Update app.py

app.py

@@ -1,25 +1,84 @@
+import os
+
 import streamlit as st
 import yfinance as yf
 import pandas as pd
 from langchain.agents import create_csv_agent, AgentType
+import re
+import sqlite3
+from langchain.chat_models import ChatOpenAI
 from htmlTemplates import css, user_template, bot_template
 
-from langchain.llms import GPT4All
-from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+# openai.api_key = os.environ("OPENAI_API_KEY")  # vLLM server is not authenticated
+os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY')
+
 
-local_path = (
-    "tinyllama-1.1b-chat-v0.3.Q2_K.gguf"  # replace with your desired local file path
+llm = ChatOpenAI(
+    model='gpt-3.5-turbo',
+    max_tokens=500,
+    temperature=0.7,
 )
 
-# Callbacks support token-wise streaming
-callbacks = [StreamingStdOutCallbackHandler()]
 
-# Verbose is required to pass to the callback manager
-llm = GPT4All(model=local_path, callbacks=callbacks, verbose=True)
+#
+# class FinLLM(LLM):
+#
+#     @property
+#     def _llm_type(self) -> str:
+#         return "custom"
+#
+#     def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
+#         out = g4f.ChatCompletion.create(
+#             model="gpt-3.5-turbo",
+#             messages=[{"role": "user", "content": prompt}],
+#             temperature=0.5,  # You can adjust parameters as needed
+#             max_tokens=350  # Adjust the token limit as needed
+#         )  #
+#         if stop:
+#             stop_indexes = (out.find(s) for s in stop if s in out)
+#             min_stop = min(stop_indexes, default=-1)
+#             if min_stop > -1:
+#                 out = out[:min_stop]
+#         return out
+#
+#
+# llm = FinLLM()
+
+def create_users_db():
+    with sqlite3.connect('MASTER.db') as conn:
+        cursor = conn.cursor()
+        cursor.execute("""
+            CREATE TABLE IF NOT EXISTS Users (
+                user_id INTEGER PRIMARY KEY AUTOINCREMENT,
+                email TEXT UNIQUE,
+                password TEXT
+            )
+        """)
+
+def add_user_to_db(email, password):
+    with sqlite3.connect('MASTER.db') as conn:
+        cursor = conn.cursor()
+        try:
+            insert_query = "INSERT INTO Users (email, password) VALUES (?, ?)"
+            cursor.execute(insert_query, (email, password))
+        except sqlite3.IntegrityError as e:
+            # Handle specific error if the email already exists
+            print(f"Error: {e}")
+            return False
+        return True
+
+def authenticate_user(email, password):
+    with sqlite3.connect('MASTER.db') as conn:
+        cursor = conn.cursor()
+        select_query = "SELECT * FROM Users WHERE email = ? AND password = ?"
+        cursor.execute(select_query, (email, password))
+        user = cursor.fetchone()
+    return user is not None
 
 
 def init_ses_states():
     st.session_state.setdefault('chat_history', [])
+    st.session_state.setdefault('user_authenticated', False)
 
 
 def relative_returns(df):
@@ -32,71 +91,138 @@ def display_convo():
     with st.container():
         for i, message in enumerate(reversed(st.session_state.chat_history)):
             if i % 2 == 0:
-                st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
+                 st.markdown(bot_template.replace("{{MSG}}", message), unsafe_allow_html=True)
             else:
                 st.markdown(user_template.replace("{{MSG}}", message), unsafe_allow_html=True)
 
 
+def approve_password(password):
+    if len(password) >= 8 and re.search(r"(?=.*[a-z])(?=.*[A-Z])(?=.*[0-9])(?=.*[_@$#!?&*%])", password):
+        return True
+    return False
+
+
+def approve_email(email):
+    email_regex = '^[a-zA-Z0-9]+[\._]?[a-zA-Z0-9]+[@]\w+[.]\w{2,3}$'
+    if re.search(email_regex, email):
+        return True
+    else:
+        return False
+
+
+def user_authentication_tab():
+    with st.expander("User Authentication", expanded=True):
+        login_tab, create_account_tab = st.tabs(["Login", "Create Account"])
+
+        with login_tab:
+            email = st.text_input("Email:")
+            password = st.text_input("Password:", type='password')
+            if st.button("Login"):
+                if authenticate_user(email=email,password=password):
+                    st.session_state.user_authenticated = True
+                else:
+                    st.caption('Incorrect Username or Password.')
+
+            if st.session_state.user_authenticated:
+                st.caption("User Authenticated")
+
+        with create_account_tab:
+            new_email = st.text_input("New Email:")
+            new_password = st.text_input("New Password:", type='password')
+            confirm_password = st.text_input("Confirm Password:", type='password')
+            if st.button("Create Account"):
+                if not approve_email(new_email):
+                    st.caption("Invalid Email")
+                    return
+                if not approve_password(new_password):
+                    st.caption("Invalid Password")
+                    return
+                if new_password != confirm_password:
+                    st.caption("Passwords do not match")
+                    return
+                add_user_to_db(email=new_email, password=new_password)
+                st.caption(f"{new_email} Successfully Added")
+
+
 def main():
     st.set_page_config(page_title="Stock Price AI Bot", page_icon=":chart:")
     st.write(css, unsafe_allow_html=True)
+    create_users_db()
     init_ses_states()
     st.title("Stock Price AI Bot")
     st.caption("Visualizations and OpenAI Chatbot for Multiple Stocks Over A Specified Period")
 
