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import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
from pandasai import SmartDataframe
from pandasai.llm import OpenAI
from pandasai.callbacks import BaseCallback
from pandasai.responses.response_parser import ResponseParser
import os
# Set OpenAI API Token
OPENAI_API_TOKEN = os.getenv("BIT_OPENAI_API_KEY", "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")
# Load OpenAI Mini model
llm = OpenAI(api_token=OPENAI_API_TOKEN, model_name="gpt-4o-mini")
class StreamlitCallback(BaseCallback):
def __init__(self, container) -> None:
"""Initialize callback handler."""
self.container = container
def on_code(self, response: str):
self.container.code(response)
class StreamlitResponse(ResponseParser):
def __init__(self, context) -> None:
super().__init__(context)
def format_dataframe(self, result):
st.dataframe(result["value"])
return
def format_plot(self, result):
st.image(result["value"])
return
def format_other(self, result):
st.write(result["value"])
return
def process_file(file):
file_extension = file.name.split(".")[-1].lower()
try:
if file_extension == "csv":
# Detect if semicolon or comma is used as a separator
first_line = file.readline().decode("utf-8")
file.seek(0) # Reset file pointer
delimiter = ";" if ";" in first_line else ","
df = pd.read_csv(file, delimiter=delimiter)
elif file_extension in ["xls", "xlsx"]:
import openpyxl # Ensures openpyxl is available
df = pd.read_excel(file, engine="openpyxl")
else:
st.error("Unsupported file format. Please upload a CSV or Excel file.")
return None, None
except ImportError as e:
st.error(f"Error: {e}. Please install 'openpyxl' for Excel support.")
return None, None
sdf = SmartDataframe(df, config={
"llm": llm,
"save_logs": True,
"verbose": False,
"response_parser": StreamlitResponse
})
return df, sdf
def main():
st.title("AI-Powered Dataframe Analysis with OpenAI")
uploaded_file = st.file_uploader("Upload CSV or Excel File", type=["csv", "xls", "xlsx"])
if uploaded_file:
df, sdf = process_file(uploaded_file)
if df is not None:
st.subheader("🔎 Data Preview")
with st.expander("View Data Summary"):
st.write("### Data Overview")
st.dataframe(df.describe(include='all'))
st.write("### First 10 Rows of Data")
st.dataframe(df.head(10))
st.write("### Column Details")
for col in df.columns:
st.write(f"**{col}**")
st.dataframe(df[[col]].head(10))
query = st.text_area("Enter Your Query")
if query:
container = st.container()
answer = sdf.chat(query)
if __name__ == "__main__":
main()
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