Files
jasonandjason.mei 681f6ebc5f support text generation
* add gitignore

* add video api

* fix: export to video

* fix

* fix

* fix

* fix

* fix

* add i2v

* fix

* fix

* add openai

* fix: add base url

* change default models

* fix: add base url

* add v1

* fix models

* fix models

* fix models

* fix models

* fix models

* fix bug

* fix

* try to fix

* use IO.STRING test

* image fix

* add chat content

* add files

* fix optional

* fix file read

* fix file read

* change name

* add get models

* add unused apikey

* change model sort

* fix IMAGE_LIST

* fix: change to image

* add model cache

* remove json_object

* change max_tokens to 65536

* change max_tokens to 6000

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Co-authored-by: jason.mei <jason.mei@ucloud.cn>
2025-09-15 15:31:26 +08:00

168 lines
6.4 KiB
Python

from typing import Optional
from pydantic import Field
from ..utils import BaseRequest, image_to_base64
from torch import Tensor
class FluxKontextMax(BaseRequest):
"""
Flux Kontext Max for image editing.
"""
API_PATH = "/v1/images/generations"
guidance_scale: Optional[float] = Field(
default=2.5, description="The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you.")
image: Tensor = Field(...,
description="The image to generate an image from.")
prompt: str = Field(...,
description="The prompt to generate an image from.")
seed: Optional[int] = Field(
default=-1, description="\n The same seed and the same prompt given to the same version of the model\n will output the same image every time.\n ")
def __init__(
self,
prompt: str,
image: Tensor,
guidance_scale: Optional[float] = 3.5,
seed: Optional[int] = -1,
**kwargs):
super().__init__(**kwargs)
self.prompt = prompt
self.guidance_scale = guidance_scale
self.seed = seed
self.image = image_to_base64(
image) if isinstance(image, Tensor) else None
def build_payload(self) -> dict:
"""Builds the request payload dictionary."""
payload = {
"model": "black-forest-labs/flux-kontext-max",
"prompt": self.prompt,
"guidance_scale": self.guidance_scale,
"image": self.image,
"seed": self.seed,
}
return self._remove_empty_fields(payload)
# def get_api_path(self):
# """Gets the API path. Corresponds to api_path in the JSON."""
# return "/api/v3/images/generations"
def field_required(self):
return ["prompt", "image"]
def field_order(self):
"""Corresponds to x-order-properties in the JSON request_schema."""
return ["model", "prompt", "image", "seed", "guidance_scale", "response_format"]
class FluxKontextMaxMulti(BaseRequest):
"""
Flux Kontext Max for multiple image inputs.
"""
API_PATH = "/v1/images/generations"
guidance_scale: Optional[float] = Field(
default=3.5, description="The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you.")
images: list[Tensor] = Field(...,
description="The image to generate an image from.")
prompt: str = Field(...,
description="The prompt to generate an image from.")
seed: Optional[int] = Field(
default=-1, description="\n The same seed and the same prompt given to the same version of the model\n will output the same image every time.\n ")
def __init__(
self,
prompt: str,
images: list[Tensor],
guidance_scale: Optional[float] = 3.5,
seed: Optional[int] = -1,
**kwargs):
super().__init__(**kwargs)
self.prompt = prompt
self.guidance_scale = guidance_scale
self.seed = seed
self.images = [image_to_base64(
image) for image in images if isinstance(image, Tensor)]
def build_payload(self) -> dict:
"""Builds the request payload dictionary."""
payload = {
"model": "black-forest-labs/flux-kontext-max/multi",
"prompt": self.prompt,
"guidance_scale": self.guidance_scale,
"images": self.images,
"seed": self.seed,
}
return self._remove_empty_fields(payload)
# def get_api_path(self):
# """Gets the API path. Corresponds to api_path in the JSON."""
# return "/api/v3/images/generations"
def field_required(self):
return ["prompt", "images"]
def field_order(self):
"""Corresponds to x-order-properties in the JSON request_schema."""
return ["model", "prompt", "images", "seed", "guidance_scale", "response_format"]
class FluxKontextMaxT2I(BaseRequest):
"""
Flux Kontext Pro text-to-image model
"""
API_PATH = "/v1/images/generations"
prompt: str = Field(...,
description="The prompt to generate an image from.")
aspect_ratio: Optional[str] = Field(
default="1:1", description="The aspect ratio of the output image, ranging from \"21:9\" to \"9:21\", default is \"1:1\"."),
num_images: Optional[int] = Field(
default=1, description="The number of images to generate.")
guidance_scale: Optional[float] = Field(
default=3.5, description="The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you.")
seed: Optional[int] = Field(
default=-1, description="\n The same seed and the same prompt given to the same version of the model\n will output the same image every time.\n ")
def __init__(
self,
prompt: str,
aspect_ratio: Optional[str] = "1:1",
num_images: Optional[int] = 1,
guidance_scale: Optional[float] = 3.5,
seed: Optional[int] = -1,
**kwargs):
super().__init__(**kwargs)
self.prompt = prompt
self.num_images = num_images
self.guidance_scale = guidance_scale
self.aspect_ratio = aspect_ratio
self.seed = seed
def build_payload(self) -> dict:
"""Builds the request payload dictionary."""
payload = {
"model": "black-forest-labs/flux-kontext-max/text-to-image",
"prompt": self.prompt,
"aspect_ratio": self.aspect_ratio,
"n": self.num_images,
"guidance_scale": self.guidance_scale,
"seed": self.seed,
}
return self._remove_empty_fields(payload)
# def get_api_path(self):
# """Gets the API path. Corresponds to api_path in the JSON."""
# return "/api/v3/images/generations"
def field_required(self):
return ["prompt"]
def field_order(self):
"""Corresponds to x-order-properties in the JSON request_schema."""
return ["model", "prompt", "aspect_ratio", "n", "guidance_scale", "seed", "response_format"]