Update app.py

app.py

@@ -501,12 +501,17 @@ create_vector_db_and_annoy_index('med.pdf', 'vector_db.pkl', 'vector_index.ann')
 
 import gradio as gr
 
-def chatbot_interface(user_query, response_style, selected_retrieval_methods, selected_reranking_methods, chunk_size, overlap):
+def chatbot_interface(user_query, response_style, selected_retrieval_methods, selected_reranking_methods, pdf_file, chunk_size, overlap):
     vector_db_path = "vector_db.pkl"
     annoy_index_path = "vector_index.ann"
+    if pdf_file is not None:
+        pdf_path = pdf_file.name  # Get the path of the uploaded file
+        store_embeddings_in_vector_db(pdf_path, 'vector_db.pkl', 'vector_index.ann', chunk_size, overlap)
+    else:
+        return "Please upload a PDF file." 
 
     # Load the documents and create embeddings with the provided chunk_size and overlap
-    store_embeddings_in_vector_db('med.pdf', 'vector_db.pkl', 'vector_index.ann', chunk_size, overlap)
+    #store_embeddings_in_vector_db('med.pdf', 'vector_db.pkl', 'vector_index.ann', chunk_size, overlap)
 
     chatbot = MistralRAGChatbot(vector_db_path, annoy_index_path)
 
@@ -538,6 +543,7 @@ iface = gr.Interface(
     fn=chatbot_interface,
     theme=gr.themes.Soft(),
     inputs=[
+        gr.File(label="Upload PDF File"), 
         gr.Textbox(lines=5, label="User Query"),
         gr.Dropdown(["Detailed", "Concise", "Creative", "Technical"], label="Response Style"),
         gr.Dropdown(["annoy", "tfidf", "bm25", "euclidean", "jaccard"], label="Retrieval Methods", multiselect=True), # This line is changed