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Ragflow

Universal Ragflow API client for RAG operations.

Rating: 4.4 (275 reviews)
Downloads: 5,323 downloads
Version: 1.0.0

Overview

Universal Ragflow API client for RAG operations.

✨Key Features

Dataset management — Create, list, delete knowledge bases

Document upload — Upload files or text content

Chat queries — Run RAG queries against datasets

Chunk management — Trigger parsing, list chunks

Complete Documentation

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Ragflow API Client

Universal client for Ragflow — self-hosted RAG (Retrieval-Augmented Generation) platform.

Features

Dataset management — Create, list, delete knowledge bases
Document upload — Upload files or text content
Chat queries — Run RAG queries against datasets
Chunk management — Trigger parsing, list chunks

Usage

bash

# List datasets
node {baseDir}/scripts/ragflow.js datasets

# Create dataset
node {baseDir}/scripts/ragflow.js create-dataset --name "My Knowledge Base"

# Upload document
node {baseDir}/scripts/ragflow.js upload --dataset DATASET_ID --file article.md

# Chat query
node {baseDir}/scripts/ragflow.js chat --dataset DATASET_ID --query "What is stroke?"

# List documents in dataset
node {baseDir}/scripts/ragflow.js documents --dataset DATASET_ID

Configuration

Set environment variables in your .env:

bash

RAGFLOW_URL=https://your-ragflow-instance.com
RAGFLOW_API_KEY=your-api-key

API

This skill wraps Ragflow's REST API:

GET /api/v1/datasets — List datasets
POST /api/v1/datasets — Create dataset
DELETE /api/v1/datasets/{id} — Delete dataset
POST /api/v1/datasets/{id}/documents — Upload document
POST /api/v1/datasets/{id}/chunks — Trigger parsing
POST /api/v1/datasets/{id}/retrieval — RAG query

Full API docs: https://ragflow.io/docs

Examples

javascript

// Programmatic usage
const ragflow = require('{baseDir}/lib/api.js');

// Upload and parse
await ragflow.uploadDocument(datasetId, './article.md', { filename: 'article.md' });
await ragflow.triggerParsing(datasetId, [documentId]);

// Query
const answer = await ragflow.chat(datasetId, 'What are the stroke guidelines?');

Installation

Terminal bash


openclaw install ragflow

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💻Code Examples

node {baseDir}/scripts/ragflow.js documents --dataset DATASET_ID

node-basedirscriptsragflowjs-documents---dataset-datasetid.txt

## Configuration

Set environment variables in your `.env`:

RAGFLOW_API_KEY=your-api-key

ragflowapikeyyour-api-key.txt

## API

This skill wraps Ragflow's REST API:

- `GET /api/v1/datasets` — List datasets
- `POST /api/v1/datasets` — Create dataset
- `DELETE /api/v1/datasets/{id}` — Delete dataset
- `POST /api/v1/datasets/{id}/documents` — Upload document
- `POST /api/v1/datasets/{id}/chunks` — Trigger parsing
- `POST /api/v1/datasets/{id}/retrieval` — RAG query

Full API docs: https://ragflow.io/docs

## Examples

example.sh

# List datasets
node {baseDir}/scripts/ragflow.js datasets

# Create dataset
node {baseDir}/scripts/ragflow.js create-dataset --name "My Knowledge Base"

# Upload document
node {baseDir}/scripts/ragflow.js upload --dataset DATASET_ID --file article.md

# Chat query
node {baseDir}/scripts/ragflow.js chat --dataset DATASET_ID --query "What is stroke?"

# List documents in dataset
node {baseDir}/scripts/ragflow.js documents --dataset DATASET_ID

example.js

// Programmatic usage
const ragflow = require('{baseDir}/lib/api.js');

// Upload and parse
await ragflow.uploadDocument(datasetId, './article.md', { filename: 'article.md' });
await ragflow.triggerParsing(datasetId, [documentId]);

// Query
const answer = await ragflow.chat(datasetId, 'What are the stroke guidelines?');