chore: improve typing

lib/crewai/src/crewai/llm/providers/anthropic/completion.py

@@ -3,9 +3,9 @@ from __future__ import annotations
 import json
 import logging
 import os
-from typing import Any, ClassVar, cast
+from typing import TYPE_CHECKING, Any, cast
 
-from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, model_validator
+from pydantic import BaseModel, Field, PrivateAttr, model_validator
 from typing_extensions import Self
 
 from crewai.events.types.llm_events import LLMCallType
@@ -20,6 +20,11 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
 from crewai.utilities.types import LLMMessage
 
 
+if TYPE_CHECKING:
+    from crewai.agent.core import Agent
+    from crewai.task import Task
+
+
 try:
     from anthropic import Anthropic
     from anthropic.types import Message
@@ -48,6 +53,7 @@ class AnthropicCompletion(BaseLLM):
         client_params: Additional parameters for the Anthropic client
         interceptor: HTTP interceptor for modifying requests/responses at transport level
     """
+
     base_url: str | None = Field(
         default=None, description="Custom base URL for Anthropic API"
     )
@@ -121,8 +127,8 @@ class AnthropicCompletion(BaseLLM):
         tools: list[dict[str, Any]] | None = None,
         callbacks: list[Any] | None = None,
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str | Any:
         """Call Anthropic messages API.
@@ -311,8 +317,8 @@ class AnthropicCompletion(BaseLLM):
         self,
         params: dict[str, Any],
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str | Any:
         """Handle non-streaming message completion."""
@@ -399,8 +405,8 @@ class AnthropicCompletion(BaseLLM):
         self,
         params: dict[str, Any],
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str:
         """Handle streaming message completion."""
@@ -495,8 +501,8 @@ class AnthropicCompletion(BaseLLM):
         tool_uses: list[ToolUseBlock],
         params: dict[str, Any],
         available_functions: dict[str, Any],
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
     ) -> str:
         """Handle the complete tool use conversation flow.
 

lib/crewai/src/crewai/llm/providers/azure/completion.py

@@ -3,9 +3,9 @@ from __future__ import annotations
 import json
 import logging
 import os
-from typing import TYPE_CHECKING, Any, ClassVar
+from typing import TYPE_CHECKING, Any
 
-from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, model_validator
+from pydantic import BaseModel, Field, PrivateAttr, model_validator
 from typing_extensions import Self
 
 from crewai.llm.core import CONTEXT_WINDOW_USAGE_RATIO, LLM_CONTEXT_WINDOW_SIZES
@@ -18,6 +18,8 @@ from crewai.utilities.types import LLMMessage
 
 
 if TYPE_CHECKING:
+    from crewai.agent.core import Agent
+    from crewai.task import Task
     from crewai.tools.base_tool import BaseTool
 
 
@@ -66,8 +68,6 @@ class AzureCompletion(BaseLLM):
         interceptor: HTTP interceptor (not yet supported for Azure)
     """
 
-    model_config: ClassVar[ConfigDict] = ConfigDict(arbitrary_types_allowed=True)
-
     endpoint: str | None = Field(
         default=None,
         description="Azure endpoint URL (defaults to AZURE_ENDPOINT env var)",
@@ -91,7 +91,9 @@ class AzureCompletion(BaseLLM):
         default=None, description="Maximum tokens in response"
     )
     stream: bool = Field(default=False, description="Enable streaming responses")
-    client: Any = Field(default=None, exclude=True, description="Azure client instance")
+    _client: ChatCompletionsClient = PrivateAttr(
+        default_factory=ChatCompletionsClient,  # type: ignore[arg-type]
+    )
 
     _is_openai_model: bool = PrivateAttr(default=False)
     _is_azure_openai_endpoint: bool = PrivateAttr(default=False)
@@ -190,8 +192,8 @@ class AzureCompletion(BaseLLM):
         tools: list[dict[str, BaseTool]] | None = None,
         callbacks: list[Any] | None = None,
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str | Any:
         """Call Azure AI Inference chat completions API.
@@ -382,8 +384,8 @@ class AzureCompletion(BaseLLM):
         self,
         params: dict[str, Any],
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str | Any:
         """Handle non-streaming chat completion."""
@@ -478,8 +480,8 @@ class AzureCompletion(BaseLLM):
         self,
         params: dict[str, Any],
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str:
         """Handle streaming chat completion."""

lib/crewai/src/crewai/llm/providers/bedrock/completion.py

@@ -32,6 +32,9 @@ if TYPE_CHECKING:
         ToolTypeDef,
     )
 
