Update app.py

app.py

@@ -1,92 +1,29 @@
 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
 
-# openai.api_key = os.environ("OPENAI_API_KEY")  # vLLM server is not authenticated
+# Set OpenAI API Key
 os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY')
 
-
+# Initialize LangChain ChatOpenAI agent
 llm = ChatOpenAI(
     model='gpt-3.5-turbo',
     max_tokens=500,
     temperature=0.7,
 )
 
-
-#
-# 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):
     rel = df.pct_change()
     cumret = ((1 + rel).cumprod() - 1).fillna(0)
     return cumret
 
-
 def display_convo():
     with st.container():
         for i, message in enumerate(reversed(st.session_state.chat_history)):
@@ -95,134 +32,63 @@ def display_convo():
             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:
-        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)}")
-
+        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)}")
 
 if __name__ == '__main__':
     main()
-