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app.py
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import gradio as gr
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from huggingface_hub import InferenceClient
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"""
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For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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"""
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# Load the inference client
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client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
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# Function to handle the chat interaction
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def respond(
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message,
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history: list[tuple[str, str]],
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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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# Prepare the system message and chat history
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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]: # User's message
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messages.append({"role": "user", "content": val[0]})
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if val[1]: # Assistant's response
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messages.append({"role": "assistant", "content": val[1]})
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# Add the new user message
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messages.append({"role": "user", "content": message})
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response = ""
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# Use `stream=True` to receive token-by-token responses
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for message in client.chat_completion(
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messages=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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use_cache=True, # Enable caching for efficiency
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):
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# Append the content of the generated token
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token = message.choices[0].delta.content
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response += token
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yield response # Stream the response incrementally to the interface
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"""
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Customize the ChatInterface using Gradio. For details, check Gradio's documentation:
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https://www.gradio.app/docs/chatinterface
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"""
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demo = gr.ChatInterface(
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fn=respond, # Function to handle the chat
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additional_inputs=[
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gr.Textbox(
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value="You are a friendly and helpful assistant.",
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label="System message",
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), # Default system message
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gr.Slider(
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minimum=1,
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maximum=2048,
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value=512,
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step=1,
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label="Max new tokens",
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), # Slider to control max token limit
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gr.Slider(
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minimum=0.1,
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maximum=2.0,
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value=0.7,
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step=0.1,
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label="Temperature",
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), # Slider to adjust 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=0.9,
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step=0.05,
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label="Top-p (nucleus sampling)",
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), # Slider to adjust top-p
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],
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title="AI Chatbot Interface",
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description="Interact with the AI model using this chat interface. Adjust generation parameters for better control.",
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)
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# Launch the Gradio interface
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if __name__ == "__main__":
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demo.launch()
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