskConfig, TasksConfigDict, agent, task
+
+
+def test_agents_config_loads_as_dict(tmp_path: Path) -> None:
+    """Test that agents_config loads as a properly typed dictionary."""
+    agents_yaml = tmp_path / "agents.yaml"
+    agents_yaml.write_text(
+        """
+researcher:
+  role: "Research Analyst"
+  goal: "Find accurate information"
+  backstory: "Expert researcher with years of experience"
+"""
+    )
+
+    tasks_yaml = tmp_path / "tasks.yaml"
+    tasks_yaml.write_text(
+        """
+research_task:
+  description: "Research the topic"
+  expected_output: "A comprehensive report"
+"""
+    )
+
+    @CrewBase
+    class TestCrew:
+        agents_config = str(agents_yaml)
+        tasks_config = str(tasks_yaml)
+
+        @agent
+        def researcher(self):
+            from crewai import Agent
+            return Agent(config=self.agents_config["researcher"])
+
+        @task
+        def research_task(self):
+            from crewai import Task
+            return Task(config=self.tasks_config["research_task"])
+
+    crew_instance = TestCrew()
+
+    assert isinstance(crew_instance.agents_config, dict)
+    assert "researcher" in crew_instance.agents_config
+    assert crew_instance.agents_config["researcher"]["role"] == "Research Analyst"
+    assert crew_instance.agents_config["researcher"]["goal"] == "Find accurate information"
+    assert crew_instance.agents_config["researcher"]["backstory"] == "Expert researcher with years of experience"
+
+
+def test_tasks_config_loads_as_dict(tmp_path: Path) -> None:
+    """Test that tasks_config loads as a properly typed dictionary."""
+    agents_yaml = tmp_path / "agents.yaml"
+    agents_yaml.write_text(
+        """
+writer:
+  role: "Content Writer"
+  goal: "Write engaging content"
+  backstory: "Experienced content writer"
+"""
+    )
+
+    tasks_yaml = tmp_path / "tasks.yaml"
+    tasks_yaml.write_text(
+        """
+writing_task:
+  description: "Write an article"
+  expected_output: "A well-written article"
+  agent: "writer"
+"""
+    )
+
+    @CrewBase
+    class TestCrew:
+        agents_config = str(agents_yaml)
+        tasks_config = str(tasks_yaml)
+
+        @agent
+        def writer(self):
+            from crewai import Agent
+            return Agent(config=self.agents_config["writer"])
+
+        @task
+        def writing_task(self):
+            from crewai import Task
+            return Task(config=self.tasks_config["writing_task"])
+
+    crew_instance = TestCrew()
+
+    assert isinstance(crew_instance.tasks_config, dict)
+    assert "writing_task" in crew_instance.tasks_config
+    assert crew_instance.tasks_config["writing_task"]["description"] == "Write an article"
+    assert crew_instance.tasks_config["writing_task"]["expected_output"] == "A well-written article"
+    
+    from crewai import Agent
+    assert isinstance(crew_instance.tasks_config["writing_task"]["agent"], Agent)
