├── requirements.txt ├── config.json ├── .github └── FUNDING.yml ├── __init__.py ├── js └── GeminiAPINode.js ├── Gemini_workflows ├── Gemini-pro Chatbot【Zho】.json ├── Gemini 1.5 Pro + Stable Diffusion + ComfyUI = DALL·3 【Zho】.json ├── Gemini-pro【Zho】.json ├── Gemini-pro-vision【Zho】.json └── All-in-One LoRa Training【Zho】.json ├── README.md ├── GeminiAPINode.py └── LICENSE /requirements.txt: -------------------------------------------------------------------------------- 1 | google-generativeai>0.4.1 2 | -------------------------------------------------------------------------------- /config.json: -------------------------------------------------------------------------------- 1 | { 2 | "GEMINI_API_KEY": "your key" 3 | } 4 | -------------------------------------------------------------------------------- /.github/FUNDING.yml: -------------------------------------------------------------------------------- 1 | # These are supported funding model platforms 2 | 3 | github: # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2] 4 | patreon: # Replace with a single Patreon username 5 | open_collective: # Replace with a single Open Collective username 6 | ko_fi: # Replace with a single Ko-fi username 7 | tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel 8 | community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry 9 | liberapay: # Replace with a single Liberapay username 10 | issuehunt: # Replace with a single IssueHunt username 11 | otechie: # Replace with a single Otechie username 12 | lfx_crowdfunding: # Replace with a single LFX Crowdfunding project-name e.g., cloud-foundry 13 | custom: https://afdian.net/a/ZHOZHO # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2'] 14 | -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- 1 | import os 2 | import sys 3 | import filecmp 4 | import shutil 5 | import __main__ 6 | import json 7 | 8 | python = sys.executable 9 | 10 | 11 | extentions_folder = os.path.join(os.path.dirname(os.path.realpath(__main__.__file__)), 12 | "web" + os.sep + "extensions" + os.sep + "Gemini_Zho") 13 | javascript_folder = os.path.join(os.path.dirname(os.path.realpath(__file__)), "js") 14 | 15 | if not os.path.exists(extentions_folder): 16 | print('Making the "web\extensions\Gemini_Zho" folder') 17 | os.mkdir(extentions_folder) 18 | 19 | result = filecmp.dircmp(javascript_folder, extentions_folder) 20 | 21 | if result.left_only or result.diff_files: 22 | print('Update to javascripts files detected') 23 | file_list = list(result.left_only) 24 | file_list.extend(x for x in result.diff_files if x not in file_list) 25 | 26 | for file in file_list: 27 | print(f'Copying {file} to extensions folder') 28 | src_file = os.path.join(javascript_folder, file) 29 | dst_file = os.path.join(extentions_folder, file) 30 | if os.path.exists(dst_file): 31 | os.remove(dst_file) 32 | #print("disabled") 33 | shutil.copy(src_file, dst_file) 34 | 35 | 36 | # create config 37 | if not os.path.isfile(os.path.join(os.path.dirname(os.path.realpath(__file__)),"config.json")): 38 | config = { 39 | "GEMINI_API_KEY": "your key" 40 | } 41 | with open(os.path.join(os.path.dirname(os.path.realpath(__file__)),"config.json"), "w") as f: 42 | json.dump(config, f, indent=4) 43 | 44 | #load config 45 | with open(os.path.join(os.path.dirname(os.path.realpath(__file__)),"config.json"), "r") as f: 46 | config = json.load(f) 47 | 48 | 49 | from .GeminiAPINode import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS 50 | 51 | # Combine the dictionaries 52 | #NODE_CLASS_MAPPINGS = {**NODE_CLASS_MAPPINGS_G} 53 | 54 | __all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS'] 55 | -------------------------------------------------------------------------------- /js/GeminiAPINode.js: -------------------------------------------------------------------------------- 1 | 2 | import { app } from "/scripts/app.js"; 3 | import { ComfyWidgets } from "/scripts/widgets.js"; 4 | 5 | app.registerExtension({ 6 | name: "Comfy.GeminiAPINode", 7 | async beforeRegisterNodeDef(nodeType, nodeData, app) { 8 | // --- DisplayText_Zho Node 9 | if (nodeData.name === "DisplayText_Zho") { 10 | // Node Created 11 | const onNodeCreated = nodeType.prototype.onNodeCreated; 12 | nodeType.prototype.onNodeCreated = function () { 13 | const ret = onNodeCreated 14 | ? onNodeCreated.apply(this, arguments) 15 | : undefined; 16 | 17 | let DisplayText_Zho = app.graph._nodes.filter( 18 | (wi) => wi.type == nodeData.name 19 | ), 20 | nodeName = `${nodeData.name}_${DisplayText_Zho.length}`; 21 | 22 | console.log(`Create ${nodeData.name}: ${nodeName}`); 23 | 24 | const wi = ComfyWidgets.STRING( 25 | this, 26 | nodeName, 27 | [ 28 | "STRING", 29 | { 30 | default: "", 31 | placeholder: "Text output...", 32 | multiline: true, 33 | }, 34 | ], 35 | app 36 | ); 37 | wi.widget.inputEl.readOnly = true; 38 | return ret; 39 | }; 40 | // Function set value 41 | const outSet = function (texts) { 42 | if (texts.length > 0) { 43 | let widget_id = this?.widgets.findIndex( 44 | (w) => w.type == "customtext" 45 | ); 46 | 47 | if (Array.isArray(texts)) 48 | texts = texts 49 | .filter((word) => word.trim() !== "") 50 | .map((word) => word.trim()) 51 | .join(" "); 52 | 53 | this.widgets[widget_id].value = texts; 54 | app.graph.setDirtyCanvas(true); 55 | } 56 | }; 57 | 58 | // onExecuted 59 | const onExecuted = nodeType.prototype.onExecuted; 60 | nodeType.prototype.onExecuted = function (texts) { 61 | onExecuted?.apply(this, arguments); 62 | outSet.call(this, texts?.string); 63 | }; 64 | // onConfigure 65 | const onConfigure = nodeType.prototype.onConfigure; 66 | nodeType.prototype.onConfigure = function (w) { 67 | onConfigure?.apply(this, arguments); 68 | if (w?.widgets_values?.length) { 69 | outSet.call(this, w.widgets_values); 70 | } 71 | }; 72 | } 73 | // --- DisplayText_Zho Node 74 | }, 75 | }); 76 | -------------------------------------------------------------------------------- /Gemini_workflows/Gemini-pro Chatbot【Zho】.json: -------------------------------------------------------------------------------- 1 | { 2 | "last_node_id": 2, 3 | "last_link_id": 1, 4 | "nodes": [ 5 | { 6 | "id": 1, 7 | "type": "Gemini_API_S_Chat_Zho", 8 | "pos": [ 9 | 420, 10 | 370 11 | ], 12 | "size": [ 13 | 260, 14 | 140 15 | ], 16 | "flags": {}, 17 | "order": 0, 18 | "mode": 0, 19 | "outputs": [ 20 | { 21 | "name": "response", 22 | "type": "STRING", 23 | "links": [ 24 | 1 25 | ], 26 | "shape": 3, 27 | "slot_index": 0 28 | } 29 | ], 30 | "properties": { 31 | "Node name for S&R": "Gemini_API_S_Chat_Zho" 32 | }, 33 | "widgets_values": [ 34 | "展开说一下AIGC在文本、图像领域的发展", 35 | "gemini-pro" 36 | ] 37 | }, 38 | { 39 | "id": 2, 40 | "type": "DisplayText_Zho", 41 | "pos": [ 42 | 690, 43 | 370 44 | ], 45 | "size": [ 46 | 720, 47 | 1070 48 | ], 49 | "flags": {}, 50 | "order": 1, 51 | "mode": 0, 52 | "inputs": [ 53 | { 54 | "name": "text", 55 | "type": "STRING", 56 | "link": 1, 57 | "widget": { 58 | "name": "text" 59 | } 60 | } 61 | ], 62 | "outputs": [ 63 | { 64 | "name": "text", 65 | "type": "STRING", 66 | "links": null, 67 | "shape": 3 68 | } 69 | ], 70 | "properties": { 71 | "Node name for S&R": "DisplayText_Zho" 72 | }, 73 | "widgets_values": [ 74 | "", 75 | "user: 解释一下AIGC\n----------------------------------------\nmodel: AIGC，全称“人工智能生成内容”（Artificial Intelligence Generated Content），是指计算机利用人工智能技术自动生成内容。