Update app.py

app.py

@@ -1,15 +1,15 @@
 # Cultural Bias Explorer in Language Models
 # ----------------------------------------
-# This Python project uses LangChain + HuggingFaceHub to explore cultural bias
+# This Python project uses LangChain + HuggingFaceEndpoint to explore cultural bias
 # by retrieving answers to the same prompts using region-specific document bases.
 
 # Install necessary packages before running:
-# pip install langchain langchain-community faiss-cpu sentence-transformers unstructured wikipedia
+# pip install langchain huggingface_hub faiss-cpu sentence-transformers unstructured wikipedia
 
 from langchain_community.document_loaders import WikipediaLoader
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.vectorstores import FAISS
-from langchain.llms import HuggingFaceHub
+from langchain_huggingface import HuggingFaceEndpoint
 from langchain.chains import RetrievalQA
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 import os
@@ -37,12 +37,13 @@ def create_vector_store(region_topic):
     return vectorstore
 
 # ------------------ MAIN LOGIC ------------------
-# Set your HF token as environment variable or directly in the constructor (not recommended for security)
-os.environ["HUGGINGFACEHUB_API_TOKEN"] = "your_hf_token_here"  # Replace with your actual token
+# Set your Hugging Face token in HF settings or as an env variable
+# No need to manually set it here if using Hugging Face Spaces securely
 
-llm = HuggingFaceHub(
-    repo_id="mistralai/Mistral-7B-Instruct-v0.1",
-    model_kwargs={"temperature": 0.7, "max_new_tokens": 512}
+llm = HuggingFaceEndpoint(
+    repo_id="HuggingFaceH4/zephyr-7b-beta",  # free-access model
+    temperature=0.7,
+    max_new_tokens=512
 )
 
 for region in REGIONS: