aguinaldomavenda0 commited on
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c4ae273
1 Parent(s): b6685c3

Create app.py

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  1. app.py +97 -0
app.py ADDED
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+
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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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+ """
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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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+ #client = InferenceClient("unsloth/Llama-3.2-1B-Instruct")
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+
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+
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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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+ messages = [{"role": "system", "content": system_message}]
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+
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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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+
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+ messages.append({"role": "user", "content": message})
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+
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+ response = ""
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+
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+
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+ try:
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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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+ # Ensure the message has a valid structure
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+ if not message or not isinstance(message, dict):
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+ continue
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+
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+ try:
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+ # Extract content and finish reason
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+ content = message.choices[0].delta.content
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+ finish_reason = message.choices[0].finish_reason
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+
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+ # Check if the content is empty
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+ if content.strip() == "":
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+ # If the finish reason is 'stop', it's expected and we can break the loop
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+ if finish_reason == "stop":
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+ print("Stream ended normally.")
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+ break
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+ else:
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+ print("Received unexpected empty content, skipping...")
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+ continue
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+
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+ response += content
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+ yield response
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+
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+ except (AttributeError, IndexError, KeyError) as e:
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+ print(f"Error processing message: {e}")
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+ continue
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+
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+ except Exception as e:
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+ print(f"Unexpected error: {e}")
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+ yield "An error occurred while generating the response."
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+
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+ # Final check if the response is empty
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+ if response.strip() == "":
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+ yield "No response generated. Please try again or adjust the settings."
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+
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+
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+ """
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+ For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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+ """
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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 friendly Chatbot. Your name is Juninho.", 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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+ )
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+
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+
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+ if __name__ == "__main__":
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+ demo.launch()