intermediate fix chain tool response to AI

src/airflow_wingman/llm_client.py

@@ -100,7 +100,7 @@ class LLMClient:
                 # Create a follow-up completion with the tool results
                 logger.info("Making follow-up request with tool results")
                 follow_up_response = self.provider.create_follow_up_completion(
-                    messages=messages, model=model, temperature=temperature, max_tokens=max_tokens, tool_results=tool_results, original_response=response
+                    messages=messages, model=model, temperature=temperature, max_tokens=max_tokens, tool_results=tool_results, original_response=response, tools=provider_tools
                 )
 
                 content = self.provider.get_content(follow_up_response)
@@ -184,8 +184,18 @@ class LLMClient:
                 # Only stream on the final iteration
                 should_stream = (iteration == max_iterations) or not self.provider.has_tool_calls(current_response)
 
+                # Get provider-specific tool definitions from Airflow tools
+                provider_tools = self.provider.convert_tools(self.airflow_tools)
+
                 follow_up_response = self.provider.create_follow_up_completion(
-                    messages=messages, model=model, temperature=temperature, max_tokens=max_tokens, tool_results=tool_results, original_response=current_response, stream=should_stream
+                    messages=messages,
+                    model=model,
+                    temperature=temperature,
+                    max_tokens=max_tokens,
+                    tool_results=tool_results,
+                    original_response=current_response,
+                    stream=should_stream,
+                    tools=provider_tools,
                 )
 
                 # Check if this follow-up response has more tool calls

src/airflow_wingman/providers/anthropic_provider.py

@@ -104,7 +104,7 @@ class AnthropicProvider(BaseLLMProvider):
                 if callable(response.json):
                     # If json is a method, call it
                     try:
-                        logger.info(f"Anthropic response json: {json.dumps(response.json())}")
+                        logger.info(f"Anthropic response json: {json.dumps(response.model_dump_json())}")
                     except Exception as json_err:
                         logger.warning(f"Could not serialize response.json(): {str(json_err)}")
                 else:
@@ -274,6 +274,7 @@ class AnthropicProvider(BaseLLMProvider):
         tool_results: dict[str, Any] = None,
         original_response: Any = None,
         stream: bool = True,
+        tools: list[dict[str, Any]] | None = None,
     ) -> Any:
         """
         Create a follow-up completion with tool results.
@@ -286,6 +287,7 @@ class AnthropicProvider(BaseLLMProvider):
             tool_results: Results of tool executions
             original_response: Original response with tool calls
             stream: Whether to stream the response
+            tools: List of tool definitions in Anthropic format
 
         Returns:
             Anthropic response object or generator if streaming
@@ -327,7 +329,7 @@ class AnthropicProvider(BaseLLMProvider):
             temperature=temperature,
             max_tokens=max_tokens,
             stream=stream,
-            tools=None,  # No tools needed for follow-up
+            tools=tools,
         )
 
     def get_content(self, response: Any) -> str: