●6 reads●MIT License
Streamlit AI Guide: AI-Powered Streamlit Documentation Tutor
- AAIDC2025
- Gemini
- RAG
- Streamlit
Table of contents
Streamlit AI Guide: AI-Powered Streamlit Documentation Tutor
Abstract
Streamlit AI Guide is your personal AI tutor for Streamlit. It helps you learn faster by turning official documentation into a smart, chatty guide. Just ask questions in plain English, and it gives clear answers and even writes code examples on the spot. It's a simple, interactive way to master Streamlit, showing how AI can make learning easier.
1. Introduction
Learning new tools, like Streamlit for building apps, can feel like a big puzzle. It's often hard to find what you need in huge guides. I built this tool to fix that.
Streamlit AI Guide turns boring documents into a lively chat. Instead of searching forever, you just ask. The Streamlit AI Guide gives you clear answers. It can even make working code examples for you right away. This really makes learning faster. Think of it as your own Streamlit expert. It is always ready to help you build great apps!
2. Key Features
- Interactive Chat Interface: Enjoy a smooth, user-friendly chat experience right in your web browser.
- Conversational Memory: Streamlit AI Guide remembers what we've talked about. If you ask a follow-up question, like "What about its arguments?" after discussing a function, it knows what "its" refers to. This makes our chats feel natural and easy.
- Context-Aware Responses: All answers come from Streamlit’s official documentation, so it reducing AI "hallucinations" and ensuring you get accurate, reliable information
- On-Demand Code Examples: Ask how to use something like st.slider, and the guide will give you a short, working code example you can try right away.
- Focused on Streamlit Only: This guide is built for Streamlit. If you ask about math or another tool, it’ll tell you it doesn’t cover that. It sticks to what it knows best.
- See the Source: For answers that come from the documents, you can click "Show Retrieved Sources." This lets you see the exact parts the AI used. It helps you trust the answers. This source section hides itself if the AI cannot find info or cannot answer your question.
3. Technologies Used
Frontend Interface
- Streamlit – Simple and interactive UI built using Streamlit.
AI Brain (RAG System)
- LangChain – Orchestrates how the AI retrieves and responds with relevant information.
Vector Database
- ChromaDB – Stores indexed Streamlit documentation for fast, accurate lookups.
Large Language Model (LLM) & Embeddings
- Google Gemini API
gemini-1.5-flash– Handles conversation and answers.embedding-001– Converts text into embeddings for better understanding.
Document Loading & Processing
- RecursiveUrlLoader, WebBaseLoader, BeautifulSoupTransformer, RecursiveCharacterTextSplitter - These tools help load and break down content from web pages into usable chunks.
Secret Management
- python-dotenv – Keeps your API keys and environment variables safe on your local machine.
4. Technical Approach
The Streamlit AI Guide works by combining a few smart steps to give you the best answers. This entire process is called Retrieval-Augmented Generation (RAG). It means our AI can fetch specific information from a knowledge base before forming its response.
4.1. Building the Knowledge Base
Everything starts with collecting the official Streamlit documentation. The system goes through the Streamlit website and gathers content from all the important pages. Once the information is collected, it cleans each page by removing the extra code and keeping only the useful text.
After that, the clean text is split into smaller parts. These smaller parts help the AI process the information better and keep related ideas together. Each part is then turned into a special set of numbers that represent its meaning. This is done using Google's embedding model called embedding-001. These sets of numbers, along with the original text and its source, are stored in a local database called ChromaDB.
4.2. Information Retrieval
When you ask a question, the system first turns your question into the same kind of number format as the stored information. It then compares your question with everything in the database and finds the parts that are most closely related.
The AI picks out the most useful and relevant pieces of information. These selected pieces give the AI the context it needs to understand what you are asking.
4.3. Response Generation
Once the AI has the right information, it uses Google’s Gemini 1.5 Flash model to write the answer. A carefully designed prompt tells the AI how to respond and includes instructions to act like a Streamlit expert. It also includes the helpful information found in the database and any earlier messages from our chat.
The AI brings everything together and writes a clear and helpful response based on both the new information and the conversation so far. This whole process happens smoothly in the background to give you exactly what you need.
Demonstrative Interaction
Here's a quick example of how the Streamlit AI Guide can help you:
Results
Building the Streamlit AI Guide has shown clear success. We now have a working AI tutor that gives accurate answers to Streamlit questions. It makes useful code examples right in the chat. The AI successfully uses the official documentation to form its replies. This project proves that we can make learning easier and more direct using AI.
Use Cases
The Streamlit AI Guide is a great companion for anyone learning or working with Streamlit. If you're new to Streamlit, think of this guide as your personal tutor. You can ask questions anytime and get clear, simple answers without having to dig through long manuals.
If you're a busy developer, it’s there when you need a quick reminder about a function or a code example. It gives you fast, helpful answers so you can stay focused on your work.
When you run into a coding issue, the guide can help explain the problem and walk you through the solution in a way that makes sense.
And even if you just need an extra hand, it works like a reliable teammate who knows Streamlit well and is always ready to help.
Conclusion
The Streamlit AI Guide is a project that successfully brings smart AI to everyday learning. By creating an AI tutor focused just on Streamlit, it makes complex information easy to get. This tool shows how valuable AI can be when it is built to help people directly. It is a clear step towards building AI tools that really make a difference in how we learn and create.