video tutorial · text tutorial · workflow tutorial · Baidu cloud · QQ group · discord · About us

C‌‌​‎​‎‏​‍‎​‎​‎‏​‌‎​‎‍​‍‏​‍‌​‌‏omfyui_llm_party aims to develop a complete set of nodes for LLM workflow construction based on comfyui as the front end. It allows users to quickly and conveniently build their own LLM workflows and easily integrate them into their existing image workflows.

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Project Overview

ComfyUI LLM Party, from the most basic LLM multi-tool call, role setting to quickly build your own exclusive AI assistant, to the industry-specific word vector RAG and GraphRAG to localize the management of the industry knowledge base; from a single agent pipeline, to the construction of complex agent-agent radial interaction mode and ring interaction mode; from the access to their own social APP (QQ, Feishu, Discord) required by individual users, to the one-stop LLM + TTS + ComfyUI workflow required by streaming media workers; from the simple start of the first LLM application required by ordinary students, to the various parameter debugging interfaces commonly used by scientific researchers, model adaptation. All of this, you can find the answer in ComfyUI LLM Party.

Latest update

1. A new GPT-sovits node has been added, allowing you to call the GPT-sovits model to convert text into speech based on your reference audio. You can also fill in the path of your fine-tuned model (if not filled, the base model will be used for inference) to get any desired voice. To use it, you need to download the GPT-sovits project and the corresponding base model locally, then start the API service with runtime\python.exe api_v2.py in the GPT-sovits project folder. Additionally, the chatTTS node has been moved to comfyui LLM mafia. The reason is that chatTTS has many dependencies, and its license on PyPi is CC BY-NC 4.0, which is a non-commercial license. Even though the chatTTS GitHub project is under the AGPL license, we moved the chatTTS node to comfyui LLM mafia to avoid unnecessary trouble. We hope everyone understands!
2. Now supports OpenAI’s latest model, the o1 series!
3. Added a local file control tool that allows the LLM to control files in your specified folder, such as reading, writing, appending, deleting, renaming, moving, and copying files.Due to the potential danger of this node, it is included in comfyui LLM mafia.
4. New SQL tools allow LLM to query SQL databases.
5. Updated the multilingual version of the README. Workflow for translating the README document: translate_readme
6. Updated 4 iterator nodes (text iterator, picture iterator, excel iterator, json iterator). The iterator modes are: sequential, random, and infinite. The order will be output in sequence until the index limit is exceeded, the process will be automatically aborted, and the index value will be reset to 0. Random will choose a random index output, and infinite will loop output.
7. Added Gemini API loader node, now compatible with Gemini official API!Since Gemini generates an error with a return code of 500 if the returned parameter contains Chinese characters during the tool call, some tool nodes are unavailable.example workflow:start_with_gemini
8. Added lore book node, you can insert your background settings when talking to LLM, example workflow: lorebook
9. Added FLUX prompt word generator mask node, which can generate Hearthstone cards, Game King cards, posters, comics and other styles of prompt words, which can make the FLUX model straight out. Reference workflow: FLUX prompt word

User Guide

1. For the instructions for using the node, please refer to: how to use nodes

2. If there are any issues with the plugin or you have other questions, feel free to join the QQ group: 931057213.

3. Please refer to the workflow tutorial: Workflow Tutorial, thanks to HuangYuChuh for your contribution!

4. Advanced workflow gameplay account:openart

5. More workflows please refer to the workflow folder.

Vedio tutorial

1. Building a Modular AI with ComfyUI×LLM: A Step-by-Step Tutorial (Super Easy!)

2. Teach you GPT-4o access to comfyui | Make workflow call another workflow | Make LLM a tool

3. Disguise your workflow as GPT to access WeChat | Omost compatible! Flexibly create your own dalle3

4. How to play interactive fiction games in comfyui

5. AI girlfriend, and is your shape | comfyui on the implementation of graphRAG, linkage neoa4j | comfyui workflow access streamlit front-end

Model support

1. Support all API calls in openai format(Combined with oneapi can call almost all LLM APIs, also supports all transit APIs), base_url selection reference config.ini.example, which has been tested so far:

