elevenlabs-cli-tool 0.1.4

CLI tool to manage ElevenLabs conversational AI agents

ElevenLabs Conversational AI Agent Manager CLI

A powerful CLI tool to manage ElevenLabs Conversational AI agents using local configuration files. Features hash-based change detection, templates, multi-environment support, and continuous syncing.

Features

• Complete Agent Configuration: Full ElevenLabs agent schema support (ASR, TTS, platform settings, etc.)
• Template System: Pre-built templates for common use cases
• Multi-environment Support: Deploy across dev, staging, production with environment-specific configs
• Hash-based Updates: Only sync when configuration actually changes
• Continuous Monitoring: Watch mode for automatic updates
• Agent Import: Fetch existing agents from ElevenLabs workspace
• Widget: View HTML widget snippets for agents

Installation

git clone https://github.com/angelogiacco/convai-cli
cd elevenlabs_cli
poetry install
poetry shell  # optional

Configuration

Set your ElevenLabs API key:

export ELEVENLABS_API_KEY="your_api_key_here"

Quick Start

# 1. Initialize project
convai init

# 2. Create agent with template
convai add "Customer Support Bot" --template customer-service

# 3. Edit configuration
# Edit agent_configs/prod/customer_support_bot.json

# 4. Sync to ElevenLabs
convai sync

# 5. Watch for changes (optional)
convai watch

Directory Structure

The tool uses a flexible directory structure in your project:

your_project_root/
├── agents.json              # Central agent configuration file
├── agent_configs/           # Agent configuration files
│   ├── prod/                # Production environment configs
│   │   ├── customer_support_bot.json
│   │   └── sales_assistant.json
│   ├── dev/                 # Development environment configs
│   │   └── test_bot.json
│   └── staging/             # Staging environment configs
├── convai.lock              # Lock file to store agent IDs and config hashes
└── pyproject.toml           # Project metadata and dependencies

Central Agent Configuration (agents.json)

The agents.json file defines all your agents and their environment-specific configurations:

{
    "agents": [
        {
            "name": "Customer Support Bot",
            "environments": {
                "prod": {
                    "config": "agent_configs/prod/customer_support_bot.json"
                },
                "dev": {
                    "config": "agent_configs/dev/customer_support_bot.json"
                }
            }
        }
    ]
}

Quick Start

Here's how to get started in under 2 minutes:

# 1. Initialize your project
convai init

# 2. Add a new agent (creates config + uploads to ElevenLabs)
convai add "Customer Support Bot"

# 3. Edit the generated config file to customize your agent
# agent_configs/prod/customer_support_bot.json

# 4. Sync changes to ElevenLabs
convai sync

# 5. Watch for automatic updates (optional)
convai watch

That's it! Your agent is now live and will automatically update whenever you change the config.

Usage

The main entry point for the CLI is convai (after installation). You can also run it via poetry run convai or python -m elevenlabs_cli_tool.main.

1. Initialize Project

Run this command in the root of your project where you want to manage agents.

convai init

This will create:

• An agents.json file
• A convai.lock file

2. Add a New Agent

Create a new agent - this will create the config file, upload to ElevenLabs, and save the ID:

convai add "Docs support agent"

This will:

• Create a config file at agent_configs/prod/docs_support_agent.json with default settings
• Upload the agent to ElevenLabs and get an ID
• Add the agent to agents.json with the ID
• Update the lock file

Create for specific environment

convai add "Dev Bot" --env development

Create config only (don't upload to ElevenLabs yet)

convai add "My Bot" --skip-upload

Custom config path

convai add "Custom Bot" --config-path "custom/path/bot.json"

