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import gradio as gr |
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from openai import OpenAI, APIError |
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import os |
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import tenacity |
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import asyncio |
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ACCESS_TOKEN = os.getenv("HF_TOKEN") |
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client = OpenAI( |
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base_url="https://api-inference.huggingface.co/v1/", |
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api_key=ACCESS_TOKEN, |
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) |
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@tenacity.retry(wait=tenacity.wait_exponential(multiplier=1, min=4, max=10)) |
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async def respond( |
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message, |
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history, |
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system_message, |
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max_tokens, |
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temperature, |
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top_p, |
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): |
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try: |
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messages = [{"role": "system", "content": system_message}] |
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for val in history: |
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if val[0]: |
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messages.append({"role": "user", "content": val[0]}) |
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if val[1]: |
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messages.append({"role": "assistant", "content": val[1]}) |
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messages.append({"role": "user", "content": message}) |
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response = "" |
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stream = client.chat.completions.create( |
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model="NousResearch/Hermes-3-Llama-3.1-8B", |
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max_tokens=max_tokens, |
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stream=True, |
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temperature=temperature, |
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top_p=top_p, |
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messages=messages, |
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) |
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for chunk in stream: |
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if hasattr(chunk.choices[0].delta, 'content'): |
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token = chunk.choices[0].delta.content |
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response += token |
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return response |
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except APIError as e: |
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error_details = e.body |
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error_type = error_details.get("type") |
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error_code = error_details.get("code") |
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error_param = error_details.get("param") |
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error_message = error_details.get("message") |
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if error_type: |
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error_str = f"{error_type}: {error_message} (code: {error_code}, param: {error_param})" |
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else: |
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error_str = "An error occurred during streaming" |
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print(f"Error: {error_str}") |
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return error_str |
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except Exception as e: |
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print(f"Error: {e}") |
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return "Error occurred. Please try again." |
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def launch_app(): |
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try: |
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demo = gr.Blocks() |
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with demo: |
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gr.Markdown("# Chatbot") |
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message = gr.Textbox(label="Message") |
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history = gr.State([["", ""]]) |
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system_message = gr.Textbox(label="System message") |
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max_tokens = gr.Slider(minimum=1, maximum=2048, value=2048, step=1, label="Max new tokens") |
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temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature") |
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top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P") |
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response = gr.Text(label="Response") |
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def generate_response(message, history, system_message, max_tokens, temperature, top_p): |
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new_history = history + [[message, ""]] |
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response = asyncio.run(respond(message, history, system_message, max_tokens, temperature, top_p)) |
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new_history[-1][1] = response |
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return response, new_history |
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gr.Button("Generate Response").click( |
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generate_response, |
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inputs=[message, history, system_message, max_tokens, temperature, top_p], |
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outputs=[response, history], |
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show_progress=False, |
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) |
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demo.launch(show_error=True) |
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except KeyError as e: |
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print(f"Error: {e}") |
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print("Please try again.") |
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if __name__ == "__main__": |
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launch_app() |
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