• ollama(Recommended! If you are calling locally, it is highly recommended to use ollama to host your local model!)
• Tongyi Qianwen /qwen
• zhipu qingyan/glm
• deepseek
• kimi/moonshot
• doubao

2. API calls that support Gemini format:

• Gemini

3. Most of the local models supported by the transformer library AutoModelForCausalLM class have been tested so far(If the model type on the local model node does not know what to choose, choose llama, which can be adapted with high probability):

• ClosedCharacter/Peach-9B-8k-Roleplay(Recommended! Role-playing model)
• omost-llama-3-8b-4bits(Recommended! Rich prompt model)
• meta-llama/llama-2-7b-chat-hf
• Qwen/Qwen2-7B-Instruct
• xtuner/llava-llama-3-8b-v1_1-gguf
• THUDM/chatglm3-6b(Due to the new calling format of GLM4, developers cannot maintain all local large model calls, because it is recommended that everyone use ollama to call locally!)

4. Model download

• Baidu cloud address, extraction code: qyhu

Download

• You can configure the language in config.ini, currently only Chinese (zh_CN) and English (en_US), the default is your system language.
• Install using one of the following methods:

Method 1:

1. Search for comfyui_LLM_party in the comfyui manager and install it with one click.
2. Restart comfyui.

Method 2:

1. Navigate to the custom_nodes subfolder under the ComfyUI root folder.
2. Clone this repository with git clone https://github.com/heshengtao/comfyui_LLM_party.git.

Method 3:

1. Click CODE in the upper right corner.
2. Click download zip.
3. Unzip the downloaded package into the custom_nodes subfolder under the ComfyUI root folder.

Environment Deployment

1. Navigate to the comfyui_LLM_party project folder.
2. Enter pip install -r requirements.txt in the terminal to deploy the third-party libraries required by the project into the comfyui environment. Please ensure you are installing within the comfyui environment and pay attention to any pip errors in the terminal.
3. If you are using the comfyui launcher, you need to enter path_in_launcher_configuration\python_embeded\python.exe -m pip install -r requirements.txt in the terminal to install. The python_embeded folder is usually at the same level as your ComfyUI folder.
4. If you have some environment configuration problems, you can try to use the dependencies in requirements_fixed.txt.

Configuration

APIKEY can be configured using one of the following methods

Method 1:

1. Open the config.ini file in the project folder of the comfyui_LLM_party.
2. Enter your openai_api_key, base_url in config.ini.
3. If you are using an ollama model, fill in http://127.0.0.1:11434/v1/ in base_url, ollama in openai_api_key, and your model name in model_name, for example: llama3.
4. If you want to use Google search or Bing search tools, enter your google_api_key, cse_id or bing_api_key in config.ini.
5. If you want to use image input LLM, it is recommended to use image bed imgbb and enter your imgbb_api in config.ini.
6. Each model can be configured separately in the config.ini file, which can be filled in by referring to the config.ini.example file. After you configure it, just enter model_name on the node.

Method 2:

1. Open the comfyui interface.
2. Create a Large Language Model (LLM) node and enter your openai_api_key and base_url directly in the node.
3. If you use the ollama model, use LLM_api node, fill in http://127.0.0.1:11434/v1/ in base_url node, fill in ollama in api_key, and fill in your model name in model_name, for example: llama3.
4. If you want to use image input LLM, it is recommended to use graph bed imgbb and enter your imgbb_api_key on the node.

Changelog

1. You can right-click in the comfyui interface, select llm from the context menu, and you will find the nodes for this project. how to use nodes
2. Supports API integration or local large model integration. Modular implementation for tool invocation.When entering the base_url, please use a URL that ends with /v1/.You can use ollama to manage your model. Then, enter http://127.0.0.1:11434/v1/ for the base_url, ollama for the api_key, and your model name for the model_name, such as: llama3.

