#!/usr/bin/env python3 import os import json import requests import gradio as gr ENDPOINT = os.getenv("VLLM_ENDPOINT") MODEL = os.getenv("VLLM_MODEL") if not ENDPOINT or not MODEL: raise ValueError("VLLM_ENDPOINT and VLLM_MODEL environment variables must be set") def respond( message, history: list[dict[str, str]], system_message, max_tokens, temperature, top_p, ): """ Send messages to vLLM endpoint and stream the response. """ messages = [{"role": "system", "content": system_message}] messages.extend(history) messages.append({"role": "user", "content": message}) payload = { "model": MODEL, "messages": messages, "max_tokens": max_tokens, "temperature": temperature, "top_p": top_p, "stream": True } try: response = requests.post( ENDPOINT, headers={"Content-Type": "application/json"}, data=json.dumps(payload), stream=True ) response.raise_for_status() accumulated_response = "" for line in response.iter_lines(): if line: line = line.decode('utf-8') if line.startswith('data: '): line = line[6:] # Remove 'data: ' prefix if line.strip() == '[DONE]': break try: chunk = json.loads(line) if 'choices' in chunk and len(chunk['choices']) > 0: delta = chunk['choices'][0].get('delta', {}) content = delta.get('content', '') if content: accumulated_response += content yield accumulated_response except json.JSONDecodeError: continue except Exception as e: yield f"Error: {str(e)}" chatbot = gr.ChatInterface( respond, type="messages", additional_inputs=[ gr.Textbox(value="You are a friendly Chatbot.", label="System message"), gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), gr.Slider( minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)", ), ], ) with gr.Blocks(title="vLLM Chatbot") as demo: gr.Markdown("# 💬 Chat Interface") gr.Markdown(""" Configure the endpoint via environment variables: - `VLLM_ENDPOINT`: vLLM server URL - `VLLM_MODEL`: Model name """) chatbot.render() if __name__ == "__main__": demo.launch()