### 3. Templates

```bash
# List available templates
convai templates-list

# Show template configuration
convai template-show customer-service

# Create agent with template
convai add "Support Agent" --template customer-service

Available templates:

• default: Complete configuration with all fields
• minimal: Essential fields only
• voice-only: Voice conversation optimized
• text-only: Text conversation optimized
• customer-service: Customer support scenarios
• assistant: General AI assistant

4. Sync Changes

# Sync all agents in all environments
convai sync

# Sync specific agent
convai sync --agent "Support Bot"

# Sync specific environment
convai sync --env production

# Dry run to preview changes
convai sync --dry-run

# Sync specific agent in specific environment
convai sync --agent "Support Bot" --env production

5. Check Status

# Show status for all agents and environments
convai status

# Show status for specific agent
convai status --agent "Support Bot"

# Show status for specific environment
convai status --env production

# Show status for specific agent in specific environment
convai status --agent "Support Bot" --env production

6. Watch Mode

# Watch all agents in prod environment
convai watch

# Watch specific agent
convai watch --agent "Support Bot"

# Watch specific environment
convai watch --env development

# Custom check interval
convai watch --interval 10

7. Import Existing Agents

# Fetch all agents from ElevenLabs
convai fetch

# Fetch agents matching search term
convai fetch --search "support"

# Fetch to specific environment
convai fetch --env staging

# Dry run to see what would be imported
convai fetch --dry-run

# Custom output directory
convai fetch --output-dir "imported_configs"

8. View Widget Code

# View widget snippet for agent in prod environment
convai widget "Support Bot"

# Generate widget for specific environment
convai widget "Support Bot" --env development

9. List Agents

# List all configured agents
convai list-agents

Agent Configuration

Minimal Example

{
    "name": "Support Bot",
    "conversation_config": {
        "agent": {
            "prompt": {
                "prompt": "You are a helpful customer service representative.",
                "llm": "gemini-2.0-flash",
                "temperature": 0.1
            },
            "language": "en"
        },
        "tts": {
            "model_id": "eleven_turbo_v2",
            "voice_id": "cjVigY5qzO86Huf0OWal"
        }
    },
    "tags": ["customer-service"]
}

Common Workflows

New Project Setup

convai init
convai add "My Agent" --template assistant
# Edit agent_configs/prod/my_agent.json
convai sync

Multi-Environment Development

# Create agents for different environments
convai add "Support Bot" --env development --template customer-service
convai add "Support Bot" --env production --template customer-service

# Edit configs for each environment
# agent_configs/development/support_bot.json - relaxed settings
# agent_configs/production/support_bot.json - production settings

# Sync environments separately
convai sync --env development
convai sync --env production

# Check status per environment
convai status --env development
convai status --env production

Import and Sync Existing Agents

convai init
convai fetch --env production
convai status
# Edit configs as needed
convai sync

Continuous Development Workflow

# Start watching for changes (runs in background)
convai watch --env development --interval 5

# In another terminal, edit your agent configs
# Changes will automatically sync to ElevenLabs!

# Check status anytime
convai status --env development

Environment-Specific Configuration

Lock File Structure

The convai.lock file stores agent IDs and configuration hashes per environment:

{
    "agents": {
        "Support Bot": {
            "production": {
                "id": "agent-id-1",
                "hash": "config-hash-1"
            },
            "development": {
                "id": "agent-id-2", 
                "hash": "config-hash-2"
            }
        }
    }
}

Environment Tags

When creating or updating agents, the CLI automatically adds environment tags to help organize your agents in the ElevenLabs dashboard.

Widget Integration

Generate HTML widget code for your agents:

convai widget "Support Bot"

Output:

<elevenlabs-convai agent-id="your-agent-id"></elevenlabs-convai>
<script src="https://unpkg.com/@elevenlabs/convai-widget-embed" async type="text/javascript"></script>

Command Reference

Command	Description	Options
convai init [path]	Initialize project	Optional path (default: current directory)
convai add <name>	Create new agent	--template, --env, --skip-upload, --config-path
convai templates-list	List available templates	None
convai template-show <template>	Show template config	--agent-name
convai sync	Synchronize agents	--agent, --env, --dry-run
convai status	Show agent status	--agent, --env
convai watch	Monitor and auto-sync	--agent, --env, --interval
convai fetch	Import agents from ElevenLabs	--agent, --search, --env, --output-dir, --dry-run
convai list-agents	List configured agents	None
convai widget <name>	Generate widget HTML	--env

Troubleshooting

Common Issues

API Key Not Found

export ELEVENLABS_API_KEY="your_api_key_here"
# Or add to your .env file
echo "ELEVENLABS_API_KEY=your_api_key_here" >> .env

Agent Not Found Error

• Check if agent exists: convai list-agents
• Verify environment: convai status --env <environment>
• Check agents.json format

Sync Issues

• Verify config file exists and is valid JSON
• Check lock file: cat convai.lock
• Use dry-run to preview: convai sync --dry-run

Template Not Found

• List available templates: convai templates-list
• Check spelling of template name

Config File Errors

• Validate JSON syntax
• Check required fields (name, conversation_config)
• Refer to template examples: convai template-show <template>

Debug Commands

# Check overall status
convai status

# Check specific environment
convai status --env development

# Preview sync changes
convai sync --dry-run

# Get help for any command
convai <command> --help

Reset and Clean Start

# Remove lock file to reset agent IDs
rm convai.lock

# Re-initialize
convai init

# Re-sync all agents
convai sync

Best Practices

1. Environment Separation: Use different environments for development, staging, and production
2. Descriptive Names: Use clear, descriptive names for agents
3. Version Control: Commit agents.json and config files, exclude convai.lock
4. Template Usage: Start with templates and customize as needed
5. Regular Syncing: Use watch mode during development
6. Testing: Test agents in development before promoting to production

Development

Running Tests

poetry run pytest

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

Project Structure

elevenlabs_cli_tool/
├── main.py              # Main CLI application
├── utils.py             # Utility functions
├── elevenlabsapi.py     # ElevenLabs API client
├── templates.py         # Agent templates
└── __init__.py

Support

For issues, questions, or feature requests:

1. Check the troubleshooting section above
2. Use convai --help or convai <command> --help
3. Check existing GitHub issues
4. Create a new issue with details about your problem