# Introduction
Some nodes for stable diffusion comfyui.Sometimes it helps conveniently to use less nodes for doing the same things.

If you use workflow in my "blogs" repo, you need to dowmload these nodes.I don't guarantee that the nodes will stay the same always. Some nodes maybe have been changed if you update the new version.
# How to install
## The repo
The same with others custom nodes. Just cd custom_nodes and then git clone.
## Translator model
If you use prompt translator to translate Chinese to English offline, you need download some models.
Download the translator models from https://huggingface.co/facebook/mbart-large-50-many-to-one-mmt/tree/main into folder named "model" of this repo.
The model folder tree of this repo:
model/
└── mbart-large-50-many-to-many-mmt__only_to_English/
    ├── pytorch_model.bin
    ├── config.json
    ├── sentencepiece.bpe.model
    ├── special_tokens_map.json
    ├── tmp2l0rt359
    └── tokenizer_config.json
## Environments
cd (this repo)
pip install -r requirements.txt

# Nodes Introductions
## tdxh_image
- "TdxhImageToSize": TdxhImageToSize can Convert an image to size.
- "TdxhImageToSizeAdvanced":TdxhImageToSizeAdvanced can Convert an image to size and it will let you choose what to follow:"only_width", "only_height", "both_width_and_height","width * height", "only_ratio","only_image","get_SDXL_best_size".
## tdxh_model
- "TdxhLoraLoader": TdxhLoraLoader adds a switch to the "LoraLoader", which shows as "bool_int" (0 -> OFF, 1 -> ON), and lets you choose "only_strength_both" or "strength_model_and_strength_clip".
## tdxh_data
- "TdxhIntInput": TdxhIntInput returns the "INT" type.
- "TdxhFloatInput": TdxhFloatInput returns the "FLOAT" type.
- "TdxhStringInput": TdxhStringInput returns the "STRING" type.
- "TdxhSaveText": TdxhSaveText saves input text to an output text file and returns both the input text and the saved path as "STRING" outputs.
- "TdxhStringInputTranslator": TdxhStringInputTranslator returns the translated "STRING" type. (You need to download the translator model.)
## tdxh_bool
- "TdxhOnOrOff": TdxhOnOrOff returns the "NUMBER" and "INT" type. When switching to ON, it returns 1; when switching to OFF, it returns 0.
- "TdxhBoolNumber": TdxhBoolNumber is similar to TdxhOnOrOff but lets you choose what to follow. "control_by_master" is the main control: if OFF, it returns "bool_int"; if ON, then only when both "bool_int_from_master" and "bool_int" are 1 does it return 1.
## tdxh_efficiency
- "TdxhClipVison": TdxhClipVison adds a switch to the "CLIPVisionLoader" and the "clip_vision".
- "TdxhControlNetProcessor": TdxhControlNetProcessor adds a switch to ControlNet nodes and lets you preprocess the image. (It needs AUX preprocessor nodes.)
- "TdxhControlNetApply": TdxhControlNetApply adds a switch to ControlNet nodes and makes them more efficient to use.
- "TdxhReference": TdxhReference makes the "reference_only" node more efficient.
- "TdxhImg2ImgLatent": TdxhImg2ImgLatent can switch between original(main) latent and image latent (OFF -> main latent, ON -> image latent).

## tdxh_ltx23
- "TdxhLtx23MultimodalDirector": TdxhLtx23MultimodalDirector is a multimodal control hub for LTX 2.3 style workflows. It accepts text, a dynamic image sequence, optional reference audio, and optional reference video frames, then outputs a ready-to-use positive prompt, negative prompt, modality-specific guidance strings, and a structured JSON control plan. The node is meant to sit upstream of LTX prompt/conditioning workflows so users can keep character consistency, scene continuity, voice or ambience guidance, and video style/camera/rhythm guidance in one place.

## API nodes
### DeepSeek API nodes
This repo now includes:
- `TdxhDeepSeekChat`

Config priority:
1. environment variable `DEEPSEEK_API_KEY`
2. local file `deepseek_config.json`

You can create `deepseek_config.json` from `deepseek_config.example.json`:

```json
{
  "api_key": "sk-your-deepseek-api-key",
  "base_url": "https://api.deepseek.com",
  "timeout_seconds": 120
}
```

Notes:
- `TdxhDeepSeekChat` outputs `answer`, `reasoning`, `status`
- `TdxhDeepSeekChat` now has a `thinking_enabled` toggle, switching between `deepseek-chat` and `deepseek-reasoner`
- `TdxhDeepSeekChat` auto-enables JSON mode when the prompt clearly asks for JSON output
- both nodes support optional multi-round history with `keep_history`
- `clear_history` clears the stored conversation state inside the node instance
- config files are stored under `api_nodes/configs/`

