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This guide walks you through getting an API key and making your first API calls to list datasets, create a project, and export annotations.

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Step 1: Get Your API Key

  1. Log in to Mission Control.
  2. Navigate to Settings → API Keys.
  3. Click Create API Key, give it a name, and copy the key.
API keys are only displayed once at creation time. Store your key in a secure location before closing the dialog.
Set the key as an environment variable: 
export AVALA_API_KEY="avala_sk_your_api_key"

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Step 2: Choose Your Client

# No installation needed — just include the header:
# -H "X-Avala-Api-Key: $AVALA_API_KEY"
Python and TypeScript SDKs are coming soon. For now, call the REST API directly using any HTTP client. The examples below use requests (Python) and fetch (TypeScript).

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Step 3: Create Your First Dataset and Project

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List Your Datasets

curl https://server.avala.ai/api/v1/datasets/ \
  -H "X-Avala-Api-Key: $AVALA_API_KEY"

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Create a Project

curl -X POST https://server.avala.ai/api/v1/projects/ \
  -H "X-Avala-Api-Key: $AVALA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "My First Project",
    "dataset_id": "dataset_abc123",
    "task_type": "image-annotation",
    "label_config": {
      "labels": [
        {"name": "car", "color": "#FF0000"},
        {"name": "pedestrian", "color": "#00FF00"},
        {"name": "cyclist", "color": "#0000FF"}
      ]
    }
  }'

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Create an Export

curl -X POST https://server.avala.ai/api/v1/exports/ \
  -H "X-Avala-Api-Key: $AVALA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "project_id": "project_abc123",
    "format": "json"
  }'
Exports are processed asynchronously. Poll the export status endpoint to check when your export is ready for download.

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Next Steps

Core Concepts

Understand datasets, projects, tasks, and the annotation lifecycle.

API Reference

Full endpoint reference with request and response schemas.

Mission Control

Learn the web UI for annotation, project management, and quality control.