Quickstart
Send your first text, image, or embedding request in minutes.
Get from zero to a successful API response in a few minutes.
1. Create an API key
- Sign in at https://ai.lumowp.com/en/login
- Open Dashboard → Settings → API Keys
- Create a key and copy it immediately — the full secret is shown only once
Store the key in an environment variable:
export LUMO_AI_API_KEY="pk_your-api-key-here"
Keys always start with pk_.
2. Inspect your account and models
curl -X GET "https://ai.lumowp.com/api/external/ai" \
-H "X-API-Key: $LUMO_AI_API_KEY"
A successful response includes your user profile, subscription/credit info, token stats, allowed providers/models, embedding providers, rate-limit details, and supported_features.
Important: copy a model name from this response. Model catalogs differ by site and change over time.
3. Generate text
curl -X POST "https://ai.lumowp.com/api/external/ai" \
-H "X-API-Key: $LUMO_AI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "Explain machine learning in simple terms",
"model": "lumo-ai",
"provider": "deepseek",
"type": "text",
"max_tokens": 1000,
"temperature": 0.7
}'
Example success payload:
{
"success": true,
"data": {
"content": "Machine learning is a subset of artificial intelligence...",
"model": "lumo-ai",
"provider": "deepseek",
"tokens_used": 150,
"remaining_tokens": 9850,
"usage_percentage": "1.5"
}
}
4. Generate an image
curl -X POST "https://ai.lumowp.com/api/external/ai" \
-H "X-API-Key: $LUMO_AI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A futuristic cityscape with flying cars at sunset",
"model": "openai/gpt-image-1-mini",
"provider": "openai",
"type": "image",
"size": "1024x1024",
"quality": "medium",
"style": "vivid"
}'
Use an image model from image_generation_providers in the GET response. Prefer quality: low | medium | high (legacy standard / hd still work).
5. Create embeddings (optional)
curl -X POST "https://ai.lumowp.com/api/external/ai" \
-H "X-API-Key: $LUMO_AI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"type": "embedding",
"model": "text-embedding-3-small",
"input": "semantic search example"
}'
Only call this when supported_features.embedding is true and the model appears under embedding_providers.
Checklist
- Valid
pk_…API key with provider/model permissions - Enough remaining credits/tokens for the request
- Model name taken from live
GETdiscovery - Correct
type:"text","image", or"embedding"
Continue with Authentication or jump to Code Examples.