From 2dfa33bacb92bb5c7fde4abe7af2801daf748c99 Mon Sep 17 00:00:00 2001 From: cjkindel Date: Mon, 6 Jul 2026 15:05:05 -0700 Subject: [PATCH 1/7] Align deps with advanced-media library --- griptape-nodes-library.json | 599 +++++++++++++++-------------- pyproject.toml | 8 +- uv.lock | 746 +++++++++++++----------------------- 3 files changed, 581 insertions(+), 772 deletions(-) diff --git a/griptape-nodes-library.json b/griptape-nodes-library.json index 62cea7d..dc92395 100644 --- a/griptape-nodes-library.json +++ b/griptape-nodes-library.json @@ -1,304 +1,307 @@ { - "name": "Griptape Modular Diffusion Nodes Library", - "library_schema_version": "0.4.0", - "settings": [ - { - "description": "Configuration settings for the Modular Diffusion Library temporary file storage", - "category": "modular_diffusion_library", - "contents": { - "temp_folder_name": "intermediates" - } - }, - { - "description": "Configuration settings for cleaning up the Modular Diffusion Library temporary file storage", - "category": "modular_diffusion_library", - "contents": { - "max_directory_size_gb": 5, - "enable_directory_cleanup": false - } - }, - { - "description": "Configuration settings for image preview intermediates in diffusion pipeline runtime. Enables real-time image previews during generation but will slow down inference time.", - "category": "modular_diffusion_library", - "contents": { - "enable_image_preview_intermediates": false - } - } - ], - "metadata": { - "author": "Griptape, Inc.", - "description": "Modular Diffusion nodes for Griptape Nodes.", - "library_version": "0.3.0", - "engine_version": "0.77.3", - "tags": [ - "Griptape", - "AI" + "name": "Griptape Modular Diffusion Nodes Library", + "library_schema_version": "0.4.0", + "settings": [ + { + "description": "Configuration settings for the Modular Diffusion Library temporary file storage", + "category": "modular_diffusion_library", + "contents": { + "temp_folder_name": "intermediates" + } + }, + { + "description": "Configuration settings for cleaning up the Modular Diffusion Library temporary file storage", + "category": "modular_diffusion_library", + "contents": { + "max_directory_size_gb": 5, + "enable_directory_cleanup": false + } + }, + { + "description": "Configuration settings for image preview intermediates in diffusion pipeline runtime. Enables real-time image previews during generation but will slow down inference time.", + "category": "modular_diffusion_library", + "contents": { + "enable_image_preview_intermediates": false + } + } ], - "dependencies": { - "pip_dependencies": [ - "accelerate>=1.6.0", - "av>=14.0.0", - "beautifulsoup4>=4.13.4", - "controlnet-aux>=0.0.9", - "static-ffmpeg>=2.8", - "diffusers @ git+https://github.com/huggingface/diffusers.git@037efdae1d53ef893e7412e91fba4f31fc3fd537", - "imageio[ffmpeg]>=2.37.2", - "ninja>=1.13.0", - "numpy>=2.2.4", - "opencv-python>=4.11.0.86", - "peft>=0.17.0", - "pillow>=11.2.1", - "sentencepiece>=0.2.0", - "cmake==3.31.6", - "spandrel>=0.4.1", - "torch==2.7.0", - "torchvision==0.22.0", - "torchaudio==2.7.0", - "safetensors>=0.8.0rc0", - "transformers @ https://github.com/huggingface/transformers/archive/136c621c00b2536d1f608ed3c6de59b9897afbb8.zip", - "tokenizers>=0.22.0,<0.23", - "tqdm>=4.67.1", - "ultralytics>=8.0.0", - "optimum-quanto>=0.2.7", - "protobuf>=6.31.0", - "prodigyopt>=1.1.2; sys_platform == 'win32'", - "bitsandbytes>=0.46.0; sys_platform == 'win32'", - "ftfy>=6.3.1", - "sam2>=1.1.0", - "scipy>=1.10.0", - "matplotlib>=3.10.3", - "supervision>=0.27.0", - "griptape[drivers-prompt-amazon-bedrock,drivers-prompt-anthropic,drivers-prompt-cohere,drivers-prompt-ollama,drivers-web-scraper-trafilatura,drivers-web-search-duckduckgo,drivers-web-search-exa,loaders-image]>=1.8.12", - "openexr>=3.3.0" - ], - "pip_install_flags": [ - "--preview", - "--torch-backend=auto" - ] - }, - "resources": { - "required": { - "compute": [ - [ - "cuda", - "mps" - ], - "has_any" + "metadata": { + "author": "Griptape, Inc.", + "description": "Modular Diffusion nodes for Griptape Nodes.", + "library_version": "0.3.0", + "engine_version": "0.77.3", + "tags": [ + "Griptape", + "AI" + ], + "dependencies": { + "pip_dependencies": [ + "accelerate>=1.6.0", + "av>=14.0.0", + "beautifulsoup4>=4.13.4", + "controlnet-aux>=0.0.9", + "static-ffmpeg>=2.8", + "diffusers==0.39.0", + "imageio[ffmpeg]>=2.37.2", + "ninja>=1.13.0", + "numpy>=2.2.4", + "opencv-python>=4.11.0.86", + "peft>=0.17.0", + "pillow>=11.2.1", + "sentencepiece>=0.2.0", + "cmake==3.31.6", + "spandrel>=0.4.1", + "torch==2.7.0", + "torchvision==0.22.0", + "torchaudio==2.7.0", + "safetensors>=0.8.0rc0", + "transformers==5.13.0", + "tokenizers>=0.22.0,<0.23", + "tqdm>=4.67.1", + "ultralytics>=8.0.0", + "optimum-quanto>=0.2.7", + "protobuf>=6.31.0", + "prodigyopt>=1.1.2; sys_platform == 'win32'", + "bitsandbytes>=0.46.0; sys_platform == 'win32'", + "ftfy>=6.3.1", + "sam2>=1.1.0", + "scipy>=1.10.0", + "matplotlib>=3.10.3", + "supervision>=0.27.0", + "griptape[drivers-prompt-amazon-bedrock,drivers-prompt-anthropic,drivers-prompt-cohere,drivers-prompt-ollama,drivers-web-scraper-trafilatura,drivers-web-search-duckduckgo,drivers-web-search-exa,loaders-image]>=1.9.4", + "openexr>=3.3.0" + ], + "pip_install_flags": [ + "--preview", + "--torch-backend=auto" + ] + }, + "resources": { + "required": { + "compute": [ + [ + "cuda", + "mps" + ], + "has_any" + ] + } + }, + "declarations": [ + { + "type": "lifecycle_stage", + "stage": "LABS" + } ] - } }, - "declarations": [ - { "type": "lifecycle_stage", "stage": "LABS" } + "categories": [], + "nodes": [ + { + "class_name": "LatentDiffusionPipelineBuilderNode", + "file_path": "./modular_diffusion_nodes_library/nodes/latent_diffusion_pipeline_builder_node.py", + "metadata": { + "category": "ModularDiffusion/Pipeline", + "description": "Build and cache latent-compatible \ud83e\udde8 Diffusers Pipelines. Any LoRAs wired into this node are fused permanently into the cached weights \u2014 changing them rebuilds the pipeline. For dynamic adapters that swap per generation, use the LoRA Pipeline node instead.", + "display_name": "Modular Diffusion Pipeline Builder", + "group": "diffusion" + } + }, + { + "class_name": "DiffusionPipelineGenerateLatentNode", + "file_path": "./modular_diffusion_nodes_library/nodes/diffusion_pipeline_generate_latent_node.py", + "metadata": { + "category": "ModularDiffusion/Processing", + "description": "Generate latents via \ud83e\udde8 Diffusers Pipelines.", + "display_name": "Generate Media Latents (Modular Diffusion Pipeline)", + "group": "diffusion" + } + }, + { + "class_name": "NoiseLatentNode", + "file_path": "./modular_diffusion_nodes_library/nodes/noise_latent_node.py", + "metadata": { + "category": "ModularDiffusion/Create", + "description": "Create an initial noise latent tensor for a selected \ud83e\udde8 Diffusers pipeline.", + "display_name": "Create Noise Latents", + "group": "diffusion" + } + }, + { + "class_name": "EmptyLatentNode", + "file_path": "./modular_diffusion_nodes_library/nodes/empty_latent_node.py", + "metadata": { + "category": "ModularDiffusion/Create", + "description": "Create a zero-filled (empty) latent tensor for a selected \ud83e\udde8 Diffusers pipeline.", + "display_name": "Create Empty Latents", + "group": "diffusion" + } + }, + { + "class_name": "AddLatentsNode", + "file_path": "./modular_diffusion_nodes_library/nodes/add_latents.py", + "metadata": { + "category": "ModularDiffusion/Transform", + "description": "Add two latent artifacts elementwise.", + "display_name": "Add Latents", + "group": "diffusion" + } + }, + { + "class_name": "SubtractLatentsNode", + "file_path": "./modular_diffusion_nodes_library/nodes/subtract_latents.py", + "metadata": { + "category": "ModularDiffusion/Transform", + "description": "Subtract