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import gradio as gr |
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from huggingface_hub import InferenceClient |
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") |
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def respond(message, history, system_message, max_tokens, temperature, top_p): |
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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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for message in client.chat_completion( |
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messages, |
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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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): |
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token = message.choices[0].delta.content |
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response += token |
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yield response |
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demo = gr.ChatInterface( |
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fn=respond, |
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additional_inputs=[ |
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gr.Textbox(lines=2, label="System Message", placeholder="You are a helpful assistant."), |
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gr.Slider(0, 1024, value=256, step=1, label="Max Tokens"), |
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gr.Slider(0, 1, value=0.7, step=0.01, label="Temperature"), |
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gr.Slider(0, 1, value=0.9, step=0.01, label="Top-p") |
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], |
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title="Chat with Zephyr-7b", |
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description="Chatbot powered by Hugging Face Inference API." |
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) |
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demo.launch() |
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