Update app.py
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app.py
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import gradio as gr
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from
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message,
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history: list[dict[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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hf_token: gr.OAuthToken,
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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(token=hf_token.token, model="openai/gpt-oss-20b")
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):
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choices = message.choices
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token = ""
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if len(choices) and choices[0].delta.content:
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token = choices[0].delta.content
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"""
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"""
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chatbot = gr.ChatInterface(
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respond,
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type="messages",
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additional_inputs=[
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gr.Textbox(value="You are a friendly Chatbot.", 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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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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import torch
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# Model setup
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model_name = "IniNLP247/Kenko-mental-health-llama-3-model"
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print("🔄 Loading Kenko Mental Health Model...")
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# Load tokenizer and model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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if tokenizer.pad_token is None:
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tokenizer.pad_token = tokenizer.eos_token
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype=torch.float16, # Changed from 'dtype' to 'torch_dtype'
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device_map="auto"
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)
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# Create pipeline for easier inference
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pipe = pipeline(
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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return_full_text=False,
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max_new_tokens=300,
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temperature=0.7,
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top_p=0.9,
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repetition_penalty=1.1,
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pad_token_id=tokenizer.pad_token_id
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)
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print("✅ Model loaded successfully!")
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def chat_with_kenko(message, history):
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"""Chat function for Gradio interface"""
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# Build conversation context
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conversation = ""
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for user_msg, bot_msg in history:
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conversation += f"User: {user_msg}\nKenko: {bot_msg}\n\n"
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# Create prompt in instruction format
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prompt = f"""### Instruction:
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You are Kenko, a compassionate mental health therapist. Provide empathetic, helpful, and professional responses to support the user's mental wellbeing.
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{conversation}User: {message}
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### Response:
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"""
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# Generate response
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try:
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response = pipe(prompt)[0]['generated_text']
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return response.strip()
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except Exception as e:
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return f"I'm sorry, I'm having trouble processing your message right now. Error: {str(e)}"
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# Custom CSS for a calming interface
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css = """
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.gradio-container {
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font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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}
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"""
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# Create Gradio interface
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with gr.Blocks(
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title="Kenko - Mental Health Assistant",
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theme=gr.themes.Soft(),
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css=css
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) as demo:
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gr.Markdown("""
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# 🧠💚 Kenko - Your Mental Health Assistant
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Welcome! I'm Kenko, an AI mental health therapist here to provide support, guidance, and a listening ear.
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Feel free to share what's on your mind - I'm here to help you through whatever you're experiencing.
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*Please remember: I'm an AI assistant and cannot replace professional mental health care. In crisis situations, please contact emergency services or a mental health professional.*
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""")
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chatbot = gr.Chatbot(
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height=500,
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show_label=False,
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container=True,
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bubble_full_width=False,
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avatar_images=("👤", "🧠")
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)
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with gr.Row():
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msg = gr.Textbox(
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placeholder="Share what's on your mind... (press Enter to send)",
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container=False,
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scale=7,
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lines=2,
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max_lines=4
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)
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send_btn = gr.Button("Send 💬", scale=1, variant="primary")
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with gr.Row():
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clear_btn = gr.Button("🗑️ Clear Chat", scale=1, variant="secondary")
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examples_btn = gr.Button("💡 Example Topics", scale=1, variant="secondary")
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# Example prompts
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with gr.Row(visible=False) as examples_row:
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gr.Examples(
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examples=[
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"I've been feeling really anxious lately and I don't know why.",
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"I'm having trouble sleeping and my mind won't stop racing.",
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"I feel overwhelmed with work and personal responsibilities.",
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"I'm struggling with low self-esteem and negative thoughts.",
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"I'm having difficulty in my relationships.",
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"I feel lonely and isolated.",
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"I'm dealing with grief and loss.",
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"I want to build better coping strategies."
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],
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inputs=msg,
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label="Try these conversation starters:"
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)
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with gr.Accordion("ℹ️ About Kenko", open=False):
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gr.Markdown("""
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**What I can help with:**
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- Active listening and emotional support
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- Coping strategies and stress management techniques
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- Guidance on anxiety, depression, and mood concerns
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- Relationship and communication advice
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- Mindfulness and self-care suggestions
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- Building healthy habits and routines
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**Important Notes:**
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- I'm an AI trained to provide mental health support
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- For immediate crisis support, contact emergency services (911) or crisis hotlines
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- Consider professional therapy for ongoing mental health needs
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- I don't diagnose conditions or prescribe medications
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**Privacy:** Your conversations are not stored or shared.
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""")
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def respond(message, chat_history):
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if not message.strip():
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return "", chat_history
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bot_response = chat_with_kenko(message, chat_history)
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chat_history.append((message, bot_response))
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return "", chat_history
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def toggle_examples():
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return gr.Row(visible=True)
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msg.submit(respond, [msg, chatbot], [msg, chatbot])
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send_btn.click(respond, [msg, chatbot], [msg, chatbot])
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clear_btn.click(lambda: [], outputs=chatbot)
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examples_btn.click(toggle_examples, outputs=examples_row)
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if __name__ == "__main__":
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demo.launch() # Simplified for HF Spaces - no need for server config
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