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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 DistilBertTokenizer, DistilBertForQuestionAnswering
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import torch
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# Set
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st.
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#
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st.
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st.write("یہ ایک سادہ چیٹ بوٹ ہے جو اردو زبان میں جواب دیتا ہے۔ اپنا سوال درج کریں!")
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# Load a lightweight multilingual model
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@st.cache_resource
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def load_model():
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try:
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tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-multilingual-cased")
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model = DistilBertForQuestionAnswering.from_pretrained("distilbert-base-multilingual-cased")
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return model, tokenizer
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except Exception as e:
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st.error(f"ماڈل لوڈ کرنے میں خرابی: {str(e)}")
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return None, None
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model, tokenizer = load_model()
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if model is None or tokenizer is None:
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st.error("ماڈل یا ٹوکنائزر لوڈ نہیں ہوا۔ براہ کرم لاگز چیک کریں۔")
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st.stop()
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#
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#
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outputs = model(**inputs)
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# Since this is a QA model, we'll simulate a response
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start_scores = outputs.start_logits
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end_scores = outputs.end_logits
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start_idx = torch.argmax(start_scores)
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end_idx = torch.argmax(end_scores) + 1
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answer_tokens = inputs["input_ids"][0][start_idx:end_idx]
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response = tokenizer.decode(answer_tokens, skip_special_tokens=True)
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#
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# Display chat history
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# User input
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if prompt := st.chat_input("اپنا سوال یہاں لکھیں..."):
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st.session_state.messages.append({"role": "user", "content": prompt})
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with st.chat_message("user"):
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st.write(prompt)
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with st.chat_message("assistant"):
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with st.spinner("جواب تیار کر رہا ہوں..."):
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response = generate_response(prompt)
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st.write(response)
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st.session_state.messages.append({"role": "assistant", "content": response})
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# Sidebar
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st.sidebar.title("معلومات")
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st.sidebar.write("یہ `distilbert-base-multilingual-cased` م��ڈل استعمال کرتا ہے۔")
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import streamlit as st
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# Set the title of the app
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st.title("Urdu AI Chatbot 🤖")
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# Define intents and responses (keyword-based)
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intents = {
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"greeting": {
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"keywords": ["ہیلو", "سلام", "آداب", "حال", "کیسے ہو", "کیسے ہیں"],
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"response": "السلام علیکم! میں ٹھیک ہوں، شکریہ۔ آپ کیسے ہیں؟"
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},
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"farewell": {
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"keywords": ["الوداع", "خدا حافظ", "بعد میں ملتے ہیں"],
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"response": "خدا حافظ! آپ کا دن اچھا گزرے۔"
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},
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"thanks": {
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"keywords": ["شکریہ", "بہت شکریہ", "مہربانی"],
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"response": "خوش آمدید! کیا میں آپ کی مزید مدد کر سکتا ہوں؟"
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}
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}
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# Function to detect intent using keywords
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def detect_intent(user_input):
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user_input = user_input.lower()
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for intent, data in intents.items():
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for keyword in data["keywords"]:
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if keyword in user_input:
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return intent
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return "unknown"
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# Initialize 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 input
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user_input = st.text_input("آپ کا پیغام یہاں لکھیں:", "ہیلو، آپ کیسے ہیں؟")
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# Send button
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if st.button("بھیجیں"):
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if user_input:
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# Add user message to chat history
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st.session_state.chat_history.append(f"آپ: {user_input}")
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# Detect intent using keywords (no model needed)
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intent = detect_intent(user_input)
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# Get response based on intent
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if intent != "unknown":
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response = intents[intent]["response"]
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else:
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response = "معذرت، میں اس سوال کا جواب نہیں دے سکتا۔ براہ کرم ایک آسان سوال پوچھیں۔"
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# Add AI response to chat history
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st.session_state.chat_history.append(f"AI: {response}")
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else:
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st.warning("براہ کرم ایک پیغام لکھیں۔")
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# Display chat history
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st.write("چیٹ کی تاریخ:")
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for message in st.session_state.chat_history:
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st.write(message)
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