Quick Start

1. Install from PyPI

pip install loom-memory

This installs Loom and registers the loom CLI command.

2. Install from Source (optional)

If you prefer to install from source:

git clone https://github.com/TeamEcho-AI/Loom.git
cd Loom

# Create and activate a Python 3.10 conda environment
conda create -n loom python=3.10 -y
conda activate loom

# Install dependencies
pip install -r requirements.txt

# Install Loom as a package
pip install -e .

For development mode with testing and linting tools, run pip install -e ".[dev]" instead.

3. Initialize & Configure

# Initialize the project (generates config + template files)
loom init

This creates the files Loom needs to run:

File	Purpose
`configs/loom.yaml`	Your config — edit this to set LLM provider, model, etc.
`templates/general.json`	Built-in general template (editable)
`templates/roleplay.json`	Built-in roleplay template (editable)

Then configure your LLM provider (pick one):

YAML Config
Environment Variables

Open configs/loom.yaml and set api_key, model, base_url:

llm:
  api_key: "your-api-key"
  model: "gpt-4o"
  base_url: "https://api.openai.com/v1"

cp .env.example .env
# Edit .env: fill in API_KEY, MODEL, BASE_URL

Environment variables override YAML config values.

4. Verify installation

These examples run without an API key:

# Schema operations
python examples/01_basic_schema.py

# Input converters
python examples/03_converters.py

5. Run with LLM

Requires a configured API key:

# Full chat with memory
python examples/02_chat_with_memory.py

# Or start the web server
loom serve
# Open http://localhost:8666

# Or run as a background daemon
loom serve start
loom serve status

Next Steps

Python API

Learn how to use Loom programmatically.

CLI Reference

Explore the full command-line interface.

Service Management

Run Loom as a daemon with auto-start on boot.

Schema Templates

Use preset templates or create your own.

Configuration

Customize LLM provider, persistence, and more.

​1. Install from PyPI

​2. Install from Source (optional)

​3. Initialize & Configure

​4. Verify installation

​5. Run with LLM

​Next Steps

Python API

CLI Reference

Service Management

Schema Templates

Configuration

1. Install from PyPI

2. Install from Source (optional)

3. Initialize & Configure

4. Verify installation

5. Run with LLM

Next Steps