--- title: "RAG (Data)" description: "How to use our inbuilt RAG" icon: "database" --- # Using RAG in Rowboat Rowboat provides multiple ways to enhance your agents' context with Retrieval-Augmented Generation (RAG). This guide will help you set up and use each RAG feature. RAG is called "Data" on the build view in the Rowboat UI. --- ## Types of RAG | RAG Type | Description | Configuration Required | |----------|-------------|------------------------| | **Text RAG** | Process and reason over text content directly | No configuration needed | | **File Uploads** | Upload PDF files directly from your device | No configuration needed | | **URL Scraping** | Scrape content from web URLs using Firecrawl | Requires API key setup | URL Scraping does not require any setup in the managed version of Rowboat. Adding data sources for RAG in Rowboat ## RAG Features ### 1. Text RAG Process and reason over text content directly ### 2. File Uploads - Upload PDF files directly from your device - **Open Source Version**: Files are stored locally on your machine - **Managed Version**: Files are stored in cloud S3 storage - Files are parsed using OpenAI by default You can also use Google's Gemini model for parsing as it is better at parsing larger files. #### 2.1 Using Gemini for File Parsing To use Google's Gemini model for parsing uploaded PDFs, set the following variables: ```bash # Enable Gemini for file parsing export USE_GEMINI_FILE_PARSING=true export GOOGLE_API_KEY=your_google_api_key ``` ### 3. URL Scraping Rowboat uses Firecrawl for URL scraping. You can have a maximum of 100 URLs. **Open Source Version**: To enable URL scraping, set the following variables: ```bash export USE_RAG_SCRAPING=true export FIRECRAWL_API_KEY=your_firecrawl_api_key ``` **Managed Version**: No configuration required - URL scraping is handled automatically.