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Merge pull request #171 from griptape-ai:remove/black-forest

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Remove/black-forest
This commit is contained in:
Jason Schleifer
2024-11-28 05:23:44 +13:00
committed by GitHub
parent eab7e3cbb8 b850c60b45
commit da0bf86eb1
13 changed files with 8 additions and 394 deletions
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README.md
+3
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@@ -104,6 +104,9 @@ You can previous and download more examples [here](examples/README.md).
## Recent Changelog
### Nov 28, 2024
* ⚠️ **Temporarily removed BlackForestLabs Driver nodes while resolving install issues**. There appears to be an installation issue for these nodes, so I'm _temporarily_ removing them until it's resolved.
### Nov 27, 2024
* Added example: [PDF -> Profile Pic](examples/pdf_to_profile_pic.png) where a resume in pdf form is summarized, then used as inspiration for an image generation prompt to create a profile picture.
__init__.py
-6
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@@ -118,11 +118,6 @@ from .nodes.drivers.gtUIAzureOpenAiImageGenerationDriver import (
gtUIAzureOpenAiImageGenerationDriver,
)
# - BlackForest Labs
from .nodes.drivers.gtUIBlackForestImageGenerationDriver import (
gtUIBlackForestImageGenerationDriver,
)
# - Cohere
from .nodes.drivers.gtUICohereEmbeddingDriver import gtUICohereEmbeddingDriver
from .nodes.drivers.gtUICoherePromptDriver import gtUICoherePromptDriver
@@ -376,7 +371,6 @@ NODE_CLASS_MAPPINGS = {
"Griptape Driver: Amazon Bedrock Stable Diffusion": gtUIAmazonBedrockStableDiffusionImageGenerationDriver,
"Griptape Driver: Amazon Bedrock Titan": gtUIAmazonBedrockTitanImageGenerationDriver,
"Griptape Driver: Azure OpenAI Image Generation": gtUIAzureOpenAiImageGenerationDriver,
"Griptape Driver: Black Forest Labs Image Generation": gtUIBlackForestImageGenerationDriver,
"Griptape Driver: Leonardo.AI": gtUILeonardoImageGenerationDriver,
"Griptape Driver: OpenAI Image Generation": gtUIOpenAiImageGenerationDriver,
"Griptape Driver: OpenAI Compatible Image Generation": gtUIOpenAiCompatibleImageGenerationDriver,
examples/README.md
-20
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@@ -18,26 +18,6 @@ Uses `Griptape Load: Text` node to import a PDF of a robot resume, then the `Gri
![Profile Pic](pdf_to_profile_pic.png)
Download: [pdf_to_profile_pic.png](pdf_to_profile_pic.png)
## Black Forest Labs - Flux Pro 1.1 Image Generation
Use Black Forest Labs Flux models with Griptape!
![BFL Flux-Pro-1.1](griptape_black_forest_labs_create_image.png)
Download: [griptape_black_forest_labs_create_image.png](griptape_black_forest_labs_create_image.png)
## Black Forest Labs - Flux Pro 1.0-Canny - Image Variation
Use Black Forest Labs Flux-Pro-1.0-canny with Griptape to create a variation on an image.
![BFL flux-pro-1.0-canny](griptape_black_forest_labs_create_variation.png)
Download: [griptape_black_forest_labs_create_variation.png](griptape_black_forest_labs_create_variation.png)
## Black Forest Labs - Flux Pro 1.0-Fill - Image Inpainting
Use Black Forest Labs Flux-Pro-1.0-fill with Griptape to perform inpainting on an image.
![BFL flux-pro-1.0-fill](griptape_black_forest_flux_inpainting.png)
Download: [griptape_black_forest_flux_inpainting.png](griptape_black_forest_flux_inpainting.png)
## Griptape Expert Photographers
Use Agents as experts in their field to help provide feedback that will generate more advanced outputs. Utilizes multiple models - including Ollama running locally. If you don't have Ollama installed, feel free to use another `prompt_driver`.