+    assert crew_instance.tasks_config["writing_task"]["agent"].role == "Content Writer"
+
+
+def test_empty_config_files_load_as_empty_dicts(tmp_path: Path) -> None:
+    """Test that empty config files load as empty dictionaries."""
+    agents_yaml = tmp_path / "agents.yaml"
+    agents_yaml.write_text("")
+
+    tasks_yaml = tmp_path / "tasks.yaml"
+    tasks_yaml.write_text("")
+
+    @CrewBase
+    class TestCrew:
+        agents_config = str(agents_yaml)
+        tasks_config = str(tasks_yaml)
+
+    crew_instance = TestCrew()
+
+    assert isinstance(crew_instance.agents_config, dict)
+    assert isinstance(crew_instance.tasks_config, dict)
+    assert len(crew_instance.agents_config) == 0
+    assert len(crew_instance.tasks_config) == 0
+
+
+def test_missing_config_files_load_as_empty_dicts(tmp_path: Path) -> None:
+    """Test that missing config files load as empty dictionaries with warning."""
+    nonexistent_agents = tmp_path / "nonexistent_agents.yaml"
+    nonexistent_tasks = tmp_path / "nonexistent_tasks.yaml"
+
+    @CrewBase
+    class TestCrew:
+        agents_config = str(nonexistent_agents)
+        tasks_config = str(nonexistent_tasks)
+
+    crew_instance = TestCrew()
+
+    assert isinstance(crew_instance.agents_config, dict)
+    assert isinstance(crew_instance.tasks_config, dict)
+    assert len(crew_instance.agents_config) == 0
+    assert len(crew_instance.tasks_config) == 0
+
+
+def test_config_types_are_exported() -> None:
+    """Test that AgentConfig, TaskConfig, and type aliases are properly exported."""
+    from crewai.project import AgentConfig, AgentsConfigDict, TaskConfig, TasksConfigDict
+
+    assert AgentConfig is not None
+    assert TaskConfig is not None
+    assert AgentsConfigDict is not None
+    assert TasksConfigDict is not None
+
+
+def test_agents_config_type_annotation_exists(tmp_path: Path) -> None:
+    """Test that agents_config has proper type annotation at runtime."""
+    agents_yaml = tmp_path / "agents.yaml"
+    agents_yaml.write_text(
+        """
+analyst:
+  role: "Data Analyst"
+  goal: "Analyze data"
+"""
+    )
+
+    tasks_yaml = tmp_path / "tasks.yaml"
+    tasks_yaml.write_text(
+        """
+analysis:
+  description: "Analyze the data"
+  expected_output: "Analysis report"
+"""
+    )
+
+    @CrewBase
+    class TestCrew:
+        agents_config = str(agents_yaml)
+        tasks_config = str(tasks_yaml)
+
+        @agent
+        def analyst(self):
+            from crewai import Agent
+            return Agent(config=self.agents_config["analyst"])
+
+        @task
+        def analysis(self):
+            from crewai import Task
+            return Task(config=self.tasks_config["analysis"])
+
+    crew_instance = TestCrew()
+
+    assert hasattr(crew_instance, "agents_config")
+    assert hasattr(crew_instance, "tasks_config")
+    assert isinstance(crew_instance.agents_config, dict)
+    assert isinstance(crew_instance.tasks_config, dict)

