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import streamlit as st
from lida import Manager, TextGenerationConfig , llm
from dotenv import load_dotenv
import os
import openai
from PIL import Image
from io import BytesIO
import base64
load_dotenv()
openai.api_key = os.getenv('OPENAI_API_KEY')
def base64_to_image(base64_string):
# Decode the base64 string
byte_data = base64.b64decode(base64_string)
# Use BytesIO to convert the byte data to image
return Image.open(BytesIO(byte_data))
lida = Manager(text_gen = llm("openai"))
textgen_config = TextGenerationConfig(n=1, temperature=0.5, model="gpt-3.5-turbo-0301", use_cache=True)
menu = st.sidebar.selectbox("Choose an Option", ["Summarize", "Question based Graph"])
if menu == "Summarize":
st.subheader("Summarization of your Data")
file_uploader = st.file_uploader("Upload your CSV", type="csv")
if file_uploader is not None:
path_to_save = "filename.csv"
with open(path_to_save, "wb") as f:
f.write(file_uploader.getvalue())
summary = lida.summarize("filename.csv", summary_method="default", textgen_config=textgen_config)
st.write(summary)
goals = lida.goals(summary, n=2, textgen_config=textgen_config)
for goal in goals:
st.write(goal)
i = 0
library = "seaborn"
textgen_config = TextGenerationConfig(n=1, temperature=0.2, use_cache=True)
charts = lida.visualize(summary=summary, goal=goals[i], textgen_config=textgen_config, library=library)
img_base64_string = charts[0].raster
img = base64_to_image(img_base64_string)
st.image(img)
elif menu == "Question based Graph":
st.subheader("Query your Data to Generate Graph")
file_uploader = st.file_uploader("Upload your CSV", type="csv")
if file_uploader is not None:
path_to_save = "filename1.csv"
with open(path_to_save, "wb") as f:
f.write(file_uploader.getvalue())
text_area = st.text_area("Query your Data to Generate Graph", height=200)
if st.button("Generate Graph"):
if len(text_area) > 0:
st.info("Your Query: " + text_area)
lida = Manager(text_gen = llm("openai"))
textgen_config = TextGenerationConfig(n=1, temperature=0.2, use_cache=True)
summary = lida.summarize("filename1.csv", summary_method="default", textgen_config=textgen_config)
user_query = text_area
charts = lida.visualize(summary=summary, goal=user_query, textgen_config=textgen_config)
charts[0]
image_base64 = charts[0].raster
img = base64_to_image(image_base64)
st.image(img)
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