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Update 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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#
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st.set_page_config(page_title="AI Chatbot", layout="centered")
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# Load the model pipeline
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@st.cache_resource
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def load_pipeline():
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model_name = "Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2"
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pipe = load_pipeline()
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# App UI
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st.title("🤖 AI Chatbot")
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st.markdown(
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"""
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Welcome to the **AI Chatbot** powered by Hugging Face's **Llama-3.1-8B-Lexi-Uncensored-V2** model.
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"""
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)
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#
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user_input = st.text_area(
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"Your Message",
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placeholder="Type your message here...",
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height=100
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)
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#
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if st.button("Generate Response"):
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if user_input.strip():
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with st.spinner("Generating response..."):
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else:
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st.warning("Please enter a message before clicking the button.")
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# Footer
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st.markdown("---")
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st.markdown("Made with ❤️ using [Streamlit](https://streamlit.io) and [Hugging Face](https://huggingface.co).")
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import streamlit as st
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from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
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# Streamlit app configuration
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st.set_page_config(page_title="AI Chatbot", layout="centered")
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# Load the model pipeline
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@st.cache_resource
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def load_pipeline():
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model_name = "Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2"
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# Load tokenizer and model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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device_map="auto", # Use GPU if available
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rope_scaling=None # Avoid issues with rope_scaling
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)
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return pipeline("text-generation", model=model, tokenizer=tokenizer)
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pipe = load_pipeline()
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# Streamlit App UI
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st.title("🤖 AI Chatbot")
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st.markdown(
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"""
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Welcome to the **AI Chatbot** powered by Hugging Face's **Llama-3.1-8B-Lexi-Uncensored-V2** model.
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Type your message below and interact with the AI!
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"""
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)
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# User input area
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user_input = st.text_area(
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"Your Message",
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placeholder="Type your message here...",
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height=100
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)
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# Button to generate response
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if st.button("Generate Response"):
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if user_input.strip():
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with st.spinner("Generating response..."):
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try:
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response = pipe(user_input, max_length=150, num_return_sequences=1)
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st.text_area("Response", value=response[0]["generated_text"], height=200)
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except Exception as e:
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st.error(f"An error occurred: {e}")
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else:
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st.warning("Please enter a message before clicking the button.")
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# Footer
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st.markdown("---")
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st.markdown("Made with ❤️ using [Streamlit](https://streamlit.io) and [Hugging Face](https://huggingface.co).")
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