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create the file app.py
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app.py
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import streamlit as st
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from transformers import pipeline
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# Load a Hugging Face chat model
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@st.cache_resource
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def load_chatbot():
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return pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1", max_new_tokens=200)
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chatbot = load_chatbot()
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# Streamlit UI
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st.title("💬 Chat with Mistral (Open Source ChatGPT)")
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st.markdown("Ask me anything!")
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if "history" not in st.session_state:
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st.session_state.history = []
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user_input = st.text_input("Your message", "")
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if user_input:
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st.session_state.history.append({"role": "user", "content": user_input})
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# Construct prompt
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full_prompt = "\n".join(
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[f"{m['role'].capitalize()}: {m['content']}" for m in st.session_state.history]
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) + "\nAssistant:"
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response = chatbot(full_prompt)[0]["generated_text"]
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# Get only the new assistant response
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reply = response[len(full_prompt):].strip()
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st.session_state.history.append({"role": "assistant", "content": reply})
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# Display chat history
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for message in st.session_state.history:
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st.markdown(f"**{message['role'].capitalize()}:** {message['content']}")
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