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Upload app.py with huggingface_hub

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  1. app.py +63 -0
app.py ADDED
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+
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+ SYSTEM_PROMPT = "My primary function is to provide assessments for plants. These assessments are relevant, useful, and accurate. Keep in mind that I am user-friendly and professional."
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+ TITLE = "Plant Assessment Pro"
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+ EXAMPLE_INPUT = "Plant Health Assessment"
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+ import gradio as gr
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+ from gradio_client import Client
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+ import os
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+ import requests
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+
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+ tulu = "https://tonic1-tulu.hf.space/--replicas/2l5qd/"
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+
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+
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+ def predict_beta(message, chatbot=[], system_prompt=""):
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+ client = Client(tulu)
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+
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+ try:
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+ max_new_tokens = 650
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+ temperature = 0.4
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+ top_p = 0.9
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+ repetition_penalty = 0.9
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+ advanced = True
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+
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+ # Making the prediction
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+ result = client.predict(
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+ message,
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+ system_prompt,
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+ max_new_tokens,
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+ temperature,
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+ top_p,
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+ repetition_penalty,
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+ advanced,
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+ fn_index=0
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+ )
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+ print("Raw API Response:", result) # Debugging print
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+ if result is not None:
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+ print("Processed bot_message:", result) # Debugging print
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+ return result
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+ else:
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+ print("No response or empty response from the model.") # Debugging print
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+ return None
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+
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+ except Exception as e:
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+ error_msg = f"An error occurred: {str(e)}"
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+ print(error_msg) # Debugging print
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+ return None
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+
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+ def test_preview_chatbot(message, history):
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+ response = predict_beta(message, history, SYSTEM_PROMPT)
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+ return response
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+
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+
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+ welcome_preview_message = f"""
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+ Welcome to **{TITLE}** using [Allen AI/Tulu](https://huggingface.co/allenai/tulu-2-dpo-13b) ! Say something like:
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+
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+ ''{EXAMPLE_INPUT}''
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+ """
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+
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+ chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)])
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+ textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT)
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+
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+ demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview)
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+
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+ demo.launch()