AI Skill Hub 强烈推荐:ComfyUI 节点式AI图像生成 是一款优质的AI工具。已获得 2.2k 颗 GitHub Star,AI 综合评分 8.2 分,在同类工具中表现稳健。如果你正在寻找可靠的AI工具解决方案,这是一个值得深入了解的选择。
在ComfyUI中集成MCP协议、Omost视觉框架、GPT-Sovits语音合成、ChatTTS文本转语音、GOT动画生成等多模态AI能力。为创意工作者和开发者提供一体化的AI智能体工作流框架,支持复杂任务自动化和多模态内容生成。
ComfyUI 节点式AI图像生成 是一款基于 Python 开发的开源工具,专注于 MCP协议、多模态AI、工作流自动化 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
在ComfyUI中集成MCP协议、Omost视觉框架、GPT-Sovits语音合成、ChatTTS文本转语音、GOT动画生成等多模态AI能力。为创意工作者和开发者提供一体化的AI智能体工作流框架,支持复杂任务自动化和多模态内容生成。
ComfyUI 节点式AI图像生成 是一款基于 Python 开发的开源工具,专注于 MCP协议、多模态AI、工作流自动化 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:pip 安装(推荐)
pip install comfyui_llm_party
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install comfyui_llm_party
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/heshengtao/comfyui_LLM_party
cd comfyui_LLM_party
pip install -e .
# 验证安装
python -c "import comfyui_llm_party; print('安装成功')"
# 命令行使用
comfyui_llm_party --help
# 基本用法
comfyui_llm_party input_file -o output_file
# Python 代码中调用
import comfyui_llm_party
# 示例
result = comfyui_llm_party.process("input")
print(result)
# comfyui_llm_party 配置文件示例(config.yml) app: name: "comfyui_llm_party" debug: false log_level: "INFO" # 运行时指定配置文件 comfyui_llm_party --config config.yml # 或通过环境变量配置 export COMFYUI_LLM_PARTY_API_KEY="your-key" export COMFYUI_LLM_PARTY_OUTPUT_DIR="./output"
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.
comfyui_LLM_party project folder.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.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.requirements_fixed.txt.0. If you have never used ComfyUI and encounter some dependency issues while installing the LLM party in ComfyUI, please click here to download the Windows portable package that includes the LLM party. Please note that this portable package contains only the party and manager plugins, and is exclusively compatible with the Windows operating system.(If you need to install LLM party into an existing comfyui, this step can be skipped.)
1. Drag the following workflows into your comfyui, then use comfyui-Manager to install the missing nodes.
- Use API to call LLM: start_with_LLM_api
- Using aisuite to call LLM: start_with_aisuite
- Manage local LLM with ollama: start_with_Ollama
- Use local LLM in distributed format: start_with_LLM_local
- Use local LLM in GGUF format: start_with_LLM_GGUF
- Use local VLM in distributed format: start_with_VLM_local (Currently, support is extended for Llama-3.2-Vision/Qwen/Qwen2.5-VL/deepseek-ai/Janus-Pro.)
- Use local VLM in GGUF format: start_with_VLM_GGUF
- Utilize API calls to LLM for generating SD prompts and images: start_with_VLM_API_for_SD
- Employ ollama to call minicpm for generating SD prompts and images: start_with_ollama_minicpm_for_SD
- Utilize the local qwen-vl to generate SD prompts and images: start_with_qwen_vl_local_for_SD
2. If you are using API, fill in your base_url (it can be a relay API, make sure it ends with /v1/), for example: https://api.openai.com/v1/ and api_key in the API LLM loader node.
3. If you are using ollama, turn on the is_ollama option in the API LLM loader node, no need to fill in base_url and api_key.
4. If you are using a local model, fill in your model path in the local model loader node, for example: E:\model\Llama-3.2-1B-Instruct. You can also fill in the Huggingface model repo id in the local model loader node, for example: lllyasviel/omost-llama-3-8b-4bits.
5. Due to the high usage threshold of this project, even if you choose the quick start, I hope you can patiently read through the project homepage.
<a href="https://space.bilibili.com/26978344"> <img src="img/B.png" width="100" height="100" style="border-radius: 80%; overflow: hidden;" alt="octocat"/> </a> <a href="https://www.youtube.com/@comfyui-LLM-party"> <img src="img/YT.png" width="100" height="100" style="border-radius: 80%; overflow: hidden;" alt="octocat"/> </a>
config.ini, currently only Chinese (zh_CN) and English (en_US) are available, with the default set to your system language.config.ini, you can configure whether to enable fast installation. The fast_installed option defaults to False, and if you do not require the usage of the GGUF model, it can be set to True.架构完整的多模态AI工具集,融合MCP标准与ComfyUI生态,创新性强且维护活跃。适合AI开发者和创意工作者深度定制。
该工具使用 AGPL-3.0 协议,商用场景请仔细阅读协议条款,必要时咨询法律意见。
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建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
⚠️ AGPL 3.0 — 最严格的 Copyleft,网络服务端使用也需开源,SaaS 使用受限。
总体来看,ComfyUI 节点式AI图像生成 是一款质量优秀的AI工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | comfyui_LLM_party |
| 原始描述 | 开源MCP工具:LLM Agent Framework in ComfyUI includes MCP sever, Omost,GPT-sovits, ChatTTS,GOT。⭐2.2k · Python |
| Topics | MCP协议多模态AI工作流自动化语音合成视觉生成 |
| GitHub | https://github.com/heshengtao/comfyui_LLM_party |
| License | AGPL-3.0 |
| 语言 | Python |
收录时间:2026-05-13 · 更新时间:2026-05-16 · License:AGPL-3.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。