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Create app.py
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app.py
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import gradio as gr
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def chat(user_input, history=[]):
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"""
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Chat function that takes user input and conversation history,
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returns the model response and updates the history. Handles potential
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memory issues by clearing conversation history after a certain length.
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Args:
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user_input: String containing the user's message.
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history: List of tuples containing conversation history
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(user_message, model_response).
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Returns:
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A tuple containing the model response and updated history (limited length).
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"""
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# Update history with user input
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history.append((user_input, None))
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# Clear conversation history if it exceeds a certain length (adjust as needed)
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if len(history) > 10:
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history = history[-5:] # Keep the most recent 5 interactions
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# Access the loaded model (replace with appropriate error handling)
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model = gr.get("chatbot_model")
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# Generate response using the model (consider error handling and retries)
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response = model(user_input, max_length=50, do_sample=True)[0]['generated_text']
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# Update history with model response
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history.append((None, response))
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return response, history
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# Attempt to load the model from Hugging Face (consider error handling)
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try:
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chatbot_model = gr.load("models/lucas-w/mental-health-chatbot-3")
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except Exception as e:
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print(f"Error loading model: {e}")
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chatbot_model = None # Handle the case where model loading fails
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# Launch the Gradio interface with error handling
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if chatbot_model is not None:
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interface = gr.Interface(
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fn=chat,
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inputs="textbox",
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outputs="textbox",
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interpretation="chat",
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title="Mental Health Chatbot",
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description="Talk to a mental health assistant",
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elem_id="chat-container",
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css="""
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#chat-container {
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height: 400px;
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overflow-y: scroll;
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}
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"""
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)
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interface.launch()
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else:
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print("Failed to launch chatbot. Please check model availability and error messages.")
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