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Aamir commited on
Create chatbot.app
Browse files- chatbot.app +66 -0
chatbot.app
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import streamlit as st
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from streamlit_chat import message
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import random
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# Title and UI Customization
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st.set_page_config(page_title="AI Chatbot", page_icon="🤖", layout="wide")
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st.markdown(
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"""
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<style>
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.main {background-color: #f5f7fa;}
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.stButton button {background-color: #6200EE; color: white; border-radius: 12px;}
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#chat-container {animation: fadeIn 2s ease-in;}
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@keyframes fadeIn {from {opacity: 0;} to {opacity: 1;}}
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</style>
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""",
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unsafe_allow_html=True,
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)
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# Load Hugging Face Model
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def load_model():
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model_name = "gpt2" # Replace with your preferred Hugging Face model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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return tokenizer, model
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tokenizer, model = load_model()
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# Store Chat History
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if "chat_history" not in st.session_state:
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st.session_state.chat_history = []
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# User Interface
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def chatbot_ui():
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st.markdown(
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"""
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<div id="chat-container" style="text-align: center;">
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<h1>🚀 AI Chatbot</h1>
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<p>Ask me anything, and I'll do my best to help you!</p>
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</div>
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""",
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unsafe_allow_html=True,
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)
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user_input = st.text_input(🔍"Type your question:", "")
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if st.button("Send") and user_input:
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generate_response(user_input)
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# Display Chat History
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for i, chat in enumerate(st.session_state.chat_history):
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if chat['role'] == 'user':
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message(chat['content'], is_user=True, key=f'user_{i}')
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else:
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message(chat['content'], key=f'bot_{i}')
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# Generate Response
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def generate_response(user_input):
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inputs = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors="pt")
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outputs = model.generate(inputs, max_length=200, num_return_sequences=1, do_sample=True, temperature=0.7)
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bot_reply = tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Update Chat History
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st.session_state.chat_history.append({"role": "user", "content": user_input})
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st.session_state.chat_history.append({"role": "bot", "content": bot_reply})
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chatbot_ui()
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