### Kimi API nodes
This repo now also includes:
- `TdxhKimiChat`
- `TdxhKimiDynamicVisionChat`
- `TdxhLocalQwenVLDynamicVisionChat`

Config priority:
1. environment variable `MOONSHOT_API_KEY`
2. environment variable `KIMI_API_KEY`
3. local file `kimi_config.json`

You can create `kimi_config.json` from `kimi_config.example.json`:

```json
{
  "api_key": "sk-your-moonshot-api-key",
  "base_url": "https://api.moonshot.ai/v1",
  "chat_model": "kimi-k2-turbo-preview",
  "thinking_model": "kimi-k2.5",
  "vision_model": "moonshot-v1-8k-vision-preview",
  "timeout_seconds": 120
}
```

Notes:
- `TdxhKimiChat` defaults to a faster Moonshot chat model for non-thinking text requests and keeps `kimi-k2.5` for thinking requests
- `TdxhKimiChat` can disable thinking by sending `thinking: {"type":"disabled"}`
- `TdxhKimiChat` already has a `thinking_enabled` toggle in the node UI
- `TdxhKimiDynamicVisionChat` supports a dynamic number of image inputs with an `Update inputs` button
- dynamic image inputs allow trailing image inputs to be empty, but do not allow gaps in the middle; if `image_4` is connected then `image_1` to `image_3` must also be connected
- `TdxhKimiDynamicVisionChat` requires Moonshot Open Platform endpoints, not the Kimi Code endpoint
- `TdxhLocalQwenVLDynamicVisionChat` wraps the local `ComfyUI-QwenVL` GGUF backend under the tdxh naming convention
- `TdxhLocalQwenVLDynamicVisionChat` supports dynamic image inputs with an `Update inputs` button and also accepts one fixed optional `video` input
- `TdxhLocalQwenVLDynamicVisionChat` allows images and the fixed video input to be used together in one local multimodal request
- `TdxhLocalQwenVLDynamicVisionChat` does not add extra pip dependencies inside this repo, but it requires the external `ComfyUI-QwenVL` plugin to be installed
- `TdxhLocalQwenVLDynamicVisionChat` also depends on that plugin's GGUF vision runtime, such as a vision-capable `llama-cpp-python` build and matching QwenVL GGUF/mmproj model files
- ComfyUI placeholder images coming from `LoadImage(example.png)` are treated as empty image inputs, including common resize-like preprocessing results
- `TdxhKimiDynamicVisionChat` uploads valid images to Moonshot Files and reuses them via `ms://file_id` for lower request overhead on repeated calls
- both nodes output `reasoning_content` when the model returns it
- if `keep_history` is enabled, the node stores `reasoning_content` in assistant history to follow Moonshot's thinking-model guidance
- config files are stored under `api_nodes/configs/`

### Multi-platform fallback node
This repo also includes:
- `TdxhMultiPlatformChat`
- `TdxhMultiPlatformDynamicVisionChat`

Features:
- supports provider priority ordering with `provider_1`, `provider_2`, and `provider_3`
- `provider_3` defaults to `disabled` so the node structure can stay stable for future expansion
- current providers: `deepseek`, `kimi`, `LocalQwen3VL-8B-Instruct-Q4_K_M`, `LocalQwen3VL-8B-Thinking-Q8_0`
- in `TdxhMultiPlatformChat`, the two `LocalQwen3VL` entries are exposed for consistent provider lists but return a clear vision-only unsupported status
- reserved for future extension by adding more providers
- automatically falls back to the next provider when the previous one returns a non-OK status
- outputs:
  - `answer`
  - `reasoning`
  - `status`
  - `used_provider`
  - `attempt_log`

Vision notes:
- `TdxhMultiPlatformDynamicVisionChat` supports dynamic image inputs with an `Update inputs` button
- `TdxhMultiPlatformDynamicVisionChat` supports `kimi`, `LocalQwen3VL-8B-Instruct-Q4_K_M`, and `LocalQwen3VL-8B-Thinking-Q8_0` in the same fallback chain, and also accepts one fixed optional `video` input
- if all connected images are placeholders such as `LoadImage(example.png)`, the node treats them as empty and falls back to text chat
- `deepseek` is kept as a reserved provider slot but returns an explicit unsupported error until DeepSeek publishes official public vision API documentation

# Thanks
Some codes are from The official [ComfyUI](https://github.com/comfyanonymous/ComfyUI.git) and other custom nodes like The [was-node-suite-comfyui](https://github.com/WASasquatch/was-node-suite-comfyui.git).
The translator's main code is from [prompt_translator](https://github.com/ParisNeo/prompt_translator.git).