Update app.py

app.py

@@ -1,107 +1,126 @@
-"""
-import streamlit as st
-import firebase_admin
-from firebase_admin import credentials, auth
-
-
+from langchain_community.vectorstores import FAISS
+from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain.prompts import PromptTemplate
+import os
+from langchain.memory import ConversationBufferWindowMemory
+from langchain.chains import ConversationalRetrievalChain
 import streamlit as st
-
-st.set_page_config(initial_sidebar_state="collapsed")
-
+import time
+from dotenv import load_dotenv, find_dotenv
+from langchain_together import Together
+
+load_dotenv(find_dotenv())
+st.set_page_config(page_title="VX1000 BetaV")
+col1, col2, col3 = st.columns([1, 2, 1])
+with col2:
+    st.title("VX1000 BetaV 🦾")
+    st.caption('⚠️ **_Note: Please Wait 5 second after Prompt_**')
+
+#st.sidebar.title("Welcome to VX1000 BetaV Model")
+#st.sidebar.title("Shoot your questions")
 st.markdown(
     """
-<style>
-    [data-testid="collapsedControl"] {
-        display: none
-    }
+    <style>
+div.stButton > button:first-child {
+    background-color: #ffd0d0;
+}
+
+div.stButton > button:active {
+    background-color: #ff6262;
+}
+
+.st-emotion-cache-6qob1r {
+    position: relative;
+    height: 100%;
+    width: 100%;
+    background-color: black;
+    overflow: overlay;
+}
+
+   div[data-testid="stStatusWidget"] div button {
+        display: none;
+        }
 
-       .reportview-container {
+    .reportview-container {
             margin-top: -2em;
         }
         #MainMenu {visibility: hidden;}
         .stDeployButton {display:none;}
+        footer {visibility: hidden;}
         #stDecoration {display:none;}
-    </style>
-    
-</style>
+    button[title="View fullscreen"]{
+    visibility: hidden;}
+        </style>
 """,
     unsafe_allow_html=True,
 )
 
 
+def reset_conversation():
+    st.session_state.messages = []
+    st.session_state.memory.clear()
 
-# Check if Firebase Admin SDK has been initialized
-if not firebase_admin._apps:
-    # Initialize Firebase Admin SDK
-    cred = credentials.Certificate("tokens/gdfg-cf9d9-firebase-adminsdk-593q1-5d02a16c64.json") # Update with your own service account key
-    firebase_admin.initialize_app(cred)
-
-# Function to sign up a new user
-def signup(email, password):
-    try:
-        user = auth.create_user(email=email, password=password)
-        st.success("User created successfully!")
-        return True
-    except Exception as e:
-        st.error(f"Error creating user: {e}")
-        return False
-
-# Function to log in existing user
-def login(email, password):
-    try:
-        user = auth.get_user_by_email(email)
-        st.session_state['logged_in'] = True  # Initialize the 'logged_in' key
-        st.success("Login successful!")
-        return True
-    except Exception as e:
-        st.error(f"Error logging in: {e}")
-        return False
-
-# Main function
-def main():
-    st.title("VX1000 BetaV")
-
-    # Sign up form
-    with st.form("signup_form"):
-        st.header("Sign Up")
-        email = st.text_input("Email")
-        password = st.text_input("Password", type="password")
-        signup_button = st.form_submit_button("Sign Up")
-
-    if signup_button:
-        if signup(email, password):
-            # Redirect to another Python code after signup
-            st.success("Check your Mail")
-            # Insert code for redirection here
-
-    # Login form
-    with st.form("login_form"):
-        st.header("Login")
-        email = st.text_input("Email")
-        password = st.text_input("Password", type="password")
-        login_button = st.form_submit_button("Login")
-
-   # if login_button:
-        if login(email, password):
-            if 'logged_in' in st.session_state and st.session_state['logged_in']:  # Check if logged in
-                st.switch_page("pages/VX1000 BetaV Model.py")# Redirect to new page after successful login
-            else:
-                st.warning("An unexpected error occurred. Please try again.")
-
-    st.markdown(
-        """
-        <hr style="margin-top: 50px;">
-        <footer style="text-align: center;">
-            <p>© 2024 VX1000 BetaV All rights reserved.</p>
-            <p>Made with ❤️ by<a href="https://builtwithtarun.me/" target="_blank"> Tarun</a></p>
-            
-        </footer> 
-        """,
-        unsafe_allow_html=True
-    )
-
-if __name__ == "__main__":
-    main()
-""" 
-import streamlit as st
-<p>© 2024 VX1000 BetaV All rights reserved.</p>
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+if "memory" not in st.session_state:
+    st.session_state.memory = ConversationBufferWindowMemory(k=2, memory_key="chat_history", return_messages=True)
+
+embeddings = HuggingFaceEmbeddings(model_name="nomic-ai/nomic-embed-text-v1-ablated",    model_kwargs={"trust_remote_code": True})
+db = FAISS.load_local("data_byte", embeddings, allow_dangerous_deserialization=True)
+db_retriever = db.as_retriever(search_type="similarity", search_kwargs={"k": 4})
+
+prompt_template = """<s>[INST]This is a chat template ,Don't generate gym related every time answer,your name is VX1000 BetaV Model,this model is made by Tarun,trained by Tarun,made by Tarun ,llm model is made by Tarun,you have 1 bilion parameters, and you are the private gpt model , your primary objective is to provide accurate and concise information related to code, question solving,  based on the user's questions. Do not generate your own questions and answers. You will adhere strictly to the instructions provided, offering relevant context from the knowledge base while avoiding unnecessary details. Your responses will be brief, to the point, and in compliance with the established format. If a question falls outside the given context, rely on your own knowledge base to generate an appropriate response. You will prioritize the user's query and refrain from posing additional questions and do not repeat the prompt template and the things that you have said already.
+QUESTION: {question}
+CONTEXT: {context}
+CHAT HISTORY: {chat_history}[/INST]
+ASSISTANT:
+</s>
+"""
+
+prompt = PromptTemplate(template=prompt_template,
+                        input_variables=['question', 'context', 'chat_history'])
+
+llm = Together(
+    model="mistralai/Mixtral-8x7B-Instruct-v0.1",
+    temperature=0.7,
+    max_tokens=1024,
+    top_k=1,
+    together_api_key=os.environ['T_API']
+)
+
+qa = ConversationalRetrievalChain.from_llm(
+    llm=llm,
+    memory=st.session_state.memory,
+    retriever=db_retriever,
+    combine_docs_chain_kwargs={'prompt': prompt}
+)
+
+for message in st.session_state.messages:
+    with st.chat_message(message.get("role")):
+        st.write(message.get("content"))
+
+input_prompt = st.chat_input("Say something")
+
+if input_prompt:
+    with st.chat_message("user"):
+        st.write(input_prompt)
+
+    st.session_state.messages.append({"role": "user", "content": input_prompt})
+
+    with st.chat_message("assistant"):
+        with st.status("Lifting data, one bit at a time 💡🦾...", expanded=True):
+            result = qa.invoke(input=input_prompt)
+
+            message_placeholder = st.empty()
+
+            full_response = "⚠️ **_Note: Information provided may be inaccurate._** \n\n\n"
+        for chunk in result["answer"]:
+            full_response += chunk
+            time.sleep(0.02)
+
+            message_placeholder.markdown(full_response + " ▌")
+        st.button('Reset All Chat 🗑️', on_click=reset_conversation)
+
+    st.session_state.messages.append({"role": "assistant", "content": result["answer"]})