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AutoGPT/autogpt_platform/backend/backend/blocks/ideogram.py
Reinier van der Leer 113e87a23c refactor(backend): Reduce circular imports (#12068) 
I'm getting circular import issues because there is a lot of
cross-importing between `backend.data`, `backend.blocks`, and other
modules. This change reduces block-related cross-imports and thus risk
of breaking circular imports.

### Changes 🏗️

- Strip down `backend.data.block`
- Move `Block` base class and related class/enum defs to
`backend.blocks._base`
  - Move `is_block_auth_configured` to `backend.blocks._utils`
- Move `get_blocks()`, `get_io_block_ids()` etc. to `backend.blocks`
(`__init__.py`)
  - Update imports everywhere
- Remove unused and poorly typed `Block.create()`
  - Change usages from `block_cls.create()` to `block_cls()`
- Improve typing of `load_all_blocks` and `get_blocks`
- Move cross-import of `backend.api.features.library.model` from
`backend/data/__init__.py` to `backend/data/integrations.py`
- Remove deprecated attribute `NodeModel.webhook`
  - Re-generate OpenAPI spec and fix frontend usage
- Eliminate module-level `backend.blocks` import from `blocks/agent.py`
- Eliminate module-level `backend.data.execution` and
`backend.executor.manager` imports from `blocks/helpers/review.py`
- Replace `BlockInput` with `GraphInput` for graph inputs

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - CI static type-checking + tests should be sufficient for this
2026-02-12 12:07:49 +00:00

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from enum import Enum
from typing import Any, Dict, Literal, Optional
from pydantic import SecretStr
from backend.blocks._base import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.data.model import (
APIKeyCredentials,
CredentialsField,
CredentialsMetaInput,
SchemaField,
)
from backend.integrations.providers import ProviderName
from backend.util.request import Requests
TEST_CREDENTIALS = APIKeyCredentials(
id="01234567-89ab-cdef-0123-456789abcdef",
provider="ideogram",
api_key=SecretStr("mock-ideogram-api-key"),
title="Mock Ideogram API key",
expires_at=None,
)
TEST_CREDENTIALS_INPUT = {
"provider": TEST_CREDENTIALS.provider,
"id": TEST_CREDENTIALS.id,
"type": TEST_CREDENTIALS.type,
"title": TEST_CREDENTIALS.type,
}
class IdeogramModelName(str, Enum):
V3 = "V_3"
V2 = "V_2"
V1 = "V_1"
V1_TURBO = "V_1_TURBO"
V2_TURBO = "V_2_TURBO"
class MagicPromptOption(str, Enum):
AUTO = "AUTO"
ON = "ON"
OFF = "OFF"
class StyleType(str, Enum):
AUTO = "AUTO"
GENERAL = "GENERAL"
REALISTIC = "REALISTIC"
DESIGN = "DESIGN"
RENDER_3D = "RENDER_3D"
ANIME = "ANIME"
class ColorPalettePreset(str, Enum):
NONE = "NONE"
EMBER = "EMBER"
FRESH = "FRESH"
JUNGLE = "JUNGLE"
MAGIC = "MAGIC"
MELON = "MELON"
MOSAIC = "MOSAIC"
PASTEL = "PASTEL"
ULTRAMARINE = "ULTRAMARINE"
class AspectRatio(str, Enum):
ASPECT_10_16 = "ASPECT_10_16"
ASPECT_16_10 = "ASPECT_16_10"
ASPECT_9_16 = "ASPECT_9_16"
ASPECT_16_9 = "ASPECT_16_9"
ASPECT_3_2 = "ASPECT_3_2"
ASPECT_2_3 = "ASPECT_2_3"
ASPECT_4_3 = "ASPECT_4_3"
ASPECT_3_4 = "ASPECT_3_4"
ASPECT_1_1 = "ASPECT_1_1"
ASPECT_1_3 = "ASPECT_1_3"
ASPECT_3_1 = "ASPECT_3_1"
class UpscaleOption(str, Enum):
AI_UPSCALE = "AI Upscale"
NO_UPSCALE = "No Upscale"
class IdeogramModelBlock(Block):
class Input(BlockSchemaInput):
credentials: CredentialsMetaInput[
Literal[ProviderName.IDEOGRAM], Literal["api_key"]
] = CredentialsField(
description="The Ideogram integration can be used with any API key with sufficient permissions for the blocks it is used on.",
)
prompt: str = SchemaField(
description="Text prompt for image generation",
placeholder="e.g., 'A futuristic cityscape at sunset'",
title="Prompt",
)
ideogram_model_name: IdeogramModelName = SchemaField(
description="The name of the Image Generation Model, e.g., V_3",
default=IdeogramModelName.V3,
title="Image Generation Model",
advanced=False,
)
aspect_ratio: AspectRatio = SchemaField(
