Upload app.py

app.py

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+"""
+This is a streamlit application that allows user to query multiple csv
+files and return the answer based on the text in the csv files.
+
+It uses streamlit to create a web application to load the csv files and
+query them.
+
+Langchain and OpenAI API are used to generate the answer based on the
+text in the csv files.
+
+Credit: https://www.youtube.com/@alejandro_ao 👊🏿
+"""
+
+from langchain.agents import create_csv_agent
+from langchain.chat_models import ChatOpenAI
+from langchain.agents.agent_types import AgentType
+#from dotenv import load_dotenv
+import os
+import pandas as pd
+import streamlit as st
+
+
+def main():
+    # set the page title
+    st.set_page_config("Data Analysis Helper \U0001F4CA")
+    st.markdown("# Data Analysis Helper")
+    st.markdown("This tool helps you analyze your CSV files. Please remember to **remove personal information** first, such as names, addresses, phone numbers, emails, etc.")
+    st.markdown("## How to use this tool")
+    st.markdown("1. Upload your CSV file")
+    st.markdown("2. Ask a question about your CSV file")
+    st.markdown("3. Wait for the answer to appear")
+    st.markdown("## Example questions")
+    st.markdown("1. What is the average age?")
+    st.markdown("2. What is the average income?")
+    st.markdown("3. What is the average age of people who live in London?")
+    st.markdown("Go to [this page](https://openai.com/pricing) to get an OpenAI API key.")
+    st.markdown("The API key takes the following form: sk****hx. NB: This is not a viable key.")
+    
+    # text input to ask for openai api key
+    # then hide the input
+    openai_api_key = st.text_input("Enter your OpenAI API key", type="password")
+
+    # set this key as an environment variable
+    os.environ["OPENAI_API_KEY"] = openai_api_key
+
+    # load the api key from the .env file
+    #load_dotenv()
+    
+    # inform the user that the api key is loaded
+    if os.getenv("OPENAI_API_KEY") is None or os.getenv("OPENAI_API_KEY") == "":
+        print("OPENAI_API_KEY is not set")
+        exit(1)
+    else:
+        print("OPENAI_API_KEY is set")
+        
+    # inform user that the model being used is the turbo model
+    st.write("Using the gpt-3.5-turbo-0613 model from OpenAI")
+
+
+    # Upload the CSV file
+    csv_file = st.file_uploader("Upload a CSV file", type="csv")
+
+    # if the user has uploaded a csv file then save it to the current directory
+    if csv_file is not None:
+        with open(os.path.join(os.getcwd(), csv_file.name), "wb") as f:
+            f.write(csv_file.getbuffer())
+        st.write("CSV file uploaded to: ", os.path.join(os.getcwd(), csv_file.name))
+
+        # see a preview of the csv file
+        st.write("Preview of the CSV file:")
+         # see a preview of the csv file
+        df = pd.read_csv(os.path.join(os.getcwd(), csv_file.name))
+        st.dataframe(df.head())  # Display the first few rows of the DataFrame
+
+        # create the agent
+        agent = create_csv_agent(
+            ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613"),
+            os.path.join(os.getcwd(), csv_file.name),
+            verbose=True,
+            agent_type=AgentType.OPENAI_FUNCTIONS,
+        )
+
+        # ask the user for a question
+        user_question = st.text_input("Ask a question \U0001F914 about your CSV: ")
+
+        # if the user has asked a question then run the agent
+        if user_question is not None and user_question != "":
+            with st.spinner(text="In progress..."):
+                st.write(agent.run(user_question))
+
+if __name__ == "__main__":
+    main()