the right latent from the left latent elementwise.", + "display_name": "Subtract Latents", + "group": "diffusion" + } + }, + { + "class_name": "MultiplyLatentsNode", + "file_path": "./modular_diffusion_nodes_library/nodes/multiply_latents.py", + "metadata": { + "category": "ModularDiffusion/Transform", + "description": "Multiply two latent artifacts elementwise.", + "display_name": "Multiply Latents", + "group": "diffusion" + } + }, + { + "class_name": "SaveLatentTensorNode", + "file_path": "./modular_diffusion_nodes_library/nodes/save_latent_tensor.py", + "metadata": { + "category": "ModularDiffusion/IO", + "description": "Save a latent artifact to a torch .pt file.", + "display_name": "Save Latent Tensor", + "group": "diffusion" + } + }, + { + "class_name": "VaeEncodeNode", + "file_path": "./modular_diffusion_nodes_library/nodes/vae_encoder.py", + "metadata": { + "category": "ModularDiffusion/Encode\\Decode", + "description": "Encode images or video into VAE latent space via \ud83e\udde8 Diffusers Pipelines.", + "display_name": "Encode Media", + "group": "diffusion" + } + }, + { + "class_name": "VaeMaskEncodeNode", + "file_path": "modular_diffusion_nodes_library/nodes/vae_mask_encoder.py", + "metadata": { + "category": "ModularDiffusion/Encode\\Decode", + "description": "Encode a source image and mask into an inpaint artifact (mask + masked-image latent) for use with inpainting pipelines.", + "display_name": "Encode Masked Media", + "group": "diffusion" + } + }, + { + "class_name": "VaeDecodeNode", + "file_path": "./modular_diffusion_nodes_library/nodes/vae_decoder.py", + "metadata": { + "category": "ModularDiffusion/Encode\\Decode", + "description": "Decode VAE latent images or video via \ud83e\udde8 Diffusers Pipelines.", + "display_name": "Decode Media", + "group": "diffusion" + } + }, + { + "class_name": "DecodeHdrNode", + "file_path": "./modular_diffusion_nodes_library/nodes/decode_hdr_node.py", + "metadata": { + "category": "ModularDiffusion/Encode\\Decode", + "description": "Decode HDR VAE latent, apply tone mapping, and optionally save a raw EXR sequence.", + "display_name": "Decode HDR Latents", + "group": "diffusion" + } + }, + { + "class_name": "LatentCompositeMaskNode", + "file_path": "./modular_diffusion_nodes_library/nodes/latent_composite_mask_node.py", + "metadata": { + "category": "ModularDiffusion/Transform", + "description": "Composite two latent tensors together by pasting masked latent into destination latent.", + "display_name": "Latents Composite Mask", + "group": "diffusion" + } + }, + { + "class_name": "ControlNetNode", + "file_path": "./modular_diffusion_nodes_library/nodes/controlnet_node.py", + "metadata": { + "category": "ModularDiffusion/Conditioning", + "description": "ControlNet node for configuring different ControlNet models.", + "display_name": "Configure ControlNet", + "group": "diffusion" + } + }, + { + "class_name": "ControlNetDiffusionPipelineBuilderNode", + "file_path": "./modular_diffusion_nodes_library/nodes/controlnet_pipeline_node.py", + "metadata": { + "category": "ModularDiffusion/Pipeline", + "description": "Add ControlNet model to the pipeline.", + "display_name": "ControlNet Pipeline", + "group": "diffusion" + } + }, + { + "class_name": "LoraActivationPipelineNode", + "file_path": "./modular_diffusion_nodes_library/nodes/lora_pipeline_node.py", + "metadata": { + "category": "ModularDiffusion/Pipeline", + "description": "Layers non-fused LoRA adapters on top of an existing pipeline. The base pipeline stays untouched, so the same model can power multiple branches (one with adapters, one without). Adapters are loaded and activated per generation, then released \u2014 ideal for in-context (IC) LoRAs, distillation/acceleration LoRAs, slider LoRAs, or any