Update app.py

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 
 from langchain_community.document_loaders import PyPDFLoader
-from langchain_community.text_splitter import RecursiveCharacterTextSplitter
+from langchain_text_splitters import RecursiveCharacterTextSplitter
 from langchain_community.embeddings import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
 from langchain.chains import RetrievalQA
@@ -12,34 +12,27 @@ def run_qa(pdf_path, question):
     if pdf_path is None or question.strip() == "":
         return "Please upload a PDF and enter a question."
 
-    # Load PDF
     loader = PyPDFLoader(pdf_path)
     docs = loader.load()
 
-    # Split into chunks
     splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=150)
     chunks = splitter.split_documents(docs)
 
-    # Create embeddings + vector store
     embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
     vectordb = FAISS.from_documents(chunks, embeddings)
 
-    # LLM
     llm = ChatOpenAI(temperature=0)
 
-    # Retrieval QA chain
     qa = RetrievalQA.from_chain_type(
         llm=llm,
         retriever=vectordb.as_retriever(),
         return_source_documents=True
     )
 
-    # Newer LangChain-safe call
     result = qa.invoke({"query": question})
 
     answer_text = result.get("result", "")
     source_docs = result.get("source_documents", [])
-
     sources = "\n\n".join([d.page_content[:500] for d in source_docs[:2]])
 
     return f"### Answer\n{answer_text}\n\n---\n### Sources\n{sources}"