internal/cli/README.md
This is the Go implementation of the RAGFlow command-line interface, compatible with the Python version's syntax.
ls, search, mkdir, cat, rmgo build -o ragflow_cli ./cmd/ragflow_cli.go
./ragflow_cli
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
The Virtual Filesystem provides a unified filesystem interface over RAGFlow's RESTful APIs.
ls, search, mkdir commands across all providers/datasets, /datasets/{name}/files| Path | Description |
|---|---|
/datasets | List all datasets |
/datasets/{name} | List documents in dataset (default behavior) |
/datasets/{name}/{doc} | Get document info |
ls [path] [options] - List nodes at pathList 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 messageExamples:
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 contentSemantic search in datasets.
Options:
-n, --number - Number of top results to return (default: 10)Output Formats:
--output plain - Plain text format--output table - Table format with bordersExamples:
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
cat <path> - Display contentDisplay 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
-- Authentication
LOGIN USER '[email protected]';
-- 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.