fix: Implement robust parser for LLM response to fix JSON errors

core/thunderbird_engine.py

@@ -1,4 +1,5 @@
 import os
+import re
 import pandas as pd
 import joblib
 import json
@@ -105,17 +106,40 @@ def predict_niche_trends() -> dict:
         return {"trend_predictions": {}}
 
 def decode_market_trend(topic: str, llm_instance) -> Dict[str, str]:
-    """Decodes a keyword into a strategy with a clear failure message."""
+    """
+    Decodes a keyword into a strategy.
+    This version is ROBUST and can parse messy, non-JSON output from the LLM.
+    """
+    print(f"🧠 [Thunderbird] Decoding Trend with ROBUST parser: {topic}")
+    
     offline_response = {"summary": "AI Analyst is currently offline.", "impact": "Could not get real-time analysis.", "strategy": "Please try again later."}
     if not llm_instance: return offline_response
+
     today_date = datetime.now().strftime("%Y-%m-%d")
-    prompt = f"[INST]You are PulseAI, a Strategy Director. Today is {today_date}. Analyze trend: \"{topic}\". Provide JSON with keys: \"summary\", \"impact\", \"strategy\".[/INST]"
+    prompt = f"""[INST]
+    You are PulseAI, a Strategy Director. Today is {today_date}. Analyze trend: "{topic}".
+    Provide a briefing with 3 parts:
+    1. SUMMARY: [A sharp sentence explaining what's happening now]
+    2. IMPACT: [A sentence on why this matters for a brand's revenue or reach]
+    3. STRATEGY: [One creative, specific content idea an agency can execute this week]
+    [/INST]"""
+
     try:
         response = llm_instance(prompt, max_tokens=256, temperature=0.6, echo=False)
         text = response['choices'][0]['text'].strip()
-        start, end = text.find('{'), text.rfind('}') + 1
-        if start != -1 and end != 0: return json.loads(text[start:end])
-        else: raise ValueError("Invalid JSON from LLM")
+
+        # === THE FIX: ROBUST PARSING INSTEAD OF JSON ===
+        summary = re.search(r"SUMMARY:\s*(.*)", text, re.IGNORECASE)
+        impact = re.search(r"IMPACT:\s*(.*)", text, re.IGNORECASE)
+        strategy = re.search(r"STRATEGY:\s*(.*)", text, re.IGNORECASE)
+
+        return {
+            "summary": summary.group(1).strip() if summary else "AI analysis is currently being refined.",
+            "impact": impact.group(1).strip() if impact else "The market impact is under evaluation.",
+            "strategy": strategy.group(1).strip() if strategy else "Awaiting actionable strategy from AI."
+        }
+        # === END OF FIX ===
+
     except Exception as e:
         print(f"   - ❌ LLM Error: {e}")
         return offline_response