workflow that swaps adapters between runs.", + "display_name": "LoRA Pipeline", + "group": "diffusion" + } + }, + { + "class_name": "MediaGenConditioningNode", + "file_path": "./modular_diffusion_nodes_library/nodes/media_gen_conditioning_node.py", + "metadata": { + "category": "ModularDiffusion/Conditioning", + "description": "Conditioning node for media generation pipelines. Supports image or video conditioning inputs with configurable strength.", + "display_name": "Media Generation Conditioning", + "group": "diffusion" + } + }, + { + "class_name": "LatentUpsamplerNode", + "file_path": "./modular_diffusion_nodes_library/nodes/latent_upsampler_node.py", + "metadata": { + "category": "ModularDiffusion/Processing", + "description": "Spatially upsample a latent tensor using a latent upsampler model.", + "display_name": "Latent Upsampler", + "group": "diffusion" + } + }, + { + "class_name": "LoadLora", + "file_path": "./modular_diffusion_nodes_library/nodes/load_lora_node.py", + "metadata": { + "category": "ModularDiffusion/Pipeline", + "description": "Load a LoRA file from a local path and expose it as a `loras` output. Wire to the Modular Diffusion Pipeline Builder to fuse the LoRA into the cached weights, or to a LoRA Pipeline node to activate it dynamically per generation.", + "display_name": "Load LoRA", + "group": "diffusion" + } + } + ], + "workflows": [ + "workflows/templates/Image2Image.py", + "workflows/templates/MultistageText2Image.py", + "workflows/templates/Text2Image.py", + "workflows/templates/ControlnetText2Image.py", + "workflows/templates/LoRAText2Image.py", + "workflows/templates/FirstAndLastFrameImage2Video.py", + "workflows/templates/LTX23-HDR-Text2Video-Upsample-Two-Stage.py", + "workflows/templates/LTX23-IC-LoRA.py", + "workflows/templates/Inpainting.py", + "workflows/templates/Flux2KleinGuidedInpainting.py", + "workflows/templates/ControlnetInpainting.py", + "workflows/templates/SuccessFailure.py", + "workflows/templates/VideoInpaintingAndOutpaintingWANVace.py", + "workflows/templates/FluxKontextImageEdit.py", + "workflows/templates/FluxKontextInpainting.py" ] - }, - "categories": [], - "nodes": [ - { - "class_name": "LatentDiffusionPipelineBuilderNode", - "file_path": "./modular_diffusion_nodes_library/nodes/latent_diffusion_pipeline_builder_node.py", - "metadata": { - "category": "ModularDiffusion/Pipeline", - "description": "Build and cache latent-compatible 🧨 Diffusers Pipelines. Any LoRAs wired into this node are fused permanently into the cached weights — changing them rebuilds the pipeline. For dynamic adapters that swap per generation, use the LoRA Pipeline node instead.", - "display_name": "Modular Diffusion Pipeline Builder", - "group": "diffusion" - } - }, - { - "class_name": "DiffusionPipelineGenerateLatentNode", - "file_path": "./modular_diffusion_nodes_library/nodes/diffusion_pipeline_generate_latent_node.py", - "metadata": { - "category": "ModularDiffusion/Processing", - "description": "Generate latents via 🧨 Diffusers Pipelines.", - "display_name": "Generate Media Latents (Modular Diffusion Pipeline)", - "group": "diffusion" - } - }, - { - "class_name": "NoiseLatentNode", - "file_path": "./modular_diffusion_nodes_library/nodes/noise_latent_node.py", - "metadata": { - "category": "ModularDiffusion/Create", - "description": "Create an initial noise latent tensor for a selected 🧨 Diffusers pipeline.", - "display_name": "Create Noise Latents", - "group": "diffusion" - } - }, - { - "class_name": "EmptyLatentNode", - "file_path": "./modular_diffusion_nodes_library/nodes/empty_latent_node.py", - "metadata": { - "category": "ModularDiffusion/Create", - "description": "Create a zero-filled (empty) latent tensor for a selected 🧨 Diffusers pipeline.", - "display_name": "Create Empty