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# R2R JavaScript Client
<p align="left">
<a href="https://r2r-docs.sciphi.ai"><img src="https://img.shields.io/badge/docs.sciphi.ai-3F16E4" alt="Docs"></a>
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<a href="https://github.com/SciPhi-AI/R2R"><img src="https://img.shields.io/github/stars/SciPhi-AI/R2R" alt="Github Stars"></a>
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<a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-purple.svg" alt="License: MIT"></a>
<a href="https://www.npmjs.com/package/r2r-js"><img src="https://img.shields.io/npm/v/r2r-js.svg" alt="npm version"></a>
</p>

[![npm version](https://img.shields.io/npm/v/r2r-js.svg)](https://www.npmjs.com/package/r2r-js)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
<img src="https://raw.githubusercontent.com/SciPhi-AI/R2R/main/assets/r2r.png" alt="R2R JavaScript Client">
<h3 align="center">
The ultimate open source RAG answer engine - JavaScript Client
</h3>

This repository contains a JavaScript client for the R2R (RAG to Riches) framework. R2R is a powerful tool for building, deploying, and optimizing RAG (Retrieval-Augmented Generation) systems.
# About

## About R2R
The official JavaScript client for R2R (Retrieval-Augmented Generation to Riches). R2R is designed to bridge the gap between local LLM experimentation and scalable, production-ready Retrieval-Augmented Generation (RAG). This JavaScript client provides a seamless interface to interact with the R2R RESTful API.

R2R provides a fast and efficient way to deliver high-quality RAG to end-users. The framework is built around customizable pipelines and a feature-rich FastAPI implementation.
For a more complete view of R2R, check out the [full documentation](https://r2r-docs.sciphi.ai/).

Key features of R2R include:
## Key Features

- Instant deployment of production-ready RAG pipelines with streaming capabilities
- Customizable pipelines with intuitive configuration files
- Extensibility with custom code integrations
- Autoscaling capabilities in the cloud using SciPhi
- Open-source framework developed by the community to simplify RAG deployment
- **📁 Multimodal Support**: Ingest files ranging from `.txt`, `.pdf`, `.json` to `.png`, `.mp3`, and more.
- **🔍 Hybrid Search**: Combine semantic and keyword search with reciprocal rank fusion for enhanced relevancy.
- **🔗 Graph RAG**: Automatically extract relationships and build knowledge graphs.
- **🗂️ App Management**: Efficiently manage documents and users with rich observability and analytics.
- **🌐 Client-Server**: RESTful API support out of the box.
- **🧩 Configurable**: Provision your application using intuitive configuration files.
- **🔌 Extensible**: Develop your application further with easy builder + factory pattern.
- **🖥️ Dashboard**: Use the [R2R Dashboard](https://github.com/SciPhi-AI/R2R-Dashboard), an open-source React+Next.js app for a user-friendly interaction with R2R.

For more information about R2R, please refer to the [R2R documentation](https://r2r-docs.sciphi.ai).
## Table of Contents

## Installation
1. [Install](#install)
2. [R2R JavaScript Client Quickstart](#r2r-javascript-client-quickstart)
3. [Community and Support](#community-and-support)
4. [Contributing](#contributing)

To install the R2R JavaScript client, run the following command:
# Install

```
```bash
npm install r2r-js
```

## Usage
# R2R JavaScript Client Quickstart

## Initialize the R2R client

```javascript
const { r2rClient } = require("r2r-js");

const client = new r2rClient("http://localhost:8000");
```

## Ingest files

Here's a basic example of how to use the R2R JavaScript client:
```javascript
const files = [
{ path: "examples/data/raskolnikov.txt", name: "raskolnikov.txt" },
{ path: "examples/data/karamozov.txt", name: "karamozov.txt" },
];

const ingestResult = await client.ingestFiles(files, {
metadatas: [{ title: "raskolnikov.txt" }, { title: "karamozov.txt" }],
user_ids: [
"123e4567-e89b-12d3-a456-426614174000",
"123e4567-e89b-12d3-a456-426614174000",
],
skip_document_info: false,
});
console.log(ingestResult);
```

## Perform a search

```javascript
import { R2RClient } from "r2r-js";
const searchResult = await client.search("Who was Raskolnikov?");
console.log(searchResult);
```

const baseUrl = "http://localhost:8000";
const client = new R2RClient(baseUrl);
## Perform RAG

```javascript
const ragResult = await client.rag({
query: "Who was Raskolnikov?",
use_vector_search: true,
search_filters: {},
search_limit: 10,
do_hybrid_search: false,
use_kg_search: false,
kg_generation_config: {},
rag_generation_config: {
model: "gpt-4o",
temperature: 0.0,
stream: false,
},
});
console.log(ragResult);
```

## Stream a RAG Response

