Update app.py

Some necessary indentation changes.

app.py

@@ -1,300 +1,300 @@
-import os
-import sqlite3
-import hashlib
-
-import streamlit as st
-
-import google.generativeai as genai
-
-from langchain.chains import conversational_retrieval
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-
-from langchain_community.document_loaders import PyPDFLoader
-from langchain_community.vectorstores import FAISS
-from langchain.chains.question_answering import load_qa_chain
-from langchain.prompts import PromptTemplate
-
-from langchain_google_genai import ChatGoogleGenerativeAI, GoogleGenerativeAIEmbeddings
-
-import sqlite3
-from datetime import datetime
-from PyPDF2 import PdfReader
-
-import pytz
-import streamlit as st
-
-from dotenv import load_dotenv
-
-from streamlit_lottie import st_lottie
-import requests
-import random
-
-# Load environemnt variables from .env files
-load_dotenv()
-
-from embed import add_user, create_table, peek, verify_user
-
-# Create the User table
-create_table()
-
-st.set_page_config(page_title="Chat with PDF", layout="centered")
-
-# Initialize Gemini API
-goggle_api_key = os.getenv("GOGGLE_API_KEY")
-genai.configure(api_key= goggle_api_key)
-print(goggle_api_key)
-
-# Initialize session state
-if 'chat_history' not in st.session_state:
-  st.session_state.chat_history = {}
-if 'flow_messages' not in st.session_state:
-  st.session_state.flow_messages = {}
-
-def get_greeting_message():
-  ist = pytz.timezone('Asia/Kolkata')
-  current_datetime_ist = datetime.now(ist)
-  current_hour = current_datetime_ist.hour
-
-  if 5 <= current_hour < 12:
-      return "Good morning!"
-  elif 12 <= current_hour < 18:
-      return "Good afternoon!"
-  else:
-      return "Good evening!"
-
-
-# Initialize Gemini API
-google_api_key = os.getenv("GOOGLE_API_KEY")
-if not google_api_key:
-    google_api_key = 'AIzaSyBaxMCjBV5fBlsKUmFb-8SGgkiirv1ZKck'
-genai.configure(api_key=google_api_key)
-
-# Global variable for embeddings
-embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001", google_api_key=google_api_key)
-
-def get_pdf_text(pdf_docs):
-    text = ""
-    for pdf in pdf_docs:
-        pdf_reader = PdfReader(pdf)
-        for page in pdf_reader.pages:
-            text += page.extract_text()
-    return text
-
-def get_text_chunks(text):
-    text_splitter = RecursiveCharacterTextSplitter(chunk_size=10000, chunk_overlap=1000)
-    chunks = text_splitter.split_text(text)
-    return chunks
-
-def get_vector_store(text_chunks):
-    vector_store = FAISS.from_texts(text_chunks, embedding=embeddings)
-    vector_store.save_local("faiss_index")
-
-def load_faiss_index():
-    return FAISS.load_local("faiss_index", embeddings, allow_dangerous_deserialization=True)
-
-def get_conversational_chain():
-    prompt_template = """
-    Answer the question as detailed as possible from the provided context, make sure to provide all the details, if the answer is not in
-    provided context just say, "answer is not available in the context", don't provide the wrong answer\n\n
-    Context:\n {context}?\n
-    Question: \n{question}\n
-
-    Answer:
-    """
-
-    model = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest", temperature=0.3)
-    prompt = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
-    chain = load_qa_chain(model, chain_type="stuff", prompt=prompt)
-    return chain
-
-def process_user_input(user_question):
-    new_db = load_faiss_index()
-    docs = new_db.similarity_search(user_question)
-    chain = get_conversational_chain()
-    response = chain({"input_documents": docs, "question": user_question}, return_only_outputs=True)
-    print(response)
-    return response["output_text"]  
-
-def load_lottie_url(url: str):
-    r = requests.get(url)
-    if r.status_code != 200:
-        return None
-    return r.json()
-
-
-
-def login():
-  st.subheader("Login")
-  username = st.text_input("Username")
-  password = st.text_input("Password", type="password")
-
-  if st.button("Login"):
-    user = verify_user(username, password)
-    if user:
-      st.success(f"Logged In as {username}")
-      st.session_state.logged_in = True
-      st.session_state.username = username
-      st.rerun()
-      return True
-    else:
-        st.error("Username or password is incorrect.")