这些内容可以是文本、图像、代码、音乐、视频等形式，也可以是代码的自动生成。AIGC包括自然语言生成（NLG）、机器翻译（MT）、图像生成、音乐生成、代码生成等多种技术。\n\nAIGC近年来发展迅速，并逐步实现商业化落地。AIGC技术可用于提升广告、内容和服务的个性化推荐，增强生产力和效率，促进科技创新，具有广阔的应用前景。\n\nAIGC技术目前存在的主要挑战包括：\n\n- **数据挑战：** AIGC模型需要大量高质量数据进行训练，但是获取和标记这些数据通常非常耗时且昂贵。\n- **模型挑战：** AIGC模型通常非常复杂，需要强大的计算资源和专业知识才能构建和部署。\n- **应用挑战：** AIGC技术需要与现有系统和流程集成，才能真正发挥作用。\n\n尽管面临这些挑战，AIGC技术仍然具有很大的发展潜力。随着数据、模型和应用技术的不断进步，AIGC技术将逐渐被广泛采用，并对各种行业产生重大影响。\n\nAIGC技术的主要优势包括：\n\n- **效率高：** AIGC技术可以自动生成内容，从而提高效率。\n- **成本低：** AIGC技术可以降低内容生产成本。\n- **创造性：** AIGC技术可以生成出人类无法创造的内容。\n- **定制化：** AIGC技术可以根据用户需求生成定制化内容。\n- **可扩展性：** AIGC技术可以扩展到大量数据和任务。\n----------------------------------------\nuser: 展开说一下AIGC在文本、图像领域的发展\n----------------------------------------\nmodel: **文本领域**\n\n在文本领域，AIGC技术主要包括自然语言生成（NLG）和机器翻译（MT）。\n\n- **自然语言生成（NLG）：** NLG技术可以将结构化数据或代码转换成自然语言文本。例如，NLG技术可以将天气数据转换成天气预报文本，将财务数据转换成财务报告文本，将代码转换成注释清晰的代码文档。\n- **机器翻译（MT）：** MT技术可以将一种语言的文本翻译成另一种语言的文本。MT技术在新闻、旅游、电子商务等领域都有广泛的应用。\n\n近年来，随着深度学习技术的进步，NLG和MT技术取得了显著的进展。NLG模型在文本生成任务上的表现已经接近甚至超过了人类。MT模型的翻译质量也大幅提高，在许多场景下已经可以替代人工翻译。\n\n**图像领域**\n\n在图像领域，AIGC技术主要包括图像生成和图像编辑。\n\n- **图像生成：** 图像生成技术可以根据文本描述、草图或其他信息自动生成图像。例如，用户可以输入“一只坐在草地上的猫”这样的文本描述，图像生成模型就可以生成一张符合描述的猫的图像。\n- **图像编辑：** 图像编辑技术可以对现有图像进行编辑、增强或风格转换。例如，用户可以将一张黑白照片转换成彩色照片，或者将一张照片转换成油画风格的照片。\n\n近年来，随着GAN（生成对抗网络）技术和扩散模型技术的进步，图像生成和图像编辑技术取得了突破性的进展。图像生成模型可以生成逼真度极高的图像，图像编辑模型也可以实现各种复杂的效果。\n\n## AIGC在文本和图像领域的应用\n\nAIGC技术在文本和图像领域有广泛的应用，包括：\n\n- **新闻写作：** AIGC技术可以自动生成新闻报道、体育报道、财经报道等。\n- **文学创作：** AIGC技术可以自动生成小说、诗歌、剧本等。\n- **广告文案创作：** AIGC技术可以自动生成广告文案、产品介绍文案等。\n- **客服服务：** AIGC技术可以自动生成客服回复、常见问题解答等。\n- **图像创作：** AIGC技术可以自动生成插图、海报、广告图片等。\n- **图像编辑：** AIGC技术可以自动编辑图片、修复图片、风格转换等。\n\n## AIGC在文本和图像领域的未来发展\n\nAIGC技术在文本和图像领域仍处于早期发展阶段，但其发展潜力巨大。随着数据、模型和应用技术的不断进步，AIGC技术将逐渐被广泛采用，并对各种行业产生重大影响。\n\n在未来，AIGC技术可能会在以下方面取得进一步的发展：\n\n- **更逼真、更具创造性的内容生成：** AIGC模型将能够生成更加逼真、更加具创造性的文本和图像内容。\n- **更广泛的应用场景：** AIGC技术将被应用到更多场景中，例如医疗、教育、娱乐等。\n- **更无缝的与人类合作：** AIGC技术将与人类合作，共同创造出更加优质的内容。\n\nAIGC技术有望成为未来内容生产和消费的新范式，并对人类社会产生深远的影响。\n----------------------------------------" 76 | ] 77 | } 78 | ], 79 | "links": [ 80 | [ 81 | 1, 82 | 1, 83 | 0, 84 | 2, 85 | 0, 86 | "STRING" 87 | ] 88 | ], 89 | "groups": [], 90 | "config": {}, 91 | "extra": {}, 92 | "version": 0.4 93 | } -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 |

Gemini项目图

2 | 3 | 6 | 7 |

Gemini in ComfyUI

8 | 11 | 12 | 🆕 最新 Gemini 1.5 Pro 模型已加入！ 13 | 14 | ![G1 5发](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/8c3105c7-e165-4b6b-8a46-6ed09ecfb388) 15 | 16 | - 支持系统指令设置（System Instruction） 17 | - 支持多模态 + 多轮对话 18 | - 可以读取视频、音频等文件（上限 20G） 19 | - 支持输入的 token 上限达到了 104万8576 20 | - 目前速率限制比较严，每分钟只有 2 次，每天只有 1000 次 21 | 22 | 25 | 26 | ![Dingtalk_20240411194828](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/c1f71846-db5e-4bb1-a1b7-0b278ee95ea8) 27 | 28 | 29 | 已支持文件上传功能，不过还仅限于单个文件（图片、txt文件、pdf文件、音频mp3文件等），未来会支持多文件上传（用于读取视频） 30 | 31 | 34 | 35 | All-in-One LoRa Training 预处理、自动打标、训练、测试 LoRA 一条龙工作流 36 | 37 | https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/d461f656-6888-48a8-b4f8-b70b7e46504d 38 | 39 | 40 | V2.0 聊天机器人节点 41 | 42 | https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/cb64ee29-a983-47fd-b26b-55386314afdd 43 | 44 | 45 | 将 Gemini pro vision 用于批量打标 46 | 47 | 48 | https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/00addc94-1587-40d6-83f4-6b47dc1db665 49 | 50 | 51 | 52 | ## 项目介绍 | Info 53 | 54 | - 将 Google Gemini 引入到 ComfyUI 中，现在你可以用它为你生成提示词、描述图像，也可与它畅聊人生 55 | 56 | - 目前 Gemini API 免费开放（20240502 开始计费），你可以在这里申请一个自己的 API Key：[Gemini API 申请](https://makersuite.google.com/app/apikey) 57 | 58 | - 最新 Gemini 1.5 Pro 模型： 59 | 60 | - 支持系统指令设置（System Instruction） 61 | - 支持多模态 + 多轮对话， 62 | - 可以读取视频、音频等文件（上限 20G） 63 | - 支持输入的 token 上限达到了 104万8576 64 | - 目前速率限制比较严，每分钟只有 2 次，每天只有 1000 次 65 | 66 | - 版本：V3.0 新增 Gemini 1.5 Pro 模型、系统指令、文件上传 67 | 68 | 69 | 70 | ## 详细说明 | Features 71 | 72 | - Gemini 目前提供 3 种模型： 73 | 74 | - Gemini-pro: 文本模型 75 | 76 | - Genimi-pro-vision: 文本 + 图像模型 77 | 78 | - Gemini 1.5 Pro：文本 + 图像 + 文件（音频、视频等各类） 模型 79 | 80 | 81 | - Gemini 1.5 Pro 新节点： 82 | 83 | - 🆕Gemini_15P_Advance_Zho：支持系统指令设置（System Instruction） 84 | 85 | - 🆕Gemini_15P_Chat_Advance_Zho：支持系统指令设置（System Instruction）+ 多轮对话 86 | 87 | - 📄Gemini_FileUpload_Zho：支持单文件上传（图片、音频、文本txt、pdf等），暂未支持视频（多文件）上传 88 | 89 | - 📄Gemini_File_Zho：文件读取对话，最大 token 数为 1048576 90 | 91 | 92 | - 2 类节点: 93 | 94 | - 隐式 API KEY：将 Gemini_API_Key 设置为了环境变量，更安全，方便分享工作流（不会外泄 API KEY） 95 | 96 | ㊙️Gemini_Zho：同时支持 3 种模型，其中 Genimi-pro-vision 和 Gemini 1.5 Pro 可接受图像作为输入 97 | 98 | ㊙️Gemini_Vsion_ImgURL_Zho：Genimi-pro-vision 和 Gemini 1.5 Pro 模型，接受图像链接作为输入 99 | 100 | ㊙️Gemini_Chat_Zho：Genimi-pro 和 Gemini 1.5 Pro 模型，支持上下文对话，聊天机器人，Gemini 1.5 Pro 支持图像输入的上下文对话 101 | 102 | - 显式API KEY：直接在节点中输入 Gemini_API_Key，仅供个人私密使用，请勿将包含 API KEY 的工作流分享出去 103 | 104 | ✨Gemini_API_Zho：同时支持 3 种模型，其中 Genimi-pro-vision 和 Gemini 1.5 Pro 可接受图像作为输入 105 | 106 | ✨Gemini_API_Vsion_ImgURL_Zho：Genimi-pro-vision 和 Gemini 1.5 Pro 模型，接受图像链接作为输入 107 | 108 | ✨Gemini_API_Chat_Zho：：Genimi-pro 和 Gemini 1.5 Pro 模型，支持上下文对话，聊天机器人，Gemini 1.5 Pro 支持图像输入的上下文对话 109 | 110 | - 辅助节点: 111 | 112 | - ✨DisplayText_Zho：显示文本 113 | 114 | - ✨ConcatText_Zho：使用 “，” 连接文本 115 | 116 | - 节点示例： 117 | 118 | 121 | 122 | ![Dingtalk_20231220180446](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/3cba8d69-09bb-470c-940c-7f796c869d63) 123 | 124 | 聊天机器人 125 | 126 | ![image](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/8a38f437-0148-4777-b872-e88995dd53d2) 127 | 128 | 129 | ## 参数说明 | Parameters 130 | 131 | - image（非必要）：选择 Gemini-pro 时无需接入图像，选择 Genimi-pro-vision 时需要接入图像，选择 Gemini 1.5 Pro 既可接入也可不接 132 | - prompt：提示词 133 | - model_name：模型选择，Gemini-pro 或 Genimi-pro-vision 或 Gemini 1.5 Pro 134 | - stream：流式传输响应 135 | - api_key：输入 Gemini_API_Key （仅在显式节点上有） 136 | 137 | ## 使用方法 | How to use 138 | 139 | - 首先需要申请一个自己的 Gemini_API_Key：[Gemini API 申请](https://makersuite.google.com/app/apikey) 140 | 141 | - 选择隐式节点㊙️（推荐）：将你的 Gemini_API_Key 添加到 `config.json` 文件中，运行时会自动加载 142 | 143 | - 选择显示节点✨：直接将 Gemini_API_Key 输入到节点的 api_key 中（注意：请勿将包含此节点的工作流分享出去，以免泄露你的 API Key） 144 | 145 | - 使用注意：本地使用请确保你可以有效连接到 Google Gemini 的服务，推荐使用 Colab 或 Kaggle（无连接问题） 146 | 147 | - 使用新版 Gemini 1.5 Pro 需要更新依赖 google-generativeai > 0.4.1 148 | 149 | ## 安装 | Install 150 | 151 | - 推荐使用管理器 ComfyUI Manager 安装 152 | 153 | - 手动安装： 154 | 1. `cd custom_nodes` 155 | 2. `git clone https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini.git` 156 | 3. `cd custom_nodes/ComfyUI-Gemini` 157 | 4. `pip install -r requirements.txt` 158 | 5. 