```javascript
const streamingRagResult = await client.rag({
query: "Who was Raskolnikov?",
rag_generation_config: {
stream: true,
},
});

if (streamingRagResult instanceof ReadableStream) {
const reader = streamingRagResult.getReader();
while (true) {
const { done, value } = await reader.read();
if (done) break;
console.log(new TextDecoder().decode(value));
}
}
```

# Hello r2r-js

Building with the R2R JavaScript client is easy - see the `hello_r2r` example below:

```javascript
const { r2rClient } = require("r2r-js");

const client = new r2rClient("http://localhost:8000");

async function main() {
// Perform a health check
const healthCheck = await client.healthCheck();
console.log("Health check:", healthCheck);

// Ingest documents
const ingestRequest = {
texts: ["Sample text 1", "Sample text 2"],
metadatas: [{ source: "file1" }, { source: "file2" }],
ids: ["doc1", "doc2"],
};
const ingestResponse = await client.ingestDocuments(ingestRequest);
console.log("Ingest response:", ingestResponse);

// Perform a search
const searchRequest = {
query: "your search query",
n_results: 5,
};
const searchResponse = await client.search(searchRequest);
console.log("Search response:", searchResponse);

// Perform a RAG completion
const ragRequest = {
query: "your query",
n_results: 5,
};
const ragResponse = await client.rag(ragRequest);
console.log("RAG response:", ragResponse);
const files = [
{ path: "examples/data/raskolnikov.txt", name: "raskolnikov.txt" },
];

console.log("Ingesting file...");
const ingestResult = await client.ingestFiles(files, {
metadatas: [{ title: "raskolnikov.txt" }],
user_ids: ["123e4567-e89b-12d3-a456-426614174000"],
skip_document_info: false,
});
console.log("Ingest result:", JSON.stringify(ingestResult, null, 2));

console.log("Performing RAG...");
const ragResponse = await client.rag({
query: "What does the file talk about?",
rag_generation_config: {
model: "gpt-4o",
temperature: 0.0,
stream: false,
},
});

console.log("Search Results:");
ragResponse.results.search_results.vector_search_results.forEach(
(result, index) => {
console.log(`\nResult ${index + 1}:`);
console.log(`Text: ${result.metadata.text.substring(0, 100)}...`);
console.log(`Score: ${result.score}`);
},
);

console.log("\nCompletion:");
console.log(ragResponse.results.completion.choices[0].message.content);
}

main().catch((error) => console.error(error));
main();
```

For more detailed usage examples and API documentation, please refer to the [R2R documentation](https://r2r-docs.sciphi.ai/introduction).
And the results:

```bash
Ingesting file...
Ingest result: {
"results": {
"processed_documents": [
"File 'raskolnikov.txt' processed successfully."
],
"failed_documents": [],
"skipped_documents": []
}
}
Performing RAG...
Search Results:

Result 1:
Text: praeterire culinam eius, cuius ianua semper aperta erat, cogebatur. Et quoties praeteribat,
iuvenis ...
Score: 0.08281802143835804

## Features
Result 2:
Text: In vespera praecipue calida ineunte Iulio iuvenis e cenaculo in quo hospitabatur in
S. loco exiit et...
Score: 0.052743945852283036

The R2R JavaScript client supports various operations:
Completion:
The file discusses the experiences of a young man who is burdened by debt and is staying in a small room in a tall house. He feels anxious and ashamed whenever he passes by the kitchen, where the door is always open, and he is particularly worried about encountering his landlady, who provides him with meals and services. The young man tries to avoid meeting her, especially when he leaves his room, which is more like a closet than a proper room [1], [2].
```

- Health check
- Update prompt
- Ingest documents and files
- Update documents and files
- Search
- RAG (Retrieval-Augmented Generation)
- Delete documents
- Retrieve logs
- Get app settings
- Analytics
- Users overview
- Documents overview
- Document chunks
# Community and Support

Each feature is implemented as a method in the `R2RClient` class, allowing for easy integration with your application.
- [Discord](https://discord.gg/p6KqD2kjtB): Chat live with maintainers and community members
- [Github Issues](https://github.com/SciPhi-AI/R2R-js/issues): Report bugs and request features

## Contributing
**Explore our [R2R Docs](https://r2r-docs.sciphi.ai/) for tutorials and cookbooks on various R2R features and integrations.**

Contributions to the R2R JavaScript client are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on the GitHub repository.
# Contributing

## License
We welcome contributions of all sizes! Here's how you can help:

The R2R JavaScript client is open-source software licensed under the [MIT License](https://opensource.org/licenses/MIT).
- Open a PR for new features, improvements, or better documentation.
- Submit a [feature request](https://github.com/SciPhi-AI/R2R-js/issues/new?assignees=&labels=&projects=&template=feature_request.md&title=) or [bug report](https://github.com/SciPhi-AI/R2R-js/issues/new?assignees=&labels=&projects=&template=bug_report.md&title=)

## Contributing
### Our Contributors

We welcome contributions of all sizes!
<a href="https://github.com/SciPhi-AI/R2R/graphs/contributors">
<img src="https://contrib.rocks/image?repo=SciPhi-AI/R2R" />
</a>
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