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DataBridge Documentation

What is DataBridge?

Getting Started

Get the most out of DataBridge by customizing it to your needs

Configure DataBridge

An overview of Retrieval Augmented Generation with Vector Similarity Search

Introduction to RAG

An overview of rules based ingestion in DataBridge

Rules

When retrieving text information is not enough

Multimodal Data

Work with unstructured information with the same consistency and guarantees as structured information

Database Primitives

A collection of recipes to help you get started with DataBridge

Cache Augmented Generation: Speeding up RAG

Embedding and Retrieving Complex Multi-Modal Data

Knowledge Graph - Based RAG

Retrieving over Video Data

Integrating your data with Claude.ai and other MCP clients

Model Context Protocol

Readiness check that verifies the application is initialized.

Readiness Check

Ingest Text

Ingest File

Retrieve Chunks

Retrieve Documents

Generate completion using relevant chunks as context.

Query Completion

List Documents

Get Document

Get usage statistics for the authenticated user.

Get Usage Stats

Get Recent Usage

Create a new cache with specified configuration.

Create Cache

Get Cache

Update cache with new documents matching its filter.

Update Cache

Add Docs To Cache

Query Cache

Generate a local URI for development. This endpoint is unprotected.

Generate Local Uri

Introduction

Get started with the DataBridge Python SDK

Quick Start

Advanced Usage

Image Handling

Using DataBridge asynchronously with Python

Asynchronous Usage

Detailed API documentation for DataBridge Python SDK

API Reference

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