-    return False
-
-def signup():
-  st.subheader("Create New Account")
-  new_username = st.text_input("Enter Username")
-  new_password = st.text_input("Enter Password", type="password")
-  confirm_password = st.text_input("Confirm Password", type="password")
-
-  if st.button("Sign Up"):
-    if new_password == confirm_password:
-      try:
-        add_user(new_username, new_password)
-        peek()
-        st.success("You have successfully created an account!")
-        st.info("Go to Login Menu to login")
-      except sqlite3.IntegrityError:
-        st.error("Username already taken, please choose a different one.")
-  else:
-    st.warning("Passwords do not match.")
-
-def marketplace(username):
-    # Custom CSS for better aesthetics
-    st.markdown("""
-    <style>
-    .stApp {
-        background-color: #f0f2f6;
-    }
-    .stButton>button {
-        background-color: #4CAF50;
-        color: white;
-        border-radius: 10px;
-    }
-    .stTextInput>div>div>input {
-        border-radius: 10px;
-    }
-    </style>
-    """, unsafe_allow_html=True)
-
-    # Create two columns for layout
-    col1, col2 = st.columns([1, 2])
-
-    with col1:
-        st.subheader(f"Welcome, {username}!")
-        
-        # Display current date and time
-        ist = pytz.timezone('Asia/Kolkata')
-        current_datetime_ist = datetime.now(ist)
-        st.write(f"Current Date (IST): {current_datetime_ist.strftime('%Y-%m-%d')}")
-        st.write(f"Current Time (IST): {current_datetime_ist.strftime('%H:%M:%S')}")
-
-        # Add a Lottie animation
-        lottie_url = "https://assets5.lottiefiles.com/packages/lf20_ktwnwv5m.json"
-        lottie_json = load_lottie_url(lottie_url)
-        if lottie_json:
-            st_lottie(lottie_json, speed=1, height=200, key="initial")
-
-        # Category selection
-        sections = ["Astrology", "Biology", "Business", "Chemistry", "Medicine", 
-                    "Physics", "Sports", "Life Science", "Spirituality", "Others"]
-        selected_section = st.selectbox("Select a category", sections)
-
-        # File uploader
-        uploaded_file = st.file_uploader(f"Upload a PDF for {selected_section}", type="pdf")
-
-        if uploaded_file:
-            with st.spinner(f"Processing {uploaded_file.name}..."):
-                pdf_text = get_pdf_text([uploaded_file])
-                text_chunks = get_text_chunks(pdf_text)
-                get_vector_store(text_chunks)
-            st.success("Document processed successfully!")