+    from crewai.agent.core import Agent
+    from crewai.task import Task
+
 
 try:
     from boto3.session import Session
@@ -261,8 +264,8 @@ class BedrockCompletion(BaseLLM):
         tools: list[dict[Any, Any]] | None = None,
         callbacks: list[Any] | None = None,
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str | Any:
         """Call AWS Bedrock Converse API."""
@@ -347,8 +350,8 @@ class BedrockCompletion(BaseLLM):
         messages: list[dict[str, Any]],
         body: BedrockConverseRequestBody,
         available_functions: Mapping[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
     ) -> str:
         """Handle non-streaming converse API call following AWS best practices."""
         try:
@@ -528,8 +531,8 @@ class BedrockCompletion(BaseLLM):
         messages: list[dict[str, Any]],
         body: BedrockConverseRequestBody,
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
     ) -> str:
         """Handle streaming converse API call with comprehensive event handling."""
         full_response = ""

lib/crewai/src/crewai/llm/providers/gemini/completion.py

@@ -1,6 +1,6 @@
 import logging
 import os
-from typing import Any, ClassVar, cast
+from typing import TYPE_CHECKING, Any, ClassVar, cast
 
 from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, model_validator
 from typing_extensions import Self
@@ -16,6 +16,11 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
 from crewai.utilities.types import LLMMessage
 
 
+if TYPE_CHECKING:
+    from crewai.agent.core import Agent
+    from crewai.task import Task
+
+
 try:
     from google import genai  # type: ignore[import-untyped]
     from google.genai import types  # type: ignore[import-untyped]
@@ -196,8 +201,8 @@ class GeminiCompletion(BaseLLM):
         tools: list[dict[str, Any]] | None = None,
         callbacks: list[Any] | None = None,
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str | Any:
         """Call Google Gemini generate content API.
@@ -383,8 +388,8 @@ class GeminiCompletion(BaseLLM):
         system_instruction: str | None,
         config: types.GenerateContentConfig,
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str | Any:
         """Handle non-streaming content generation."""
@@ -449,8 +454,8 @@ class GeminiCompletion(BaseLLM):
         contents: list[types.Content],
         config: types.GenerateContentConfig,
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str:
         """Handle streaming content generation."""

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

@@ -11,7 +11,7 @@ from openai import APIConnectionError, NotFoundError, OpenAI
 from openai.types.chat import ChatCompletion, ChatCompletionChunk
 from openai.types.chat.chat_completion import Choice
 from openai.types.chat.chat_completion_chunk import ChoiceDelta
-from pydantic import BaseModel, Field, model_validator
+from pydantic import BaseModel, Field, PrivateAttr, model_validator
 from typing_extensions import Self
 
 from crewai.events.types.llm_events import LLMCallType
@@ -74,9 +74,7 @@ class OpenAICompletion(BaseLLM):
     )
     reasoning_effort: str | None = Field(None, description="Reasoning effort level")
 
-    client: OpenAI = Field(
+    _client: OpenAI = PrivateAttr(default_factory=OpenAI)
-        default_factory=OpenAI, exclude=True, description="OpenAI client instance"
-    )
     is_o1_model: bool = Field(False, description="Whether this is an O1 model")
     is_gpt4_model: bool = Field(False, description="Whether this is a GPT-4 model")
 
@@ -92,7 +90,7 @@ class OpenAICompletion(BaseLLM):
             http_client = httpx.Client(transport=transport)
             client_config["http_client"] = http_client
 
-        self.client = OpenAI(**client_config)
+        self._client = OpenAI(**client_config)
 
         self.is_o1_model = "o1" in self.model.lower()
         self.is_gpt4_model = "gpt-4" in self.model.lower()
@@ -279,14 +277,14 @@ class OpenAICompletion(BaseLLM):
         self,
         params: dict[str, Any],
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str | Any:
         """Handle non-streaming chat completion."""
         try:
             if response_model:
-                parsed_response = self.client.beta.chat.completions.parse(
+                parsed_response = self._client.beta.chat.completions.parse(
                     **params,
                     response_format=response_model,
                 )
@@ -310,7 +308,7 @@ class OpenAICompletion(BaseLLM):
                     )
                     return structured_json
 
-            response: ChatCompletion = self.client.chat.completions.create(**params)
+            response: ChatCompletion = self._client.chat.completions.create(**params)
 
             usage = self._extract_openai_token_usage(response)
 
@@ -402,8 +400,8 @@ class OpenAICompletion(BaseLLM):
         self,
         params: dict[str, Any],
         available_functions: dict[str, Any] | None = None,
-        from_task: Any | None = None,
+        from_task: Task | None = None,
-        from_agent: Any | None = None,
+        from_agent: Agent | None = None,
         response_model: type[BaseModel] | None = None,
     ) -> str:
         """Handle streaming chat completion."""
@@ -412,7 +410,7 @@ class OpenAICompletion(BaseLLM):
 
         if response_model:
             completion_stream: Iterator[ChatCompletionChunk] = (
-                self.client.chat.completions.create(**params)
+                self._client.chat.completions.create(**params)
             )
 
             accumulated_content = ""
@@ -455,7 +453,7 @@ class OpenAICompletion(BaseLLM):
                 )
                 return accumulated_content
 
-        stream: Iterator[ChatCompletionChunk] = self.client.chat.completions.create(
+        stream: Iterator[ChatCompletionChunk] = self._client.chat.completions.create(
             **params
         )