Files
ragflow/internal/cli
Jin Hai e96bc37d06 Go: use NATS as the message queue (#15327)
### What problem does this PR solve?

```
RAGFlow(admin)> mq publish 'msg2';
SUCCESS
RAGFlow(admin)> mq publish 'msg3';
SUCCESS
RAGFlow(admin)> mq list;
+---------+---------------+
| message | subject       |
+---------+---------------+
| msg1    | tasks.RAGFLOW |
| msg2    | tasks.RAGFLOW |
| msg3    | tasks.RAGFLOW |
+---------+---------------+
RAGFlow(admin)> mq pull 2;
+---------+---------------+
| message | subject       |
+---------+---------------+
| msg1    | tasks.RAGFLOW |
| msg2    | tasks.RAGFLOW |
+---------+---------------+
RAGFlow(admin)> mq pull noack;
+---------+---------------+
| message | subject       |
+---------+---------------+
| abc     | tasks.RAGFLOW |
+---------+---------------+
RAGFlow(admin)> mq show
+-------------------+----------------+--------+---------------+---------------+-------------------+---------------+
| ack_pending_count | consumer_count | memory | message_count | pending_count | redelivered_count | waiting_count |
+-------------------+----------------+--------+---------------+---------------+-------------------+---------------+
| 2                 | 1              | 0      | 2             | 0             | 1                 | 0             |
+-------------------+----------------+--------+---------------+---------------+-------------------+---------------+

RAGFlow(admin)> list ingestors;
+--------------+-------------------------------------------+--------+
| host         | name                                      | status |
+--------------+-------------------------------------------+--------+
| 192.168.1.38 | ingestor-8f0e4bd5650a4ac58b0151969fbf6935 | alive  |
+--------------+-------------------------------------------+--------+

RAGFlow(admin)> list ingestion tasks;
+----------------------------------+----------------------------------+-----------+------+-------------+----------------------------------+
| document_id                      | id                               | status    | step | user        | user_id                          |
+----------------------------------+----------------------------------+-----------+------+-------------+----------------------------------+
| ffe64fae423411f1a2d938a74640adcc | 90d3d0f6528941c1ac8eb0360effccc4 | COMPLETED | 5    | aaa@aaa.com | 2ba4881420fa11f19e9c38a74640adcc |
+----------------------------------+----------------------------------+-----------+------+-------------+----------------------------------+

RAGFlow(admin)> remove ingestion tasks '90d3d0f6528941c1ac8eb0360effccc4';
+---------+----------------------------------+
| delete  | task_id                          |
+---------+----------------------------------+
| success | 90d3d0f6528941c1ac8eb0360effccc4 |
+---------+----------------------------------+

RAGFlow(admin)> stop ingestion tasks 'e89e20d9a25848a1b79bd9345ddbfe1d';
+----------+----------------------------------+
| status   | task_id                          |
+----------+----------------------------------+
| STOPPING | e89e20d9a25848a1b79bd9345ddbfe1d |
+----------+----------------------------------+

# Publish a message
RAGFlow(admin)> mq publish 'cdd';
SUCCESS

# List current tasks in the message queue
RAGFlow(admin)> mq list
+----------------------------------+---------------+
| message                          | subject       |
+----------------------------------+---------------+
| 7ce392a3c1624cd2be4b5276e8825059 | tasks.RAGFLOW |
+----------------------------------+---------------+

# Consume a task from the message queue
RAGFlow(admin)> mq pull
