Spaces:
Sleeping
Sleeping
mindmatters
Browse files
app.py
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import gradio as gr
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from huggingface_hub import InferenceClient
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# Replace with your chosen model
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client = InferenceClient("Qwen/Qwen2.5-7B-Instruct")
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SYSTEM_PROMPT = """
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You are MindMate, a compassionate mental health support chatbot.
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Your role is to:
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- Listen empathetically and respectfully.
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- Help users explore their feelings and thoughts.
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- Suggest healthy coping strategies and self-care techniques.
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- Encourage seeking support from trusted friends, family, counselors, therapists, or healthcare professionals when appropriate.
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- Never diagnose medical or mental health conditions.
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- Never claim to be a licensed therapist or psychologist.
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- Avoid judgmental language.
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- Be supportive, calm, and encouraging.
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If a user expresses thoughts of self-harm, suicide, or harming others:
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- Encourage them to contact emergency services or a crisis hotline immediately.
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- Encourage them to reach out to a trusted person nearby.
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- Respond with urgency, compassion, and care.
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"""
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def respond(message, history):
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# Add previous conversation
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if history:
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messages.append({"role": "assistant", "content": bot_msg})
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messages.append({"role": "user", "content": message})
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response = client.chat_completion(
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messages
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max_tokens=
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temperature=0.7
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return response.choices[0].message.content.strip()
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# 🧠 MindMate
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A supportive mental health chatbot designed to provide emotional support and coping suggestions.
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⚠️ **Disclaimer:** This chatbot is not a substitute for professional mental health care, diagnosis, or treatment. If you are experiencing a crisis or are in immediate danger, contact emergency services or a crisis hotline in your area.
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"""
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chatbot = gr.ChatInterface(
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fn=respond,
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title="🧠 MindMate",
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description=description,
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chatbot=gr.Chatbot(height=500)
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)
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chatbot.launch()
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import gradio as gr
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from huggingface_hub import InferenceClient
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client = InferenceClient("Qwen/Qwen2.5-7B-Instruct")
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def respond(message, history):
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messages = [{"role": "system", "content": "You are a friendly chatbot."}]
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if history:
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messages.extend(history)
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messages.append({"role": "user", "content": message})
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response = client.chat_completion(
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messages,
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max_tokens=100
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return response.choices[0].message.content.strip()
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chatbot = gr.ChatInterface(respond)
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chatbot.launch()
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