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import spaces
import gradio as gr
import torch
import subprocess
import requests
from gradio import State
# Function to start the ochat server
@spaces.GPU
def start_ochat_server():
print(f"Is CUDA available: {torch.cuda.is_available()}")
print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
command = [
"python", "-m", "ochat.serving.openai_api_server",
"--model", "openchat/openchat_3.5"
]
# Start the server in a separate process
try:
subprocess.Popen(command)
return "ochat server started successfully"
except Exception as e:
return f"Failed to start ochat server: {e}"
start_ochat_server()
def user(message, history):
return "", history + [[message, None]]
def bot(history):
return chat_with_ochat(history[-1][0]), history + [[None, chat_with_ochat(history[-1][0])]]
# Function to send a message to the ochat server and get a response
def chat_with_ochat(message):
url = "http://0.0.0.0:18888/v1/chat/completions"
headers = {"Content-Type": "application/json"}
data = {
"model": "openchat_3.5",
"messages": [{"role": "user", "content": message}]
}
try:
response = requests.post(url, json=data, headers=headers)
if response.status_code == 200:
return response.json()['choices'][0]['message']['content']
else:
return f"Error: Server responded with status code {response.status_code}"
except requests.RequestException as e:
return f"Error: {e}"
# Create a Gradio Blocks interface with session state
with gr.Blocks(theme=gr.themes.Soft()) as app:
gr.Markdown("## vLLM OpenChat-3.5 Interface")
gr.Markdown("Run on your own machine using this command: ```docker run -it -p 7860:7860 --platform=linux/amd64 --gpus all \
registry.hf.space/macadeliccc-openchat-3-5-chatbot:latest python app.py```")
with gr.Row():
message = gr.Textbox(label="Your Message", placeholder="Type your message here")
chatbot = gr.Chatbot()
clear = gr.Button("Clear")
chat_history = State([]) # Session state for chat history
message.submit(user, [message, chatbot], [message, chatbot], queue=False).then(
chat_with_ochat, chatbot, chatbot
)
clear.click(lambda: None, None, chatbot, queue=False)
app.launch()