fix: Add graceful fallback synthesis when LLM API fails (401/403)

app.py

@@ -138,33 +138,49 @@ def call_perspective(perspective_name: str, query: str) -> str:
 
 def generate_synthesis(perspectives_responses: Dict[str, str], query: str) -> str:
     """Generate synthesis from all perspective responses."""
-    if not HAS_LLM:
-        return "MC synthesis: Integrating all perspectives..."
 
-    perspective_text = "\n\n".join(
-        f"**{name.upper()}**: {response[:200]}"
-        for name, response in perspectives_responses.items()
-    )
+    # Try LLM synthesis first if available
+    if HAS_LLM:
+        perspective_text = "\n\n".join(
+            f"**{name.upper()}**: {response[:200]}"
+            for name, response in perspectives_responses.items()
+        )
 
-    synthesis_prompt = f"""Synthesize these perspective responses on: {query[:100]}
+        synthesis_prompt = f"""Synthesize these perspective responses on: {query[:100]}
 
 {perspective_text}
 
 Brief unified insight:"""
 
-    try:
-        messages = [
-            {"role": "system", "content": "Synthesize multi-perspective responses concisely."},
-            {"role": "user", "content": synthesis_prompt}
-        ]
-        response = client.chat_completion(
-            messages,
-            max_tokens=256,
-            temperature=0.7,
-        )
-        return response.choices[0].message.content
-    except Exception as e:
-        return f"Synthesis error: {str(e)[:100]}"
+        try:
+            messages = [
+                {"role": "system", "content": "Synthesize multi-perspective responses concisely."},
+                {"role": "user", "content": synthesis_prompt}
+            ]
+            response = client.chat_completion(
+                messages,
+                max_tokens=256,
+                temperature=0.7,
+            )
+            return response.choices[0].message.content
+        except Exception as e:
+            # Fall through to built-in synthesis below
+            print(f"LLM synthesis failed ({e.__class__.__name__}), using built-in synthesis")
+
+    # Built-in synthesis from perspective responses (no LLM required)
+    summaries = []
+    for name, response in perspectives_responses.items():
+        # Extract first sentence or first 100 chars
+        summary = response.split('.')[0][:120].strip()
+        if summary:
+            summaries.append(f"• **{name.title()}**: {summary}")
+
+    synthesis = "🔀 **Multi-Perspective Synthesis**\n\n" + "\n".join(summaries)
+
+    if len(synthesis) < 100:
+        synthesis += f"\n\n_Query unified across {len(perspectives_responses)} perspectives._"
+
+    return synthesis
 
 
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