Update main.py

main.py

@@ -3,6 +3,8 @@ from fastapi.responses import HTMLResponse, JSONResponse
 from fastapi.openapi.docs import get_swagger_ui_html
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
+from datetime import datetime
+import uuid
 from transformers import pipeline
 import logging, traceback
 from typing import Optional, List, Union
@@ -31,6 +33,7 @@ app.add_middleware(
 )
 
 logging.basicConfig(level=logging.INFO)
+log_store = []
 VALID_API_KEY = "my-secret-key"
 
 @app.get("/", response_class=HTMLResponse)
@@ -112,6 +115,17 @@ async def analyze(data: ReviewInput, x_api_key: str = Header(None)):
             emotion_raw = detect_emotion(data.text)
             emotion = emotion_raw["label"] if isinstance(emotion_raw, dict) and "label" in emotion_raw else str(emotion_raw)
             churn_risk = assess_churn_risk(sentiment["label"], emotion)
+            # Log churn risk analysis
+            log_entry = {
+                "timestamp": datetime.now(),
+                "product": data.product_category or "Generic",
+                "churn_risk": churn_risk,
+                "user_id": str(uuid.uuid4())  # Optional
+            }
+            log_store.append(log_entry)
+            if len(log_store) > 1000:
+                log_store = log_store[-1000:]  # keep latest 1000 entries
+
             pain_points = []
             if data.aspects:
                 from model import extract_pain_points  # 🔍 Import inline if not already
@@ -209,3 +223,8 @@ async def bulk_analyze(data: BulkReviewInput, token: str = Query(None)):
         logging.error(f"🔥 Bulk processing failed: {traceback.format_exc()}")
         raise HTTPException(status_code=500, detail="Failed to analyze bulk reviews")
 
+@app.get("/log/")
+async def get_churn_log(x_api_key: str = Header(None)):
+    if x_api_key and x_api_key != VALID_API_KEY:
+        raise HTTPException(status_code=401, detail="Unauthorized")
+    return {"log": log_store}