|
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): |
|
|
|
byte_data = base64.b64decode(base64_string) |
|
|
|
|
|
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) |
|
|