Latents", - "group": "diffusion" - } - }, - { - "class_name": "AddLatentsNode", - "file_path": "./modular_diffusion_nodes_library/nodes/add_latents.py", - "metadata": { - "category": "ModularDiffusion/Transform", - "description": "Add two latent artifacts elementwise.", - "display_name": "Add Latents", - "group": "diffusion" - } - }, - { - "class_name": "SubtractLatentsNode", - "file_path": "./modular_diffusion_nodes_library/nodes/subtract_latents.py", - "metadata": { - "category": "ModularDiffusion/Transform", - "description": "Subtract the right latent from the left latent elementwise.", - "display_name": "Subtract Latents", - "group": "diffusion" - } - }, - { - "class_name": "MultiplyLatentsNode", - "file_path": "./modular_diffusion_nodes_library/nodes/multiply_latents.py", - "metadata": { - "category": "ModularDiffusion/Transform", - "description": "Multiply two latent artifacts elementwise.", - "display_name": "Multiply Latents", - "group": "diffusion" - } - }, - { - "class_name": "SaveLatentTensorNode", - "file_path": "./modular_diffusion_nodes_library/nodes/save_latent_tensor.py", - "metadata": { - "category": "ModularDiffusion/IO", - "description": "Save a latent artifact to a torch .pt file.", - "display_name": "Save Latent Tensor", - "group": "diffusion" - } - }, - { - "class_name": "VaeEncodeNode", - "file_path": "./modular_diffusion_nodes_library/nodes/vae_encoder.py", - "metadata": { - "category": "ModularDiffusion/Encode\\Decode", - "description": "Encode images or video into VAE latent space via 🧨 Diffusers Pipelines.", - "display_name": "Encode Media", - "group": "diffusion" - } - }, - { - "class_name": "VaeMaskEncodeNode", - "file_path": "modular_diffusion_nodes_library/nodes/vae_mask_encoder.py", - "metadata": { - "category": "ModularDiffusion/Encode\\Decode", - "description": "Encode a source image and mask into an inpaint artifact (mask + masked-image latent) for use with inpainting pipelines.", - "display_name": "Encode Masked Media", - "group": "diffusion" - } - }, - { - "class_name": "VaeDecodeNode", - "file_path": "./modular_diffusion_nodes_library/nodes/vae_decoder.py", - "metadata": { - "category": "ModularDiffusion/Encode\\Decode", - "description": "Decode VAE latent images or video via 🧨 Diffusers Pipelines.", - "display_name": "Decode Media", - "group": "diffusion" - } - }, - { - "class_name": "DecodeHdrNode", - "file_path": "./modular_diffusion_nodes_library/nodes/decode_hdr_node.py", - "metadata": { - "category": "ModularDiffusion/Encode\\Decode", - "description": "Decode HDR VAE latent, apply tone mapping, and optionally save a raw EXR sequence.", - "display_name": "Decode HDR Latents", - "group": "diffusion" - } - }, - { - "class_name": "LatentCompositeMaskNode", - "file_path": "./modular_diffusion_nodes_library/nodes/latent_composite_mask_node.py", - "metadata": { - "category": "ModularDiffusion/Transform", - "description": "Composite two latent tensors together by pasting masked latent into destination latent.", - "display_name": "Latents Composite Mask", - "group": "diffusion" - } - }, - { - "class_name": "ControlNetNode", - "file_path": "./modular_diffusion_nodes_library/nodes/controlnet_node.py", - "metadata": { - "category": "ModularDiffusion/Conditioning", - "description": "ControlNet node for configuring different ControlNet models.", - "display_name": "Configure ControlNet", - "group": "diffusion" - } - }, - { - "class_name": "ControlNetDiffusionPipelineBuilderNode", - "file_path": "./modular_diffusion_nodes_library/nodes/controlnet_pipeline_node.py", - "metadata": { - "category": "ModularDiffusion/Pipeline", - "description": "Add ControlNet model to the pipeline.", - "display_name": "ControlNet Pipeline", - "group": "diffusion" - } - }, - { - "class_name": "LoraActivationPipelineNode", - "file_path": "./modular_diffusion_nodes_library/nodes/lora_pipeline_node.py", - "metadata": { - "category": "ModularDiffusion/Pipeline", - "description": "Layers