Frontend

Updated home page of the Streamlit app

frontend/components/__init__.py

@@ -1,3 +1,4 @@
 from .authors import *
 from .user_greetings import *
-from .logo import add_logo
+from .logo import add_logo
+from .toaster import toaster_messages

frontend/components/toaster.py

@@ -0,0 +1,22 @@
+import streamlit as st
+
+import time
+
+
+def toaster_messages(func: callable):
+    def wrapper():
+        msg = st.toast("Uploading PDF...")
+        time.sleep(8)
+        msg.toast("Converting PDF into small chunks...")
+        time.sleep(8)
+        msg.toast("Breaking down chunks into tokens...")
+        time.sleep(8)
+        msg.toast("Creating embeddging vectors...")
+        time.sleep(8)
+        msg.toast("Creating vector store...")
+        time.sleep(8)
+        msg.toast("Vector store created successfully!")
+
+        func()
+
+    return wrapper

frontend/layouts/mainlayout.py

@@ -1,12 +1,15 @@
 import json
 import streamlit as st
+
+import requests
+
 from typing import Callable
 from components import authors, user_greetings, add_logo
 
 
 def mainlayout(func: Callable):
     def wrapper():
-        with open("frontend/layouts/st_page_layouts.json", "r", encoding="utf-8") as f:
+        with open("layouts/st_page_layouts.json", "r", encoding="utf-8") as f:
             st_page_layouts = json.load(f)
 
         st.set_page_config(
@@ -16,7 +19,7 @@ def mainlayout(func: Callable):
                 else "home"
             ]
         )
-        add_logo("frontend/images/studybotlogo.svg", svg=True)
+        add_logo("images/studybotlogo.svg", svg=True)
         st.markdown("# Studybot 📚")
         user_greetings()
         authors()

frontend/pages/2_🤖_bot.py

@@ -1,9 +1,115 @@
+import requests
+
 import streamlit as st
 
 from layouts.mainlayout import mainlayout
 
 @mainlayout
-def bot():
-    st.subheader("Revise your subjects with Studybot!")
+def upload_data():
+    # upload pdf
+    upload_pdf = st.file_uploader("Upload PDF", type="pdf")
+    if upload_pdf is not None:
+        files = {"file": upload_pdf}
+        with st.spinner("Uploading PDF..."):
+            response = requests.post(
+                "https://hemanthsai7-studybotapi.hf.space/api/upload", files=files
+            )
+
+            if response.status_code == 200:
+                st.success(
+                    f'{response.json()["message"][0]}. Vector Store created successfully!'
+                )
+                st.session_state.uploaded_pdf=True
+            else:
+                st.error("Failed to upload PDF!")
+
+        
+
+upload_data()
+
+with st.expander("What happens when I upload a PDF? 📑", expanded=True):
+    st.info(
+        """
+        - The PDF is uploaded to the backend server. ⚙️
+
+        - The PDF is converted into small chunks for  faster processing. 🚀
+           
+        - The chunks are broken down into tokens. A token is a single word or a group of words. 📝
+
+        - The tokens are converted into embedding vectors. 📊
+
+        - The embedding vectors are stored in a vector store. 🗄️
+        """,
+        icon="ℹ️",
+    )
+
+st.divider()
+
+if "uploaded_pdf" in st.session_state.keys():
+    # chatbot
+    st.subheader("Ask Studybot a question! 🤖")
+
+
+    if "messages" not in st.session_state.keys():
+        st.session_state.messages = [
+            {
+                "role": "assistant",
+                "content": "What's troubling you? Ask me a question right away!",
+            }
+        ]
+
+    # Display or clear chat messages
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.write(message["content"])
+
+
+    def clear_chat_history():
+        st.session_state.messages = [
+            {
+                "role": "assistant",
+                "content": "What's troubling you? Ask me a question right away!",
+            }
+        ]
+
+
+    st.sidebar.button("Clear Chat History", on_click=clear_chat_history)
+
+
+    def generate_mistral_response(question: str):
+        for dict_message in st.session_state.messages:
+            if dict_message["role"] == "user":
+                question = dict_message["content"]
+
+        answer = requests.post(
+            "https://hemanthsai7-studybotapi.hf.space/api/inference",
+            json={"promptMessage": question},
+        ).json()
+
+        return answer
+
+
+    # User-provided prompt
+    if prompt := st.chat_input(
+        disabled=not st.session_state.messages[-1]["role"] == "assistant",
+        placeholder="Hello, please ask me a question! 🤖"):
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        with st.chat_message("user"):
+            st.write(prompt)
+
+    # ask question
+    st.write(st.session_state)
 
-bot()
+    # Generate a new response if last message is not from assistant
+    if st.session_state.messages[-1]["role"] != "assistant":
+        with st.chat_message("assistant"):
+            with st.spinner("Thinking..."):
+                response = generate_mistral_response(prompt)
+                placeholder = st.empty()
+                full_response = ""
+                for item in response:
+                    full_response += item
+                    placeholder.markdown(full_response)
+                placeholder.markdown(full_response)
+        message = {"role": "assistant", "content": full_response}
+        st.session_state.messages.append(message)

frontend/🏡_Home.py

@@ -63,7 +63,7 @@ def home():
         "<h2 style='text-align: center; color: black;'>Studybot Architecture</h1>",
         unsafe_allow_html=True,
     )
-    st.image("frontend/images/architecture.png")
+    st.image("images/architecture.png")
 
 
 home()