Hailuo 02 is a new AI video generation model from Hailuo AI.
WEJŚCIE
WYJŚCIE
BezczynnyKażde uruchomienie będzie kosztować 0.1. Za $10 możesz uruchomić ten model około 100 razy.
Co możesz zrobić dalej:
Przykład kodu
import requests
import time
# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "minimax/hailuo-02/fast",
"prompt": "A beautiful sunset over the ocean with gentle waves",
"width": 512,
"height": 512,
"duration": 3,
"fps": 24,
}
generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]
# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
def check_status():
while True:
response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
result = response.json()
if result["data"]["status"] in ["completed", "succeeded"]:
print("Generated video:", result["data"]["outputs"][0])
return result["data"]["outputs"][0]
elif result["data"]["status"] == "failed":
raise Exception(result["data"]["error"] or "Generation failed")
else:
# Still processing, wait 2 seconds
time.sleep(2)
video_url = check_status()Instalacja
Zainstaluj wymagany pakiet dla swojego języka programowania.
pip install requestsUwierzytelnianie
Wszystkie żądania API wymagają uwierzytelnienia za pomocą klucza API. Klucz API możesz uzyskać z panelu Atlas Cloud.
export ATLASCLOUD_API_KEY="your-api-key-here"Nagłówki HTTP
import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}Nigdy nie ujawniaj swojego klucza API w kodzie po stronie klienta ani w publicznych repozytoriach. Zamiast tego użyj zmiennych środowiskowych lub proxy backendowego.
Wyślij żądanie
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "your-model",
"prompt": "A beautiful landscape"
}
response = requests.post(url, headers=headers, json=data)
print(response.json())Wyślij żądanie
Wyślij asynchroniczne żądanie generowania. API zwróci identyfikator predykcji, którego możesz użyć do sprawdzania statusu i pobierania wyniku.
/api/v1/model/generateVideoTreść żądania
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "minimax/hailuo-02/fast",
"input": {
"prompt": "A beautiful sunset over the ocean with gentle waves"
}
}
response = requests.post(url, headers=headers, json=data)
result = response.json()
print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")Odpowiedź
{
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}Sprawdź status
Odpytuj endpoint predykcji, aby sprawdzić bieżący status żądania.
/api/v1/model/prediction/{prediction_id}Przykład odpytywania
import requests
import time
prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
while True:
response = requests.get(url, headers=headers)
result = response.json()
status = result["data"]["status"]
print(f"Status: {status}")
if status in ["completed", "succeeded"]:
output_url = result["data"]["outputs"][0]
print(f"Output URL: {output_url}")
break
elif status == "failed":
print(f"Error: {result['data'].get('error', 'Unknown')}")
break
time.sleep(3)Wartości statusu
processingŻądanie jest wciąż przetwarzane.completedGenerowanie zakończone. Wyniki są dostępne.succeededGenerowanie powiodło się. Wyniki są dostępne.failedGenerowanie nie powiodło się. Sprawdź pole błędu.Odpowiedź ukończona
{
"data": {
"id": "pred_abc123",
"status": "completed",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.mp4"
],
"metrics": {
"predict_time": 45.2
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}
}Prześlij pliki
Prześlij pliki do magazynu Atlas Cloud i uzyskaj URL, którego możesz użyć w swoich żądaniach API. Użyj multipart/form-data do przesyłania.
/api/v1/model/uploadMediaPrzykład przesyłania
import requests
url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
with open("image.png", "rb") as f:
files = {"file": ("image.png", f, "image/png")}
response = requests.post(url, headers=headers, files=files)
result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")Odpowiedź
{
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Schema wejściowy
Następujące parametry są akceptowane w treści żądania.
Brak dostępnych parametrów.
Przykładowa treść żądania
{
"model": "minimax/hailuo-02/fast"
}Schema wyjściowy
API zwraca odpowiedź predykcji z URL-ami wygenerowanych wyników.
Przykładowa odpowiedź
{
"id": "pred_abc123",
"status": "completed",
"model": "model-name",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.mp4"
],
"metrics": {
"predict_time": 45.2
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}Atlas Cloud Skills
Atlas Cloud Skills integruje ponad 300 modeli AI bezpośrednio z Twoim asystentem kodowania AI. Jedno polecenie do instalacji, a następnie używaj języka naturalnego do generowania obrazów, filmów i rozmów z LLM.
