app.py

import os
from fastapi import FastAPI, Request
from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration

# ✅ Cache dir
CACHE_DIR = "/tmp/hf_cache"
os.environ["HF_HOME"] = CACHE_DIR
os.environ["TRANSFORMERS_CACHE"] = CACHE_DIR
os.makedirs(CACHE_DIR, exist_ok=True)

# FastAPI
app = FastAPI()

# ✅ Model name
MODEL_NAME = "facebook/blenderbot-400M-distill"

# Load tokenizer & model once
tokenizer = BlenderbotTokenizer.from_pretrained(MODEL_NAME, cache_dir=CACHE_DIR)
model = BlenderbotForConditionalGeneration.from_pretrained(MODEL_NAME, cache_dir=CACHE_DIR)

@app.get("/")
async def root():
    return {"message": "BlenderBot-400M Chatbot API is running!"}

@app.post("/chat")
async def chat(req: Request):
    data = await req.json()
    user_message = data.get("message", "").strip()

    if not user_message:
        return {"reply": "Please send a valid message."}

    # Encode input
    inputs = tokenizer([user_message], return_tensors="pt")

    # Generate response
    reply_ids = model.generate(
        **inputs,
        max_length=100,
        do_sample=True,
        temperature=0.7,
        top_p=0.9,
        use_cache=False 
    )

    # Decode output
    reply = tokenizer.decode(reply_ids[0], skip_special_tokens=True)

    return {"reply": reply}

@app.get("/health")
async def health():
    return {"ready": True}