src/cleveragents/providers/registry.py

@@ -472,14 +472,14 @@ class ProviderRegistry:
         if provider_type == ProviderType.OPENAI:
             from langchain_openai import ChatOpenAI
 
-            return ChatOpenAI(model=model_id or "gpt-4o", **kwargs)  # type: ignore[arg-type]
+            return ChatOpenAI(model=model_id or "gpt-4o", **kwargs)
 
         if provider_type == ProviderType.ANTHROPIC:
             from langchain_anthropic import ChatAnthropic
 
             return ChatAnthropic(
                 model=model_id or "claude-sonnet-4-20250514",
-                **kwargs,  # type: ignore[arg-type]
+                **kwargs,
             )
 
         if provider_type in (ProviderType.GOOGLE, ProviderType.GEMINI):
@@ -487,7 +487,7 @@ class ProviderRegistry:
 
             return ChatGoogleGenerativeAI(
                 model=model_id or "gemini-2.0-flash",
-                **kwargs,  # type: ignore[arg-type]
+                **kwargs,
             )
 
         if provider_type == ProviderType.AZURE:
@@ -522,31 +522,31 @@ class ProviderRegistry:
                 deployment_name=deployment_name,
                 azure_endpoint=azure_endpoint,
                 api_version=api_version,
-                **kwargs,  # type: ignore[arg-type]
+                **kwargs,
             )
 
         if provider_type == ProviderType.GROQ:
-            from langchain_groq import ChatGroq  # type: ignore[import-untyped]
+            from langchain_groq import ChatGroq
 
             return ChatGroq(
                 model=model_id or "llama-3.1-70b-versatile",
-                **kwargs,  # type: ignore[arg-type]
+                **kwargs,
             )
 
         if provider_type == ProviderType.TOGETHER:
-            from langchain_together import ChatTogether  # type: ignore[import-untyped]
+            from langchain_together import ChatTogether
 
             return ChatTogether(
                 model=model_id or "meta-llama/Llama-3.1-70B-Instruct-Turbo",
-                **kwargs,  # type: ignore[arg-type]
+                **kwargs,
             )
 
         if provider_type == ProviderType.COHERE:
-            from langchain_cohere import ChatCohere  # type: ignore[import-untyped]
+            from langchain_cohere import ChatCohere
 
             return ChatCohere(
                 model=model_id or "command-r-plus",
-                **kwargs,  # type: ignore[arg-type]
+                **kwargs,
             )
 
         raise ValueError(f"Unsupported provider type: {provider_type}")
@@ -647,14 +647,18 @@ class ProviderRegistry:
                 max_retries=max_retries,
             )
 
-        # Create factory function for the LLM
+        # Create factory function for the LLM.
+        # Capture the narrowed ProviderType in a local variable so the closure
+        # holds a ProviderType rather than the wider ProviderType | str | None.
+        resolved_provider_type: ProviderType = provider_type
+
         def llm_factory(mid: str) -> BaseLanguageModel:
             factory_kwargs: dict[str, Any] = {"max_retries": max_retries}
             return self._create_provider_llm(
-                provider_type,
+                resolved_provider_type,
                 mid,
                 **factory_kwargs,
-            )  # type: ignore[arg-type]
+            )
 
         return LangChainChatProvider(
             name=provider_type.value,

typings/langchain_cohere/__init__.pyi

@@ -0,0 +1,25 @@
+"""Type stubs for langchain_cohere package."""
+
+from typing import Any
+
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.messages import AIMessage
+
+class ChatCohere(BaseLanguageModel[AIMessage]):
+    """Cohere chat model wrapper."""
+
+    def __init__(
+        self,
+        *,
+        model: str = ...,
+        temperature: float = ...,
+        max_tokens: int | None = None,
+        timeout: float | None = None,
+        max_retries: int = ...,
+        cohere_api_key: Any = None,
+        base_url: str | None = None,
+        streaming: bool = ...,
+        **kwargs: Any,
+    ) -> None: ...
+
+__all__ = ["ChatCohere"]

typings/langchain_groq/__init__.pyi

@@ -0,0 +1,25 @@
+"""Type stubs for langchain_groq package."""
+
+from typing import Any
+
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.messages import AIMessage
+
+class ChatGroq(BaseLanguageModel[AIMessage]):
+    """Groq chat model wrapper."""
+
+    def __init__(
+        self,
+        *,
+        model: str = ...,
+        temperature: float = ...,
+        max_tokens: int | None = None,
+        timeout: float | None = None,
+        max_retries: int = ...,
+        api_key: Any = None,
+        base_url: str | None = None,
+        streaming: bool = ...,
+        **kwargs: Any,
+    ) -> None: ...
+
+__all__ = ["ChatGroq"]

typings/langchain_together/__init__.pyi

@@ -0,0 +1,25 @@
+"""Type stubs for langchain_together package."""
+
+from typing import Any
+
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.messages import AIMessage
+
+class ChatTogether(BaseLanguageModel[AIMessage]):
+    """Together AI chat model wrapper."""
+
+    def __init__(
+        self,
+        *,
+        model: str = ...,
+        temperature: float = ...,
+        max_tokens: int | None = None,
+        timeout: float | None = None,
+        max_retries: int = ...,
+        api_key: Any = None,
+        base_url: str | None = None,
+        streaming: bool = ...,
+        **kwargs: Any,
+    ) -> None: ...
+
+__all__ = ["ChatTogether"]