Update main.py

main.py

@@ -33,8 +33,8 @@ app.add_middleware(
 )
 
 logging.basicConfig(level=logging.INFO)
-log_store = []
 VALID_API_KEY = "my-secret-key"
+log_store = []
 
 @app.get("/", response_class=HTMLResponse)
 def root():
@@ -115,6 +115,7 @@ 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(),
@@ -170,6 +171,13 @@ async def followup(request: FollowUpRequest, x_api_key: str = Header(None)):
         logging.error(f"❌ Follow-up failed: {traceback.format_exc()}")
         raise HTTPException(status_code=500, detail="Internal Server Error during follow-up.")
 
+@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}
+
+
 @app.post("/bulk/")
 async def bulk_analyze(data: BulkReviewInput, token: str = Query(None)):
     if token != VALID_API_KEY:
@@ -190,9 +198,21 @@ async def bulk_analyze(data: BulkReviewInput, token: str = Query(None)):
             summary = smart_summarize(review_text, n_clusters=2 if data.intelligence else 1)
             sentiment = sentiment_pipeline(review_text)[0]
             emotion = detect_emotion(review_text)
+            
             churn = assess_churn_risk(sentiment["label"], emotion)
             pain = extract_pain_points(review_text) if data.aspects else []
 
+            # 🔁 Log churn data
+            log_entry = {
+                "timestamp": datetime.now(),
+                "product": prod,
+                "churn_risk": churn,
+                "user_id": str(uuid.uuid4())
+            }
+            log_store.append(log_entry)
+            if len(log_store) > 1000:
+                log_store = log_store[-1000:]
+
 
             ind = auto_fill(data.industry[i] if data.industry else None, detect_industry(review_text))
             prod = auto_fill(data.product_category[i] if data.product_category else None, detect_product_category(review_text))
@@ -223,8 +243,3 @@ 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}