Python SDK for the AiUtils Developer API — 100+ AI models via one unified API
Project description
AiUtils Python SDK
Official Python SDK for the AiUtils Developer API — access 1400+ AI models (LLM, image, video, audio, 3D) through one unified API.
Install
pip install aiutils-sdk
Quick Start
from aiutils_sdk import AiUtils
client = AiUtils(api_key="ak-dev-YOUR_KEY")
# Chat completion (OpenAI-compatible)
response = client.chat.completions.create(
model="gen:deepseek:deepseek-v4-flash",
messages=[{"role": "user", "content": "Explain quantum computing"}],
max_tokens=1000,
)
print(response.choices[0].message.content)
print(f"Cost: {response.usage.dt_consumed} DT")
Authentication
client = AiUtils(
api_key="ak-dev-YOUR_KEY", # Required (get from developer.aiutils.io/api-keys)
base_url="https://developer-api.aiutils.io", # Default
timeout=60.0, # Request timeout (seconds)
)
Chat Completions
OpenAI-compatible chat completions with 90+ LLM models.
response = client.chat.completions.create(
model="gen:deepseek:deepseek-v4-flash", # Cheapest: 1.54 DT/1M tokens
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is Python?"},
],
temperature=0.7,
max_tokens=1000,
top_p=1.0,
)
print(response.choices[0].message.content)
print(f"Tokens: {response.usage.total_tokens}")
print(f"Cost: {response.usage.dt_consumed} DT")
Available LLM Models
| Model ID | Label | Cost (DT/1M tokens in) |
|---|---|---|
gen:deepseek:deepseek-v4-flash |
DeepSeek v4 Flash | 1.54 |
gen:deepseek:deepseek-chat |
DeepSeek Chat | 2.80 |
elidia-1:gpt-4.1-nano |
GPT 4.1 Nano | 1.12 |
elidia-1:gpt-4.1-mini |
GPT 4.1 Mini | 4.50 |
gen:deepseek:deepseek-v4-pro |
DeepSeek v4 Pro | 6.05 |
elidia-1:gpt-4o |
GPT 4o | 18.75 |
gen:anthropic:claude-opus-4-8 |
Claude Opus 4.8 | 105.0 |
gen:openai:gpt-5.6-sol |
GPT 5.6 Sol | 75.0 |
Use client.models.list(category="llm") for the full up-to-date list.
Image Generation
570+ image models across all vendors.
# Synchronous (immediate result)
result = client.generations.create(
model="elidia-2:flux/dev",
parameters={"prompt": "A futuristic city at sunset, cyberpunk", "image_size": "landscape_16_9"},
)
print(result.download_urls) # ['https://cdn.aiutils.io/...']
print(f"Cost: {result.dt_consumed} DT")
Image Models (sample)
| Model ID | Label | Cost |
|---|---|---|
elidia-2:flux/dev |
FLUX.1 Dev | ~0.5 DT/megapixel |
elidia-2:flux-pro/v1.1-ultra |
FLUX Pro Ultra | ~1.5 DT/megapixel |
elidia-2:stable-diffusion-v35-large |
SD 3.5 Large | ~0.3 DT/megapixel |
elidia-1:midjourney |
Midjourney | via Elidia-1 |
Video Generation
550+ video models. Most are async (take 30s-5min to complete).
# With auto-polling (blocks until done)
result = client.generations.create(
model="elidia-2:kling-video/v1.6/pro/text-to-video",
parameters={"prompt": "A drone shot over a mountain lake at dawn"},
wait_for_completion=True,
timeout=300,
)
print(result.status) # "completed"
print(result.download_urls) # ['https://cdn.aiutils.io/...mp4']
# With webhook (non-blocking, result POSTed to your URL)
result = client.generations.create(
model="elidia-2:kling-video/v1.6/pro/text-to-video",
parameters={"prompt": "Ocean waves crashing on rocks"},
wait_for_completion=False,
webhook_url="https://your-server.com/webhook/aiutils",
)
print(result.id) # "abc123-..."
print(result.status) # "processing"
# Your webhook receives the full result when done
Audio & Voice
140+ audio/voice/music models.
# Text-to-speech
result = client.generations.create(
model="elidia-2:playht/tts/v3",
parameters={"text": "Hello world", "voice": "en-US-1"},
)
print(result.download_urls)
# Music generation
result = client.generations.create(
model="elidia-1:ace-step",
parameters={"prompt": "Upbeat electronic track, 120 BPM"},
wait_for_completion=True,
)
3D Generation
48 3D models (text-to-3D, image-to-3D).
result = client.generations.create(
model="elidia-2:trellis",
parameters={"prompt": "A medieval castle"},
wait_for_completion=True,
timeout=300,
)
print(result.download_urls) # ['https://.../.glb']
Embeddings
response = client.embeddings.create(
model="text-embedding-3-small",
input=["Hello world", "How are you?"],
)
for emb in response.data:
print(f"Dimension: {len(emb.embedding)}")
print(f"Tokens: {response.usage.total_tokens}")
Model Catalog
Browse all 1400+ models with schemas and pricing.
