frontend

frontend/components/__init__.py

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

frontend/{pages → components}/file_streaming.py

@@ -1,10 +1,28 @@
 import os
+import requests
 
 import streamlit as st
 
 from langchain.callbacks.base import BaseCallbackHandler
 
 
+@st.cache_resource(ttl="1h")
+def upload_data(uploaded_files):
+    files = {"file": uploaded_files}
+    with st.spinner("Uploading PDF..."):
+        response = requests.post(
+            "http://127.0.0.1:8000/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!")
+
+
 class StreamHandler(BaseCallbackHandler):
     def __init__(
         self, container: st.delta_generator.DeltaGenerator, initial_text: str = ""

frontend/components/toaster.py

@@ -1,22 +0,0 @@
-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/pages/2_🤖_bot.py

@@ -3,113 +3,58 @@ import requests
 import streamlit as st
 
 from layouts.mainlayout import mainlayout
+from langchain.memory.chat_message_histories import StreamlitChatMessageHistory
 
-@mainlayout
-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()
+from components.file_streaming import *
 
-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. 📊
+@mainlayout
+def display():
+    with st.expander("What happens when I upload a PDF? 📑", expanded=True):
+        st.info(
+            """
+            - The PDF is uploaded to the backend server. ⚙️
 
-        - The embedding vectors are stored in a vector store. 🗄️
-        """,
-        icon="ℹ️",
-    )
+            - 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. 📝
 
-st.divider()
+            - The tokens are converted into embedding vectors. 📊
 
-if "uploaded_pdf" in st.session_state.keys():
-    # chatbot
-    st.subheader("Ask Studybot a question! 🤖")
+            - The embedding vectors are stored in a vector store. 🗄️
+            """,
+            icon="ℹ️",
+        )
 
+    st.divider()
 
-    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"])
+display()
 
+uploaded_files = st.sidebar.file_uploader(label="Upload PDF files", type=["pdf"])
 
-    def clear_chat_history():
-        st.session_state.messages = [
-            {
-                "role": "assistant",
-                "content": "What's troubling you? Ask me a question right away!",
-            }
-        ]
+if not uploaded_files:
+    st.info("Please upload PDF documents to continue.")
+    st.stop()
+upload_data(uploaded_files)
 
+msgs = StreamlitChatMessageHistory()
 
-    st.sidebar.button("Clear Chat History", on_click=clear_chat_history)
+if len(msgs.messages) == 0 or st.sidebar.button("Clear message history"):
+    msgs.clear()
+    msgs.add_ai_message("How can I help you?")
 
+avatars = {"human": "user", "ai": "assistant"}
+for msg in msgs.messages:
+    st.chat_message(avatars[msg.type]).write(msg.content)
 
-    def generate_mistral_response(question: str):
-        for dict_message in st.session_state.messages:
-            if dict_message["role"] == "user":
-                question = dict_message["content"]
+if user_query := st.chat_input(placeholder="Ask me anything!"):
+    st.chat_message("user").write(user_query)
 
-        answer = requests.post(
-            "https://hemanthsai7-studybotapi.hf.space/api/inference",
-            json={"promptMessage": question},
+    with st.chat_message("assistant"):
+        retrieval_handler = PrintRetrievalHandler(st.container())
+        stream_handler = StreamHandler(st.empty())
+        response = requests.post(
+            "http://127.0.0.1:8000/api/inference",
+            json={"promptMessage": user_query},
         ).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)
-
-    # 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)

test.py

@@ -1,26 +1,87 @@
-class A:
-    def __init__(self):
-        self._bill = 1
-
-    @property
-    def bill(self):
-        return self._bill
-    
-    @bill.setter
-    def bill(self,value):
-        self._bill = value
-        # raise PermissionError("You can't change the bill")
-
-class B(A):
-    def __init__(self):
-        super().__init__()
-        self._bill = 2
-
-# b = B()
-# print(b.bill)
-a=A()
-a.bill=3
-print(a.bill)
-
-
-    
+# class A:
+#     def __init__(self):
+#         self._bill = 1
+
+#     @property
+#     def bill(self):
+#         return self._bill
+
+#     @bill.setter
+#     def bill(self,value):
+#         self._bill = value
+#         # raise PermissionError("You can't change the bill")
+
+# class B(A):
+#     def __init__(self):
+#         super().__init__()
+#         self._bill = 2
+
+# # b = B()
+# # print(b.bill)
+# a=A()
+# a.bill=3
+# print(a.bill)
+
+# 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)
+
+# # 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)