+------+-----+----------------+
| ack  | id  | type           |
+------+-----+----------------+
| true | cdd | ingestion_test |
+------+-----+----------------+

# User mode
# List ingestion tasks, followed by dataset id
RAGFlow(user)> list ingestion tasks from '0abe79f9423311f1ad8d38a74640adcc';
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+
| create_date               | create_time   | dataset_id                       | document_id                      | id                               | schema | status    | update_date               | update_time   | user_id                          |
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+
| 2026-05-30T20:21:06+08:00 | 1780143666289 | 0abe79f9423311f1ad8d38a74640adcc | ffe64fae423411f1a2d938a74640adcc | 8d758cd14a8b4ba8ab505003fb52017d |        | COMPLETED | 2026-05-30T20:21:26+08:00 | 1780143686431 | 2ba4881420fa11f19e9c38a74640adcc |
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+

RAGFlow(user)> list ingestion tasks;
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+
| create_date               | create_time   | dataset_id                       | document_id                      | id                               | schema | status    | update_date               | update_time   | user_id                          |
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+
| 2026-06-02T19:02:31+08:00 | 1780398151417 | 0abe79f9423311f1ad8d38a74640adcc | ffe64fae423411f1a2d938a74640adcc | e89e20d9a25848a1b79bd9345ddbfe1d |        | COMPLETED | 2026-06-02T19:02:52+08:00 | 1780398172208 | 2ba4881420fa11f19e9c38a74640adcc |
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+

# Create an ingestion task
# First argument is document id, second argument is dataset id
RAGFlow(user)> start ingestion 'ffe64fae423411f1a2d938a74640adcc' from '0abe79f9423311f1ad8d38a74640adcc';
+----------------------------------+-------------------------------------------+
| document_id                      | result                                    |
+----------------------------------+-------------------------------------------+
| ffe64fae423411f1a2d938a74640adcc | task_id: 8d758cd14a8b4ba8ab505003fb52017d |
+----------------------------------+-------------------------------------------+

# Pause an ingestion task, first argument is ingestion id
RAGFlow(user)> stop ingestion '8d758cd14a8b4ba8ab505003fb52017d';
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+
| create_date               | create_time   | dataset_id                       | document_id                      | id                               | schema | status    | update_date               | update_time   | user_id                          |
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+
| 2026-05-30T20:21:06+08:00 | 1780143666289 | 0abe79f9423311f1ad8d38a74640adcc | ffe64fae423411f1a2d938a74640adcc | 8d758cd14a8b4ba8ab505003fb52017d |        | COMPLETED | 2026-05-30T20:21:26+08:00 | 1780143686431 | 2ba4881420fa11f19e9c38a74640adcc |
+---------------------------+---------------+----------------------------------+----------------------------------+----------------------------------+--------+-----------+---------------------------+---------------+----------------------------------+

# Delete an ingestion task
RAGFlow(api/default)> remove ingestion tasks 'f366450a27d54677aec1c7090add30f0';
+---------+----------------------------------+
| remove  | task_id                          |
+---------+----------------------------------+
| success | f366450a27d54677aec1c7090add30f0 |
+---------+----------------------------------+

```

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

---------

Signed-off-by: Jin Hai <haijin.chn@gmail.com>
2026-06-12 14:56:44 +08:00
..
2026-06-09 15:22:50 +08:00
2026-03-04 19:17:16 +08:00
2026-06-10 16:06:30 +08:00
2026-06-09 17:00:10 +08:00

RAGFlow CLI (Go Version)

This is the Go implementation of the RAGFlow command-line interface, compatible with the Python version's syntax.

Features

  • Interactive mode and single command execution
  • Full compatibility with Python CLI syntax
  • Recursive descent parser for SQL-like commands
  • Virtual Filesystem for intuitive resource management
  • Support for all major commands:
    • User management: LOGIN, REGISTER, CREATE USER, DROP USER, LIST USERS, etc.
    • Service management: LIST SERVICES, SHOW SERVICE, STARTUP/SHUTDOWN/RESTART SERVICE
    • Role management: CREATE ROLE, DROP ROLE, LIST ROLES, GRANT/REVOKE PERMISSION
    • Dataset management via Virtual Filesystem: ls, search, mkdir, cat, rm
    • Model management: SET/RESET DEFAULT LLM/VLM/EMBEDDING/etc.
    • And more...

Usage

Build and run

go build -o ragflow_cli ./cmd/ragflow_cli.go
./ragflow_cli

Architecture

internal/cli/
├── cli.go              # Main CLI loop and interaction
├── client.go           # RAGFlowClient with Filesystem integration
├── http_client.go      # HTTP client for API communication
├── parser/             # Command parser package
│   ├── types.go        # Token and Command types
│   ├── lexer.go        # Lexical analyzer
│   └── parser.go       # Recursive descent parser
└── filesystem/         # Virtual Filesystem
    ├── engine.go       # Core engine: path resolution, command routing
    ├── types.go        # Node, Command, Result types
    ├── base.go         # Provider interface definition    
    ├── dataset.go      # Dataset provider implementation
    ├── file.go         # File manager provider implementation
    └── utils.go        # Helper functions

Virtual Filesystem

The Virtual Filesystem provides a unified filesystem interface over RAGFlow's RESTful APIs.

Design Principles

  1. No Server-Side Changes: All logic implemented client-side using existing APIs
  2. Provider Pattern: Modular providers for different resource types (datasets, files, etc.)
  3. Unified Interface: Common ls, search, mkdir commands across all providers
  4. Path-Based Navigation: Virtual paths like /datasets, /datasets/{name}/files

Supported Paths

Path Description
/datasets List all datasets
/datasets/{name} List documents in dataset (default behavior)
/datasets/{name}/{doc} Get document info

Commands

ls [path] [options] - List nodes at path

List contents of a path in the context filesystem.

Arguments:

  • [path] - Path to list (default: "datasets")

Options:

  • -n, --limit <number> - Maximum number of items to display (default: 10)
  • -h, --help - Show ls help message

Examples:

ls                              # List all datasets (default 10)
ls -n 20                        # List 20 datasets
ls datasets/kb1                 # List files in kb1 dataset
ls datasets/kb1 -n 50           # List 50 files in kb1 dataset

search [options] - Search for content

Semantic search in datasets.

Options:

  • -n, --number - Number of top results to return (default: 10)

Output Formats:

  • Default: JSON format
  • --output plain - Plain text format
  • --output table - Table format with borders

Examples:

search "machine learning"                    # Search all datasets (JSON output)
search "neural networks" datasets/kb1        # Search in kb1
search "AI" datasets/kb1  --output plain     # Plain text output
search "RAG" -n 20                           # Return 20 results
SEARCH 'machine learning' ON DATASETS 'kb1' 'kb2'
SEARCH 'AI' ON DATASETS 'kb1' WITH top_k 1024 similarity_threshold 0.0 vector_similarity_weight 0.3 keyword true
SEARCH 'AI' ON DATASETS 'kb1' WITH cross_languages ['Chinese']

cat <path> - Display content

Display document content (if available).

Examples:

cat myskills/doc.md   # Show content of doc.md file
cat datasets/kb1/document.pdf   # Error: cannot display binary file content

Command Examples

-- Authentication
LOGIN USER 'admin@example.com';

-- User management
REGISTER USER 'john' AS 'John Doe' PASSWORD 'secret';
CREATE USER 'jane' 'password123';
DROP USER 'jane';
LIST USERS;
SHOW USER 'john';

-- Service management
LIST SERVICES;
SHOW SERVICE 1;
STARTUP SERVICE 1;
SHUTDOWN SERVICE 1;
RESTART SERVICE 1;
PING;

-- Role management
CREATE ROLE admin DESCRIPTION 'Administrator role';
LIST ROLES;
GRANT read,write ON datasets TO ROLE admin;

-- Dataset management
CREATE DATASET 'my_dataset' WITH EMBEDDING 'text-embedding-ada-002' PARSER 'naive';
LIST DATASETS;
DROP DATASET 'my_dataset';

-- Model configuration
SET DEFAULT LLM 'gpt-4';
SET DEFAULT EMBEDDING 'text-embedding-ada-002';
RESET DEFAULT LLM;


## Parser Implementation

The parser uses a hand-written recursive descent approach instead of go-yacc for:
- Better control over error messages
- Easier to extend and maintain
- No code generation step required

The parser structure follows the grammar defined in the Python version, ensuring full syntax compatibility.