lib/crewai/tests/test_flow.py

@@ -850,6 +850,31 @@ def test_flow_plotting():
     assert isinstance(received_events[0].timestamp, datetime)
 
 
+def test_method_calls_crew_detection():
+    """Test that method_calls_crew() detects .crew(), .kickoff(), and .kickoff_async() calls."""
+    from crewai.flow.visualization_utils import method_calls_crew
+    from crewai import Agent
+
+    # Test with a real Flow that uses agent.kickoff()
+    class FlowWithAgentKickoff(Flow):
+        @start()
+        def run_agent(self):
+            agent = Agent(role="test", goal="test", backstory="test")
+            return agent.kickoff("query")
+
+    flow = FlowWithAgentKickoff()
+    assert method_calls_crew(flow.run_agent) is True
+
+    # Test with a Flow that has no crew/agent calls
+    class FlowWithoutCrewCalls(Flow):
+        @start()
+        def simple_method(self):
+            return "Just a regular method"
+
+    flow2 = FlowWithoutCrewCalls()
+    assert method_calls_crew(flow2.simple_method) is False
+
+
 def test_multiple_routers_from_same_trigger():
     """Test that multiple routers triggered by the same method all activate their listeners."""
     execution_order = []

lib/crewai/tests/utilities/test_agent_utils.py

@@ -1,145 +0,0 @@
-"""Test agent utility functions."""
-
-import pytest
-from unittest.mock import MagicMock, patch
-
-from crewai.agent import Agent
-from crewai.utilities.agent_utils import handle_context_length
-from crewai.utilities.exceptions.context_window_exceeding_exception import (
-    LLMContextLengthExceededError,
-)
-from crewai.utilities.i18n import I18N
-from crewai.utilities.printer import Printer
-
-
-def test_handle_context_length_raises_exception_when_respect_context_window_false():
-    """Test that handle_context_length raises LLMContextLengthExceededError when respect_context_window is False."""
-    # Create mocks for dependencies
-    printer = Printer()
-    i18n = I18N()
-
-    # Create an agent just for its LLM
-    agent = Agent(
-        role="test role",
-        goal="test goal",
-        backstory="test backstory",
-        respect_context_window=False,
-    )
-
-    llm = agent.llm
-
-    # Create test messages
-    messages = [
-        {
-            "role": "user",
-            "content": "This is a test message that would exceed context length",
-        }
-    ]
-
-    # Set up test parameters
-    respect_context_window = False
-    callbacks = []
-
-    with pytest.raises(LLMContextLengthExceededError) as excinfo:
-        handle_context_length(
-            respect_context_window=respect_context_window,
-            printer=printer,
-            messages=messages,
-            llm=llm,
-            callbacks=callbacks,
-            i18n=i18n,
-        )
-
-    assert "Context length exceeded" in str(excinfo.value)
-    assert "user opted not to summarize" in str(excinfo.value)
-
-
-def test_handle_context_length_summarizes_when_respect_context_window_true():
-    """Test that handle_context_length calls summarize_messages when respect_context_window is True."""
-    # Create mocks for dependencies
-    printer = Printer()
-    i18n = I18N()
-
-    # Create an agent just for its LLM
-    agent = Agent(
-        role="test role",
-        goal="test goal",
-        backstory="test backstory",
-        respect_context_window=True,
-    )
-
-    llm = agent.llm
-
-    # Create test messages
-    messages = [
-        {
-            "role": "user",
-            "content": "This is a test message that would exceed context length",
-        }
-    ]
-
-    # Set up test parameters
-    respect_context_window = True
-    callbacks = []
-
-    with patch("crewai.utilities.agent_utils.summarize_messages") as mock_summarize:
-        handle_context_length(
-            respect_context_window=respect_context_window,
-            printer=printer,
-            messages=messages,
-            llm=llm,
-            callbacks=callbacks,
-            i18n=i18n,
-        )
-
-        mock_summarize.assert_called_once_with(
-            messages=messages, llm=llm, callbacks=callbacks, i18n=i18n
-        )
-
-
-def test_handle_context_length_does_not_raise_system_exit():
-    """Test that handle_context_length does NOT raise SystemExit (regression test for issue #3774)."""
-    # Create mocks for dependencies
-    printer = Printer()
-    i18n = I18N()
-
-    # Create an agent just for its LLM
-    agent = Agent(
-        role="test role",
-        goal="test goal",
-        backstory="test backstory",
-        respect_context_window=False,
-    )
-
-    llm = agent.llm
-
-    # Create test messages
-    messages = [
-        {
-            "role": "user",
-            "content": "This is a test message that would exceed context length",
-        }
-    ]
-
-    # Set up test parameters
-    respect_context_window = False
-    callbacks = []
-
-    with pytest.raises(Exception) as excinfo:
-        handle_context_length(
-            respect_context_window=respect_context_window,
-            printer=printer,
-            messages=messages,
-            llm=llm,
-            callbacks=callbacks,
-            i18n=i18n,
-        )
-
-    assert not isinstance(excinfo.value, SystemExit), (
-        "handle_context_length should not raise SystemExit. "
-        "It should raise LLMContextLengthExceededError instead."
-    )
-
-    assert isinstance(excinfo.value, LLMContextLengthExceededError), (
-        f"Expected LLMContextLengthExceededError but got {type(excinfo.value).__name__}"
-    )

lib/crewai/tests/utilities/test_llm_utils.py

@@ -1,77 +1,79 @@
 import os
+from typing import Any
 from unittest.mock import patch
 