non-fused LoRA adapters on top of an existing pipeline. The base pipeline stays untouched, so the same model can power multiple branches (one with adapters, one without). Adapters are loaded and activated per generation, then released — ideal for in-context (IC) LoRAs, distillation/acceleration LoRAs, slider LoRAs, or any workflow that swaps adapters between runs.", - "display_name": "LoRA Pipeline", - "group": "diffusion" - } - }, - { - "class_name": "MediaGenConditioningNode", - "file_path": "./modular_diffusion_nodes_library/nodes/media_gen_conditioning_node.py", - "metadata": { - "category": "ModularDiffusion/Conditioning", - "description": "Conditioning node for media generation pipelines. Supports image or video conditioning inputs with configurable strength.", - "display_name": "Media Generation Conditioning", - "group": "diffusion" - } - }, - { - "class_name": "LatentUpsamplerNode", - "file_path": "./modular_diffusion_nodes_library/nodes/latent_upsampler_node.py", - "metadata": { - "category": "ModularDiffusion/Processing", - "description": "Spatially upsample a latent tensor using a latent upsampler model.", - "display_name": "Latent Upsampler", - "group": "diffusion" - } - }, - { - "class_name": "LoadLora", - "file_path": "./modular_diffusion_nodes_library/nodes/load_lora_node.py", - "metadata": { - "category": "ModularDiffusion/Pipeline", - "description": "Load a LoRA file from a local path and expose it as a `loras` output. Wire to the Modular Diffusion Pipeline Builder to fuse the LoRA into the cached weights, or to a LoRA Pipeline node to activate it dynamically per generation.", - "display_name": "Load LoRA", - "group": "diffusion" - } - } - ], - "workflows": [ - "workflows/templates/Image2Image.py", - "workflows/templates/MultistageText2Image.py", - "workflows/templates/Text2Image.py", - "workflows/templates/ControlnetText2Image.py", - "workflows/templates/LoRAText2Image.py", - "workflows/templates/FirstAndLastFrameImage2Video.py", - "workflows/templates/LTX23-HDR-Text2Video-Upsample-Two-Stage.py", - "workflows/templates/LTX23-IC-LoRA.py", - "workflows/templates/Inpainting.py", - "workflows/templates/Flux2KleinGuidedInpainting.py", - "workflows/templates/ControlnetInpainting.py", - "workflows/templates/SuccessFailure.py", - "workflows/templates/VideoInpaintingAndOutpaintingWANVace.py", - "workflows/templates/FluxKontextImageEdit.py", - "workflows/templates/FluxKontextInpainting.py" - ] } diff --git a/pyproject.toml b/pyproject.toml index 94685ab..11986f7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,7 +12,7 @@ dependencies = [ "beautifulsoup4>=4.13.4", "controlnet-aux>=0.0.9", "static-ffmpeg>=2.8", - "diffusers @ git+https://github.com/huggingface/diffusers.git@037efdae1d53ef893e7412e91fba4f31fc3fd537", + "diffusers==0.39.0", "imageio[ffmpeg]>=2.37.2", "ninja>=1.13.0", "numpy>=2.2.4", @@ -26,7 +26,7 @@ dependencies = [ "torchvision==0.22.0", "torchaudio==2.7.0", "safetensors>=0.8.0rc0", - "transformers @ https://github.com/huggingface/transformers/archive/136c621c00b2536d1f608ed3c6de59b9897afbb8.zip", + "transformers==5.13.0", "tokenizers>=0.22.0,<0.23", "tqdm>=4.67.1", "ultralytics>=8.0.0", @@ -39,9 +39,9 @@ dependencies = [ "scipy>=1.10.0", "matplotlib>=3.10.3", "supervision>=0.27.0", - "griptape[drivers-prompt-amazon-bedrock,drivers-prompt-anthropic,drivers-prompt-cohere,drivers-prompt-ollama,drivers-web-scraper-trafilatura,drivers-web-search-duckduckgo,drivers-web-search-exa,loaders-image]>=1.8.12", + "griptape[drivers-prompt-amazon-bedrock,drivers-prompt-anthropic,drivers-prompt-cohere,drivers-prompt-ollama,drivers-web-scraper-trafilatura,drivers-web-search-duckduckgo,drivers-web-search-exa,loaders-image]>=1.9.4", "openexr>=3.3.0", - "griptape-nodes>=0.77.3", + "griptape-nodes>=0.77.5", ] [build-system] diff --git a/uv.lock