-
-        # Add a fun fact or quote
-        facts = [
-            "Did you know? The first computer programmer was a woman named Ada Lovelace.",
-            "Fun fact: The term 'bug' in computer science originated from an actual moth found in a computer.",
-            "Quote: 'The science of today is the technology of tomorrow.' - Edward Teller"
-        ]
-        st.info(random.choice(facts))
-
-    with col2:
-        st.header(f"Chat about {selected_section}")
-
-        if uploaded_file:
-            # Initialize chat history for the selected section if it doesn't exist
-            if selected_section not in st.session_state.chat_history:
-                st.session_state.chat_history[selected_section] = {"messages": []}
-
-            # Display chat history
-            for message in st.session_state.chat_history[selected_section]["messages"]:
-                with st.chat_message("user" if message["is_user"] else "assistant"):
-                    st.write(message["text"])
-
-            # User input
-            user_question = st.chat_input("Ask a question about the document:")
-            if user_question:
-                st.session_state.chat_history[selected_section]["messages"].append({"is_user": True, "text": user_question})
-                
-                with st.chat_message("user"):
-                    st.write(user_question)
-
-                with st.chat_message("assistant"):
-                    with st.spinner("Thinking..."):
-                        response = process_user_input(user_question)
-                    st.write(response)
-
-                st.session_state.chat_history[selected_section]["messages"].append({"is_user": False, "text": response})
-
-            # Clear chat button
-            if st.button("Clear Chat"):
-                st.session_state.chat_history[selected_section]["messages"] = []
-                st.rerun()
-
-            # Add a feature to download chat history
-            if st.button("Download Chat History"):
-                chat_history = "\n".join([f"{'User' if msg['is_user'] else 'AI'}: {msg['text']}" for msg in st.session_state.chat_history[selected_section]["messages"]])
-                st.download_button(
-                    label="Download",
-                    data=chat_history,
-                    file_name=f"{selected_section}_chat_history.txt",
-                    mime="text/plain"
-                )
-
-        else:
-            st.info("Please upload a PDF document to start chatting.")
-
-        # Add a feedback section
-        st.subheader("Feedback")
-        feedback = st.text_area("We'd love to hear your thoughts! Please leave your feedback here:")
-        if st.button("Submit Feedback"):
-            # Here you would typically save this feedback to a database
-            st.success("Thank you for your feedback!")
-
-    # Footer
-    st.markdown("---")
-    st.markdown("Created with ❤️ by Harshit S | © 2024 PDF Reader App")
-
-def main():
-  st.title("Choose the suitable category:")
-
-  if "logged_in" not in st.session_state:
-    st.session_state.logged_in = False
-
-  if st.session_state.logged_in:
-    marketplace(st.session_state.username)
-  else:
-    menu = ["Login", "Sign Up"]
-    choice = st.sidebar.selectbox("Menu", menu)
-
-    if choice == "Login":
-      call = login()
-      if call:
-        main()
-    elif choice == "Sign Up":
-      signup()
-
-if __name__ == "__main__":
-  print(peek())
-  main()
-
-
+import os
+import sqlite3
+import hashlib
+
+import streamlit as st
+
+import google.generativeai as genai
+
+from langchain.chains import conversational_retrieval
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+
+from langchain_community.document_loaders import PyPDFLoader
+from langchain_community.vectorstores import FAISS
+from langchain.chains.question_answering import load_qa_chain
+from langchain.prompts import PromptTemplate
+
+from langchain_google_genai import ChatGoogleGenerativeAI, GoogleGenerativeAIEmbeddings
+
+import sqlite3
+from datetime import datetime
+from PyPDF2 import PdfReader
+
+import pytz
+import streamlit as st
+
+from dotenv import load_dotenv
+
+from streamlit_lottie import st_lottie
+import requests
+import random
+
+# Load environemnt variables from .env files
+load_dotenv()
+
+from embed import add_user, create_table, peek, verify_user
+
+# Create the User table
+create_table()
+
+st.set_page_config(page_title="Chat with PDF", layout="centered")
+
+# Initialize Gemini API
+goggle_api_key = os.getenv("GOGGLE_API_KEY")
+genai.configure(api_key= goggle_api_key)
+print(goggle_api_key)
+
+# Initialize session state
+if 'chat_history' not in st.session_state:
+  st.session_state.chat_history = {}
+if 'flow_messages' not in st.session_state:
+  st.session_state.flow_messages = {}
+
+def get_greeting_message():
+  ist = pytz.timezone('Asia/Kolkata')
+  current_datetime_ist = datetime.now(ist)
+  current_hour = current_datetime_ist.hour
+
+  if 5 <= current_hour < 12:
+      return "Good morning!"
+  elif 12 <= current_hour < 18:
+      return "Good afternoon!"
+  else:
+      return "Good evening!"