examples/griptape_black_forest_flux_inpainting.png
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examples/griptape_black_forest_labs_create_image.png
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js/NodesWithVisibilityToggles.js
+3 -92
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@@ -4,97 +4,8 @@ import { formatAndDisplayJSON } from "./gtUIUtils.js";
import { hideWidget, showWidget } from "./utils.js";
import { app } from "../../../scripts/app.js";
export function setupVisibilityToggles(nodeType, nodeData, app) {
if (nodeData.name.includes("Black Forest Labs Image Generation")) {
setupBlackForestLabsImageGenerationNode(nodeType, nodeData, app);
}
// if (nodeData.name.includes("Black Forest Labs Image Generation")) {
// setupBlackForestLabsImageGenerationNode(nodeType, nodeData, app);
// }
}
function setupBlackForestLabsImageGenerationNode(nodeType, nodeData, app) {
const onNodeCreated = nodeType.prototype.onNodeCreated;
nodeType.prototype.onNodeCreated = function () {
const me = onNodeCreated?.apply(this);
const widget_model = this.widgets.find(
(w) => w.name === "image_generation_model"
);
const width_widget = this.widgets.find((w) => w.name === "width");
const height_widget = this.widgets.find((w) => w.name === "height");
const aspect_ratio_width_widget = this.widgets.find(
(w) => w.name === "aspect_ratio_width"
);
const aspect_ratio_height_widget = this.widgets.find(
(w) => w.name === "aspect_ratio_height"
);
const raw_widget = this.widgets.find((w) => w.name === "raw");
const guidance_widget = this.widgets.find((w) => w.name === "guidance");
const steps_widget = this.widgets.find((w) => w.name === "steps");
const interval_widget = this.widgets.find((w) => w.name === "interval");
const prompt_upsampling_widget = this.widgets.find(
(w) => w.name === "prompt_upsampling"
);
const image_prompt_strength_widget = this.widgets.find((w) => w.name === "image_prompt_strength");
// Hide both widgets
widget_model.callback = async () => {
hideWidget(this, width_widget);
hideWidget(this, height_widget);
hideWidget(this, aspect_ratio_width_widget);
hideWidget(this, aspect_ratio_height_widget);
hideWidget(this, raw_widget);
hideWidget(this, guidance_widget);
hideWidget(this, steps_widget);
hideWidget(this, interval_widget);
hideWidget(this, prompt_upsampling_widget);
hideWidget(this, image_prompt_strength_widget);
switch (widget_model.value) {
case "flux-pro-1.1-ultra":
showWidget(aspect_ratio_height_widget);
showWidget(aspect_ratio_width_widget);
showWidget(raw_widget);
showWidget(image_prompt_strength_widget);
break;
case "flux-pro-1.1":
showWidget(width_widget);
showWidget(height_widget);
showWidget(prompt_upsampling_widget);
break;
case "flux-pro":
showWidget(width_widget);
showWidget(height_widget);
showWidget(prompt_upsampling_widget);
showWidget(interval_widget);
showWidget(guidance_widget);
showWidget(steps_widget);
break;
case "flux-dev":
showWidget(width_widget);
showWidget(height_widget);
showWidget(guidance_widget);
showWidget(steps_widget);
showWidget(prompt_upsampling_widget);
break;
case "flux-pro-1.0-depth":
case "flux-pro-1.0-canny":
showWidget(guidance_widget);
showWidget(steps_widget);
showWidget(prompt_upsampling_widget);
break;
case "flux-pro-1.0-fill":
showWidget(guidance_widget);
showWidget(steps_widget);
showWidget(prompt_upsampling_widget);
break;
default:
break;
}
fitHeight(this, true);
};
setTimeout(() => {
widget_model.callback();
}, 5);
return me;
};
}
js/griptape_api_keys.js
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@@ -9,7 +9,6 @@ export const keys_organized = {
"AMAZON_OPENSEARCH_INDEX_NAME",
],
Anthropic: ["ANTHROPIC_API_KEY"],
"BlackForest Labs": ["BFL_API_KEY"],
"Microsoft Azure": [
"AZURE_OPENAI_ENDPOINT",
"AZURE_OPENAI_DALL_E_3_ENDPOINT",
nodes/drivers/gtUIBlackForestImageGenerationDriver.py
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@@ -1,237 +0,0 @@
from griptape.black_forest.drivers.black_forest_image_generation_driver import (
BlackForestImageGenerationDriver,
)
from .gtUIBaseImageDriver import gtUIBaseImageGenerationDriver
DEFAULT_API_KEY = "BFL_API_KEY"
models = [
"flux-pro-1.1",
"flux-pro-1.1-ultra",
"flux-pro",
"flux-dev",
"flux-pro-1.0-canny",
"flux-pro-1.0-depth",
"flux-pro-1.0-fill",
]
widths = [str(i) for i in range(256, 1441, 32)]
heights = [str(i) for i in range(256, 1441, 32)]
safety_tolerance_list = ["strict", "high", "medium", "low", "very_low", "none"]
aspect_ratios = [f"{w}:{h}" for w in range(21, 8, -1) for h in range(9, 22)]
class gtUIBlackForestImageGenerationDriver(gtUIBaseImageGenerationDriver):
DESCRIPTION = "Black Forest Image Generation Driver to use Flux models."
