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# app.py
import gradio as gr
from typing import List, Tuple, Dict, Any
MODEL_ID = "facebook/blenderbot-400M-distill"
model = None
tokenizer = None
def ensure_model_loaded():
global model, tokenizer
if model is None or tokenizer is None:
from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
tokenizer = BlenderbotTokenizer.from_pretrained(MODEL_ID)
model = BlenderbotForConditionalGeneration.from_pretrained(MODEL_ID)
def generate_reply(context: str) -> str:
ensure_model_loaded()
inputs = tokenizer(context, return_tensors="pt")
reply_ids = model.generate(**inputs, max_length=120, no_repeat_ngram_size=2)
reply = tokenizer.decode(reply_ids[0], skip_special_tokens=True)
return reply
def history_to_context_from_tuples(history: List[Tuple[str, str]]) -> str:
ctx = ""
for u, b in history:
ctx += f"User: {u}\nBot: {b}\n"
return ctx
def history_to_context_from_messages(history: List[Dict[str, str]]) -> str:
# messages are like {"role":"user"/"assistant","content":"..."}
ctx = ""
for msg in history:
role = msg.get("role", "")
content = msg.get("content", "")
if role and content:
if role.lower().startswith("user"):
ctx += f"User: {content}\n"
else:
ctx += f"Bot: {content}\n"
return ctx
def chat(state: List[Any], message: str):
"""
state is the Gradio chatbot state.
We support both:
- tuples: [("hi","hello"), ...]
- messages: [{"role":"user","content":"hi"}, {"role":"assistant","content":"hello"}, ...]
Gradio will pass state back as-is.
"""
# detect format
context = ""
if state and isinstance(state[0], dict):
# messages format
context = history_to_context_from_messages(state)
elif state and isinstance(state[0], (list, tuple)):
# nested list/tuple format
# convert [(user,bot), ...] -> context
context = history_to_context_from_tuples(state)
else:
# empty or unknown -> fine
context = ""
context += f"User: {message}\nBot:"
reply = generate_reply(context)
# append to state in messages format (preferred)
# we'll append two entries: user then assistant
# If original state was tuples, convert reply to tuple for compatibility
if state and isinstance(state[0], dict):
state.append({"role":"user","content": message})
state.append({"role":"assistant","content": reply})
return state, state
else:
# use tuples format for backward compatibility
state.append((message, reply))
return state, state
with gr.Blocks() as demo:
gr.Markdown("## 🤖 Anuj's Chatbot — stable (messages format)")
# Use the new 'messages' type to avoid deprecation warning
chatbot = gr.Chatbot(type="messages")
state = gr.State([])
with gr.Row():
msg = gr.Textbox(show_label=False, placeholder="Type a message and press Enter...")
msg.submit(chat, [state, msg], [state, chatbot])
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860)
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