# List models by category
models = client.models.list(category="image", vendor="elidia-2", page_size=50)
for m in models.data:
print(f"{m.id} — {m.label} ({m.pricing.credits} DT/{m.pricing.unit})")
# Get full model detail with input/output schema
detail = client.models.get("elidia-2:flux/dev")
print(detail) # Includes input_schema, output_schema, pricing
Categories
| Category | Count | Description |
|---|---|---|
llm |
97 | Chat completions, reasoning, vision |
image |
570 | Text-to-image, image-to-image |
video |
551 | Text-to-video, image-to-video |
audio |
141 | TTS, voice cloning, audio effects |
music |
1 | Music generation |
3d |
48 | Text-to-3D, image-to-3D |
Wallet & Billing
Check balance and view transaction history.
# Check balance
balance = client.wallet.balance()
print(f"Available: {balance.balance_dt} DT")
print(f"Today used: {balance.daily_dt_used} DT")
# View transaction history
txns = client.wallet.transactions(limit=10)
for t in txns.transactions:
print(f"{t.created_at} | {t.type} | {t.amount_dt} DT | {t.description}")
# Estimate cost before running
estimate = client.wallet.estimate_cost(
model="gen:deepseek:deepseek-v4-flash",
parameters={"max_tokens": 2000},
)
print(f"Estimated cost: {estimate.estimated_dt} DT (${estimate.estimated_usd:.4f})")
Webhooks
Configure global webhook to receive all async results, or use per-request webhooks.
Global Webhook (account-level)
# Set global webhook — all async completions delivered here
client.webhooks.set_config(
url="https://your-server.com/webhook/aiutils",
events=["generation.completed", "generation.failed", "balance.low"],
secret="whsec_your_signing_secret", # For signature verification
)
# Check current config
config = client.webhooks.get_config()
print(f"Active: {config.is_active}, URL: {config.url}")
# View delivery history (for debugging)
deliveries = client.webhooks.list_deliveries(limit=10)
for d in deliveries.deliveries:
print(f"{d.created_at} | {d.event} | {d.status} | HTTP {d.response_code}")
# Remove webhook
client.webhooks.delete_config()
Per-Request Webhook
# Override global webhook for this specific request
result = client.generations.create(
model="elidia-2:kling-video/v1.6/pro/text-to-video",
parameters={"prompt": "A cat playing piano"},
wait_for_completion=False,
webhook_url="https://your-server.com/webhook/this-specific-job",
)
Webhook Payload
Your webhook endpoint receives a POST with:
{
"event": "generation.completed",
"generation_id": "abc123-...",
"status": "completed",
"model": "elidia-2:flux/dev",
"output": { ... },
"download_urls": ["https://cdn.aiutils.io/..."],
"dt_consumed": 5,
"created_at": 1721234567.89
}
Headers include X-Webhook-Signature (HMAC-SHA256 of body using your secret).
Cost Estimation
Estimate cost BEFORE running any request.
# Estimate chat cost
estimate = client.wallet.estimate_cost(
model="gen:deepseek:deepseek-v4-flash",
parameters={"max_tokens": 4000},
)
print(f"~{estimate.estimated_dt} DT (${estimate.estimated_usd:.4f})")
print(f"Provider: ${estimate.breakdown['provider_cost_usd']:.4f}")
print(f"Platform fee: {estimate.breakdown['platform_fee_pct']}%")
# Estimate generation cost
estimate = client.wallet.estimate_cost(
model="elidia-2:flux/dev",
parameters={"image_size": "landscape_16_9"},
)
Error Handling
from aiutils_sdk import (
AiUtils, AuthenticationError, InsufficientDTError,
RateLimitError, APIError, ProviderError,
)
try:
response = client.chat.completions.create(...)
except AuthenticationError:
print("Invalid API key — check developer.aiutils.io/api-keys")
except InsufficientDTError:
print("Not enough DT — top up at developer.aiutils.io/billing")
except RateLimitError:
print("Too many requests — back off and retry")
except APIError as e:
print(f"API error ({e.status_code}): {e}")
except ProviderError:
print("AI provider error — retry")
Pricing
All usage is billed in DT (Developer Tokens): 1 DT = $0.001 USD.
Cost formula: DT = CEIL(provider_cost_usd * 1.08 * 1000)
The 8% platform fee is the only markup — no hidden costs.
| Tier | Input (DT/1M tokens) | Output (DT/1M tokens) |
|---|---|---|
| Budget (DeepSeek Flash) | 1.54 | 3.08 |
| Standard (GPT-4o-mini) | 1.69 | 6.75 |
| Premium (Claude Opus) | 105 | 450 |
For media models, costs vary per model — use client.wallet.estimate_cost() or check model.pricing in the catalog.
Context Manager
with AiUtils(api_key="ak-dev-YOUR_KEY") as client:
response = client.chat.completions.create(...)
# HTTP connections cleaned up automatically
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