Update app.py

app.py

@@ -2,7 +2,6 @@ import streamlit as st
 import requests
 from bs4 import BeautifulSoup
 from transformers import pipeline
-from langchain import LanguageModelChain, PromptTemplate, QAPrompt
 
 # Function to scrape text content from a URL
 def scrape_text_from_url(url):
@@ -24,15 +23,6 @@ def scrape_text_from_url(url):
 def load_qa_model():
     return pipeline('question-answering')
 
-# Create LangChain pipeline
-def create_langchain_pipeline(model):
-    template = PromptTemplate(
-        input_variables=["context", "question"],
-        template="Context: {context}\nQuestion: {question}\nAnswer:"
-    )
-    qa_prompt = QAPrompt(template=template)
-    return LanguageModelChain(llm=model, prompt=qa_prompt)
-
 # Streamlit app
 st.title("Question Answering from URL")
 url = st.text_input("Enter the URL of the webpage:")
@@ -41,9 +31,8 @@ if url:
     if text:
         st.write("Webpage content successfully retrieved!")
         qa_model = load_qa_model()
-        langchain_pipeline = create_langchain_pipeline(qa_model)
 
         question = st.text_input("Enter your question:")
         if question:
-            answer = langchain_pipeline.run(context=text, question=question)
-            st.write("Answer:", answer)
+            result = qa_model(question=question, context=text)
+            st.write("Answer:", result['answer'])