Upload app.py

app.py

@@ -1,103 +1,77 @@
 import streamlit as st
 from streamlit_chat import message
-from langchain_openai import ChatOpenAI
-from langchain.chains import ConversationChain
-from langchain.chains.conversation.memory import (ConversationBufferMemory, 
-                                                  ConversationSummaryMemory, 
-                                                  ConversationBufferWindowMemory
-               
-                                                  )
 
-if 'conversation' not in st.session_state:
-    st.session_state['conversation'] =None
-if 'messages' not in st.session_state:
-    st.session_state['messages'] =[]
-if 'API_Key' not in st.session_state:
-    st.session_state['API_Key'] =''
+from langchain.document_loaders import CSVLoader
+from langchain_openai import OpenAIEmbeddings
+from langchain.chains import RetrievalQA
+from langchain.chains import ConversationalRetrievalChain
 
-# Setting page title and header
-st.set_page_config(page_title="ChatMate: Your Professional AI Conversation Partner Solution", page_icon=":robot_face:")
-st.markdown("<h1 style='text-align: center; color: navy;'>ChatMate</h1>", unsafe_allow_html=True)
-st.markdown("<h4 style='text-align: center;'>A cutting-edge language model</h4>", unsafe_allow_html=True)
-st.markdown("<p style='text-align: right'>By <a href='https://entzyeung.github.io/portfolio/index.html'>Lorentz Yeung</a></p>", unsafe_allow_html=True)
+from langchain_openai import ChatOpenAI
+import os
+from langchain_community.vectorstores import Chroma
 
-st.markdown("<p style='text-align: left;'>I am capable of recalling previous parts of our conversation, such as remembering your name if you share it with me.</p>", unsafe_allow_html=True)
-st.session_state['API_Key']= st.text_input("First, to get it work, put your OpenAI API Key here please, the system will enter for you automatically.",type="password")
-st.markdown("<p style='text-align: left;'>Then Tell me how I can help:</p>", unsafe_allow_html=True)
+import tempfile
 
 
+user_api_key = st.sidebar.text_input(
+    label="#### Your OpenAI API key 👇",
+    placeholder="user_historye your openAI API key, sk-",
+    type="password")
 
-# API Keys
-# st.sidebar.text_input() will automatically update st.session_state['API_Key'] with the input value whenever the user types into the field. 
-st.sidebar.title("Introduction")
-st.sidebar.markdown("""
-ChatMate is an advanced conversational AI interface, expertly crafted to demonstrate the fusion of Streamlit's user-friendly design and OpenAI's powerful GPT-3.5 model. Here are its highlights:
+# uploaded_file = st.sidebar.file_uploader("upload", type="csv")
 
-<ul style='text-align: left;'>
-<li><strong>Intuitive Interface</strong>: Built with Streamlit, ChatMate offers a clean, responsive user experience, allowing for natural dialogue with the AI.</li>
-<li><strong>Advanced NLP</strong>: Incorporating OpenAI's most advanced GPT model, the app provides nuanced understanding and generation of human-like text, showcasing the model's impressive capabilities.</li>
-<li><strong>State Management</strong>: Utilizes <code>ConversationChain</code> and <code>ConversationMemory</code> from <code>langchain</code> to preserve the context and flow, ensuring coherent and engaging interactions.</li>
-<li><strong>Python Proficiency</strong>: The app's robust backend, written in Python, reflects the data scientist’s adeptness in programming and system design.</li>
-<li><strong>Secure Interaction</strong>: Streamlit's session state management is used for secure API key handling and user input retention across sessions.</li>
-</ul>
+persist_directory = "chroma/db"
+embeddings = OpenAIEmbeddings()
+KaggleX_courses_db = Chroma(persist_directory = persist_directory, embedding_function=embeddings)
 
-ChatMate is developed by Lorentz Yeung
-""", unsafe_allow_html=True)
 
-#st.session_state['API_Key']= st.sidebar.text_input("Put your OpenAI API Key here please, the system will enter for you automatically.",type="password")
 
-# summarise_button = st.sidebar.button("Summarise the conversation", key="summarise")
-#if summarise_button:
-#    summarise_placeholder = st.sidebar.write("Nice chatting with you my friend ❤️")
+if KaggleX_courses_db :
 
+    KaggleX_courses_db = Chroma(persist_directory = persist_directory, embedding_function=embeddings)
+    retriever = KaggleX_courses_db.as_retriever() # search_kwargs={"k": 4}
 
+    chain = ConversationalRetrievalChain.from_llm(llm = ChatOpenAI(temperature=0.0,model_name='gpt-3.5-turbo',
+                                                                openai_api_key=user_api_key),
+                                                                retriever = retriever)
 
-# Function to get response from the model
-def getresponse(userInput, api_key):
+    def conversational_chat(query):
 
-    if st.session_state['conversation'] is None:
+        result = chain({"question": query, "chat_history": st.session_state['history']})
+        st.session_state['history'].append((query, result["answer"]))
 
-        llm = ChatOpenAI(
-            temperature=0,
-            openai_api_key=api_key,
-            model_name='gpt-3.5-turbo'
-        )
+        return result["answer"]
 
-        st.session_state['conversation'] = ConversationChain(
-            llm=llm,
-            verbose=True,
-            memory=ConversationSummaryMemory(llm=llm)
-        )
+    if 'history' not in st.session_state:
+        st.session_state['history'] = []
 
-    response=st.session_state['conversation'].predict(input=userInput)
-    print(st.session_state['conversation'].memory.buffer)
-    
+    if 'ai_history' not in st.session_state:
+        st.session_state['ai_history'] = ["Hello ! Ask me anything about KaggleX courses!"]
 
-    return response
+    if 'user_history' not in st.session_state:
+        st.session_state['user_history'] = ["I would like to know more about the KaggleX courses!]
 
+    #container for the chat history
+    response_container = st.container()
+    #container for the user's text input
+    container = st.container()
 
+    with container:
+        with st.form(key='my_form', clear_on_submit=True):
 
-response_container = st.container()
-# Here we will have a container for user input text box
-container = st.container()
+            user_input = st.text_input("Query:", placeholder="Learn more about the courses in KaggleX:", key='input')
+            submit_button = st.form_submit_button(label='Ask')
 
-# User input and response display
-with container:
-    with st.form(key='my_form', clear_on_submit=True):
-        user_input = st.text_area("Ask me questions please", key='input', height=100)
-        submit_button = st.form_submit_button(label='Send')
+        if submit_button and user_input:
+            output = conversational_chat(user_input) # if the button is clicked, then submit he query to the Chain, and take the history from session_state.
 
-        if submit_button:
-            st.session_state['messages'].append(user_input)
-            model_response=getresponse(user_input,st.session_state['API_Key'])
-            st.session_state['messages'].append(model_response)
-            
+            st.session_state['user_history'].append(user_input) # store the user input to user history
+            st.session_state['ai_history'].append(output) # store the AI prediction to ai history
 
-            with response_container:
-                for i in range(len(st.session_state['messages'])):
-                        if (i % 2) == 0:
-                            message(st.session_state['messages'][i], is_user=True, key=str(i) + '_user')
-                        else:
-                            message(st.session_state['messages'][i], key=str(i) + '_AI')
+    # the chat interface.
+    if st.session_state['ai_history']:
+        with response_container:
+            for i in range(len(st.session_state['ai_history'])):
+                message(st.session_state["user_history"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile")
+                message(st.session_state["ai_history"][i], key=str(i), avatar_style="thumbs")
 
-