Update app.py

app.py

@@ -1,5 +1,4 @@
 import streamlit as st
-
 from PyPDF2 import PdfReader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_google_genai import GoogleGenerativeAIEmbeddings
@@ -8,24 +7,49 @@ from langchain.vectorstores import FAISS
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain.chains.question_answering import load_qa_chain
 from langchain.prompts import PromptTemplate
-import os 
+import os
+import json
 
-st.set_page_config(page_title="RAG Demo - Evan Perez", layout ="wide")
+####CREDIT#####
+#Credit to author (Sri Laxmi) of oringal code reference: SriLaxmi1993
+#Sri LaxmiGithub Link: https://github.com/SriLaxmi1993/Document-Genie-using-RAG-Framwork
+#Sri Laxmi Youtube:https://www.youtube.com/watch?v=SkY2u4UUr6M&t=112s
+###############
 
-api_key = 'AIzaSyCvXRggpO2yNwIpZmoMy_5Xhm2bDyD-pOo'
+st.set_page_config(page_title="Gemini RAG", layout="wide")
 
+# This is the first API key input; no need to repeat it in the main function.
+api_key = 'AIzaSyCvXRggpO2yNwIpZmoMy_5Xhm2bDyD-pOo'
 
 #os.mkdir('faiss_index')
 
-import subprocess
+#empty faise_index and chat_history.json
+def delete_files_in_folder(folder_path):
+    try:
+        # Iterate over all the files in the folder
+        chat_history_file = "chat_history.json"
+        if os.path.exists(chat_history_file):
+            os.remove(chat_history_file)
+        for file_name in os.listdir(folder_path):
+            file_path = os.path.join(folder_path, file_name)
+            if os.path.isfile(file_path):  # Check if it's a file
+                os.remove(file_path)  # Delete the file
+                print(f"Deleted file: {file_path}")
+        print("All files within the folder have been deleted successfully!")
+    except Exception as e:
+        print(f"An error occurred: {e}")
+
+
+with st.sidebar:
+    st.title("Menu:")
 
-# Read requirements.txt file
-with open('requirements.txt', 'r') as f:
-    packages = f.read().splitlines()
+    if st.button("Reset Files", key="reset_button"):
+        folder_path = 'faiss_index'
+        delete_files_in_folder(folder_path)
+
+    CH_size = st.slider("Chunk Size", 0, 1000, 450)
+    CH_overlap = st.slider("Chunk Overlap", 0, 1000, 50)
 
-# Install packages
-for package in packages:
-    subprocess.call(['pip', 'install', package])
 
 def get_pdf_text(pdf_docs):
     text = ""
@@ -36,7 +60,7 @@ def get_pdf_text(pdf_docs):
     return text
 
 def get_text_chunks(text):
-    text_splitter = RecursiveCharacterTextSplitter(chunk_size=450, chunk_overlap=50)
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=CH_size, chunk_overlap=CH_overlap)
     chunks = text_splitter.split_text(text)
     return chunks
 
@@ -59,6 +83,31 @@ def get_conversational_chain():
     chain = load_qa_chain(model, chain_type="stuff", prompt=prompt)
     return chain
 
+#chat history functionality
+def update_chat_history(question, reply):
+    # Check if chat history file exists
+    chat_history_file = "chat_history.json"
+    if os.path.exists(chat_history_file):
+        # If file exists, load existing chat history
+        with open(chat_history_file, "r") as file:
+            chat_history = json.load(file)
+    else:
+        # If file doesn't exist, initialize chat history
+        chat_history = {"conversations": []}
+
+    # Add current conversation to chat history
+    chat_history["conversations"].append({"question": question, "reply": reply})
+
+    # Write updated chat history back to file
+    with open(chat_history_file, "w") as file:
+        json.dump(chat_history, file, indent=4)
+        # Display chat history
+    st.subheader("Chat History")
+    for conversation in chat_history["conversations"]:
+        st.write(f"**Question:** {conversation['question']}")
+        st.write(f"**Reply:** {conversation['reply']}")
+        st.write("---")
+
 def user_input(user_question, api_key):
     embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001", google_api_key=api_key)
     new_db = FAISS.load_local("faiss_index", embeddings)
@@ -67,18 +116,23 @@ def user_input(user_question, api_key):
     response = chain({"input_documents": docs, "question": user_question}, return_only_outputs=True)
     st.write("Reply: ", response["output_text"])
 
+    #chat history
+    update_chat_history(user_question, response["output_text"])
+
+
 def main():
-    st.header("RAG based LLM Applicatoin")
+    st.header("RAG based LLM Application")
 
     user_question = st.text_input("Ask a Question from the PDF Files", key="user_question")
 
-    if user_question and api_key:  # Ensure API key and user question are provided
+    if user_question and api_key:
         user_input(user_question, api_key)
 
     with st.sidebar:
         st.title("Menu:")
+
         pdf_docs = st.file_uploader("Upload your PDF Files and Click on the Submit & Process Button", accept_multiple_files=True, key="pdf_uploader")
-        if st.button("Submit & Process", key="process_button") and api_key:  # Check if API key is provided before processing
+        if st.button("Submit & Process", key="process_button") and api_key:
             with st.spinner("Processing..."):
                 raw_text = get_pdf_text(pdf_docs)
                 text_chunks = get_text_chunks(raw_text)
@@ -86,4 +140,4 @@ def main():
                 st.success("Done")
 
 if __name__ == "__main__":
-    main() 
+    main()