Update app.py

app.py

@@ -22,7 +22,7 @@ This chatbot is built using the Retrieval-Augmented Generation (RAG) framework,
 
 Follow these simple steps to interact with the chatbot:
 
-1. **Upload Your Documents**: The system accepts multiple PDF files at once, analyzing the content to provide comprehensive insights.
+1. **Upload Your Documents**: The system accepts a PDF file at one time, analyzing the content to provide comprehensive insights.
 
 2. **Ask a Question**: After processing the documents, ask any question related to the content of your uploaded documents for a precise answer.
 """)
@@ -70,7 +70,7 @@ def get_conversational_chain():
 def embedding(chunk,query):
     embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
     db = Chroma.from_documents(chunk,embeddings, persist_directory="./chroma_db")
-    docs = db3.similarity_search(query)
+    docs = db.similarity_search(query)
     chain = get_conversational_chain()
     response = chain({"input_documents": docs, "question": query}, return_only_outputs=True)
     st.write("Reply: ", response["output_text"])
@@ -81,7 +81,7 @@ def embedding(chunk,query):
 def main():
     st.header("Chat with your pdf💁")
     st.title("Menu:")
-    pdf_docs = st.file_uploader("Upload your PDF Files and Click on the Submit & Process Button", accept_multiple_files=False, key="pdf_uploader")
+    pdf_docs = st.file_uploader("Upload your PDF File and Click on the Submit & Process Button", accept_multiple_files=False, key="pdf_uploader")
     query = st.text_input("Ask a Question from the PDF Files", key="query")
     if st.button("Submit & Process", key="process_button"):
         with st.spinner("Processing..."):