+
+
+# Initialize Gemini API
+google_api_key = os.getenv("GOOGLE_API_KEY")
+if not google_api_key:
+    google_api_key = 'AIzaSyBaxMCjBV5fBlsKUmFb-8SGgkiirv1ZKck'
+genai.configure(api_key=google_api_key)
+
+# Global variable for embeddings
+embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001", google_api_key=google_api_key)
+
+def get_pdf_text(pdf_docs):
+    text = ""
+    for pdf in pdf_docs:
+        pdf_reader = PdfReader(pdf)
+        for page in pdf_reader.pages:
+            text += page.extract_text()
+    return text
+
+def get_text_chunks(text):
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=10000, chunk_overlap=1000)
+    chunks = text_splitter.split_text(text)
+    return chunks
+
+def get_vector_store(text_chunks):
+    vector_store = FAISS.from_texts(text_chunks, embedding=embeddings)
+    vector_store.save_local("faiss_index")
+
+def load_faiss_index():
+    return FAISS.load_local("faiss_index", embeddings, allow_dangerous_deserialization=True)
+
+def get_conversational_chain():
+    prompt_template = """
+    Answer the question as detailed as possible from the provided context, make sure to provide all the details, if the answer is not in
+    provided context just say, "answer is not available in the context", don't provide the wrong answer\n\n
+    Context:\n {context}?\n
+    Question: \n{question}\n
+
+    Answer:
+    """
+
+    model = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest", temperature=0.3)
+    prompt = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
+    chain = load_qa_chain(model, chain_type="stuff", prompt=prompt)
+    return chain
+
+def process_user_input(user_question):
+    new_db = load_faiss_index()
+    docs = new_db.similarity_search(user_question)
+    chain = get_conversational_chain()
+    response = chain({"input_documents": docs, "question": user_question}, return_only_outputs=True)
+    print(response)
+    return response["output_text"]  
+
+def load_lottie_url(url: str):
+    r = requests.get(url)
+    if r.status_code != 200:
+        return None
+    return r.json()
+
+
+
+def login():
+  st.subheader("Login")
+  username = st.text_input("Username")
+  password = st.text_input("Password", type="password")
+
+  if st.button("Login"):
+    user = verify_user(username, password)
+    if user:
+      st.success(f"Logged In as {username}")
+      st.session_state.logged_in = True
+      st.session_state.username = username
+      st.rerun()
+      return True
+    else:
+        st.error("Username or password is incorrect.")
+    return False
+
+def signup():
+  st.subheader("Create New Account")
+  new_username = st.text_input("Enter Username")
+  new_password = st.text_input("Enter Password", type="password")
+  confirm_password = st.text_input("Confirm Password", type="password")
+
+  if st.button("Sign Up"):
+    if new_password == confirm_password:
+      try:
+        add_user(new_username, new_password)
+        peek()
+        st.success("You have successfully created an account!")
+        st.info("Go to Login Menu to login")
+      except sqlite3.IntegrityError:
+        st.error("Username already taken, please choose a different one.")
+    else:
+        st.warning("Passwords do not match.")
+
+def marketplace(username):
+    # Custom CSS for better aesthetics
+    st.markdown("""
+    <style>
+    .stApp {
+        background-color: #f0f2f6;
+    }
+    .stButton>button {
+        background-color: #4CAF50;
+        color: white;
+        border-radius: 10px;
+    }
+    .stTextInput>div>div>input {
+        border-radius: 10px;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+    # Create two columns for layout
+    col1, col2 = st.columns([1, 2])
+
+    with col1:
+        st.subheader(f"Welcome, {username}!")