@classmethod
def INPUT_TYPES(s):
inputs = super().INPUT_TYPES()
inputs["optional"].update(
{
"image_generation_model": (
models,
{
"default": models[0],
"tooltip": "Select the image generation model.",
},
),
"width": (
widths,
{"default": "1024", "tooltip": "Select the desired image width."},
),
"height": (
heights,
{"default": "768", "tooltip": "Select the desired image height."},
),
"aspect_ratio_width": (
"INT",
{
"default": 16,
"min": 9,
"max": 21,
"tooltip": "Select the desired aspect width.",
},
),
"aspect_ratio_height": (
"INT",
{
"default": 9,
"min": 9,
"max": 21,
"tooltip": "Select the desired aspect height.",
},
),
"prompt_upsampling": (
"BOOLEAN",
{
"default": False,
"tooltip": "Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation.",
"label_on": "True (Modify Prompt)",
"label_off": "False (No Modification)",
},
),
"safety_tolerance": (
safety_tolerance_list,
{
"default": safety_tolerance_list[2],
"tooltip": "Select the safety tolerance level.",
},
),
"steps": (
"INT",
{
"default": None,
"tooltip": "Number of steps for the image generation process. Values: 1-50",
"min": 0,
"max": 50,
},
),
"guidance": (
"FLOAT",
{
"default": 0.0,
"tooltip": "Optional guidance scale for image generation. \n\nFor 'flux-dev' and 'flux-pro', values are 1.5-5. High guidance scales improve prompt adherence at the cost of reduced realism.\n\nFor 'flux-pro-1.0-canny' and 'flux-pro-1.0-depth' values are 1-100 and higher guidance applies image over prompt.",
},
),
"interval": (
"INT",
{
"default": None,
"tooltip": "Optional interval parameter for guidance control. Values: 1-4",
"min": 0,
"max": 4,
},
),
"seed": (
"INT",
{
"default": 10342349342,
"tooltip": "Seed for random number generation.",
},
),
"raw": (
"BOOLEAN",
{
"default": False,
"tooltip": "Generate less processed, more natural-looking images",
},
),
"image_prompt_strength": (
"FLOAT",
{
"default": 0.1,
"tooltip": "Image prompt strength. Values: 0.0-1.0. Higher values increase the influence of the image.",
"min": 0,
"max": 1,
},
),
"api_key_env_var": (
"STRING",
{
"default": DEFAULT_API_KEY,
"tooltip": "Enter the environment variable name for the API key, not the actual API key.",
},
),
}
)
return inputs
def build_params(self, **kwargs):
model = kwargs.get("image_generation_model", models[0])
width = kwargs.get("width", "1024")
height = kwargs.get("height", "768")
aspect_ratio_width = kwargs.get("aspect_ratio_width", 16)
aspect_ratio_height = kwargs.get("aspect_ratio_height", 9)
aspect_ratio = f"{aspect_ratio_width}:{aspect_ratio_height}"
prompt_upsampling = kwargs.get("prompt_upsampling", False)
safety_tolerance_str = kwargs.get("safety_tolerance", safety_tolerance_list[2])
safety_tolerance = safety_tolerance_list.index(safety_tolerance_str)
image_prompt_strength = kwargs.get("image_prompt_strength", 0.1)
seed = kwargs.get("seed", 10342349342)
steps = kwargs.get("steps", None)
guidance = kwargs.get("guidance", None)
interval = kwargs.get("interval", 0.5)
raw = kwargs.get("raw", False)
api_key = self.getenv(kwargs.get("api_key_env_var", DEFAULT_API_KEY))
params = {}
if model:
params["model"] = model
if safety_tolerance:
params["safety_tolerance"] = int(safety_tolerance)
if seed:
params["seed"] = int(seed)
if api_key:
params["api_key"] = api_key
# Ultra model specific settings
if model == "flux-pro-1.1-ultra":
if aspect_ratio:
params["aspect_ratio"] = aspect_ratio
if raw:
params["raw"] = bool(raw)
if image_prompt_strength:
params["image_prompt_strength"] = float(image_prompt_strength)
# Fill model specific settings
if model == "flux-pro-1.0-fill":
if guidance is not None and guidance > 0:
if guidance < 1.5:
guidance == 1.5
if guidance > 100:
raise ValueError(
f"When using {model}, guidance must be between 1.5 and 100."
)
params["guidance"] = float(guidance)
# Canny/Depth model specific settings
if model in ["flux-pro-1.0-canny", "flux-pro-1.0-depth"]:
if guidance is not None and guidance > 0:
if guidance < 1:
guidance == 1
params["guidance"] = float(guidance)
# Dev/Pro specific settings
if model in ["flux-dev", "flux-pro"]:
if guidance is not None and guidance > 0:
if guidance < 1.5:
guidance == 1.5
if guidance > 5:
raise ValueError(
f"When using {model}, guidance must be between 1.5 and 5."
