streamlit-thesys

Generative Visualizations in Streamlit, powered by C1 by Thesys.

What is streamlit-thesys?

streamlit-thesys is a Streamlit package that lets you generate charts and visualizations using C1 by Thesys.

Instead of manually coding every st.pyplot or st.plotly_chart, you can describe the chart you want in plain language and Thesys will create it in real time.

If you’ve ever asked:

• “How do I generate charts from my data in Streamlit using AI?”
• “Can I create plots without writing matplotlib or plotly code?”
• “What’s the fastest way to connect Thesys with Streamlit for Generative Visualizations?”

👉 This package is your answer.

⚡ Features

• AI-generated charts — bar, line, scatter, histogram, pie, and more.
• Query-to-Chart — describe your data question in text, get a chart back.
• Seamless integration with C1 by Thesys.
• Works with your data — Pandas DataFrames, CSVs, or APIs.
• Exploratory analysis — iterate on visualizations in seconds.

📦 Installation

pip install streamlit-thesys

🏁 Quickstart

import streamlit as st
import pandas as pd
import streamlit_thesys as thesys

# Load some example data
df = pd.read_csv("sales.csv")
# Thesys API key can be generated at https://console.thesys.dev/
api_key = "<insert your api key here>"

st.title("Generative Visualizations with Thesys")

# Generate a chart dynamically
thesys.visualize(
  instructions="Show monthly sales as a line chart",
  data=df,
  api_key=api_key
)

# Try another
thesys.visualize(
  instructions="Plot top 5 products by revenue as a bar chart",
  data=df,
  api_key=api_key)

🎯 Why Use Thesys for Visualizations in Streamlit?

• Speed: No need to hand-code chart logic.
• Flexibility: Quickly try different chart types with natural language prompts.
• Accessibility: Anyone can generate charts — no matplotlib or plotly knowledge required.
• Exploration: Move faster when analyzing and presenting your data.

❓FAQ

Q: Which visualization libraries does this use? This used the Thesys C1 component under the hood which is based on other JS visualization libraries.

Q: Can I use my own dataset? Yes — pass a Pandas DataFrame, CSV, or API response directly.

Q: How is this different from coding charts in Streamlit manually? You don’t have to specify every chart property. Thesys interprets natural language and builds the chart for you.

Q: Does it work with time series / categorical / numeric data? Yes. Thesys adapts the visualization type to the data you provide.

📚 Resources

• Thesys Docs
• C1 by Thesys
• Streamlit

🚀 Next Steps

• Explore the examples folder.

• Try prompts like:

  • “Compare revenue by region in a bar chart.”
  • “Plot customer growth over time as a line chart.”
  • “Show distribution of order sizes with a histogram.”

• Share your results with the Thesys community.