Update main.py

main.py

@@ -254,7 +254,6 @@ async def bulk_analyze(data: BulkReviewInput, token: str = Query(None)):
         raise HTTPException(status_code=500, detail="Failed to analyze bulk reviews")
 
 # Already set with os.environ — nothing else needed
-
 @app.post("/rootcause/")
 async def root_cause_analysis(payload: dict, x_api_key: str = Header(None)):
     if x_api_key and x_api_key != VALID_API_KEY:
@@ -278,25 +277,38 @@ async def root_cause_analysis(payload: dict, x_api_key: str = Header(None)):
         Suggestion: ...
         """
 
-        response = openai.chat.completions.create(
-            model="gpt-4",
-            messages=[{"role": "user", "content": prompt}]
-        )
-
-        output = response.choices[0].message.content
-        lines = output.splitlines()
-
-        def extract_line(tag):
-            for line in lines:
-                if line.lower().startswith(tag.lower()):
-                    return line.split(":", 1)[-1].strip()
-            return "—"
+        # Models to try in order
+        models_to_try = ["gpt-4", "gpt-4o-mini", "gpt-3.5-turbo"]
+
+        last_error = None
+        for model_name in models_to_try:
+            try:
+                response = openai.chat.completions.create(
+                    model=model_name,
+                    messages=[{"role": "user", "content": prompt}]
+                )
+                output = response.choices[0].message.content
+                lines = output.splitlines()
+
+                def extract_line(tag):
+                    for line in lines:
+                        if line.lower().startswith(tag.lower()):
+                            return line.split(":", 1)[-1].strip()
+                    return "—"
+
+                return {
+                    "problem": extract_line("Problem"),
+                    "cause": extract_line("Cause"),
+                    "suggestion": extract_line("Suggestion"),
+                    "model_used": model_name
+                }
+            except Exception as e:
+                last_error = str(e)
+                logging.warning(f"Model {model_name} failed: {last_error}")
+                continue
 
-        return {
-            "problem": extract_line("Problem"),
-            "cause": extract_line("Cause"),
-            "suggestion": extract_line("Suggestion")
-        }
+        # If all models fail
+        raise HTTPException(status_code=500, detail=f"All model attempts failed. Last error: {last_error}")
 
     except Exception as e:
         logging.error(f"Root cause analysis failed: {traceback.format_exc()}")