重启 ComfyUI 159 | 160 | ## 工作流 | Workflow 161 | 162 | ### V3.0 平替 DALL·3 163 | 164 | [Gemini 1.5 Pro + Stable Diffusion + ComfyUI = DALL·3 ](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/blob/main/Gemini_workflows/Gemini%201.5%20Pro%20%2B%20Stable%20Diffusion%20%2B%20ComfyUI%20%3D%20DALL%C2%B73%20%E3%80%90Zho%E3%80%91.json) 165 | 166 | 167 | ![Dingtalk_20240411195451](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/4e32d13d-615e-4441-931e-233c07cc958c) 168 | 169 | 170 | ### V2.0 工作流（隐式）（V1.1工作流依旧可用） 171 | 172 | [Gemini-pro Chatbot【Zho】](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/blob/main/Gemini_workflows/Gemini-pro%20Chatbot%E3%80%90Zho%E3%80%91.json) 173 | 174 | ![image](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/8a38f437-0148-4777-b872-e88995dd53d2) 175 | 176 | ### V1.1 工作流（隐式） 177 | 178 | [Gemini-pro【Zho】](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/blob/main/Gemini_workflows/Gemini-pro%E3%80%90Zho%E3%80%91.json) 179 | 180 | ![Dingtalk_20231220183708](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/7f0e222a-2de4-4c5b-883a-2172667d1d5b) 181 | 182 | [Genimi-pro-vision【Zho】](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/blob/main/Gemini_workflows/Gemini-pro-vision%E3%80%90Zho%E3%80%91.json) 183 | 184 | ![Dingtalk_20231220192932](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/db4f4bf6-a0cf-42af-ac5a-7e2afd1bda93) 185 | 186 | ![Dingtalk_20231220190218](https://github.com/ZHO-ZHO-ZHO/ComfyUI-Gemini/assets/140084057/5bb57f7b-f00f-454a-9435-c1b8a02ae71a) 187 | 188 | 189 | ## 更新日志 | Changelog 190 | 191 | 20240411 192 | 193 | - V3.0版：新增 Gemini 1.5 Pro 模型、系统指令、文件上传 194 | 195 | - 新增 平替 DALL·3 工作流（Gemini 1.5 Pro + Stable Diffusion + ComfyUI = DALL·3） 196 | 197 | 20231229 198 | 199 | - V2.1版：修复 Deadline of 60.0s bug，方法来自官方：https://github.com/google/generative-ai-python/issues/117 200 | 201 | 20231222 202 | 203 | - V2.0版：新增上下文聊天节点，相当于聊天机器人 204 | - 💬Gemini_Chat_Zho（隐式） 205 | - 💬Gemini_API_Chat_Zho（显示） 206 | 207 | 20231221 208 | 209 | - V1.1版：修改 API KEY 的加载方式为自动添加 config.json ，将 API KEY 写入即可 210 | 211 | - 已登陆 manager 不用手动安装了 212 | 213 | 20231220 214 | 215 | - 实现 Genimi-pro-vision 模型调用，支持图像或图像链接输入 216 | - 增加隐式节点，更加安全 217 | - 增加辅助节点 218 | 219 | 20231219 220 | 221 | - 创建 ComfyUI Gemini 项目，实现 Gemini-pro 模型调用 222 | 223 | 224 | ## Stars 225 | 226 | [![Star History Chart](https://api.star-history.com/svg?repos=ZHO-ZHO-ZHO/ComfyUI-Gemini&type=Timeline)](https://star-history.com/#ZHO-ZHO-ZHO/ComfyUI-Gemini&Timeline) 227 | 228 | 229 | ## 关于我 | About me 230 | 231 | 📬 **联系我**： 232 | - 邮箱：zhozho3965@gmail.com 233 | - QQ 群：839821928 234 | 235 | 🔗 **社交媒体**： 236 | - 个人页：[-Zho-](https://jike.city/zho) 237 | - Bilibili：[我的B站主页](https://space.bilibili.com/484366804) 238 | - X（Twitter）：[我的Twitter](https://twitter.com/ZHOZHO672070) 239 | - 小红书：[我的小红书主页](https://www.xiaohongshu.com/user/profile/63f11530000000001001e0c8?xhsshare=CopyLink&appuid=63f11530000000001001e0c8&apptime=1690528872) 240 | 241 | 💡 **支持我**： 242 | - B站：[B站充电](https://space.bilibili.com/484366804) 243 | - 爱发电：[为我充电](https://afdian.net/a/ZHOZHO) 244 | 245 | 246 | ## Credits 247 | 248 | - DisplayText节点参考了：[ComfyUI_Custom_Nodes_AlekPet](https://github.com/AlekPet/ComfyUI_Custom_Nodes_AlekPet)，感谢 AlekPet ！ 249 | -------------------------------------------------------------------------------- /Gemini_workflows/Gemini 1.5 Pro + Stable Diffusion + ComfyUI = DALL·3 【Zho】.json: -------------------------------------------------------------------------------- 1 | { 2 | "last_node_id": 19, 3 | "last_link_id": 19, 4 | "nodes": [ 5 | { 6 | "id": 11, 7 | "type": "ModelSamplingContinuousEDM", 8 | "pos": [ 9 | 100, 10 | 280 11 | ], 12 | "size": [ 13 | 310, 14 | 110 15 | ], 16 | "flags": {}, 17 | "order": 4, 18 | "mode": 0, 19 | "inputs": [ 20 | { 21 | "name": "model", 22 | "type": "MODEL", 23 | "link": 12, 24 | "slot_index": 0 25 | } 26 | ], 27 | "outputs": [ 28 | { 29 | "name": "MODEL", 30 | "type": "MODEL", 31 | "links": [ 32 | 11 33 | ], 34 | "shape": 3, 35 | "slot_index": 0 36 | } 37 | ], 38 | "properties": { 39 | "Node name for S&R": "ModelSamplingContinuousEDM" 40 | }, 41 | "widgets_values": [ 42 | "v_prediction", 43 | 120, 44 | 0.002 45 | ] 46 | }, 47 | { 48 | "id": 5, 49 | "type": "EmptyLatentImage", 50 | "pos": [ 51 | 100, 52 | 440 53 | ], 54 | "size": [ 55 | 310, 56 | 110 57 | ], 58 | "flags": {}, 59 | "order": 0, 60 | "mode": 0, 61 | "outputs": [ 62 | { 63 | "name": "LATENT", 64 | "type": "LATENT", 65 | "links": [ 66 | 2 67 | ], 68 | "slot_index": 0 69 | } 70 | ], 71 | "properties": { 72 | "Node name for S&R": "EmptyLatentImage" 73 | }, 74 | "widgets_values": [ 75 | 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| 7, 458 | 0, 459 | 3, 460 | 2, 461 | "CONDITIONING" 462 | ], 463 | [ 464 | 7, 465 | 3, 466 | 0, 467 | 8, 468 | 0, 469 | "LATENT" 470 | ], 471 | [ 472 | 8, 473 | 4, 474 | 2, 475 | 8, 476 | 1, 477 | "VAE" 478 | ], 479 | [ 480 | 10, 481 | 8, 482 | 0, 483 | 10, 484 | 0, 485 | "IMAGE" 486 | ], 487 | [ 488 | 11, 489 | 11, 490 | 0, 491 | 3, 492 | 0, 493 | "MODEL" 494 | ], 495 | [ 496 | 12, 497 | 4, 498 | 0, 499 | 11, 500 | 0, 501 | "MODEL" 502 | ], 503 | [ 504 | 16, 505 | 13, 506 | 0, 507 | 17, 508 | 0, 509 | "STRING" 510 | ], 511 | [ 512 | 17, 513 | 17, 514 | 0, 515 | 6, 516 | 1, 517 | "STRING" 518 | ] 519 | ], 520 | "groups": [], 521 | "config": {}, 522 | "extra": {}, 523 | "version": 0.4 524 | } -------------------------------------------------------------------------------- /Gemini_workflows/Gemini-pro【Zho】.json: -------------------------------------------------------------------------------- 1 | { 2 | "last_node_id": 16, 3 | "last_link_id": 19, 4 | "nodes": [ 5 | { 6 | "id": 4, 7 | "type": "CheckpointLoaderSimple", 8 | "pos": [ 9 | 90, 10 | 190 11 | ], 12 | "size": [ 13 | 310, 14 | 100 15 | ], 16 | "flags": {}, 17 | "order": 0, 18 | "mode": 0, 19 | "outputs": [ 20 | { 21 | "name": "MODEL", 22 | "type": "MODEL", 23 | "links": [ 24 | 17 25 | ], 26 | "slot_index": 0 27 | }, 28 | { 29 | "name": "CLIP", 30 | "type": "CLIP", 31 | "links": [ 32 | 3, 33 | 5 34 | ], 35 | "slot_index": 1 36 | }, 37 | { 38 | "name": "VAE", 39 | "type": "VAE", 40 | "links": [ 41 | 8 42 | ], 43 | "slot_index": 2 44 | } 45 | ], 46 | "properties": { 47 | "Node name for S&R": "CheckpointLoaderSimple" 48 | }, 49 | "widgets_values": [ 50 | "XXMix_9realisticSDXL.safetensors" 51 | ] 52 | }, 53 | { 54 | "id": 6, 55 | "type": "CLIPTextEncode", 56 | "pos": [ 57 | 410, 58 | 310 59 | ], 60 | "size": [ 61 | 210, 62 | 50 63 | ], 64 | "flags": {}, 65 | "order": 7, 66 | "mode": 0, 67 | "inputs": [ 68 | { 69 | "name": "clip", 70 | "type": "CLIP", 71 | "link": 3 72 | }, 73 | { 74 | "name": "text", 75 | "type": "STRING", 76 | "link": 19, 77 | "widget": { 78 | "name": "text" 79 | }, 80 | "slot_index": 1 81 | } 82 | ], 83 | "outputs": [ 84 | { 85 | "name": "CONDITIONING", 86 | "type": "CONDITIONING", 87 | "links": [ 88 | 4 89 | ], 90 | "slot_index": 0 91 | } 92 | ], 93 | "properties": { 94 | "Node name for S&R": "CLIPTextEncode" 95 | }, 96 | "widgets_values": [ 97 | "beautiful scenery nature glass bottle landscape, , purple galaxy bottle," 98 | ] 99 | }, 100 | { 101 | "id": 7, 102 | "type": "CLIPTextEncode", 103 | "pos": [ 104 | 410, 105 | 400 106 | ], 107 | "size": [ 108 | 210, 109 | 90 110 | ], 111 | "flags": {}, 112 | "order": 4, 113 | "mode": 0, 114 | "inputs": [ 115 | { 116 | "name": "clip", 117 | "type": "CLIP", 118 | "link": 5 119 | } 120 | ], 121 | "outputs": [ 122 | { 123 | "name": "CONDITIONING", 124 | "type": "CONDITIONING", 125 | "links": [ 126 | 6 127 | ], 128 | "slot_index": 0 129 | } 130 | ], 131 | "properties": { 132 | "Node name for S&R": "CLIPTextEncode" 133 | }, 134 | "widgets_values": [ 135 | "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), tooth, open mouth" 136 | ] 137 | }, 138 | { 139 | "id": 5, 140 | "type": "EmptyLatentImage", 141 | "pos": [ 142 | 90, 143 | 330 144 | ], 145 | "size": [ 146 | 310, 147 | 110 148 | ], 149 | "flags": {}, 150 | "order": 1, 151 | "mode": 0, 152 | "outputs": [ 153 | { 154 | "name": "LATENT", 155 | "type": "LATENT", 156 | "links": [ 157 | 2 158 | ], 159 | "slot_index": 0 160 | } 161 | ], 162 | "properties": { 163 | "Node name for S&R": "EmptyLatentImage" 164 | }, 165 | "widgets_values": [ 166 | 768, 167 | 1280, 168 | 1 169 | ] 170 | }, 171 | { 172 | "id": 11, 173 | "type": "DisplayText_Zho", 174 | "pos": [ 175 | 410, 176 | 540 177 | ], 178 | "size": [ 179 | 210, 180 | 190 181 | ], 182 | "flags": {}, 183 | "order": 5, 184 | "mode": 0, 185 | "inputs": [ 186 | { 187 | "name": "text", 188 | "type": "STRING", 189 | "link": 10, 190 | "widget": { 191 | "name": "text" 192 | } 193 | } 194 | ], 195 | "outputs": [ 196 | { 197 | "name": "text", 198 | "type": "STRING", 199 | "links": [ 200 | 15 201 | ], 202 | "shape": 3, 203 | "slot_index": 0 204 | } 205 | ], 206 | "properties": { 207 | "Node name for S&R": "DisplayText_Zho" 208 | }, 209 | "widgets_values": [ 210 | "", 211 | "Cinematic portrait of a beautiful ethereal 20-year-old girl, soft smile and gentle eyes, elegant loose white dress, intricate gold jewelry, cherry blossom tree background, unreal engine cinematic lighting, photorealistic, octane render, trending on artstation, 4k, 8k" 212 | ], 213 | "color": "#223", 214 | "bgcolor": "#335" 215 | }, 216 | { 217 | "id": 10, 218 | "type": "Gemini_API_S_Zho", 219 | "pos": [ 220 | 90, 221 | 480 222 | ], 223 | "size": [ 224 | 310, 225 | 250 226 | ], 227 | "flags": {}, 228 | "order": 2, 229 | "mode": 0, 230 | "inputs": [ 231 | { 232 | "name": "image", 233 | "type": "IMAGE", 234 | "link": null 235 | } 236 | ], 237 | "outputs": [ 238 | { 239 | "name": "text", 240 | "type": "STRING", 241 | "links": [ 242 | 10 243 | ], 244 | "shape": 3, 245 | "slot_index": 0 246 | } 247 | ], 248 | "properties": { 249 | "Node name for S&R": "Gemini_API_S_Zho" 250 | }, 251 | "widgets_values": [ 252 | "text = 'Draw a beautiful 20-year-old girl, smiling' # @param {type:\"string\"}\n\nprompt = \"You are creating a prompt for Stable Diffusion to generate an image. Please generate a text prompt for %s. Only respond with the prompt itself, but embellish it as needed but keep it under 80 tokens.\" % text", 253 | "gemini-pro", 254 | false 255 | ], 256 | "color": "#223", 257 | "bgcolor": "#335" 258 | }, 259 | { 260 | "id": 8, 261 | "type": "VAEDecode", 262 | "pos": [ 263 | 630, 264 | 540 265 | ], 266 | "size": [ 267 | 220, 268 | 50 269 | ], 270 | "flags": {}, 271 | "order": 9, 272 | "mode": 0, 273 | "inputs": [ 274 | { 275 | "name": "samples", 276 | "type": "LATENT", 277 | "link": 7 278 | }, 279 | { 280 | "name": "vae", 281 | "type": "VAE", 282 | "link": 8 283 | } 284 | ], 285 | "outputs": [ 286 | { 287 | "name": "IMAGE", 288 | "type": "IMAGE", 289 | "links": [ 290 | 16 291 | ], 292 | "slot_index": 0 293 | } 294 | ], 295 | "properties": { 296 | "Node name for S&R": "VAEDecode" 297 | } 298 | }, 299 | { 300 | "id": 13, 301 | "type": "ConcatText_Zho", 302 | "pos": [ 303 | 630, 304 | 630 305 | ], 306 | "size": [ 307 | 220, 308 | 100 309 | ], 310 | "flags": {}, 311 | "order": 6, 312 | "mode": 0, 313 | "inputs": [ 314 | { 315 | "name": "text_2", 316 | "type": "STRING", 317 | "link": 15, 318 | "widget": { 319 | "name": "text_2" 320 | } 321 | } 322 | ], 323 | "outputs": [ 324 | { 325 | "name": "text", 326 | "type": "STRING", 327 | "links": [ 328 | 19 329 | ], 330 | "shape": 3, 331 | "slot_index": 0 332 | } 333 | ], 334 | "properties": { 335 | "Node name for S&R": "ConcatText_Zho" 336 | }, 337 | "widgets_values": [ 338 | "xxmixgirl", 339 | "" 340 | ], 341 | "color": "#223", 342 | "bgcolor": "#335" 343 | }, 344 | { 345 | "id": 16, 346 | "type": "SelfAttentionGuidance", 347 | "pos": [ 348 | 410, 349 | 190 350 | ], 351 | "size": [ 352 | 210, 353 | 80 354 | ], 355 | "flags": {}, 356 | "order": 3, 357 | "mode": 0, 358 | "inputs": [ 359 | { 360 | "name": "model", 361 | "type": "MODEL", 362 | "link": 17, 363 | "slot_index": 0 364 | } 365 | ], 366 | "outputs": [ 367 | { 368 | "name": "MODEL", 369 | "type": "MODEL", 370 | "links": [ 371 | 18 372 | ], 373 | "shape": 3, 374 | 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980 | 29, 981 | 0, 982 | 27, 983 | 2, 984 | "CONDITIONING" 985 | ], 986 | [ 987 | 39, 988 | 30, 989 | 0, 990 | 27, 991 | 3, 992 | "LATENT" 993 | ], 994 | [ 995 | 40, 996 | 27, 997 | 0, 998 | 31, 999 | 0, 1000 | "LATENT" 