Just build it
How we design Streamlit to bias you toward forward progress.
How to build a movie recommendation app without the complexities of vector databases
Use the Streamlit-Weaviate Connection to integrate a vector database
How to create an AI chatbot using one API to access multiple LLMs
Programmatically integrate AI with Replicate and Streamlit
Streamlit 101: The fundamentals of a Python data app
Streamlit empowers data scientists to quickly build interactive data apps effortlessly
pip vs. uv: How Streamlit Cloud sped up app load times by 55%
After discovering a dependency installation bottleneck, we decided to try out Astral uv – the new pip drop-in replacement written in Rust.
Meet Snowflake Arctic, our new LLM!
A truly open large language model that pushes the frontiers of cost-effective training and openness.
Grounded multi-doc Q&A made simple with AI21
In just a few steps, build a context-based question-answering app based on your own documents and powered by AI21’s RAG Engine and task-specific models
Build a real-time RAG chatbot using Google Drive and Sharepoint
Keep your chatbot’s knowledge base up-to-date with Pathway and LlamaIndex
Building a dashboard in Python using Streamlit
Using pandas for data wrangling, Altair/Plotly for data visualization, and Streamlit as your frontend
Connect your Streamlit apps to Supabase
Learn how to connect your Streamlit apps to Supabase with the st-supabase-connection component
Using time-based RAG in LLM apps
Build a GitHub commit chatbot using Timescale Vector, pgvector, and LlamaIndex