anyfast 0.0.1

AnyFast Python SDK

AnyFast Python SDK

AnyFast Python SDK for AI services including chat completions, image generation, video generation and asset management.

Installation

pip install anyfast

Configuration

from anyfast import AnyFast

client = AnyFast(
    api_key="your-api-key",
    base_url="https://www.anyfast.ai",  # optional, this is the default
)

Or use the ANYFAST_API_KEY environment variable:

client = AnyFast()

Options

Parameter	Default	Description
api_key	ANYFAST_API_KEY env var	API key for authentication
base_url	https://www.anyfast.ai	API base URL
gateway_url	https://www.anyfast.ai	Gateway URL
timeout	30.0	Request timeout in seconds

Chat Completions

OpenAI-compatible (/v1/chat/completions)

Works with GPT, Claude, Doubao, DeepSeek, Qwen, Grok, Gemini (compat), MiniMax, Kimi, etc.

result = client.chat.completions(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(result["choices"][0]["message"]["content"])

Streaming

for chunk in client.chat.completions(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
    stream=True,
):
    content = chunk["choices"][0].get("delta", {}).get("content", "")
    print(content, end="", flush=True)

Anthropic Messages (/v1/messages)

result = client.chat.messages(
    model="claude-sonnet-4-20250514",
    messages=[{"role": "user", "content": "Hello!"}],
    max_tokens=1024,
)
print(result["content"][0]["text"])

Doubao Responses (/v1/responses)

result = client.chat.responses(
    model="doubao-seed-2.0-pro",
    input="Hello!",
)
print(result["output"][0]["content"][0]["text"])

Supports multimodal input:

result = client.chat.responses(
    model="doubao-seed-1-6-vision-250815",
    input=[
        {
            "role": "user",
            "content": [
                {"type": "input_text", "text": "What is in this image?"},
                {"type": "input_image", "image_url": "https://example.com/photo.png"},
            ],
        }
    ],
)

Gemini Native (/v1beta/models/{model}:generateContent)

result = client.chat.gemini(
    "gemini-2.0-flash",
    contents=[
        {"role": "user", "parts": [{"text": "Hello!"}]},
    ],
)
print(result["candidates"][0]["content"]["parts"][0]["text"])

Image Generation

Synchronous

result = client.image.generate(
    model="flux-2-pro",
    prompt="A beautiful sunset over the ocean",
    size="1024x1024",
)
print(result["data"][0]["url"])

Async with Polling

response = client.image.generate_async(
    model="doubao-seedream-5-0-260128",
    prompt="A beautiful sunset over the ocean",
)

status = client.image.query_task(response.task_id)
while status.is_processing():
    import time
    time.sleep(2)
    status = client.image.query_task(response.task_id)

Blocking Run

status = client.image.run(
    {"model": "flux-2-pro", "prompt": "A beautiful sunset"},
    poll_interval=3.0,
    timeout=180.0,
)

if status.is_completed():
    print(status.result)

Video Generation

Seedance

status = client.video.run(
    {
        "model": "seedance",
        "content": [{"type": "text", "text": "A cat playing with a ball"}],
        "resolution": "720p",
        "ratio": "16:9",
        "duration": 5,
    },
    poll_interval=5.0,
    timeout=600.0,
)

Image-to-video:

status = client.video.run({
    "model": "seedance",
    "content": [
        {"type": "text", "text": "Make it come alive"},
        {"type": "image_url", "image_url": {"url": "https://example.com/frame.jpg"}, "role": "first_frame"},
    ],
})

Kling

# Text-to-video
status = client.video.run_kling_text2video(
    {
        "model_name": "kling-v2-master",
        "prompt": "A sunset over the ocean",
        "mode": "pro",
        "duration": "10",
        "aspect_ratio": "16:9",
    },
    poll_interval=5.0,
)

# Image-to-video
status = client.video.run_kling_image2video({
    "model_name": "kling-v2-master",
    "image": "https://example.com/frame.jpg",
    "prompt": "Make it move",
})

# Multi-image-to-video
status = client.video.run_kling_multi_image2video({
    "model_name": "kling-v1-6",
    "image_list": [
        {"image": "https://example.com/1.jpg"},
        {"image": "https://example.com/2.jpg"},
    ],
    "prompt": "Transition between scenes",
})

Manual polling for Kling:

response = client.video.kling_text2video(
    model_name="kling-v2-master",
    prompt="A cat",
)

status = client.video.kling_query_task("text2video", response.task_id)

Asset Management (ByteDance Volc)

# Create asset group
group = client.asset.create_group(Name="my-group")

# List groups
groups = client.asset.list_groups()

# Upload asset
asset = client.asset.create_asset(
    GroupId=group["Id"],
    Name="reference-image",
    AssetType="Image",
    URL="https://example.com/image.png",
)

# List assets
assets = client.asset.list_assets(Filter={"GroupIds": [group["Id"]]})

Error Handling

from anyfast import AnyFastError, AuthenticationError, BadRequestError

try:
    result = client.chat.completions(
        model="gpt-4o",
        messages=[{"role": "user", "content": "Hello"}],
    )
except AuthenticationError as e:
    print(f"Auth failed: {e}")
except BadRequestError as e:
    print(f"Bad request: {e}")
except AnyFastError as e:
    print(f"Status: {e.status}, Code: {e.code}, Message: {e}")

License

Apache License 2.0