set timeouts on llm clients

ra_aid/chat_models/deepseek_chat.py

@@ -10,8 +10,8 @@ from langchain_openai import ChatOpenAI
 class ChatDeepseekReasoner(ChatOpenAI):
     """ChatDeepseekReasoner with custom overrides for R1/reasoner models."""
 
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
+    def __init__(self, *args, timeout: int = 180, max_retries: int = 5, **kwargs):
+        super().__init__(*args, timeout=timeout, max_retries=max_retries, **kwargs)
 
     def invocation_params(
         self, options: Optional[Dict[str, Any]] = None, **kwargs: Any

ra_aid/llm.py

@@ -20,6 +20,10 @@ known_temp_providers = {
     "deepseek",
 }
 
+# Constants for API request configuration
+LLM_REQUEST_TIMEOUT = 180
+LLM_MAX_RETRIES = 5
+
 logger = get_logger(__name__)
 
 
@@ -51,6 +55,8 @@ def create_deepseek_client(
             if is_expert
             else (temperature if temperature is not None else 1),
             model=model_name,
+            timeout=LLM_REQUEST_TIMEOUT,
+            max_retries=LLM_MAX_RETRIES,
         )
 
     return ChatOpenAI(
@@ -58,6 +64,8 @@ def create_deepseek_client(
         base_url=base_url,
         temperature=0 if is_expert else (temperature if temperature is not None else 1),
         model=model_name,
+        timeout=LLM_REQUEST_TIMEOUT,
+        max_retries=LLM_MAX_RETRIES,
     )
 
 
@@ -76,12 +84,16 @@ def create_openrouter_client(
             if is_expert
             else (temperature if temperature is not None else 1),
             model=model_name,
+            timeout=LLM_REQUEST_TIMEOUT,
+            max_retries=LLM_MAX_RETRIES,
         )
 
     return ChatOpenAI(
         api_key=api_key,
         base_url="https://openrouter.ai/api/v1",
         model=model_name,
+        timeout=LLM_REQUEST_TIMEOUT,
+        max_retries=LLM_MAX_RETRIES,
         **({"temperature": temperature} if temperature is not None else {}),
     )
 
@@ -188,11 +200,17 @@ def create_llm_client(
         }
         if is_expert:
             openai_kwargs["reasoning_effort"] = "high"
-        return ChatOpenAI(**openai_kwargs)
+        return ChatOpenAI(**{
+            **openai_kwargs,
+            "timeout": LLM_REQUEST_TIMEOUT,
+            "max_retries": LLM_MAX_RETRIES,
+        })
     elif provider == "anthropic":
         return ChatAnthropic(
             api_key=config["api_key"],
             model_name=model_name,
+            timeout=LLM_REQUEST_TIMEOUT,
+            max_retries=LLM_MAX_RETRIES,
             **temp_kwargs,
         )
     elif provider == "openai-compatible":
@@ -200,12 +218,16 @@ def create_llm_client(
             api_key=config["api_key"],
             base_url=config["base_url"],
             model=model_name,
+            timeout=LLM_REQUEST_TIMEOUT,
+            max_retries=LLM_MAX_RETRIES,
             **temp_kwargs,
         )
     elif provider == "gemini":
         return ChatGoogleGenerativeAI(
             api_key=config["api_key"],
             model=model_name,
+            timeout=LLM_REQUEST_TIMEOUT,
+            max_retries=LLM_MAX_RETRIES,
             **temp_kwargs,
         )
     else: