responses feedback items: whitelist input-shape fields — api rejects response-only fields like status as unknown parameters (live 400)

fjerkroa_bot/openai_responder.py

@@ -304,6 +304,31 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
                 items.append({"role": role, "content": str(content)})
         return items
 
+    # Only these item types travel back as input; response-only fields like `status`
+    # are rejected by the API as unknown parameters (live 400, 2026-07-17)
+    _RESPONSES_FEEDBACK_FIELDS = {
+        "reasoning": ("id", "summary", "encrypted_content"),
+        "function_call": ("id", "call_id", "name", "arguments"),
+    }
+
+    @classmethod
+    def _responses_feedback(cls, output: List[Any]) -> List[Dict[str, Any]]:
+        """Reasoning + function_call items in input shape — keeps the chain of thought (ENV-23)."""
+        items: List[Dict[str, Any]] = []
+        for item in output or []:
+            fields = cls._RESPONSES_FEEDBACK_FIELDS.get(getattr(item, "type", None) or "")
+            if not fields:
+                continue  # message items need not travel back
+            data: Dict[str, Any] = {"type": item.type}
+            for field in fields:
+                value = getattr(item, field, None)
+                if field == "summary" and isinstance(value, list):
+                    value = [part if isinstance(part, dict) else part.model_dump() for part in value]
+                if value is not None:
+                    data[field] = value
+            items.append(data)
+        return items
+
     @staticmethod
     def _responses_refused(result: Any) -> bool:
         for item in getattr(result, "output", []) or []:
@@ -350,8 +375,8 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
                 return answer, limit
             tool_names = [call.name for call in calls]
             logging.info(f"🔧 OpenAI requested function calls: {tool_names}")
-            # Pass ALL output items back — reasoning items keep the chain of thought (ENV-23)
-            context = context + [item if isinstance(item, dict) else item.model_dump() for item in result.output]
+            # Pass reasoning + function_call items back — keeps the chain of thought (ENV-23)
+            context = context + self._responses_feedback(result.output)
             for call in calls:
                 function_args = json.loads(call.arguments) if call.arguments else {}
                 logging.info(f"🔧 Executing tool: {call.name} with args: {function_args}")