description="Aspect ratio for the generated image",
default=AspectRatio.ASPECT_1_1,
title="Aspect Ratio",
advanced=False,
)
upscale: UpscaleOption = SchemaField(
description="Upscale the generated image",
default=UpscaleOption.NO_UPSCALE,
title="Upscale Image",
advanced=False,
)
magic_prompt_option: MagicPromptOption = SchemaField(
description="Whether to use MagicPrompt for enhancing the request",
default=MagicPromptOption.AUTO,
title="Magic Prompt Option",
advanced=True,
)
seed: Optional[int] = SchemaField(
description="Random seed. Set for reproducible generation",
default=None,
title="Seed",
advanced=True,
)
style_type: StyleType = SchemaField(
description="Style type to apply, applicable for V_2 and above",
default=StyleType.AUTO,
title="Style Type",
advanced=True,
)
negative_prompt: Optional[str] = SchemaField(
description="Description of what to exclude from the image",
default=None,
title="Negative Prompt",
advanced=True,
)
color_palette_name: ColorPalettePreset = SchemaField(
description="Color palette preset name, choose 'None' to skip",
default=ColorPalettePreset.NONE,
title="Color Palette Preset",
advanced=True,
)
custom_color_palette: Optional[list[str]] = SchemaField(
description=(
"Only available for model version V_2 or V_2_TURBO. Provide one or more color hex codes "
"(e.g., ['#000030', '#1C0C47', '#9900FF', '#4285F4', '#FFFFFF']) to define a custom color "
"palette. Only used if 'color_palette_name' is 'NONE'."
),
default=None,
title="Custom Color Palette",
advanced=True,
)
class Output(BlockSchemaOutput):
result: str = SchemaField(description="Generated image URL")
def __init__(self):
super().__init__(
id="6ab085e2-20b3-4055-bc3e-08036e01eca6",
description="This block runs Ideogram models with both simple and advanced settings.",
categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
input_schema=IdeogramModelBlock.Input,
output_schema=IdeogramModelBlock.Output,
test_input={
"ideogram_model_name": IdeogramModelName.V2,
"prompt": "A futuristic cityscape at sunset",
"aspect_ratio": AspectRatio.ASPECT_1_1,
"upscale": UpscaleOption.NO_UPSCALE,
"magic_prompt_option": MagicPromptOption.AUTO,
"seed": None,
"style_type": StyleType.AUTO,
"negative_prompt": None,
"color_palette_name": ColorPalettePreset.NONE,
"custom_color_palette": [
"#000030",
"#1C0C47",
"#9900FF",
"#4285F4",
"#FFFFFF",
],
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
(
"result",
"https://ideogram.ai/api/images/test-generated-image-url.png",
),
],
test_mock={
"run_model": lambda api_key, model_name, prompt, seed, aspect_ratio, magic_prompt_option, style_type, negative_prompt, color_palette_name, custom_colors: "https://ideogram.ai/api/images/test-generated-image-url.png",
"upscale_image": lambda api_key, image_url: "https://ideogram.ai/api/images/test-upscaled-image-url.png",
},
test_credentials=TEST_CREDENTIALS,
)
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
seed = input_data.seed
# Step 1: Generate the image
result = await self.run_model(
api_key=credentials.api_key,
model_name=input_data.ideogram_model_name.value,
prompt=input_data.prompt,
seed=seed,
aspect_ratio=input_data.aspect_ratio.value,
magic_prompt_option=input_data.magic_prompt_option.value,
style_type=input_data.style_type.value,
negative_prompt=input_data.negative_prompt,
color_palette_name=input_data.color_palette_name.value,
custom_colors=input_data.custom_color_palette,
)
# Step 2: Upscale the image if requested
if input_data.upscale == UpscaleOption.AI_UPSCALE:
result = await self.upscale_image(
api_key=credentials.api_key,
image_url=result,
)
yield "result", result
async def run_model(
self,
api_key: SecretStr,
model_name: str,
prompt: str,
seed: Optional[int],
aspect_ratio: str,
magic_prompt_option: str,
style_type: str,
negative_prompt: Optional[str],
color_palette_name: str,
custom_colors: Optional[list[str]],
):
# Use V3 endpoint for V3 model, legacy endpoint for others
if model_name == "V_3":
return await self._run_model_v3(
