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| import gradio as gr | |
| import os | |
| from openai import OpenAI | |
| async def generate_response(user_input): | |
| client = OpenAI( | |
| base_url="https://api-inference.huggingface.co/v1/", | |
| api_key=os.getenv('HUGGINGFACE_API_KEY') | |
| ) | |
| messages = [ | |
| {"role": "user", "content": user_input} | |
| ] | |
| response = client.chat.completions.create( | |
| model= 'meta-llama/Llama-3.1-70B-Instruct', | |
| messages=messages, | |
| max_tokens=16384, | |
| max_completion_tokens=16384 | |
| ) | |
| return response.choices[0].message.content | |
| demo = gr.Interface( | |
| fn=generate_response, | |
| inputs=gr.Textbox(label="Your message"), | |
| outputs=gr.Textbox(label="AI Response"), | |
| title="AI Chat Interface", | |
| description="Chat with Llama 3.1 Nemotron" | |
| ) | |
| demo.launch() |