Obsługiwani klienci
Instalacja
npx skills add AtlasCloudAI/atlas-cloud-skillsSkonfiguruj klucz API
Uzyskaj klucz API z panelu Atlas Cloud i ustaw go jako zmienną środowiskową.
export ATLASCLOUD_API_KEY="your-api-key-here"Możliwości
Po zainstalowaniu możesz używać języka naturalnego w swoim asystencie AI, aby uzyskać dostęp do wszystkich modeli Atlas Cloud.
Serwer MCP
Serwer MCP Atlas Cloud łączy Twoje IDE z ponad 300 modelami AI za pośrednictwem Model Context Protocol. Działa z każdym klientem kompatybilnym z MCP.
Obsługiwani klienci
Instalacja
npx -y atlascloud-mcpKonfiguracja
Dodaj następującą konfigurację do pliku ustawień MCP w swoim IDE.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}Dostępne narzędzia
API Schema
Schema niedostępnaZaloguj się, aby wyświetlić historię zapytań
Musisz być zalogowany, aby uzyskać dostęp do historii zapytań modelu.
Zaloguj sięMiniMax Hailuo 02 Fast
This is a fast version of Hailuo 02 that can generate videos in 6s and 10s at 512p resolution.
Hailuo 02 is a new AI video generation model, from Hailuo AI, created on MiniMax's evolving framework. It has been fine-tuned to deliver ultra-clear 1080P resolution and unprecedented responsiveness while even handling, the craziest of physics driven scenes.
Indeed, artists have discovered that for highly intricate scenarios, such as gymnastics, MiniMax Hailuo 02 is currently the only model globally capable of delivering such performance. We eagerly invite the community to explore and unlock even more creative possibilities.
Our journey began late last August when we informally launched a demo webpage showcasing an early version of our video generation model. To our surprise, it attracted significant attention and acclaim from talented creators worldwide. This pivotal moment led to the development of Hailuo Video 01, our AI native video generation product, which has since empowered creators to generate over 370 million videos globally.
Returning to our foundational principle of "Intelligence with Everyone," our ambition is to equip global creators to fully unleash their imagination, elevate the quality of their video content, and lower the barriers to video creation. Crucially, we strive to achieve this without imposing prohibitive costs that would limit the widespread accessibility of this technology.
To this end, our team embarked on a quest to develop a more efficient video generation model architecture. This pursuit culminated in the core framework of MiniMax Hailuo 02, which we've named Noise-aware Compute Redistribution (NCR). In essence, the new architecture's central idea is as follows:
At a comparable parameter scale, the new architecture boosts our training and inference efficiency by 2.5 times. This significant gain enables us to implement a much larger parameter model—thereby enhancing its expressive capabilities—without increasing costs for creators. This approach also leaves ample room for inference optimization. We ultimately expanded the model's total parameter count to 3 times that of its predecessor.
A larger parameter count and heightened training efficiency mean our model can learn from a more extensive dataset. The wealth of feedback from Hailuo 01 provided invaluable guidance for our model training strategy. As a result, we expanded our training data volume by 4 times, achieving significant improvements in data quality and diversity.
With this architectural innovation, combined with a threefold increase in parameters and four times the training data, our model has taken a significant leap forward, particularly in its adherence to complex instructions and its rendering of extreme physics. The new model accurately interprets and executes highly detailed prompts, delivering more precise outputs. Furthermore, the efficiency gains from the new architecture also mean we can offer native 1080p video generation at a very affordable price point.
An early iteration of this model was tested by users on the Artificial Analysis Video Arena, where it secured the second position globally. Stay tuned for an upcoming new version!
These model enhancements are now fully integrated into the Hailuo Video web platform, mobile application, and our API platform. We currently offer three distinct versions: 768p-6s, 768p-10s, and 1080p-6s. True to our commitment, and thanks to the aforementioned architectural innovation, we continue to offer creators and developers the most open access and affordable pricing in the industry.
Through sustained technological research and development, coupled with deep collaborations with creators, developers, and artists, our mission and strategic direction have become ever clearer.
MiniMax Hailuo 02 represents a new milestone, and we are poised for rapid advancements in the following areas:
-
Enhancing generation speed
-
Improving alignment, leading to higher generation success rates and improved stability
-
Advancing model features beyond Text-to-Video (T2V) and Image-to-Video (I2V)
And, as always, we remain steadfast in our commitment to relentlessly exploring the upper limits of what technology and art can achieve together.
