Delete server.py

server.py

@@ -1,61 +0,0 @@
-from fastapi import FastAPI, Request
-from fastapi.middleware.cors import CORSMiddleware
-import requests
-import openai  # or use llama API
-import os
-from pydantic import BaseModel
-
-app = FastAPI()
-
-# Allow Gradio frontend access
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# Load environment variables
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
-class FeedbackRequest(BaseModel):
-    message: str
-
-@app.post("/auto_feedback")
-async def auto_feedback(data: FeedbackRequest):
-    user_message = data.message
-
-    # ---- Step 1: Generate AI response (Llama/OpenAI) ----
-    ai_prompt = f"User feedback: {user_message}\nGive short reflection + improvement suggestion."
-    try:
-        completion = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=[{"role": "user", "content": ai_prompt}]
-        )
-        ai_text = completion.choices[0].message["content"]
-    except Exception as e:
-        ai_text = f"Error generating feedback: {e}"
-
-    # ---- Step 2: Send data to Pulse Survey API ----
-    pulse_payload = {
-        "feedback_text": user_message,
-        "ai_feedback": ai_text,
-        "source": "HuggingFace_Chatbot"
-    }
-    try:
-        pulse_response = requests.post(
-            "https://your-pulse-survey-api.com/api/save_feedback",
-            json=pulse_payload,
-            timeout=10
-        )
-        pulse_status = pulse_response.status_code
-    except Exception as e:
-        pulse_status = f"Failed to send: {e}"
-
-    # ---- Step 3: Return structured response ----
-    return {
-        "user_feedback": user_message,
-        "ai_response": ai_text,
-        "pulse_status": pulse_status
-    }