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import gradio as gr |
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from huggingface_hub import InferenceClient |
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client = InferenceClient("mradermacher/airoboros_none_resp_gpt-4o-mini_inst_gpt-4o_resp-GGUF") |
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def respond(messages, system_message, max_tokens, temperature, top_p): |
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chat_messages = [{"role": "system", "content": system_message}] + messages |
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response = "" |
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prompt = "" |
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for msg in chat_messages: |
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role = msg.get("role", "") |
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content = msg.get("content", "") |
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if role == "system": |
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prompt += f"System: {content}\n" |
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elif role == "user": |
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prompt += f"User: {content}\n" |
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elif role == "assistant": |
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prompt += f"Assistant: {content}\n" |
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prompt += "Assistant: " |
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generation = client.text_generation( |
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prompt, |
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max_new_tokens=max_tokens, |
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temperature=temperature, |
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top_p=top_p, |
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stream=True, |
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) |
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for token in generation: |
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response += token.text |
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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(value="You are a friendly Chatbot.", 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( |
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minimum=0.1, |
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maximum=1.0, |
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value=0.95, |
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step=0.05, |
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label="Top-p (nucleus sampling)", |
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), |
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], |
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type="messages", |
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) |
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if __name__ == "__main__": |
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demo.launch() |