+from crewai.cli.constants import DEFAULT_LLM_MODEL
 from crewai.llm import LLM
 from crewai.llms.base_llm import BaseLLM
 from crewai.utilities.llm_utils import create_llm
 import pytest
 
 
-try:
-    from litellm.exceptions import BadRequestError
-except ImportError:
-    BadRequestError = Exception
-
-
-def test_create_llm_with_llm_instance():
-    existing_llm = LLM(model="gpt-4o")
-    llm = create_llm(llm_value=existing_llm)
-    assert llm is existing_llm
-
-
-def test_create_llm_with_valid_model_string():
-    llm = create_llm(llm_value="gpt-4o")
-    assert isinstance(llm, BaseLLM)
-    assert llm.model == "gpt-4o"
-
-
-def test_create_llm_with_invalid_model_string():
-    # For invalid model strings, create_llm succeeds but call() fails with API error
-    llm = create_llm(llm_value="invalid-model")
-    assert llm is not None
-    assert isinstance(llm, BaseLLM)
-
-    # The error should occur when making the actual API call
-    # We expect some kind of API error (NotFoundError, etc.)
-    with pytest.raises(Exception):  # noqa: B017
-        llm.call(messages=[{"role": "user", "content": "Hello, world!"}])
-
-
-def test_create_llm_with_unknown_object_missing_attributes():
-    class UnknownObject:
-        pass
-
-    unknown_obj = UnknownObject()
-    llm = create_llm(llm_value=unknown_obj)
-
-    # Should succeed because str(unknown_obj) provides a model name
-    assert llm is not None
-    assert isinstance(llm, BaseLLM)
-
-
-def test_create_llm_with_none_uses_default_model():
+def test_create_llm_with_llm_instance() -> None:
     with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True):
-        with patch("crewai.utilities.llm_utils.DEFAULT_LLM_MODEL", "gpt-4o-mini"):
+        existing_llm = LLM(model="gpt-4o")
+        llm = create_llm(llm_value=existing_llm)
+        assert llm is existing_llm
+
+
+def test_create_llm_with_valid_model_string() -> None:
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True):
+        llm = create_llm(llm_value="gpt-4o")
+        assert isinstance(llm, BaseLLM)
+        assert llm.model == "gpt-4o"
+
+
+def test_create_llm_with_invalid_model_string() -> None:
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True):
+        # For invalid model strings, create_llm succeeds but call() fails with API error
+        llm = create_llm(llm_value="invalid-model")
+        assert llm is not None
+        assert isinstance(llm, BaseLLM)
+
+        # The error should occur when making the actual API call
+        # We expect some kind of API error (NotFoundError, etc.)
+        with pytest.raises(Exception):  # noqa: B017
+            llm.call(messages=[{"role": "user", "content": "Hello, world!"}])
+
+
+def test_create_llm_with_unknown_object_missing_attributes() -> None:
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True):
+        class UnknownObject:
+            pass
+
+        unknown_obj = UnknownObject()
+        llm = create_llm(llm_value=unknown_obj)
+
+        # Should succeed because str(unknown_obj) provides a model name
+        assert llm is not None
+        assert isinstance(llm, BaseLLM)
+
+
+def test_create_llm_with_none_uses_default_model() -> None:
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True):
+        with patch("crewai.utilities.llm_utils.DEFAULT_LLM_MODEL", DEFAULT_LLM_MODEL):
             llm = create_llm(llm_value=None)
             assert isinstance(llm, BaseLLM)
-            assert llm.model == "gpt-4o-mini"
+            assert llm.model == DEFAULT_LLM_MODEL
 
 
-def test_create_llm_with_unknown_object():
-    class UnknownObject:
-        model_name = "gpt-4o"
-        temperature = 0.7
-        max_tokens = 1500
+def test_create_llm_with_unknown_object() -> None:
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True):
+        class UnknownObject:
+            model_name = "gpt-4o"
+            temperature = 0.7
+            max_tokens = 1500
 
