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Canstralian
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18415e8
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Parent(s):
bc15f0b
Update app.py
Browse files
app.py
CHANGED
@@ -1,9 +1,7 @@
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import gradio as gr
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from huggingface_hub import InferenceClient
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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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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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def respond(
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temperature,
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top_p,
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):
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# Set the default system message to the friendly Python chatbot message
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system_message = system_message or "You are a friendly Python code writing Chatbot. Assist with Python programming tasks, debugging, and code optimization. Provide solutions for Python-related queries, help with libraries, algorithms, and best practices, and generate clean, efficient code for various applications."
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# Prepare the conversation history and current message
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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": message})
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response = ""
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# Request the response from the model
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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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yield response
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gr.Textbox(value="You are a friendly Python code writing Chatbot. Assist with Python programming tasks, debugging, and code optimization. Provide solutions for Python-related queries, help with libraries, algorithms, and best practices, and generate clean, efficient code for various applications.", 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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label="Top-p (nucleus sampling)",
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),
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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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import gradio as gr
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from huggingface_hub import InferenceClient
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# Initialize the Inference Client
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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def respond(
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temperature,
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top_p,
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):
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system_message = system_message or "You are a friendly Python code writing Chatbot. Assist with Python programming tasks, debugging, and code optimization. Provide solutions for Python-related queries, help with libraries, algorithms, and best practices, and generate clean, efficient code for various applications."
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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": 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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yield response
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def clear_chat():
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return [], ""
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# Chatbot Interface
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demo = gr.Interface(
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fn=respond,
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inputs=[
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gr.Textbox(value="You are a friendly Python code writing Chatbot. Assist with Python programming tasks, debugging, and code optimization. Provide solutions for Python-related queries, help with libraries, algorithms, and best practices, and generate clean, efficient code for various applications.", label="System message"),
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gr.Textbox(placeholder="Enter your message here...", label="User Input", lines=2),
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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 (nucleus sampling)"),
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],
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outputs=[
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gr.Chatbot(label="Chat History"),
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gr.Textbox(label="Current Response", placeholder="Chatbot will reply here...", interactive=False)
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],
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live=True,
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allow_flagging="never", # Disable flagging
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layout="vertical",
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theme="huggingface", # Optionally, set a different theme
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)
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# Add additional features to the interface
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with demo:
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gr.Button("Clear Chat", elem_id="clear-chat").click(clear_chat, outputs=["chatbot", "textbox"])
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if __name__ == "__main__":
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demo.launch()
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