Deep Research Agents for Your Data, via API
Listed in categories:
Open SourceDeveloper ToolsArtificial Intelligence
Description
R2R (Reason to Retrieve) is an advanced AI retrieval system that supports Retrieval-Augmented Generation (RAG) with production-ready features. Built around a RESTful API, R2R offers multimodal content ingestion, hybrid search capabilities, knowledge graphs, and comprehensive document management. It also includes a Deep Research API that utilizes a multistep reasoning system to fetch relevant data from knowledge bases and the internet, delivering richer context-aware answers for complex queries.
How to use R2R?
To use R2R, install the SDK via pip or npm, set up your API key, and initialize the R2R client. You can then ingest documents, perform searches, and manage your data through the API.
Core features of R2R:
1️⃣
Multimodal Ingestion: Supports various file types including txt, pdf, json, png, mp3, and more.
2️⃣
Hybrid Search: Combines semantic and keyword search with reciprocal rank fusion.
3️⃣
Knowledge Graphs: Automatically extracts entities and relationships for enhanced data understanding.
4️⃣
Agentic RAG: Integrates reasoning agents with retrieval capabilities for improved query responses.
5️⃣
User Access Management: Provides complete authentication and collection systems.
Why could be used R2R?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Academic research requiring in-depth data retrieval and analysis. | ✅ | |
| # 2 | Business intelligence for extracting insights from diverse document formats. | ✅ | |
| # 3 | Content management systems needing advanced search and document handling capabilities. | ✅ | |
Who developed R2R?
SciPhi is the creator of R2R, focusing on advanced AI solutions that enhance data retrieval and processing capabilities. They provide support and community engagement through platforms like Discord.