Update mcp_servers.py

mcp_servers.py

@@ -1,6 +1,7 @@
-# mcp_servers.py (Corrected for TypeError)
+# mcp_servers.py (Robust JSON Parsing Update)
 import asyncio
 import json
+import re # <-- 1. Import regex module
 from typing import Dict, Optional, Tuple, List, Any
 from personas import PERSONAS_DATA
 import google.generativeai as genai
@@ -11,9 +12,36 @@ from utils import load_prompt
 
 EVALUATION_PROMPT_TEMPLATE = load_prompt(config.PROMPT_FILES["evaluator"])
 
-class BusinessSolutionEvaluator:
-    """Implements the "LLM-as-a-Judge"."""
+# --- 2. New Helper Function ---
+def extract_json(text: str) -> dict:
+    """
+    Robustly extracts a JSON object from a string, ignoring markdown or text headers.
+    """
+    try:
+        # First, try standard cleaning (removing markdown code blocks)
+        clean_text = text.strip()
+        if "```json" in clean_text:
+             clean_text = clean_text.split("```json")[1].split("```")[0].strip()
+        elif "```" in clean_text:
+             clean_text = clean_text.split("```")[1].split("```")[0].strip()
+        
+        return json.loads(clean_text)
+    except json.JSONDecodeError:
+        # If that fails, use Regex to find the first '{' and last '}'
+        # This handles cases like "Here is the JSON: { ... }"
+        try:
+            match = re.search(r'(\{.*\})', text, re.DOTALL)
+            if match:
+                return json.loads(match.group(1))
+        except:
+            pass
     
+    # If we still can't find JSON, raise the original text for debugging
+    raise ValueError(f"Could not extract JSON from response: {text[:100]}...")
+
+
+class BusinessSolutionEvaluator:
+    # (Init is unchanged)
     def __init__(self, gemini_client: Optional[genai.GenerativeModel]):
         if not gemini_client:
             raise ValueError("BusinessSolutionEvaluator requires a Google/Gemini client.")
@@ -24,33 +52,36 @@ class BusinessSolutionEvaluator:
     async def evaluate(self, problem: str, solution_text: str) -> dict:
         print(f"Evaluating solution (live): {solution_text[:50]}...")
         prompt = EVALUATION_PROMPT_TEMPLATE.format(problem=problem, solution_text=solution_text)
+        
         try:
             response = await self.gemini_model.generate_content_async(
                 prompt,
                 generation_config=genai.types.GenerationConfig(
-                    response_mime_type="application/json"
-                    # --- FIX: REMOVED a line here ---
-                    # model=config.MODELS["Gemini"]["judge"] <-- This was the bug
+                    response_mime_type="application/json",
+                    model=config.MODELS["Gemini"]["judge"]
                 )
             )
-            json_text = response.text.strip().replace("```json", "").replace("```", "")
-            if not json_text.startswith("{"):
-                raise Exception(f"API returned non-JSON text: {json_text}")
-            v_fitness = json.loads(json_text)
+            
+            # --- 3. Use the new robust extractor ---
+            v_fitness = extract_json(response.text)
+            
             print(f"Evaluation complete (live): {v_fitness}")
             return v_fitness
+        
         except Exception as e:
-            print(f"ERROR: BusinessSolutionEvaluator failed to parse JSON or call API: {e}")
+            print(f"ERROR: BusinessSolutionEvaluator failed: {e}")
+            # We update the fallback justification so you can see the error in the UI logs
+            error_msg = str(e).replace("\n", " ")[:100]
             return {
-                "Novelty": {"score": 1, "justification": f"Error during evaluation: {e}"},
-                "Usefulness_Feasibility": {"score": 1, "justification": f"Error during evaluation: {e}"},
-                "Flexibility": {"score": 1, "justification": f"Error during evaluation: {e}"},
-                "Elaboration": {"score": 1, "justification": f"Error during evaluation: {e}"},
-                "Cultural_Appropriateness": {"score": 1, "justification": f"Error during evaluation: {e}"}
+                "Novelty": {"score": 1, "justification": f"System Error: {error_msg}"},
+                "Usefulness_Feasibility": {"score": 1, "justification": "System Error"},
+                "Flexibility": {"score": 1, "justification": "System Error"},
+                "Elaboration": {"score": 1, "justification": "System Error"},
+                "Cultural_Appropriateness": {"score": 1, "justification": "System Error"}
             }
 
+# (Rest of the file: AgentCalibrator, get_llm_response remains UNCHANGED)
 class AgentCalibrator:
-    # (This class is unchanged)
     def __init__(self, api_clients: dict, evaluator: BusinessSolutionEvaluator):
         self.evaluator = evaluator
         self.api_clients = {name: client for name, client in api_clients.items() if client}
@@ -136,8 +167,7 @@ async def get_llm_response(client_name: str, client, system_prompt: str, user_pr
             ]
             response = await model.generate_content_async(full_prompt,
                 generation_config=genai.types.GenerationConfig(
-                    # --- FIX: REMOVED a line here ---
-                    # model=config.MODELS["Gemini"]["default"] <-- This was the bug
+                    # model parameter removed here as it's set on client init
                 ))
             return response.text