Streamlit ↗

Documentation Index#

Fetch the complete documentation index at: https://docs.trychroma.com/llms.txt Use this file to discover all available pages before exploring further.

Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science. In just a few minutes you can build and deploy powerful data apps.

Apache 2.0 License | Site

Install#

Install Streamlit: pip install streamlit

Install streamlit-chromadb-connection, which connects your Streamlit app to Chroma through st.connection: pip install streamlit-chromadb-connection

Main Benefits#

• Easy to get started with Streamlit’s straightforward syntax
• Built-in chatbot functionality
• Pre-built integration with Chroma via streamlit-chromadb-connection
• Deploy apps for free on Streamlit Community Cloud

Simple Example#

Python#

import streamlit as st
from streamlit_chromadb_connection.chromadb_connection import ChromadbConnection

configuration = {
    "client": "PersistentClient",
    "path": "/tmp/.chroma"
}

collection_name = "documents_collection"

conn = st.connection("chromadb",
                     type=ChromaDBConnection,
                     **configuration)
documents_collection_df = conn.get_collection_data(collection_name)
st.dataframe(documents_collection_df)

Resources#

• Instructions for using streamlit-chromadb-connection to connect your Streamlit app to Chroma
• Demo app for streamlit-chromadb-connection
• Streamlit’s st.connection documentation
• Guide to using vector databases with Streamlit

Tutorials#

• Build an “Ask the Doc” app using Chroma, Streamlit, and LangChain
• Summarize documents with Chroma, Streamlit, and LangChain
• Build a custom chatbot with Chroma, Streamlit, and LangChain
• Build a RAG bot using Chroma, Streamlit, and LangChain
• Build a PDF QA chatbot with Chroma, Streamlit, and OpenAI