• API access sample workflow: start_with_LLM_api
• Local model access sample workflow: start_with_LLM_local
• ollama access sample workflow: ollama

3. Local knowledge base integration with RAG support.sample workflow: Knowledge Base RAG Search
4. Ability to invoke code interpreters.
5. Enables online queries, including Google search support.sample workflow: movie query workflow
6. Implement conditional statements within ComfyUI to categorize user queries and provide targeted responses.sample workflow: intelligent customer service
7. Supports looping links for large models, allowing two large models to engage in debates.sample workflow: Tram Challenge Debate
8. Attach any persona mask, customize prompt templates.
9. Supports various tool invocations, including weather lookup, time lookup, knowledge base, code execution, web search, and single-page search.
10. Use LLM as a tool node.sample workflow: LLM Matryoshka dolls
11. Rapidly develop your own web applications using API + Streamlit.
12. Added a dangerous omnipotent interpreter node that allows the large model to perform any task.
13. It is recommended to use the show_text node under the function submenu of the right-click menu as the display output for the LLM node.
14. Supported the visual features of GPT-4O!sample workflow:GPT-4o
15. A new workflow intermediary has been added, which allows your workflow to call other workflows!sample workflow:Invoke another workflow
16. Adapted to all models with an interface similar to OpenAI, such as: Tongyi Qianwen/QWEN, Zhigu Qingyan/GLM, DeepSeek, Kimi/Moonshot. Please fill in the base_url, api_key, and model_name of these models into the LLM node to call them.
17. Added an LVM loader, now you can call the LVM model locally, support lava-llama-3-8b-v1_1-gguf model, other LVM models should theoretically run if they are GGUF format.The example workflow can be found here: start_with_LVM.json.
18. I wrote a fastapi.py file, and if you run it directly, you’ll get an OpenAI interface on http://127.0.0.1:8817/v1/. Any application that can call GPT can now invoke your comfyui workflow! I will create a tutorial to demonstrate the details on how to do this.
19. I’ve separated the LLM loader and the LLM chain, dividing the model loading and model configuration. This allows for sharing models across different LLM nodes!
20. macOS and mps devices are now supported! Thanks to bigcat88 for their contribution!
21. You can build your own interactive novel game, and go to different endings according to the user's choice! Example workflow reference: interactive_novel
22. Adapted to OpenAI's whisper and tts functions, voice input and output can be realized. Example workflow reference: voice_input&voice_output
23. Compatible with Omost!!! Please download omost-llama-3-8b-4bits to experience it now! Sample workflow reference: start_with_OMOST
24. Added LLM tools to send messages to WeCom, DingTalk, and Feishu, as well as external functions to call.
25. Added a new text iterator, which can output only part of the characters at a time. It is safe to split the text according to Carriage Return and chunk size, and will not be divided from the middle of the text. chunk_overlap refers to how many characters the divided text overlaps. In this way, you can enter super long text in batches, as long as you don't have a brain to click, or open the loop in comfyui to execute, it can be automatically executed. Remember to turn on the is_locked property, which can automatically lock the workflow at the end of the input and will not continue to execute. Example workflow: text iteration input
26. Added the model name attribute to the local LLM loader, local llava loader. If it is empty, it will be loaded using various local paths in the node. If it is not empty, it will be loaded using the path parameters you fill in yourself in config.ini. If it is not empty and not in config.ini, it will be downloaded from huggingface or loaded from the model save directory of huggingface. If you want to download from huggingface, please fill in the format of for example: THUDM/glm-4-9b-chat.Attention! Models loaded in this way must be adapted to the transformer library.
27. Added JSON file parsing node and JSON value node, which allows you to get the value of a key from a file or text. Thanks to guobalove for your contribution!
28. Improved the code of tool call. Now LLM without tool call function can also open is_tools_in_sys_prompt attribute (local LLM does not need to be opened by default, automatic adaptation). After opening, the tool information will be added to the system prompt word, so that LLM can call the tool.Related papers on implementation principles: Achieving Tool Calling Functionality in LLMs Using Only Prompt Engineering Without Fine-Tuning
29. A new custom_tool folder is created to store the code of the custom tool. You can refer to the code in the custom_tool folder, put the code of the custom tool into the custom_tool folder, and you can call the custom tool in LLM.
30. Added Knowledge Graph tool, so that LLM and Knowledge Graph can interact perfectly. LLM can modify Knowledge Graph according to your input, and can reason on Knowledge Graph to get the answers you need. Example workflow reference: graphRAG_neo4j
31. Added personality AI function, 0 code to develop your own girlfriend AI or boyfriend AI, unlimited dialogue, permanent memory, stable personality. Example workflow reference: Mylover Personality AI
32. You can use this LLM tool maker to automatically generate LLM tools, save the tool code you generated as a python file, and then copy the code to the custom_tool folder, and then you create a new node. Example workflow: LLM tool generator.
33. It supports duckduckgo search, but it has significant limitations. It seems that only English keywords can be entered, and multiple concepts cannot appear in keywords. The advantage is that there are no APIkey restrictions.
34. It supports the function of calling multiple knowledge bases separately, and it is possible to specify which knowledge base is used to answer questions in the prompt word. Example workflow: multiple knowledge bases are called separately.
35. Support LLM input extra parameters, including advanced parameters such as json out. Example workflow: LLM input extra parameters.Separate prompt words with json_out.
36. Added the function of connecting the agent to discord. (still testing)
37. Added the function of connecting the agent to Feishu, thank you very much guobalove for your contribution! Refer to the workflow Feishu robot.
38. Added universal API call node and a large number of auxiliary nodes for constructing the request body and grabbing the information in the response.
39. Added empty model node, you can uninstall LLM from video memory at any location!
40. The chatTTS node has been added, thank you very much for the contribution of guobalove! model_path parameter can be empty! It is recommended to use HF mode to load the model, the model will be automatically downloaded from hugging face, no need to download manually; if using local loading, please put the model'sasset and config folders in the root directory. Baidu cloud address, extraction code: qyhu; if using custom mode to load, please put the model's asset and config folders under model_path.