1001 | ], 1002 | [ 1003 | 41, 1004 | 25, 1005 | 2, 1006 | 31, 1007 | 1, 1008 | "VAE" 1009 | ], 1010 | [ 1011 | 42, 1012 | 31, 1013 | 0, 1014 | 32, 1015 | 0, 1016 | "IMAGE" 1017 | ] 1018 | ], 1019 | "groups": [], 1020 | "config": {}, 1021 | "extra": {}, 1022 | "version": 0.4 1023 | } -------------------------------------------------------------------------------- /GeminiAPINode.py: -------------------------------------------------------------------------------- 1 | import os 2 | import io 3 | import json 4 | import requests 5 | import torch 6 | import google.generativeai as genai 7 | from io import BytesIO 8 | from PIL import Image 9 | 10 | p = os.path.dirname(os.path.realpath(__file__)) 11 | 12 | def get_gemini_api_key(): 13 | try: 14 | config_path = os.path.join(p, 'config.json') 15 | with open(config_path, 'r') as f: 16 | config = json.load(f) 17 | api_key = config["GEMINI_API_KEY"] 18 | except: 19 | print("出错啦 Error: API key is required") 20 | return "" 21 | return api_key 22 | 23 | class Gemini_API_Zho: 24 | 25 | def __init__(self, api_key=None): 26 | self.api_key = api_key 27 | if self.api_key is not None: 28 | genai.configure(api_key=self.api_key,transport='rest') 29 | 30 | @classmethod 31 | def INPUT_TYPES(cls): 32 | return { 33 | "required": { 34 | "prompt": ("STRING", {"default": "What is the meaning of life?", "multiline": True}), 35 | "model_name": (["gemini-pro", "gemini-pro-vision", "gemini-1.5-pro-latest"],), 36 | "stream": ("BOOLEAN", {"default": False}), 37 | "api_key": ("STRING", {"default": ""}) # Add api_key as an input 38 | }, 39 | "optional": { 40 | "image": ("IMAGE",), 41 | } 42 | } 43 | 44 | RETURN_TYPES = ("STRING",) 45 | RETURN_NAMES = ("text",) 46 | FUNCTION = "generate_content" 47 | 48 | CATEGORY = "Zho模块组/✨Gemini" 49 | 50 | def tensor_to_image(self, tensor): 51 | # 确保张量是在CPU上 52 | tensor = tensor.cpu() 53 | 54 | # 将张量数据转换为0-255范围并转换为整数 55 | # 这里假设张量已经是H x W x C格式 56 | image_np = tensor.squeeze().mul(255).clamp(0, 255).byte().numpy() 57 | 58 | # 创建PIL图像 59 | image = Image.fromarray(image_np, mode='RGB') 60 | return image 61 | 62 | def generate_content(self, prompt, model_name, stream, api_key, image=None): 63 | if api_key: 64 | self.api_key = api_key 65 | genai.configure(api_key=self.api_key,transport='rest') 66 | if not self.api_key: 67 | raise ValueError("API key is required") 68 | 69 | model = genai.GenerativeModel(model_name) 70 | 71 | if model_name == 'gemini-pro': 72 | if stream: 73 | response = model.generate_content(prompt, stream=True) 74 | textoutput = "\n".join([chunk.text for chunk in response]) 75 | else: 76 | response = model.generate_content(prompt) 77 | textoutput = response.text 78 | 79 | if model_name == 'gemini-pro-vision': 80 | if image == None: 81 | raise ValueError("gemini-pro-vision needs image") 82 | else: 83 | # 转换图像 84 | pil_image = self.tensor_to_image(image) 85 | 86 | # 直接使用PIL图像 87 | if stream: 88 | response = model.generate_content([prompt, pil_image], stream=True) 89 | textoutput = "\n".join([chunk.text for chunk in response]) 90 | else: 91 | response = model.generate_content([prompt, pil_image]) 92 | textoutput = response.text 93 | 94 | if model_name == 'gemini-1.5-pro-latest': 95 | if image == None: 96 | if stream: 97 | response = model.generate_content(prompt, stream=True) 98 | textoutput = "\n".join([chunk.text for chunk in response]) 99 | else: 100 | response = model.generate_content(prompt) 101 | textoutput = response.text 102 | else: 103 | # 转换图像 104 | pil_image = self.tensor_to_image(image) 105 | 106 | # 直接使用PIL图像 107 | if stream: 108 | response = model.generate_content([prompt, pil_image], stream=True) 109 | textoutput = "\n".join([chunk.text for chunk in response]) 110 | else: 111 | response = model.generate_content([prompt, pil_image]) 112 | textoutput = response.text 113 | 114 | return (textoutput,) 115 | 116 | 117 | class Gemini_API_Vsion_ImgURL_Zho: 118 | 119 | def __init__(self, api_key=None): 120 | self.api_key = api_key 121 | if self.api_key is not None: 122 | genai.configure(api_key=self.api_key,transport='rest') 123 | 124 | @classmethod 125 | def INPUT_TYPES(cls): 126 | return { 127 | "required": { 128 | "prompt": ("STRING", {"default": "Describe this image", "multiline": True}), 129 | "image_url": ("STRING", {"default": ""}), 130 | "model_name": (["gemini-pro-vision", "gemini-1.5-pro-latest"],), 131 | "stream": ("BOOLEAN", {"default": False}), 132 | "api_key": ("STRING", {"default": ""}) # Add api_key as an input 133 | } 134 | } 135 | 136 | RETURN_TYPES = ("STRING",) 137 | RETURN_NAMES = ("text",) 138 | FUNCTION = "generate_content" 139 | 140 | CATEGORY = "Zho模块组/✨Gemini" 141 | 142 | def generate_content(self, prompt, model_name, stream, api_key, image_url): 143 | if api_key: 144 | self.api_key = api_key 145 | genai.configure(api_key=self.api_key,transport='rest') 146 | if not self.api_key: 147 | raise ValueError("API key is required") 148 | 149 | # Load the image from the URL 150 | response = requests.get(image_url) 151 | if response.status_code != 200: 152 | raise ValueError("Failed to load image from URL") 153 | img = Image.open(BytesIO(response.content)) 154 | 155 | model = genai.GenerativeModel(model_name) 156 | 157 | if stream: 158 | response = model.generate_content([prompt, img], stream=True) 159 | textoutput = "\n".join([chunk.text for chunk in response]) 160 | else: 161 | response = model.generate_content([prompt, img]) 162 | textoutput = response.text 163 | 164 | return (textoutput,) 165 | 166 | #chat 167 | class Gemini_API_Chat_Zho: 168 | 169 | def __init__(self, api_key=None): 170 | self.api_key = api_key 171 | self.chat = None # 初始化时，聊天实例为空 172 | if self.api_key is not None: 173 | genai.configure(api_key=self.api_key,transport='rest') 174 | 175 | @classmethod 176 | def INPUT_TYPES(cls): 177 | return { 178 | "required": { 179 | "prompt": ("STRING", {"default": "What is the meaning of life?", "multiline": True}), 180 | "model_name": (["gemini-pro", "gemini-1.5-pro-latest"],), 181 | "api_key": ("STRING", {"default": ""}) # Add api_key as an input 182 | }, 183 | "optional": { 184 | "image": ("IMAGE",), 185 | } 186 | } 187 | 188 | RETURN_TYPES = ("STRING",) 189 | RETURN_NAMES = ("response",) 190 | FUNCTION = "generate_chat" 191 | 192 | CATEGORY = "Zho模块组/✨Gemini" 193 | 194 | def generate_chat(self, prompt, model_name, api_key): 195 | if api_key: 196 | self.api_key = api_key 197 | genai.configure(api_key=self.api_key,transport='rest') 198 | if not self.api_key: 199 | raise ValueError("API key is required") 200 | 201 | if not