b/uv.lock index 981cd53..02ead4b 100644 --- a/uv.lock +++ b/uv.lock @@ -3,7 +3,9 @@ revision = 3 requires-python = ">=3.12, <4" resolution-markers = [ "sys_platform == 'win32'", - "sys_platform != 'win32'", + "(python_full_version >= '3.14' and sys_platform == 'linux') or (platform_machine != 'aarch64' and sys_platform == 'linux') or (platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version < '3.14' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", + "sys_platform != 'linux' and sys_platform != 'win32'", ] [[package]] @@ -17,7 +19,8 @@ dependencies = [ { name = "psutil" }, { name = "pyyaml" }, { name = "safetensors" }, - { name = "torch" }, + { name = "torch", version = "2.7.0", source = { registry = "https://pypi.org/simple" }, marker = "sys_platform != 'linux' and sys_platform != 'win32'" }, + { name = "torch", version = "2.7.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "sys_platform == 'linux' or sys_platform == 'win32'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/ca/14/787e5498cd062640f0f3d92ef4ae4063174f76f9afd29d13fc52a319daae/accelerate-1.13.0.tar.gz", hash = "sha256:d631b4e0f5b3de4aff2d7e9e6857d164810dfc3237d54d017f075122d057b236", size = 402835, upload-time = "2026-03-04T19:34:12.359Z" } wheels = [ @@ -158,9 +161,9 @@ name = "bitsandbytes" version = "0.49.2" 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Pin to a specific commit if you need stability, and expect breakage when updating. > -> ## ⚠️ Using alongside the Advanced Media Library -> The Diffusers Library and the Advanced Media Library share several upstream dependencies (e.g. `diffusers`, `transformers`, `torch`) and may pin them to different versions. Installing both libraries from their default branches can cause dependency mismatches and runtime errors. -> -> If you need both libraries in the same environment, install the Advanced Media Library from its [`modular-diffusion-library-compatible-branch`](https://github.com/griptape-ai/griptape-nodes-library-advanced-media/compare/main...modular-diffusion-library-compatible-branch) instead of `main`: -> ```text -> https://github.com/griptape-ai/griptape-nodes-library-advanced-media@modular-diffusion-library-compatible-branch -> ``` +> ## Using alongside the Advanced Media Library +> The Diffusers Library and the Advanced Media Library share several upstream dependencies (e.g. `diffusers`, `transformers`, `torch`). Both libraries pin these to the same versions on their `main` branches, so you can install both from `main` in the same environment. ![Diffusers Nodes](docs/assets/hero.png) From 9037a471da7b026afab54f4d96b6ce831667453b Mon Sep 17 00:00:00 2001 From: cjkindel Date: Mon, 6 Jul 2026 15:19:26 -0700 Subject: [PATCH 4/7] lib json engine version bump --- griptape-nodes-library.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/griptape-nodes-library.json b/griptape-nodes-library.json index dc92395..2e401d6 100644 --- a/griptape-nodes-library.json +++ b/griptape-nodes-library.json @@ -29,7 +29,7 @@ "author": "Griptape, Inc.", "description": "Modular Diffusion nodes for Griptape Nodes.", "library_version": "0.3.0", - "engine_version": "0.77.3", + "engine_version": "0.77.5", "tags": [ "Griptape", "AI" From c5f8f7c20a212c760d41dc7c0d9a1e2a9c25d53c Mon Sep 17 00:00:00 2001 From: cjkindel Date: Mon, 6 Jul 2026 15:40:48 -0700 Subject: [PATCH 5/7] pyright ignore templates --- pyproject.toml | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 095aea2..e48b05d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -75,6 +75,11 @@ name = "pytorch-cu128" url = "https://download.pytorch.org/whl/cu128" explicit = true +[tool.pyright] +# Generated workflow templates are excluded from linting (see ruff extend-exclude); +# exclude them from type checking too. +exclude = ["workflows/templates"] + [tool.ruff] line-length = 120 target-version = "py312" From 76c08f1b9baa3ece5ed9b055376bef7f37a6146c Mon Sep 17 00:00:00 2001 From: cjkindel Date: Mon, 6 Jul 2026 16:03:52 -0700 Subject: [PATCH 6/7] copy adv media's pyright config --- pyproject.toml | 19 ++++++++++++++++++- 1 file changed, 18 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index e48b05d..db3e199 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -76,9 +76,26 @@ url = "https://download.pytorch.org/whl/cu128" explicit = true [tool.pyright] +venvPath = "." +venv = ".venv" +include = ["."] # Generated workflow templates are excluded from linting (see ruff extend-exclude); # exclude them from type checking too. -exclude = ["workflows/templates"] +exclude = [".venv", "**/node_modules", "**/__pycache__", "**/.*", "workflows/templates"] +pythonVersion = "3.12" +reportIncompatibleMethodOverride = false +reportMissingImports = false +reportMissingModuleSource = false +reportAttributeAccessIssue = false +reportPrivateImportUsage = false +reportCallIssue = false +reportArgumentType = false +reportOptionalSubscript = false +reportReturnType = false +reportOptionalCall = false +reportGeneralTypeIssues = false +reportIndexIssue = false +reportAssignmentType = false [tool.ruff] line-length = 120 From 546c34757b9824dc51652e29cf4669ca78e3add0 Mon Sep 17 00:00:00 2001 From: cjkindel Date: Mon, 6 Jul 2026 16:05:43 -0700 Subject: [PATCH 7/7] fix reportOptionalMemberAccess sites --- .../latent_pipeline_drivers/base_driver.py | 3 +++ .../latent_pipeline_drivers/flux.py | 2 +- .../latent_pipeline_drivers/flux2_base.py | 2 +- 3 files changed, 5 insertions(+), 2 deletions(-) diff --git a/modular_diffusion_nodes_library/latent_pipeline_drivers/base_driver.py b/modular_diffusion_nodes_library/latent_pipeline_drivers/base_driver.py index 2586c18..f21c64d 100644 --- a/modular_diffusion_nodes_library/latent_pipeline_drivers/base_driver.py +++ b/modular_diffusion_nodes_library/latent_pipeline_drivers/base_driver.py @@ -435,6 +435,9 @@ def _get_inpaint_pipe(self) -> DiffusionPipeline | None: def _get_inpaint_kwargs(self, artifact: InpaintMaskArtifact) -> dict[str, Any]: """Map an InpaintMaskArtifact to pipeline call kwargs.""" device, dtype = self._get_device_and_type() + if artifact.source_latent is None: + msg = "Attempted to build inpaint kwargs. Failed because the InpaintMaskArtifact has no source_latent." + raise ValueError(msg) result: dict[str, Any] = { "image": artifact.source_latent.to(device=device, dtype=dtype), "mask_image": artifact.mask_image, diff --git a/modular_diffusion_nodes_library/latent_pipeline_drivers/flux.py b/modular_diffusion_nodes_library/latent_pipeline_drivers/flux.py index e34711f..df65d58 100644 --- a/modular_diffusion_nodes_library/latent_pipeline_drivers/flux.py +++ b/modular_diffusion_nodes_library/latent_pipeline_drivers/flux.py @@ -165,7 +165,7 @@ def create_noise_latent(self, source_shape: tuple[int, ...], generator_state: Ge batch_size=1, dtype=dtype, ) - latents = output_state.get("latents") + latents = output_state["latents"] latents = latents.to(device) latents = self.unpack_latents(latents, height, width) return self._make_latent_artifact( diff --git a/modular_diffusion_nodes_library/latent_pipeline_drivers/flux2_base.py b/modular_diffusion_nodes_library/latent_pipeline_drivers/flux2_base.py index e71276e..d125e9d 100644 --- a/modular_diffusion_nodes_library/latent_pipeline_drivers/flux2_base.py +++ b/modular_diffusion_nodes_library/latent_pipeline_drivers/flux2_base.py @@ -62,7 +62,7 @@ def create_noise_latent(self, source_shape: tuple[int, ...], generator_state: Ge unpack_latents = Flux2UnpackLatentsStep() latents_state = self._call_block(unpack_latents, latents=packed_latents, latent_ids=latent_ids) - latents = latents_state.get("latents") + latents = latents_state["latents"] latents = latents.to(device) return self._make_latent_artifact( latents,