+        
+        # Display current date and time
+        ist = pytz.timezone('Asia/Kolkata')
+        current_datetime_ist = datetime.now(ist)
+        st.write(f"Current Date (IST): {current_datetime_ist.strftime('%Y-%m-%d')}")
+        st.write(f"Current Time (IST): {current_datetime_ist.strftime('%H:%M:%S')}")
+
+        # Add a Lottie animation
+        lottie_url = "https://assets5.lottiefiles.com/packages/lf20_ktwnwv5m.json"
+        lottie_json = load_lottie_url(lottie_url)
+        if lottie_json:
+            st_lottie(lottie_json, speed=1, height=200, key="initial")
+
+        # Category selection
+        sections = ["Astrology", "Biology", "Business", "Chemistry", "Medicine", 
+                    "Physics", "Sports", "Life Science", "Spirituality", "Others"]
+        selected_section = st.selectbox("Select a category", sections)
+
+        # File uploader
+        uploaded_file = st.file_uploader(f"Upload a PDF for {selected_section}", type="pdf")
+
+        if uploaded_file:
+            with st.spinner(f"Processing {uploaded_file.name}..."):
+                pdf_text = get_pdf_text([uploaded_file])
+                text_chunks = get_text_chunks(pdf_text)
+                get_vector_store(text_chunks)
+            st.success("Document processed successfully!")
+
+        # Add a fun fact or quote
+        facts = [
+            "Did you know? The first computer programmer was a woman named Ada Lovelace.",
+            "Fun fact: The term 'bug' in computer science originated from an actual moth found in a computer.",
+            "Quote: 'The science of today is the technology of tomorrow.' - Edward Teller"
+        ]
+        st.info(random.choice(facts))
+
+    with col2:
+        st.header(f"Chat about {selected_section}")
+
+        if uploaded_file:
+            # Initialize chat history for the selected section if it doesn't exist
+            if selected_section not in st.session_state.chat_history:
+                st.session_state.chat_history[selected_section] = {"messages": []}
+
+            # Display chat history
+            for message in st.session_state.chat_history[selected_section]["messages"]:
+                with st.chat_message("user" if message["is_user"] else "assistant"):
+                    st.write(message["text"])
+
+            # User input
+            user_question = st.chat_input("Ask a question about the document:")
+            if user_question:
+                st.session_state.chat_history[selected_section]["messages"].append({"is_user": True, "text": user_question})
+                
+                with st.chat_message("user"):
+                    st.write(user_question)
+
+                with st.chat_message("assistant"):
+                    with st.spinner("Thinking..."):
+                        response = process_user_input(user_question)
+                    st.write(response)
+
+                st.session_state.chat_history[selected_section]["messages"].append({"is_user": False, "text": response})
+
+            # Clear chat button
+            if st.button("Clear Chat"):
+                st.session_state.chat_history[selected_section]["messages"] = []
+                st.rerun()
+
+            # Add a feature to download chat history
+            if st.button("Download Chat History"):
+                chat_history = "\n".join([f"{'User' if msg['is_user'] else 'AI'}: {msg['text']}" for msg in st.session_state.chat_history[selected_section]["messages"]])
+                st.download_button(
+                    label="Download",
+                    data=chat_history,
+                    file_name=f"{selected_section}_chat_history.txt",
+                    mime="text/plain"
+                )
+
+        else:
+            st.info("Please upload a PDF document to start chatting.")
+
+        # Add a feedback section
+        st.subheader("Feedback")
+        feedback = st.text_area("We'd love to hear your thoughts! Please leave your feedback here:")
+        if st.button("Submit Feedback"):
+            # Here you would typically save this feedback to a database
+            st.success("Thank you for your feedback!")
+
+    # Footer
+    st.markdown("---")
+    st.markdown("Created with ❤️ by Harshit S | © 2024 PDF Reader App")
+
+def main():
+  st.title("Choose the suitable category:")
+
+  if "logged_in" not in st.session_state:
+    st.session_state.logged_in = False
+
+  if st.session_state.logged_in:
+    marketplace(st.session_state.username)
+  else:
+    menu = ["Login", "Sign Up"]
+    choice = st.sidebar.selectbox("Menu", menu)
+
+    if choice == "Login":
+      call = login()
+      if call:
+        main()
+    elif choice == "Sign Up":
+      signup()
+
+if __name__ == "__main__":
+  print(peek())
+  main()
+
+