Update main.py

main.py

@@ -245,3 +245,53 @@ async def bulk_analyze(data: BulkReviewInput, token: str = Query(None)):
     except Exception as e:
         logging.error(f"🔥 Bulk processing failed: {traceback.format_exc()}")
         raise HTTPException(status_code=500, detail="Failed to analyze bulk reviews")
+
+from openai import OpenAI
+openai_client = OpenAI()
+
+@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:
+        raise HTTPException(status_code=401, detail="Invalid API key")
+
+    try:
+        text = payload.get("text", "").strip()
+        if not text or len(text.split()) < 5:
+            raise HTTPException(status_code=400, detail="Insufficient input for root cause analysis.")
+
+        prompt = f"""
+        Analyze the following customer feedback and extract:
+        1. The main problem
+        2. The possible root cause
+        3. A suggested fix or which team might need to handle it
+
+        Feedback: '''{text}'''
+        Format your answer as:
+        Problem: ...
+        Cause: ...
+        Suggestion: ...
+        """
+
+        response = openai_client.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 "—"
+
+        return {
+            "problem": extract_line("Problem"),
+            "cause": extract_line("Cause"),
+            "suggestion": extract_line("Suggestion")
+        }
+
+    except Exception as e:
+        logging.error(f"Root cause analysis failed: {traceback.format_exc()}")
+        raise HTTPException(status_code=500, detail="Root cause generation failed.")