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app.py

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+import os
+from dotenv import load_dotenv
+import streamlit as st
+from langchain_openai import ChatOpenAI
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+from langchain.document_loaders import WikipediaLoader  # Import for loading Wikipedia articles
+
+# Load environment variables from a .env file
+load_dotenv()  # Adjust the path if necessary
+
+os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
+
+# Create a prompt template
+prompt = ChatPromptTemplate.from_messages(
+    [
+        ('system', "You are a helpful assistant. Please respond to the question asked based mostly on the context provided. Context: {context}. If not present in context, say not present in the given context"),
+        ("user", "Question: {question}")
+    ]
+)
+
+st.title("Question and Answering")
+
+# Initialize session state variables if not present
+if "input_type" not in st.session_state:
+    st.session_state.input_type = "Direct Text Input"
+if "input_text" not in st.session_state:
+    st.session_state.input_text = ""
+if "context_text" not in st.session_state:
+    st.session_state.context_text = ""
+
+# Function to reset session state when switching input type
+def reset_inputs():
+    st.session_state.input_text = ""
+    st.session_state.context_text = ""
+
+# Sidebar for selecting input type with reset callback
+input_type = st.sidebar.selectbox(
+    'Select Input Type',
+    ('Direct Text Input', 'Wikipedia Topic'),
+    key="input_type",
+    on_change=reset_inputs
+)
+
+# Handle input based on the selected type
+if input_type == 'Direct Text Input':
+    # Direct Text Input Mode
+    context_text = st.text_area("Enter your context here:", key="direct_context")
+    question = st.text_input(
+        "What question do you have in mind?", 
+        value=st.session_state.input_text,
+        key="direct_question"
+    )
+    st.session_state.input_text = question
+    st.session_state.context_text = context_text
+else:
+    # Wikipedia Topic Mode
+    topic = st.text_input("Enter Wikipedia Topic:", key="wiki_topic")
+    if topic:
+        # Load the Wikipedia article
+        full_content = WikipediaLoader(query=topic, load_max_docs=2).load()
+        
+        # Limit the content size (e.g., first 1000 characters)
+        max_length = 1000
+        st.session_state.context_text = full_content[:max_length]  # Truncate to max_length
+        if len(full_content) > max_length:
+            st.session_state.context_text += "..."  # Indicate that the text has been truncated
+
+    # Ensure the question input starts empty
+    question = st.text_input(
+        "What question do you have in mind?", 
+        value=st.session_state.input_text,
+        key="wiki_question"
+    )
+    st.session_state.input_text = question
+
+# Initialize the OpenAI model
+llm = ChatOpenAI(model="gpt-3.5-turbo")  # Use OpenAI model
+output_parser = StrOutputParser()
+chain = prompt | llm | output_parser
+
+if st.session_state.input_text:
+    # Use context_text if provided, otherwise use the loaded Wikipedia content
+    response = chain.invoke({
+        "question": st.session_state.input_text, 
+        "context": st.session_state.context_text
+    })
+    st.write(response)

requirements.txt

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+langchain
+python-dotenv
+langchain-community
+bs4 #beautifulSoup
+Wikipedia
+langchain-text-splitters
+langchain-openai
+chromadb
+sentence-transformers
+langchain_huggingface
+faiss-cpu
+langchain_chroma
+beautifulsoup4
+streamlit