Update app.py

app.py

@@ -21,11 +21,10 @@ def load_pdf_and_generate_embeddings(pdf_doc, open_ai_key, relevant_pages='all')
         #Create an instance of OpenAIEmbeddings, which is responsible for generating embeddings for text
         embeddings = OpenAIEmbeddings()
 
-        global vectordb
-
-        if relevant_pages == 'all':    
-            #To create a vector store, we use the Chroma class, which takes the documents (pages in our case) and the embeddings instance
-            vectordb = Chroma.from_documents(pages, embedding=embeddings)
+        if relevant_pages == 'all':
+            pages = pages
+        #To create a vector store, we use the Chroma class, which takes the documents (pages in our case) and the embeddings instance
+        vectordb = Chroma.from_documents(pages, embedding=embeddings)
         
         #Finally, we create the bot using the RetrievalQA class
         global pdf_qa
@@ -139,7 +138,6 @@ with gr.Blocks(css=css,theme=gr.themes.Monochrome()) as demo:
     submit_query.click(answer_query,input,output)
 
 
-#Forcing container to restart
 demo.launch()