Can I filter search results by document type?

Yes, the SDK includes a SearchFilters class that allows you to narrow down semantic search results by specific data sources, filenames, and MIME types.

Does the SDK support document management?

Yes, the SDK provides methods for ingesting files, polling for processing task completion, and deleting documents from your knowledge base.

How do I handle streaming responses with OpenRAG?

The SDK provides async stream generators in Python and event-based iterators in TypeScript to handle real-time content delivery, source attribution, and completion events.

What languages does the OpenRAG SDK support?

The OpenRAG SDK provides first-class support for Python and TypeScript/JavaScript, as well as an MCP (Model Context Protocol) server for LLM integration.

How is authentication handled in the OpenRAG SDK?

You can configure authentication using the OPENRAG_API_KEY environment variable or by passing an explicit api_key to the OpenRAGClient constructor.

OpenRAG SDK Integration | Claude Code Skill

The OpenRAG SDK skill provides a comprehensive framework for developers to embed production-grade AI retrieval and generation capabilities into their applications. It guides Claude in assisting with the installation and configuration of Python and TypeScript/JavaScript SDKs, implementing streaming chat interfaces, and managing complex document ingestion workflows. By leveraging the OpenRAG stack—including Langflow, Docling, and Opensearch—this skill enables the creation of sophisticated AI agents that can interact with private knowledge bases, manage conversation histories, and perform precise semantic searches with customizable filters.

Key Features

01Implementation of both streaming and non-streaming RAG chat interfaces

02Automated document ingestion and multi-source knowledge management

03Cross-platform SDK support for Python and TypeScript/JavaScript

04Seamless MCP (Model Context Protocol) server integration and configuration

05Advanced semantic search with metadata filtering and score thresholds

064,156 GitHub stars

Use Cases

01Integrating private knowledge bases into existing web and mobile applications

02Developing custom AI-powered chat interfaces for enterprise documentation

03Building automated document processing pipelines with semantic search capabilities

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