self.chat: 202 | model = genai.GenerativeModel(model_name) 203 | self.chat = model.start_chat(history=[]) 204 | 205 | if model_name == 'gemini-pro': 206 | response = self.chat.send_message(prompt) 207 | textoutput = response.text 208 | chat_history = self.format_chat_history(self.chat) 209 | 210 | if model_name == 'gemini-1.5-pro-latest': 211 | if image == None: 212 | response = self.chat.send_message(prompt) 213 | textoutput = response.text 214 | chat_history = self.format_chat_history(self.chat) 215 | else: 216 | # 转换图像 217 | pil_image = self.tensor_to_image(image) 218 | 219 | response = self.chat.send_message([prompt, pil_image]) 220 | textoutput = response.text 221 | chat_history = self.format_chat_history(self.chat) 222 | 223 | return (chat_history,) 224 | 225 | def format_chat_history(self, chat): 226 | formatted_history = [] 227 | for message in chat.history: 228 | formatted_message = f"{message.role}: {message.parts[0].text}" 229 | formatted_history.append(formatted_message) 230 | formatted_history.append("-" * 40) # 添加分隔线 231 | return "\n".join(formatted_history) 232 | 233 | 234 | class Gemini_API_S_Zho: 235 | 236 | def __init__(self): 237 | self.api_key = get_gemini_api_key() 238 | if self.api_key is not None: 239 | genai.configure(api_key=self.api_key,transport='rest') 240 | 241 | @classmethod 242 | def INPUT_TYPES(cls): 243 | return { 244 | "required": { 245 | "prompt": ("STRING", {"default": "What is the meaning of life?", "multiline": True}), 246 | "model_name": (["gemini-pro", "gemini-pro-vision", "gemini-1.5-pro-latest"],), 247 | "stream": ("BOOLEAN", {"default": False}), 248 | }, 249 | "optional": { 250 | "image": ("IMAGE",), 251 | } 252 | } 253 | 254 | RETURN_TYPES = ("STRING",) 255 | RETURN_NAMES = ("text",) 256 | FUNCTION = "generate_content" 257 | 258 | CATEGORY = "Zho模块组/✨Gemini" 259 | 260 | def tensor_to_image(self, tensor): 261 | # 确保张量是在CPU上 262 | tensor = tensor.cpu() 263 | 264 | # 将张量数据转换为0-255范围并转换为整数 265 | # 这里假设张量已经是H x W x C格式 266 | image_np = tensor.squeeze().mul(255).clamp(0, 255).byte().numpy() 267 | 268 | # 创建PIL图像 269 | image = Image.fromarray(image_np, mode='RGB') 270 | return image 271 | 272 | def generate_content(self, prompt, model_name, stream, image=None): 273 | if not self.api_key: 274 | raise ValueError("API key is required") 275 | 276 | model = genai.GenerativeModel(model_name) 277 | 278 | if model_name == 'gemini-pro': 279 | if stream: 280 | response = model.generate_content(prompt, stream=True) 281 | textoutput = "\n".join([chunk.text for chunk in response]) 282 | else: 283 | response = model.generate_content(prompt) 284 | textoutput = response.text 285 | 286 | if model_name == 'gemini-pro-vision': 287 | if image == None: 288 | raise ValueError("gemini-pro-vision needs image") 289 | else: 290 | # 转换图像 291 | pil_image = self.tensor_to_image(image) 292 | 293 | # 直接使用PIL图像 294 | if stream: 295 | response = model.generate_content([prompt, pil_image], stream=True) 296 | textoutput = "\n".join([chunk.text for chunk in response]) 297 | else: 298 | response = model.generate_content([prompt, pil_image]) 299 | textoutput = response.text 300 | 301 | if model_name == 'gemini-1.5-pro-latest': 302 | if image == None: 303 | if stream: 304 | response = model.generate_content(prompt, stream=True) 305 | textoutput = "\n".join([chunk.text for chunk in response]) 306 | else: 307 | response = model.generate_content(prompt) 308 | textoutput = response.text 309 | else: 310 | # 转换图像 311 | pil_image = self.tensor_to_image(image) 312 | 313 | # 直接使用PIL图像 314 | if stream: 315 | response = model.generate_content([prompt, pil_image], stream=True) 316 | textoutput = "\n".join([chunk.text for chunk in response]) 317 | else: 318 | response = model.generate_content([prompt, pil_image]) 319 | textoutput = response.text 320 | 321 | return (textoutput,) 322 | 323 | 324 | class Gemini_API_S_Vsion_ImgURL_Zho: 325 | 326 | def __init__(self): 327 | self.api_key = get_gemini_api_key() 328 | if self.api_key is not None: 329 | genai.configure(api_key=self.api_key,transport='rest') 330 | 331 | @classmethod 332 | def INPUT_TYPES(cls): 333 | return { 334 | "required": { 335 | "prompt": ("STRING", {"default": "Describe this image", "multiline": True}), 336 | "image_url": ("STRING", {"default": ""}), 337 | "model_name": (["gemini-pro-vision", "gemini-1.5-pro-latest"],), 338 | "stream": ("BOOLEAN", {"default": False}), 339 | } 340 | } 341 | 342 | RETURN_TYPES = ("STRING",) 343 | RETURN_NAMES = ("text",) 344 | FUNCTION = "generate_content" 345 | 346 | CATEGORY = "Zho模块组/✨Gemini" 347 | 348 | def generate_content(self, prompt, model_name, stream, image_url): 349 | if not self.api_key: 350 | raise ValueError("API key is required") 351 | 352 | # Load the image from the URL 353 | response = requests.get(image_url) 354 | if response.status_code != 200: 355 | raise ValueError("Failed to load image from URL") 356 | img = Image.open(BytesIO(response.content)) 357 | 358 | model = genai.GenerativeModel(model_name) 359 | 360 | if stream: 361 | response = model.generate_content([prompt, img], stream=True) 362 | textoutput = "\n".join([chunk.text for chunk in response]) 363 | else: 364 | response = model.generate_content([prompt, img]) 365 | textoutput = response.text 366 | 367 | return (textoutput,) 368 | 369 | 370 | #chat 371 | class Gemini_API_S_Chat_Zho: 372 | 373 | def __init__(self): 374 | self.api_key = get_gemini_api_key() 375 | self.chat = None # 初始化时，聊天实例为空 376 | if self.api_key is not None: 377 | genai.configure(api_key=self.api_key,transport='rest') 378 | 379 | @classmethod 380 | def INPUT_TYPES(cls): 381 | return { 382 | "required": { 383 | "prompt": ("STRING", {"default": "What is the meaning of life?", "multiline": True}), 384 | "model_name": (["gemini-pro", "gemini-1.5-pro-latest"],), 385 | }, 386 | "optional": { 387 | "image": ("IMAGE",), 388 | } 389 | } 390 | 391 | RETURN_TYPES = ("STRING",) 392 | RETURN_NAMES = ("response",) 393 | FUNCTION = "generate_chat" 394 | 395 | CATEGORY = "Zho模块组/✨Gemini" 396 | 397 | def tensor_to_image(self, tensor): 398 | # 确保张量是在CPU上 399 | tensor = tensor.cpu() 400 | 401 | # 将张量数据转换为0-255范围并转换为整数 402 | # 这里假设张量已经是H x W x C格式 403 | image_np = tensor.squeeze().mul(255).clamp(0, 255).byte().numpy() 404 | 405 | # 创建PIL图像 406 | image = Image.fromarray(image_np, mode='RGB') 407 | return image 408 | 409 | def generate_chat(self, prompt, model_name): 410 | if not self.api_key: 411 | raise ValueError("API key is required") 412 | 413 | if not self.chat: 414 | model = genai.GenerativeModel(model_name) 