-    unknown_obj = UnknownObject()
-    llm = create_llm(llm_value=unknown_obj)
-    assert isinstance(llm, BaseLLM)
-    assert llm.model == "gpt-4o"
-    assert llm.temperature == 0.7
-    assert llm.max_tokens == 1500
+        unknown_obj = UnknownObject()
+        llm = create_llm(llm_value=unknown_obj)
+        assert isinstance(llm, BaseLLM)
+        assert llm.model == "gpt-4o"
+        assert llm.temperature == 0.7
+        if hasattr(llm, 'max_tokens'):
+            assert llm.max_tokens == 1500
 
 
-def test_create_llm_from_env_with_unaccepted_attributes():
+def test_create_llm_from_env_with_unaccepted_attributes() -> None:
     with patch.dict(
         os.environ,
         {
@@ -90,25 +92,47 @@ def test_create_llm_from_env_with_unaccepted_attributes():
         assert not hasattr(llm, "AWS_REGION_NAME")
 
 
-def test_create_llm_with_partial_attributes():
-    class PartialAttributes:
-        model_name = "gpt-4o"
-        # temperature is missing
+def test_create_llm_with_partial_attributes() -> None:
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True):
+        class PartialAttributes:
+            model_name = "gpt-4o"
+            # temperature is missing
 
-    obj = PartialAttributes()
-    llm = create_llm(llm_value=obj)
-    assert isinstance(llm, BaseLLM)
-    assert llm.model == "gpt-4o"
-    assert llm.temperature is None  # Should handle missing attributes gracefully
+        obj = PartialAttributes()
+        llm = create_llm(llm_value=obj)
+        assert isinstance(llm, BaseLLM)
+        assert llm.model == "gpt-4o"
+        assert llm.temperature is None  # Should handle missing attributes gracefully
 
 
-def test_create_llm_with_invalid_type():
-    # For integers, create_llm succeeds because str(42) becomes "42"
-    llm = create_llm(llm_value=42)
-    assert llm is not None
-    assert isinstance(llm, BaseLLM)
-    assert llm.model == "42"
+def test_create_llm_with_invalid_type() -> None:
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "fake-key"}, clear=True):
+        # For integers, create_llm succeeds because str(42) becomes "42"
+        llm = create_llm(llm_value=42)
+        assert llm is not None
+        assert isinstance(llm, BaseLLM)
+        assert llm.model == "42"
 
-    # The error should occur when making the actual API call
-    with pytest.raises(Exception):  # noqa: B017
-        llm.call(messages=[{"role": "user", "content": "Hello, world!"}])
+        # The error should occur when making the actual API call
+        with pytest.raises(Exception):  # noqa: B017
+            llm.call(messages=[{"role": "user", "content": "Hello, world!"}])
+
+
+def test_create_llm_openai_missing_api_key() -> None:
+    """Test that create_llm raises error when OpenAI API key is missing"""
+    with patch.dict(os.environ, {}, clear=True):
+        with pytest.raises((ValueError, ImportError)) as exc_info:
+            create_llm(llm_value="gpt-4o")
+
+        error_message = str(exc_info.value).lower()
+        assert "openai_api_key" in error_message or "api_key" in error_message
+
+
+def test_create_llm_anthropic_missing_dependency() -> None:
+    """Test that create_llm raises error when Anthropic dependency is missing"""
+    with patch.dict(os.environ, {"ANTHROPIC_API_KEY": "fake-key"}, clear=True):
+        with patch("crewai.llm.LLM.__new__", side_effect=ImportError('Anthropic native provider not available, to install: uv add "crewai[anthropic]"')):
+            with pytest.raises(ImportError) as exc_info:
+                create_llm(llm_value="anthropic/claude-3-sonnet")
+
+            assert "Anthropic native provider not available, to install: uv add \"crewai[anthropic]\"" in str(exc_info.value)

lib/devtools/src/crewai_devtools/__init__.py

@@ -1,3 +1,3 @@
 """CrewAI development tools."""
 
-__version__ = "1.1.0"
+__version__ = "1.2.0"