)
params["guidance"] = float(guidance)
# Pro model specific settings
if model == "flux-pro":
if interval is not None and interval > 0:
params["interval"] = int(interval)
# Dev/Pro/Canny/Depth specific settings
if model in [
"flux-dev",
"flux-pro",
"flux-pro-1.0-canny",
"flux-pro-1.0-depth",
]:
if steps is not None and steps > 0:
params["steps"] = int(steps)
if prompt_upsampling:
params["prompt_upsampling"] = bool(prompt_upsampling)
# Flux-pro-1.1, flux-dev, flux-pro specific settings
if model in ["flux-dev", "flux-pro", "flux-pro-1.1"]:
if width:
params["width"] = int(width)
if height:
params["height"] = int(height)
return params
def create(self, **kwargs):
params = self.build_params(**kwargs)
params["max_attempts"] = 1
driver = BlackForestImageGenerationDriver(**params)
return (driver,)
nodes/tasks/gtUIInpaintingImageGenerationTask.py
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@@ -2,9 +2,6 @@ import base64
import os
import folder_paths
from griptape.black_forest.drivers.black_forest_image_generation_driver import (
BlackForestImageGenerationDriver,
)
from griptape.drivers import (
AmazonBedrockImageGenerationDriver,
AzureOpenAiImageGenerationDriver,
@@ -61,10 +58,6 @@ class gtUIInpaintingImageGenerationTask(gtUIBaseImageTask):
"models": ["dall-e-2"],
"default_message": "OpenAI model must be dall-e-2 for inpainting.",
},
BlackForestImageGenerationDriver: {
"models": ["flux-pro-1.0-fill"],
"default_message": "BlackForest model must be flux-pro-1.0-fill for inpainting.",
},
LeonardoImageGenerationDriver: {
"models": [],
"default_message": "Leonardo.AI does not support Inpainting. Please choose a different driver.",
@@ -123,12 +116,6 @@ class gtUIInpaintingImageGenerationTask(gtUIBaseImageTask):
if not inpainting_supported:
raise ValueError(msg)
# Quick fix for flux-pro-1.0-fill
if isinstance(driver, BlackForestImageGenerationDriver):
# check the model to make sure it's one that can handle Variation Image Generation
if driver.model == "flux-pro-1.0-fill":
driver.model = "flux-pro-1.0"
# Create an engine configured to use the driver.
engine = InpaintingImageGenerationEngine(
image_generation_driver=driver,
nodes/tasks/gtUIPromptImageVariationTask.py
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@@ -2,9 +2,6 @@ import base64
import os
import folder_paths
from griptape.black_forest.drivers.black_forest_image_generation_driver import (
BlackForestImageGenerationDriver,
)
from griptape.drivers import (
OpenAiImageGenerationDriver,
)
@@ -66,24 +63,6 @@ class gtUIPromptImageVariationTask(gtUIBaseImageTask):
api_key=OPENAI_API_KEY,
model="dall-e-2",
)
# Check if driver is BlackForestImageGenerationDriver
if isinstance(driver, BlackForestImageGenerationDriver):
# check the model to make sure it's one that can handle Variation Image Generation
if driver.model not in [
"flux-pro-1.0-canny",
"flux-pro-1.0-depth",
# "flux-dev",
"flux-pro-1.1",
# "flux-pro",
"flux-pro-1.1-ultra",
]:
raise ValueError(
f"Model {driver.model} is not supported for image variation."
)
return (
None,
f"Model {driver.model} is not supported for image variation.",
)
# Create an engine configured to use the driver.
engine = VariationImageGenerationEngine(
image_generation_driver=driver,
pyproject.toml
+2 -3
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@@ -9,7 +9,6 @@ readme = "README.md"
python = "^3.11"
python-dotenv = "^1.0.1"
griptape = { version = "^0.34.3", extras = ["all"]}
griptape-black-forest = {git = "https://github.com/griptape-ai/griptape-black-forest.git"}
[tool.poetry.group.dev.dependencies]
icecream = "^2.1.3"
@@ -27,9 +26,9 @@ priority = "explicit"
[project]
name = "comfyui-griptape"
description = "Griptape LLM(Large Language Model) Nodes for ComfyUI."
version = "1.0.22"
version = "1.0.24"
license = {file = "LICENSE"}
dependencies = ["griptape[all]==0.34.3", "python-dotenv", "git+https://github.com/griptape-ai/griptape-black-forest.git"]
dependencies = ["griptape[all]==0.34.3", "python-dotenv"]
[project.urls]
Repository = "https://github.com/griptape-ai/ComfyUI-Griptape"
requirements.txt
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@@ -1,3 +1,2 @@
griptape[all]==0.34.3
python-dotenv
git+https://github.com/griptape-ai/griptape-black-forest.git