Update app.py

app.py

@@ -1,4 +1,5 @@
 import gradio as gr
+import os
 from langchain_community.document_loaders import PyPDFLoader
 from langchain_community.vectorstores import FAISS
 from langchain.text_splitter import RecursiveCharacterTextSplitter
@@ -15,7 +16,7 @@ warnings.filterwarnings('ignore')
 
 # Set your Hugging Face API token here.
 # For deployment on Hugging Face, you can set this as an environment variable.
-import os
+
 os.environ["HUGGINGFACEHUB_API_TOKEN"] = "hf_YOUR_HUGGINGFACE_TOKEN"
 
 ## LLM - Using an open-source model from Hugging Face
@@ -86,8 +87,15 @@ def retriever_qa(file, query):
     """
     Sets up a RetrievalQA chain to answer questions based on the document.
     """
+    # Use the file path from the Gradio file object
+    file_path = file.name if file else None
+    
+    # Check if a file was uploaded
+    if not file_path:
+        return "Please upload a valid PDF file before asking a question."
+
     llm = get_llm()
-    retriever_obj = retriever(file)
+    retriever_obj = retriever(file_path)
     
     # Custom prompt to act as a conversational legal advisor
     prompt_template = f"""