415 | self.chat = model.start_chat(history=[]) 416 | 417 | if model_name == 'gemini-pro': 418 | response = self.chat.send_message(prompt) 419 | textoutput = response.text 420 | chat_history = self.format_chat_history(self.chat) 421 | 422 | if model_name == 'gemini-1.5-pro-latest': 423 | if image == None: 424 | response = self.chat.send_message(prompt) 425 | textoutput = response.text 426 | chat_history = self.format_chat_history(self.chat) 427 | else: 428 | # 转换图像 429 | pil_image = self.tensor_to_image(image) 430 | 431 | response = self.chat.send_message([prompt, pil_image]) 432 | textoutput = response.text 433 | chat_history = self.format_chat_history(self.chat) 434 | 435 | return (chat_history,) 436 | 437 | def format_chat_history(self, chat): 438 | formatted_history = [] 439 | for message in chat.history: 440 | formatted_message = f"{message.role}: {message.parts[0].text}" 441 | formatted_history.append(formatted_message) 442 | formatted_history.append("-" * 40) # 添加分隔线 443 | return "\n".join(formatted_history) 444 | 445 | 446 | # System instructions 447 | class Gemini_15P_API_S_Advance_Zho: 448 | 449 | def __init__(self): 450 | self.api_key = get_gemini_api_key() 451 | if self.api_key is not None: 452 | genai.configure(api_key=self.api_key,transport='rest') 453 | 454 | @classmethod 455 | def INPUT_TYPES(cls): 456 | return { 457 | "required": { 458 | "prompt": ("STRING", {"default": "What is the meaning of life?", "multiline": True}), 459 | "system_instruction": ("STRING", {"default": "You are creating a prompt for Stable Diffusion to generate an image. First step: describe this image, then put description into text. Second step: generate a text prompt for %s based on first step. Only respond with the prompt itself, but embellish it as needed but keep it under 80 tokens.", "multiline": True}), 460 | "model_name": (["gemini-1.5-pro-latest"],), 461 | "stream": ("BOOLEAN", {"default": False}), 462 | }, 463 | "optional": { 464 | "image": ("IMAGE",), 465 | } 466 | } 467 | 468 | RETURN_TYPES = ("STRING",) 469 | RETURN_NAMES = ("text",) 470 | FUNCTION = "generate_content" 471 | 472 | CATEGORY = "Zho模块组/✨Gemini" 473 | 474 | def tensor_to_image(self, tensor): 475 | # 确保张量是在CPU上 476 | tensor = tensor.cpu() 477 | 478 | # 将张量数据转换为0-255范围并转换为整数 479 | # 这里假设张量已经是H x W x C格式 480 | image_np = tensor.squeeze().mul(255).clamp(0, 255).byte().numpy() 481 | 482 | # 创建PIL图像 483 | image = Image.fromarray(image_np, mode='RGB') 484 | return image 485 | 486 | def generate_content(self, prompt, system_instruction, model_name, stream, image=None): 487 | if not self.api_key: 488 | raise ValueError("API key is required") 489 | 490 | model = genai.GenerativeModel(model_name, system_instruction=system_instruction) 491 | 492 | if image == None: 493 | if stream: 494 | response = model.generate_content(prompt, stream=True) 495 | textoutput = "\n".join([chunk.text for chunk in response]) 496 | else: 497 | response = model.generate_content(prompt) 498 | textoutput = response.text 499 | else: 500 | # 转换图像 501 | pil_image = self.tensor_to_image(image) 502 | 503 | # 直接使用PIL图像 504 | if stream: 505 | response = model.generate_content([prompt, pil_image], stream=True) 506 | textoutput = "\n".join([chunk.text for chunk in response]) 507 | else: 508 | response = model.generate_content([prompt, pil_image]) 509 | textoutput = response.text 510 | 511 | return (textoutput,) 512 | 513 | 514 | class Gemini_15P_API_S_Chat_Advance_Zho: 515 | 516 | def __init__(self): 517 | self.api_key = get_gemini_api_key() 518 | self.chat = None # 初始化时，聊天实例为空 519 | if self.api_key is not None: 520 | genai.configure(api_key=self.api_key,transport='rest') 521 | 522 | @classmethod 523 | def INPUT_TYPES(cls): 524 | return { 525 | "required": { 526 | "prompt": ("STRING", {"default": "What is the meaning of life?", "multiline": True}), 527 | "system_instruction": ("STRING", {"default": "You are creating a prompt for Stable Diffusion to generate an image. First step: describe this image, then put description into text. Second step: generate a text prompt for %s based on first step. Only respond with the prompt itself, but embellish it as needed but keep it under 80 tokens.", "multiline": True}), 528 | "model_name": (["gemini-1.5-pro-latest"],), 529 | }, 530 | "optional": { 531 | "image": ("IMAGE",), 532 | } 533 | } 534 | 535 | RETURN_TYPES = ("STRING",) 536 | RETURN_NAMES = ("response",) 537 | FUNCTION = "generate_chat" 538 | 539 | CATEGORY = "Zho模块组/✨Gemini" 540 | 541 | def tensor_to_image(self, tensor): 542 | # 确保张量是在CPU上 543 | tensor = tensor.cpu() 544 | 545 | # 将张量数据转换为0-255范围并转换为整数 546 | # 这里假设张量已经是H x W x C格式 547 | image_np = tensor.squeeze().mul(255).clamp(0, 255).byte().numpy() 548 | 549 | # 创建PIL图像 550 | image = Image.fromarray(image_np, mode='RGB') 551 | return image 552 | 553 | def generate_chat(self, prompt, system_instruction, model_name, image=None): 554 | if not self.api_key: 555 | raise ValueError("API key is required") 556 | 557 | if not self.chat: 558 | model = genai.GenerativeModel(model_name, system_instruction=system_instruction) 559 | self.chat = model.start_chat(history=[]) 560 | 561 | if model_name == 'gemini-1.5-pro-latest': 562 | if image == None: 563 | response = self.chat.send_message(prompt) 564 | textoutput = response.text 565 | chat_history = self.format_chat_history(self.chat) 566 | else: 567 | # 转换图像 568 | pil_image = self.tensor_to_image(image) 569 | 570 | response = self.chat.send_message([prompt, pil_image]) 571 | textoutput = response.text 572 | chat_history = self.format_chat_history(self.chat) 573 | 574 | return (chat_history,) 575 | 576 | def format_chat_history(self, chat): 577 | formatted_history = [] 578 | for message in chat.history: 579 | formatted_message = f"{message.role}: {message.parts[0].text}" 580 | formatted_history.append(formatted_message) 581 | formatted_history.append("-" * 40) # 添加分隔线 582 | return "\n".join(formatted_history) 583 | 584 | 585 | # File API 586 | class Gemini_FileUpload_API_S_Zho: 587 | 588 | def __init__(self): 589 | self.api_key = get_gemini_api_key() 590 | if self.api_key is not None: 591 | genai.configure(api_key=self.api_key,transport='rest') 592 | 593 | @classmethod 594 | def INPUT_TYPES(cls): 595 | return { 596 | "required": { 597 | "file": ("STRING", {"default": "./sample.mp3", "multiline": False}), 598 | } 599 | } 600 | 601 | RETURN_TYPES = ("FILE",) 602 | RETURN_NAMES = ("file",) 603 | FUNCTION = "file_upload" 604 | 605 | CATEGORY = "Zho模块组/✨Gemini" 606 | 607 | def file_upload(self, file): 