Next Steps Plan:

1. More model adaptations, at least covering the API interfaces of mainstream large models and local calls of mainstream open-source models, as well as more LVM model adaptations. Currently, I have only adapted the visual function calls of GPT-4;
2. More ways to build agents. The work I have completed in this area includes importing an LLM as a tool to another LLM, achieving radial construction of LLM workflows, and importing one workflow as a node into another workflow. I might develop some cooler functions in this area in the future.
3. More automation features. In the future, I will introduce more nodes that automatically push images, text, videos, and audio to other applications, as well as listening nodes that implement automatic replies to mainstream social software and forums.
4. More knowledge base management functions. The project already supports local file search and web search. In the future, I will introduce knowledge graph search and long-term memory search. This will allow agents to think logically about professional knowledge and always remember certain key information when conversing with users.
5. More tools, more persona. This part is the easiest to do but also requires the most accumulation. I hope that in the future, this project can have as many custom nodes as comfyui, with a multitude of tools and persona.

Disclaimer:

This open-source project and its contents (hereinafter referred to as "Project") are provided for reference purposes only and do not imply any form of warranty, either expressed or implied. The contributors of the Project shall not be held responsible for the completeness, accuracy, reliability, or suitability of the Project. Any reliance you place on the Project is strictly at your own risk. In no event shall the contributors of the Project be liable for any indirect, special, or consequential damages or any damages whatsoever resulting from the use of the Project.

Special thanks:

loan list

Some of the nodes in this project have borrowed from the following projects. Thank you for your contributions to the open-source community!

1. pythongosssss/ComfyUI-Custom-Scripts
2. lllyasviel/Omost

Support:

Join the community

If there is a problem with the plugin or you have any other questions, please join our community.

1. discord:discord link
2. QQ group: 931057213

3. WeChat group: Choo-Yong (enter the group after adding the small assistant WeChat)

Follow us

1. If you want to continue to pay attention to the latest features of this project, please follow the Bilibili account: Party host BB machine
2. The OpenArt account is continuously updated with the most useful party workflows:openart

Donation support

If my work has brought value to your day, consider fueling it with a coffee! Your support not only energizes the project but also warms the heart of the creator. ☕💖 Every cup makes a difference!

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