📝 CLI Reference
Insight Ingenious CLI Reference
The ingen
command-line interface provides intuitive commands for managing your AI agent workflows.
Quick Start
# Initialize a new project
ingen init
# Check your configuration
ingen status
# Validate setup (recommended)
ingen validate
# Start the server
ingen serve
# List available workflows
ingen workflows
Core Commands
ingen init
Initialize a new Insight Ingenious project in the current directory.
What it creates:
config.yml
- Project configuration (non-sensitive)profiles.yml
- Environment profiles (API keys, secrets).env.example
- Example environment variablesingenious_extensions/
- Custom agents and workflowsDockerfile and .dockerignore
- Docker deployment templatestmp/
- Temporary files and memory
Next Steps:
- Copy
.env.example
to.env
and add credentials - Set environment variables
- Run
ingen serve
ingen serve
Start the API server with web interfaces.
Options:
--config, -c
- Path to config.yml (default: ./config.yml)--profile, -p
- Path to profiles.yml (default: ./profiles.yml)--host, -h
- Host to bind (default: 0.0.0.0)--port
- Port to bind (default: 80)--no-prompt-tuner
- Disable prompt tuner interface
Interfaces:
- API:
http://localhost:80/api/v1/
- Chat:
http://localhost:80/chainlit
- Prompt Tuner:
http://localhost:80/prompt-tuner
ingen workflows [workflow-name]
Show available workflows and their requirements.
Examples:
ingen workflows # List all workflows
ingen workflows classification-agent # Show specific workflow details
ingen workflows bike-insights # Show bike insights workflow (recommended start)
Available Workflows:
classification-agent
- Route input to specialized agents (core library, minimal config)bike-insights
- Sample domain-specific analysis (project template, minimal config) ⭐ RECOMMENDEDknowledge-base-agent
- Search knowledge bases using local ChromaDB (core library, stable local implementation)sql-manipulation-agent
- Execute SQL queries using local SQLite (core library, stable local implementation)
Note:
- Core library workflows are always available
- Template workflows like
bike-insights
are created withingen init
- Only local implementations (ChromaDB, SQLite) are stable; Azure integrations are experimental
- Legacy underscore names (
classification_agent
,bike_insights
, etc.) are still supported for backward compatibility
ingen test
Run agent workflow tests.
Options:
--log-level, -l
- Set logging verbosity (DEBUG, INFO, WARNING, ERROR)--args
- Additional test arguments
Example:
ingen test --log-level DEBUG --args="--test-name=MyTest"
Utility Commands
ingen status
Check system configuration and status.
Validates:
- Environment variables
- Configuration files
- Dependencies
- Available workflows
ingen validate
Comprehensive validation of your Insight Ingenious setup.
What it validates:
- Configuration file syntax and required fields
- Profile file syntax and credentials
- Azure OpenAI connectivity
- Workflow requirements
- Dependencies
Usage:
ingen validate # Recommended before starting server
This command helps identify issues before starting the server and provides specific fix recommendations.
ingen version
Show version information.
ingen prompt-tuner
Start standalone prompt tuning interface.
Options:
--port, -p
- Port (default: 5000)--host, -h
- Host (default: 127.0.0.1)
ingen help [topic]
Show detailed help and guides.
Topics:
setup
- Initial project setupworkflows
- Understanding workflowsconfig
- Configuration detailsdeployment
- Deployment options
Data Processing Commands
ingen dataprep
Web scraping utilities using Scrapfly.
Subcommands:
crawl <url>
- Scrape single pagebatch <urls...>
- Scrape multiple pages
Example:
ingen dataprep crawl https://example.com --pretty
ingen dataprep batch https://a.com https://b.com --out results.ndjson
ingen document-processing <path>
Extract text from documents (PDF, DOCX, images).
Arguments:
path
- File path, directory, or HTTP/S URL
Options:
--engine, -e
- Extractor backend (pymupdf, pdfminer, unstructured) (default: pymupdf)--out, -o
- Output file for NDJSON results (default: stdout)
Example:
ingen document-processing document.pdf --engine pymupdf --out extracted.jsonl
ingen document-processing https://example.com/doc.pdf --out results.jsonl
Environment Setup
Required Environment Variables
export INGENIOUS_PROJECT_PATH=$(pwd)/config.yml
export INGENIOUS_PROFILE_PATH=$(pwd)/profiles.yml
Optional Environment Variables
export SCRAPFLY_API_KEY=your_key_here # For dataprep commands
Configuration Files
config.yml
Non-sensitive project configuration:
- Model settings
- Service configurations
- Logging settings
- Workflow definitions
profiles.yml
Sensitive environment-specific settings:
- API keys
- Connection strings
- Secrets
.env
Environment variables for local development.
Backward Compatibility
Legacy command names are still supported but hidden:
run_rest_api_server
→ Useserve
run_test_batch
→ Usetest
initialize_new_project
→ Useinit
workflow_requirements
→ Useworkflows
Error Handling
The CLI provides helpful error messages and suggestions:
- Missing configuration files
- Invalid workflow names
- Missing dependencies
- Environment variable issues
Use ingen status
to diagnose configuration problems.
Getting Help
ingen --help
- General helpingen <command> --help
- Command-specific helpingen help
- Comprehensive getting started guideingen help <topic>
- Topic-specific guidance