608 | if not self.api_key: 609 | raise ValueError("API key is required") 610 | 611 | your_file = genai.upload_file(file) 612 | 613 | return [your_file] 614 | 615 | 616 | class Gemini_File_API_S_Zho: 617 | 618 | def __init__(self): 619 | self.api_key = get_gemini_api_key() 620 | if self.api_key is not None: 621 | genai.configure(api_key=self.api_key,transport='rest') 622 | 623 | @classmethod 624 | def INPUT_TYPES(cls): 625 | return { 626 | "required": { 627 | "file": ("FILE",), 628 | "prompt": ("STRING", {"default": "Listen carefully to the following audio file. Provide a brief summary.", "multiline": True}), 629 | "model_name": (["gemini-1.5-pro-latest"],), 630 | "stream": ("BOOLEAN", {"default": False}), 631 | } 632 | } 633 | 634 | RETURN_TYPES = ("STRING",) 635 | RETURN_NAMES = ("text",) 636 | FUNCTION = "generate_content" 637 | 638 | CATEGORY = "Zho模块组/✨Gemini" 639 | 640 | def generate_content(self, prompt, model_name, stream, file): 641 | if not self.api_key: 642 | raise ValueError("API key is required") 643 | 644 | model = genai.GenerativeModel(model_name) 645 | 646 | if stream: 647 | response = model.generate_content([prompt, file], stream=True) 648 | textoutput = "\n".join([chunk.text for chunk in response]) 649 | else: 650 | response = model.generate_content([prompt, file]) 651 | textoutput = response.text 652 | 653 | return (textoutput,) 654 | 655 | 656 | class ConcatText_Zho: 657 | 658 | def __init__(self): 659 | pass 660 | 661 | @classmethod 662 | def INPUT_TYPES(cls): 663 | return { 664 | "required": { 665 | "text_1": ("STRING", {"multiline": True}), 666 | "text_2": ("STRING", {"multiline": True}), 667 | # 可以根据需要添加更多的文本输入 668 | }, 669 | } 670 | 671 | RETURN_TYPES = ("STRING",) 672 | RETURN_NAMES = ("text",) 673 | 674 | FUNCTION = "concat_texts" 675 | 676 | CATEGORY = "Zho模块组/✨Gemini" 677 | 678 | def concat_texts(self, **kwargs): 679 | # 将所有输入的文本合并为一个以逗号分隔的字符串 680 | texts = [kwargs[key] for key in kwargs if key.startswith('text')] 681 | combined_text = ', '.join(texts) 682 | return (combined_text,) 683 | 684 | 685 | # DisplayText node is forked from AlekPet，thanks to AlekPet！ 686 | class DisplayText_Zho: 687 | def __init__(self): 688 | pass 689 | 690 | @classmethod 691 | def INPUT_TYPES(s): 692 | 693 | return { 694 | "required": { 695 | "text": ("STRING", {"forceInput": True}), 696 | }, 697 | "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}, 698 | } 699 | 700 | RETURN_TYPES = ("STRING",) 701 | RETURN_NAMES = ("text",) 702 | OUTPUT_NODE = True 703 | FUNCTION = "display_text" 704 | 705 | CATEGORY = "Zho模块组/✨Gemini" 706 | 707 | def display_text(self, text, prompt=None, extra_pnginfo=None): 708 | return {"ui": {"string": [text,]}, "result": (text,)} 709 | 710 | 711 | NODE_CLASS_MAPPINGS = { 712 | "Gemini_API_Zho": Gemini_API_Zho, 713 | "Gemini_API_Vsion_ImgURL_Zho": Gemini_API_Vsion_ImgURL_Zho, 714 | "Gemini_API_Chat_Zho": Gemini_API_Chat_Zho, 715 | "Gemini_API_S_Zho": Gemini_API_S_Zho, 716 | "Gemini_API_S_Vsion_ImgURL_Zho": Gemini_API_S_Vsion_ImgURL_Zho, 717 | "Gemini_API_S_Chat_Zho": Gemini_API_S_Chat_Zho, 718 | "Gemini_15P_API_S_Advance_Zho": Gemini_15P_API_S_Advance_Zho, 719 | "Gemini_15P_API_S_Chat_Advance_Zho": Gemini_15P_API_S_Chat_Advance_Zho, 720 | "Gemini_FileUpload_API_S_Zho": Gemini_FileUpload_API_S_Zho, 721 | "Gemini_File_API_S_Zho": Gemini_File_API_S_Zho, 722 | "ConcatText_Zho": ConcatText_Zho, 723 | "DisplayText_Zho": DisplayText_Zho 724 | } 725 | 726 | NODE_DISPLAY_NAME_MAPPINGS = { 727 | "Gemini_API_Zho": "✨Gemini_API_Zho", 728 | "Gemini_API_Vsion_ImgURL_Zho": "✨Gemini_API_Vsion_ImgURL_Zho", 729 | "Gemini_API_Chat_Zho": "✨Gemini_API_Chat_Zho", 730 | "Gemini_API_S_Zho": "㊙️Gemini_Zho", 731 | "Gemini_API_S_Vsion_ImgURL_Zho": "㊙️Gemini_ImgURL_Zho", 732 | "Gemini_API_S_Chat_Zho": "㊙️Gemini_Chat_Zho", 733 | "Gemini_15P_API_S_Advance_Zho": "🆕Gemini_15P_Advance_Zho", 734 | "Gemini_15P_API_S_Chat_Advance_Zho": "🆕Gemini_15P_Chat_Advance_Zho", 735 | "Gemini_FileUpload_API_S_Zho": "📄Gemini_FileUpload_Zho", 736 | "Gemini_File_API_S_Zho": "📄Gemini_File_Zho", 737 | "ConcatText_Zho": "✨ConcatText_Zho", 738 | "DisplayText_Zho": "✨DisplayText_Zho" 739 | } 740 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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No Surrender of Others' Freedom. 541 | 542 | If conditions are imposed on you (whether by court order, agreement or 543 | otherwise) that contradict the conditions of this License, they do not 544 | excuse you from the conditions of this License. If you cannot convey a 545 | covered work so as to satisfy simultaneously your obligations under this 546 | License and any other pertinent obligations, then as a consequence you may 547 | not convey it at all. For example, if you agree to terms that obligate you 548 | to collect a royalty for further conveying from those to whom you convey 549 | the Program, the only way you could satisfy both those terms and this 550 | License would be to refrain entirely from conveying the Program. 551 | 552 | 13. Use with the GNU Affero General Public License. 553 | 554 | Notwithstanding any other provision of this License, you have 555 | permission to link or combine any covered work with a work licensed 556 | under version 3 of the GNU Affero General Public License into a single 557 | combined work, and to convey the resulting work. The terms of this 558 | License will continue to apply to the part which is the covered work, 559 | but the special requirements of the GNU Affero General Public License, 560 | section 13, concerning interaction through a network will apply to the 561 | combination as such. 562 | 563 | 14. Revised Versions of this License. 564 | 565 | The Free Software Foundation may publish revised and/or new versions of 566 | the GNU General Public License from time to time. Such new versions will 567 | be similar in spirit to the present version, but may differ in detail to 568 | address new problems or concerns. 569 | 570 | Each version is given a distinguishing version number. If the 571 | Program specifies that a certain numbered version of the GNU General 572 | Public License "or any later version" applies to it, you have the 573 | option of following the terms and conditions either of that numbered 574 | version or of any later version published by the Free Software 575 | Foundation. If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 599 | 600 | 16. Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | --------------------------------------------------------------------------------