Update app.py

app.py

@@ -34,8 +34,22 @@ retriever_tokenizer = AutoTokenizer.from_pretrained(retriever_model_name)
 from langchain_community.vectorstores import FAISS
 from langchain_community.embeddings import HuggingFaceEmbeddings
 
+# Initialize Hugging Face embeddings
 hf_embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2')
-faiss_index = FAISS(embedding_function=hf_embeddings)
+
+# Dummy implementations for index, docstore, and index_to_docstore_id
+# Replace with actual implementations or configurations as per LangChain documentation
+index = None
+docstore = None
+index_to_docstore_id = None
+
+# Initialize FAISS index with required parameters
+faiss_index = FAISS(
+    embedding_function=hf_embeddings,
+    index=index,
+    docstore=docstore,
+    index_to_docstore_id=index_to_docstore_id
+)
 
 # Function to extract text from a PDF file
 def extract_text_from_pdf(pdf_data):