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import gradio as gr
from openai import OpenAI, APIError
import os
import tenacity
import asyncio
ACCESS_TOKEN = os.getenv("HF_TOKEN")
client = OpenAI(
base_url="https://api-inference.huggingface.co/v1/",
api_key=ACCESS_TOKEN,
)
# Retry logic with tenacity for handling API rate limits
@tenacity.retry(wait=tenacity.wait_exponential(multiplier=1, min=4, max=10), stop=tenacity.stop_after_attempt(5))
async def respond(
message,
system_message,
max_tokens,
temperature,
top_p,
):
try:
# Only use the system message and the current message for the response
messages = [{"role": "system", "content": system_message},
{"role": "user", "content": message}]
response = ""
# Properly stream chat completions using dot notation
stream = client.chat.completions.create(
model="NousResearch/Hermes-3-Llama-3.1-8B",
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
messages=messages,
)
# Stream response and concatenate tokens
for chunk in stream:
if hasattr(chunk.choices[0].delta, 'content'):
token = chunk.choices[0].delta.content
response += token
return response
except APIError as e:
# Handle both string and dict types of error bodies
error_details = e.body
if isinstance(error_details, dict):
error_type = error_details.get("type", "Unknown")
error_code = error_details.get("code", "Unknown")
error_param = error_details.get("param", "Unknown")
error_message = error_details.get("message", "An error occurred.")
error_str = f"{error_type}: {error_message} (code: {error_code}, param: {error_param})"
else:
error_str = f"Error: {error_details}"
print(f"APIError: {error_str}")
return error_str
except Exception as e:
print(f"Exception: {e}")
return "Error occurred. Please try again."
# Async Gradio function to handle user input and response generation without history
async def generate_response(message, system_message, max_tokens, temperature, top_p):
response = await respond(message, system_message, max_tokens, temperature, top_p)
return response
def launch_app():
try:
demo = gr.Blocks()
with demo:
gr.Markdown("# Chatbot")
message = gr.Textbox(label="Message")
system_message = gr.Textbox(label="System message")
max_tokens = gr.Slider(minimum=1, maximum=2048, value=2048, step=1, label="Max new tokens")
temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P")
response = gr.Text(label="Response")
# Use the async version of generate_response without history
gr.Button("Generate Response").click(
generate_response,
inputs=[message, system_message, max_tokens, temperature, top_p],
outputs=[response],
show_progress=False,
)
demo.launch(show_error=True)
except KeyError as e:
print(f"Error: {e}")
print("Please try again.")
if __name__ == "__main__":
launch_app() |