+
     with st.sidebar:
-        asset_tickers = sorted(
-            ['DOW', 'NVDA', 'TSL', 'GOOGL', 'AMZN', 'AI', 'NIO', 'LCID', 'F', 'LYFY', 'AAPL', 'MSFT', 'BTC-USD',
-             'ETH-USD'])
-        asset_dropdown = st.multiselect('Pick Assets:', asset_tickers)
-        metric_tickers = ['Adj. Close', 'Relative Returns']
-        metric_dropdown = st.selectbox("Metric", metric_tickers)
-        viz_tickers = ['Line Chart', 'Area Chart']
-        viz_dropdown = st.multiselect("Pick Charts:", viz_tickers)
-        start = st.date_input('Start', value=pd.to_datetime('2023-01-01'))
-        end = st.date_input('End', value=pd.to_datetime('today'))
-
-    if len(asset_dropdown) > 0:
-        df = yf.download(asset_dropdown, start, end)['Adj Close']
-        if metric_dropdown == 'Relative Returns':
-            df = relative_returns(df)
-        if len(viz_dropdown) > 0:
-            with st.expander("Data Visualizations", expanded=True):
-                if "Line Chart" in viz_dropdown:
-                    st.line_chart(df)
-                if "Area Chart" in viz_dropdown:
-                    st.area_chart(df)
-
-        st.header("Chat with your Data")
-        query = st.text_input("Enter a query:")
-        chat_prompt = f'''
-            You are an AI ChatBot intended to help with user stock data.
-            \nDATA MODE: {metric_dropdown}
-            \nSTOCKS: {asset_dropdown} 
-            \nTIME PERIOD: {start} to {end}
-            \nCHAT HISTORY: {st.session_state.chat_history}
-            \nUSER MESSAGE: {query}
-            \nAI RESPONSE HERE:
-        '''
-
-        if st.button("Execute") and query:
-            with st.spinner('Generating response...'):
-                try:
-                    DF = pd.DataFrame(df)
-                    DF.to_csv('data.csv')
-                    agent = create_csv_agent(
-                        llm,
-                        'data.csv',
-                        verbose=True,
-                        agent_type=AgentType.OPENAI_FUNCTIONS,
-                    )
-                    answer = agent.run(chat_prompt)
-                    st.session_state.chat_history.append(f"USER: {query}\n")
-                    st.session_state.chat_history.append(f"AI: {answer}\n")
-                    display_convo()
-                except Exception as e:
-                    st.error(f"An error occurred: {str(e)}")
+        user_authentication_tab()
+
+
+    if st.session_state.user_authenticated:
+        with st.sidebar:
+            with st.expander("Settings",expanded=True):
+                asset_tickers = sorted(['DOW','NVDA','TSL','GOOGL','AMZN','AI','NIO','LCID','F','LYFY','AAPL', 'MSFT', 'BTC-USD', 'ETH-USD'])
+                asset_dropdown = st.multiselect('Pick Assets:', asset_tickers)
+
+                metric_tickers = ['Adj. Close', 'Relative Returns']
+                metric_dropdown = st.selectbox("Metric", metric_tickers)
+
+                viz_tickers = ['Line Chart', 'Area Chart']
+                viz_dropdown = st.multiselect("Pick Charts:", viz_tickers)
+
+                start = st.date_input('Start', value=pd.to_datetime('2023-01-01'))
+                end = st.date_input('End', value=pd.to_datetime('today'))
+
+                chatbot_temp = st.slider("Chat Bot Temperature",0.0,1.0,0.5)
+
+        # Only when a stock is selected
+        if len(asset_dropdown) > 0:
+            df = yf.download(asset_dropdown,start,end)['Adj Close']
+            if metric_dropdown == 'Relative Returns':
+                df = relative_returns(df)
+            if len(viz_dropdown) > 0:
+                with st.expander("Data Visualizations for {} of {}".format(metric_dropdown,asset_dropdown), expanded=True):
+                    if "Line Chart" in viz_dropdown:
+                        st.subheader("Line Chart")
+                        st.line_chart(df)
+                    if "Area Chart" in viz_dropdown:
+                        st.subheader("Area Chart")
+                        st.area_chart(df)
+            st.header("Chat with your Data")
+
+            query = st.text_input("Enter a query:")
+
+            chat_prompt = f'''
+                You are an AI ChatBot intended to help with user stock data.
+                \nYou have access to a pandas dataframe with the following specifications 
+                \nDATA MODE: {metric_dropdown}
+                \nSTOCKS: {asset_dropdown} 
+                \nTIME PERIOD: {start} to {end}
+                \nCHAT HISTORY: {st.session_state.chat_history}
+                \nUSER MESSAGE: {query}
+                \nAI RESPONSE HERE:
+            '''
+
+            if st.button("Execute") and query:
+                with st.spinner('Generating response...'):
+                    try:
+                        DF = pd.DataFrame(df)
+                        DF.to_csv('data.csv')
+                        agent = create_csv_agent(
+                            llm,
+                            'data.csv',
+                            verbose=True,
+                            agent_type=AgentType.OPENAI_FUNCTIONS,
+                        )
+
+                        answer = agent.run(chat_prompt)
+                        st.session_state.chat_history.append(f"USER: {query}\n")
+                        st.session_state.chat_history.append(f"AI: {answer}\n")
+                        display_convo()
+
+                    except Exception as e:
+                        st.error(f"An error occurred: {str(e)}")
 
 
 if __name__ == '__main__':
     main()
+