Update app.py
Browse files
app.py
CHANGED
@@ -3,89 +3,168 @@ from langchain.llms import HuggingFaceHub
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from langchain.chains import ConversationChain
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from langchain.memory import ConversationBufferMemory
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import os
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# Configure page
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st.set_page_config(
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# Title
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st.
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# Initialize session
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if "memory" not in st.session_state:
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st.session_state.memory = ConversationBufferMemory(
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# Initialize session state for chat history
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if "messages" not in st.session_state:
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st.session_state.messages = []
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# Hugging Face API token
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hf_api_token = os.environ.get("HF_API_TOKEN", "")
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if not hf_api_token:
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st.error("Hugging Face API token not found. Please set it in the Space secrets.")
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st.stop()
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# Select the appropriate model based on language
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model_name = "bigscience/bloom" if language == "English" else "bigscience/bloom"
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#
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)
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#
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# Display chat history
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for message in st.session_state.messages:
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st.markdown(message["content"])
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#
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if
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# Process the user input
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if prompt:
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# Add user message to chat history
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st.session_state.messages.append({"role": "user", "content": prompt})
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# Display user message
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with st.chat_message("user"):
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st.markdown(prompt)
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# Display assistant response
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with st.chat_message("assistant"):
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with st.spinner("
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with st.sidebar:
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st.header("About this Chatbot")
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if language == "English":
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st.
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else:
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st.
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from langchain.chains import ConversationChain
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from langchain.memory import ConversationBufferMemory
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import os
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from datetime import datetime, timedelta
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# Configure page
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st.set_page_config(
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page_title="Tourism Chatbot",
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page_icon="🌍",
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layout="wide"
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)
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# Title with better styling
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st.markdown("""
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<h1 style='text-align: center; color: #2E86C1;'>
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Tourism Assistant - مساعد السياحة
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</h1>
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""", unsafe_allow_html=True)
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# Initialize session states
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if "memory" not in st.session_state:
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st.session_state.memory = ConversationBufferMemory(
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return_messages=True,
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memory_key="chat_history"
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)
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if "messages" not in st.session_state:
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st.session_state.messages = []
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if "last_request" not in st.session_state:
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st.session_state.last_request = datetime.now() - timedelta(seconds=10)
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# Language selector with better styling
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language = st.selectbox(
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"Choose Language / اختر اللغة",
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["English", "العربية"],
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key="lang_select"
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)
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# Hugging Face API token with better error handling
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try:
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hf_api_token = os.environ["HF_API_TOKEN"]
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except KeyError:
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st.error("""
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Hugging Face API token not found.
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Please set it in the Space secrets as HF_API_TOKEN.
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""")
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st.stop()
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# Improved model selection with better Arabic support
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model_config = {
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"English": {
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"repo_id": "google/flan-t5-large",
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"params": {"temperature": 0.7, "max_length": 512}
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},
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"العربية": {
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"repo_id": "aubmindlab/aragpt2-base",
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"params": {"temperature": 0.5, "max_length": 1024}
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}
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}
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# Initialize the language model with error handling
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try:
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llm = HuggingFaceHub(
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repo_id=model_config[language]["repo_id"],
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huggingfacehub_api_token=hf_api_token,
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model_kwargs=model_config[language]["params"]
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)
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conversation = ConversationChain(
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llm=llm,
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memory=st.session_state.memory,
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verbose=False
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)
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except Exception as e:
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st.error(f"Failed to initialize model: {str(e)}")
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st.stop()
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# Display chat history with avatars
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for message in st.session_state.messages:
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avatar = "🧑" if message["role"] == "user" else "🤖"
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with st.chat_message(message["role"], avatar=avatar):
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st.markdown(message["content"])
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# Rate limiting check
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if (datetime.now() - st.session_state.last_request).seconds < 2:
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st.warning("Please wait a moment before sending another message.")
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st.stop()
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# User input with language-specific placeholders
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prompt = st.chat_input(
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"Ask about tourist destinations..." if language == "English"
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else "اسأل عن الوجهات السياحية..."
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)
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if prompt:
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# Update last request time
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st.session_state.last_request = datetime.now()
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# Add user message to chat history
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st.session_state.messages.append({"role": "user", "content": prompt})
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# Display user message
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with st.chat_message("user", avatar="🧑"):
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st.markdown(prompt)
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# Display assistant response
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with st.chat_message("assistant", avatar="🤖"):
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with st.spinner("Generating response..." if language == "English" else "جارٍ تحضير الرد..."):
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try:
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# Enhanced prompt engineering
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if language == "English":
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full_prompt = f"""You are an expert tourism assistant. Provide detailed, helpful information about:
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- Travel destinations
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- Cultural experiences
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- Local customs
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- Safety advice
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Question: {prompt}
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Answer:"""
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else:
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full_prompt = f"""أنت مساعد سياحي خبير. قدم معلومات مفيدة ومفصلة حول:
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- الوجهات السياحية
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- التجارب الثقافية
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- العادات المحلية
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- نصائح السلامة
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السؤال: {prompt}
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الجواب:"""
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response = conversation.predict(input=full_prompt)
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st.markdown(response)
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# Add to chat history
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st.session_state.messages.append({"role": "assistant", "content": response})
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except Exception as e:
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st.error(f"Error generating response: {str(e)}")
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st.session_state.messages.append({
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"role": "assistant",
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"content": "Sorry, I encountered an error. Please try again."
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})
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# Enhanced sidebar with clear sections
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with st.sidebar:
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st.header("ℹ️ About this Chatbot")
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if language == "English":
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st.markdown("""
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### Features:
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- Bilingual English/Arabic support
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- Tourism expert knowledge
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- Conversation memory
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**Note:** Responses may take 10-20 seconds to generate.
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""")
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else:
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st.markdown("""
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### الميزات:
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- دعم ثنائي اللغة الإنجليزية/العربية
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- معرفة خبيرة بالسياحة
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- ذاكرة المحادثة
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**ملاحظة:** قد يستغرق الرد 10-20 ثانية.
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""")
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st.markdown("---")
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st.markdown("Made with ❤️ using [Streamlit](https://streamlit.io/) and [LangChain](https://langchain.com/)")
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