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#!/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() |