Update components/code_generator_loop/mcp_brainstormer.py

components/code_generator_loop/mcp_brainstormer.py

@@ -78,28 +78,16 @@ Do not include any explanatory text, comments, or formatting outside valid JSON.
         task: str,
         tools_list: str,
         retries: int = 3,
-    ) -> Union[List[Dict[str, Any]], Dict[str, str]]:
+    ) -> List[Dict[str, Any]]:
         # 1) Validate inputs
         if not task.strip():
-            return {"error": "User task must not be empty."}
+            return [{"error": "User task must not be empty."}]
         raw = tools_list.strip()
         if not raw:
-            return {"error": "Please provide a list of existing tools (or 'none')."}
-
-        # 2) Normalize the tools_list so that each tool is on its own line
-        #    (Assumes comma‐ or newline‐separated)
-        entries = re.split(r"[\n,]+", raw)
-        normalized = "\n".join(f"- {e.strip()}" for e in entries if e.strip())
-
-        # 3) Build the prompt
-        prompt_text = self.mcp_tools_spec_prompt.format(
-            task=task,
-            tools_list=normalized,
-            example_tool=self.example_tool
-        )
+            return [{"error": "Please provide a list of existing tools (or 'none')."}]
+
+        # ...existing code...
 
-        # 4) Call the LLM with retry logic
-        last_error = None
         for _ in range(retries):
             try:
                 llm = Anthropic(model=self.model_name, temperature=0.0, max_tokens=512, timeout=30)
@@ -111,16 +99,15 @@ Do not include any explanatory text, comments, or formatting outside valid JSON.
             try:
                 specs = json.loads(response_text)
             except json.JSONDecodeError:
-                # This is a fallback: find the first top‐level JSON array
                 specs = self._extract_json_array(response_text)
 
             if isinstance(specs, list):
                 return specs
 
         if last_error:
-            return {"error": f"Failed to call LLM: {last_error}"}
+            return [{"error": f"Failed to call LLM: {last_error}"}]
         else:
-            return {"error": "Could not extract a valid JSON array from the LLM output."}
+            return [{"error": "Could not extract a valid JSON array from the LLM output."}]
 
     def create_interface(self):
         return gr.Interface(