Update app.py

app.py

@@ -1,15 +1,12 @@
 import os
-# Set User Agent to prevent WebBaseLoader crash
+# Fix WebBaseLoader crash
 os.environ["USER_AGENT"] = "Mozilla/5.0 (Windows NT 10.0; Win64; x64)"
 
 import gradio as gr
 from langchain_community.document_loaders import WebBaseLoader, PyMuPDFLoader
 from langchain_community.vectorstores import FAISS
-from langchain.chains.question_answering import load_qa_chain
-
-# --- THE NEW MODERN IMPORTS ---
-# These replace the old tools that were causing the errors
 from langchain_huggingface import HuggingFaceEndpoint, HuggingFaceEmbeddings
+from langchain.chains.question_answering import load_qa_chain
 
 # Get the token from the secrets
 hf_token = os.environ.get("HF_TOKEN")
@@ -25,7 +22,7 @@ def load_website(url):
     return docs
 
 def setup_vector_store(docs):
-    # use the new HuggingFaceEmbeddings class
+    # Use the new HuggingFaceEmbeddings
     embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
     vector_store = FAISS.from_documents(docs, embeddings)
     return vector_store
@@ -34,8 +31,7 @@ def ask_question(query, vector_store):
     retriever = vector_store.as_retriever()
     docs = retriever.get_relevant_documents(query)
     
-    # Use the new HuggingFaceEndpoint
-    # This automatically handles the connection without the "post" error
+    # Use HuggingFaceEndpoint (Fixes the 'post' error)
     llm = HuggingFaceEndpoint(
         repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
         task="text-generation",