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import gradio as gr |
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import os |
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import requests |
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API_TOKEN = os.environ.get("HF_HUB_API_TOKEN") |
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API_URL = "https://api-inference.huggingface.co/models/Qwen/Qwen3-8B-Base" |
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headers = { |
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"Authorization": f"Bearer {API_TOKEN}", |
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"Content-Type": "application/json", |
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} |
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def respond(message, history, system_message, max_tokens, temperature, top_p): |
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payload = { |
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"inputs": { |
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"past_user_inputs": [m[0] for m in history], |
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"generated_responses": [m[1] for m in history], |
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"text": message |
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}, |
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"parameters": { |
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"temperature": temperature, |
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"max_new_tokens": max_tokens, |
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"top_p": top_p |
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} |
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} |
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try: |
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response = requests.post(API_URL, headers=headers, json=payload) |
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if response.status_code != 200: |
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return f"[HTTP {response.status_code}] {response.text}" |
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result = response.json() |
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if isinstance(result, dict) and result.get("error"): |
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return f"[ERROR] {result['error']}" |
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return result[0]["generated_text"] |
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except Exception as e: |
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return f"[Exception] {str(e)}" |
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demo = gr.ChatInterface( |
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respond, |
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additional_inputs=[ |
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gr.Textbox(value="You are a helpful assistant.", label="System message"), |
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), |
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), |
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gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"), |
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], |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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