api_key,
prompt,
seed,
aspect_ratio,
magic_prompt_option,
style_type,
negative_prompt,
color_palette_name,
custom_colors,
)
else:
return await self._run_model_legacy(
api_key,
model_name,
prompt,
seed,
aspect_ratio,
magic_prompt_option,
style_type,
negative_prompt,
color_palette_name,
custom_colors,
)
async def _run_model_v3(
self,
api_key: SecretStr,
prompt: str,
seed: Optional[int],
aspect_ratio: str,
magic_prompt_option: str,
style_type: str,
negative_prompt: Optional[str],
color_palette_name: str,
custom_colors: Optional[list[str]],
):
url = "https://api.ideogram.ai/v1/ideogram-v3/generate"
headers = {
"Api-Key": api_key.get_secret_value(),
"Content-Type": "application/json",
}
# Map legacy aspect ratio values to V3 format
aspect_ratio_map = {
"ASPECT_10_16": "10x16",
"ASPECT_16_10": "16x10",
"ASPECT_9_16": "9x16",
"ASPECT_16_9": "16x9",
"ASPECT_3_2": "3x2",
"ASPECT_2_3": "2x3",
"ASPECT_4_3": "4x3",
"ASPECT_3_4": "3x4",
"ASPECT_1_1": "1x1",
"ASPECT_1_3": "1x3",
"ASPECT_3_1": "3x1",
# Additional V3 supported ratios
"ASPECT_1_2": "1x2",
"ASPECT_2_1": "2x1",
"ASPECT_4_5": "4x5",
"ASPECT_5_4": "5x4",
}
v3_aspect_ratio = aspect_ratio_map.get(
aspect_ratio, "1x1"
) # Default to 1x1 if not found
# Use JSON for V3 endpoint (simpler than multipart/form-data)
data: Dict[str, Any] = {
"prompt": prompt,
"aspect_ratio": v3_aspect_ratio,
"magic_prompt": magic_prompt_option,
"style_type": style_type,
}
if seed is not None:
data["seed"] = seed
if negative_prompt:
data["negative_prompt"] = negative_prompt
# Note: V3 endpoint may have different color palette support
# For now, we'll omit color palettes for V3 to avoid errors
try:
response = await Requests().post(url, headers=headers, json=data)
return response.json()["data"][0]["url"]
except Exception as e:
raise ValueError(f"Failed to fetch image with V3 endpoint: {e}") from e
async def _run_model_legacy(
self,
api_key: SecretStr,
model_name: str,
prompt: str,
seed: Optional[int],
aspect_ratio: str,
magic_prompt_option: str,
style_type: str,
negative_prompt: Optional[str],
color_palette_name: str,
custom_colors: Optional[list[str]],
):
url = "https://api.ideogram.ai/generate"
headers = {
"Api-Key": api_key.get_secret_value(),
"Content-Type": "application/json",
}
data: Dict[str, Any] = {
"image_request": {
"prompt": prompt,
"model": model_name,
"aspect_ratio": aspect_ratio,
"magic_prompt_option": magic_prompt_option,
}
}
# Only add style_type for V2, V2_TURBO, and V3 models (V1 models don't support it)
if model_name in ["V_2", "V_2_TURBO", "V_3"]:
data["image_request"]["style_type"] = style_type
if seed is not None:
data["image_request"]["seed"] = seed
if negative_prompt:
data["image_request"]["negative_prompt"] = negative_prompt
# Only add color palette for V2 and V2_TURBO models (V1 models don't support it)
if model_name in ["V_2", "V_2_TURBO"]:
if color_palette_name != "NONE":
data["color_palette"] = {"name": color_palette_name}
elif custom_colors:
data["color_palette"] = {
"members": [{"color_hex": color} for color in custom_colors]
}
try:
response = await Requests().post(url, headers=headers, json=data)
return response.json()["data"][0]["url"]
except Exception as e:
raise ValueError(f"Failed to fetch image with legacy endpoint: {e}") from e
async def upscale_image(self, api_key: SecretStr, image_url: str):
url = "https://api.ideogram.ai/upscale"
headers = {
"Api-Key": api_key.get_secret_value(),
}
try:
# Step 1: Download the image from the provided URL
response = await Requests().get(image_url)
image_content = response.content
# Step 2: Send the downloaded image to the upscale API
files = {
"image_file": ("image.png", image_content, "image/png"),
}
response = await Requests().post(
url,
headers=headers,
data={"image_request": "{}"},
files=files,
)
return (response.json())["data"][0]["url"]
except Exception as e:
raise ValueError(f"Failed to upscale image: {e}") from e
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