review code

custom_components/llama_conversation/ai_task.py

@@ -156,7 +156,7 @@ class LocalLLMTaskEntity(
     def _extract_data(
         self,
         raw_text: str,
-        tool_calls: list | None,
+        tool_calls: list[llm.ToolInput] | None,
         extraction_method: ResultExtractionMethod,
         chat_log: conversation.ChatLog,
         structure: vol.Schema | None,
@@ -178,8 +178,9 @@ class LocalLLMTaskEntity(
 
             if extraction_method == ResultExtractionMethod.TOOL:
                 first_tool = next(iter(tool_calls or []), None)
-                if not first_tool or not getattr(first_tool, "tool_args", None):
+                if not first_tool:
                     return None, HomeAssistantError("Please produce at least one tool call with the structured response.")
+                
                 structure(first_tool.tool_args) # validate tool call against vol schema structure
                 return ai_task.GenDataTaskResult(
                     conversation_id=chat_log.conversation_id,

custom_components/llama_conversation/backends/generic_openai.py

@@ -111,7 +111,7 @@ class GenericOpenAIAPIClient(LocalLLMClient):
             ) as response:
                 response.raise_for_status()
                 models_result = await response.json()
-        except:
+        except (asyncio.TimeoutError, aiohttp.ClientResponseError):
             _LOGGER.exception("Failed to get available models")
             return RECOMMENDED_CHAT_MODELS
             

custom_components/llama_conversation/manifest.json

@@ -1,7 +1,7 @@
 {
   "domain": "llama_conversation",
   "name": "Local LLMs",
-  "version": "0.4.4",
+  "version": "0.4.5",
   "codeowners": ["@acon96"],
   "config_flow": true,
   "dependencies": ["conversation", "ai_task"],

custom_components/llama_conversation/utils.py

@@ -279,7 +279,8 @@ def get_oai_formatted_tools(llm_api: llm.APIInstance, domains: list[str]) -> Lis
     result: List[ChatCompletionTool] = []
 
     for tool in llm_api.tools:
-        if tool.name == SERVICE_TOOL_NAME:
+        # when combining with home assistant llm APIs, it adds a prefix to differentiate tools; compare against the suffix here
+        if tool.name.endswith(SERVICE_TOOL_NAME):
             result.extend([{
                 "type": "function",
                 "function": {