AI tools for Hercules
Related Tools:
testzeus-hercules
Hercules is the world’s first open-source testing agent designed to handle the toughest testing tasks for modern web applications. It turns simple Gherkin steps into fully automated end-to-end tests, making testing simple, reliable, and efficient. Hercules adapts to various platforms like Salesforce and is suitable for CI/CD pipelines. It aims to democratize and disrupt test automation, making top-tier testing accessible to everyone. The tool is transparent, reliable, and community-driven, empowering teams to deliver better software. Hercules offers multiple ways to get started, including using PyPI package, Docker, or building and running from source code. It supports various AI models, provides detailed installation and usage instructions, and integrates with Nuclei for security testing and WCAG for accessibility testing. The tool is production-ready, open core, and open source, with plans for enhanced LLM support, advanced tooling, improved DOM distillation, community contributions, extensive documentation, and a bounty program.
LLM4SE
The collection is actively updated with the help of an internal literature search engine.
kumo-search
Kumo search is an end-to-end search engine framework that supports full-text search, inverted index, forward index, sorting, caching, hierarchical indexing, intervention system, feature collection, offline computation, storage system, and more. It runs on the EA (Elastic automic infrastructure architecture) platform, enabling engineering automation, service governance, real-time data, service degradation, and disaster recovery across multiple data centers and clusters. The framework aims to provide a ready-to-use search engine framework to help users quickly build their own search engines. Users can write business logic in Python using the AOT compiler in the project, which generates C++ code and binary dynamic libraries for rapid iteration of the search engine.
blog
这是一个程序员关于 ChatGPT 学习过程的记录，其中包括了 ChatGPT 的使用技巧、相关工具和资源的整理，以及一些个人见解和思考。 **使用技巧** * **充值 OpenAI API**：可以通过 https://beta.openai.com/account/api-keys 进行充值，支持信用卡和 PayPal。 * **使用专梯**：推荐使用稳定的专梯，可以有效提高 ChatGPT 的访问速度和稳定性。 * **使用魔法**：可以通过 https://my.x-air.app:666/#/register?aff=32853 访问 ChatGPT，无需魔法即可访问。 * **下载各种 apk**：可以通过 https://apkcombo.com 下载各种安卓应用的 apk 文件。 * **ChatGPT 官网**：ChatGPT 的官方网站是 https://ai.com。 * **Midjourney**：Midjourney 是一个生成式 AI 图像平台，可以通过 https://midjourney.com 访问。 * **文本转视频**：可以通过 https://www.d-id.com 将文本转换为视频。 * **国内大模型**：国内也有很多大模型，如阿里巴巴的通义千问、百度文心一言、讯飞星火、阿里巴巴通义听悟等。 * **查看 OpenAI 状态**：可以通过 https://status.openai.com/ 查看 OpenAI 的服务状态。 * **Canva 画图**：Canva 是一个在线平面设计平台，可以通过 https://www.canva.cn 进行画图。 **相关工具和资源** * **文字转语音**：可以通过 https://modelscope.cn/models?page=1&tasks=text-to-speech&type=audio 找到文字转语音的模型。 * **可好好玩玩的项目**： * https://github.com/sunner/ChatALL * https://github.com/labring/FastGPT * https://github.com/songquanpeng/one-api * **个人博客**： * https://baoyu.io/ * https://gorden-sun.notion.site/527689cd2b294e60912f040095e803c5?v=4f6cc12006c94f47aee4dc909511aeb5 * **srt 2 lrc 歌词**：可以通过 https://gotranscript.com/subtitle-converter 将 srt 格式的字幕转换为 lrc 格式的歌词。 * **5 种速率限制**：OpenAI API 有 5 种速率限制：RPM（每分钟请求数）、RPD（每天请求数）、TPM（每分钟 tokens 数量）、TPD（每天 tokens 数量）、IPM（每分钟图像数量）。 * **扣子平台**：coze.cn 是一个扣子平台，可以提供各种扣子。 * **通过云函数免费使用 GPT-3.5**：可以通过 https://juejin.cn/post/7353849549540589587 免费使用 GPT-3.5。 * **不蒜子 统计网页基数**：可以通过 https://busuanzi.ibruce.info/ 统计网页的基数。 * **视频总结和翻译网页**：可以通过 https://glarity.app/zh-CN 总结和翻译视频。 * **视频翻译和配音工具**：可以通过 https://github.com/jianchang512/pyvideotrans 翻译和配音视频。 * **文字生成音频**：可以通过 https://www.cnblogs.com/jijunjian/p/18118366 将文字生成音频。 * **memo ai**：memo.ac 是一个多模态 AI 平台，可以将视频链接、播客链接、本地音视频转换为文字，支持多语言转录后翻译，还可以将文字转换为新的音频。 * **视频总结工具**：可以通过 https://summarize.ing/ 总结视频。 * **可每天免费玩玩**：可以通过 https://www.perplexity.ai/ 每天免费玩玩。 * **Suno.ai**：Suno.ai 是一个 AI 语言模型，可以通过 https://bibigpt.co/ 访问。 * **CapCut**：CapCut 是一个视频编辑软件，可以通过 https://www.capcut.cn/ 下载。 * **Valla.ai**：Valla.ai 是一个多模态 AI 模型，可以通过 https://www.valla.ai/ 访问。 * **Viggle.ai**：Viggle.ai 是一个 AI 视频生成平台，可以通过 https://viggle.ai 访问。 * **使用免费的 GPU 部署文生图大模型**：可以通过 https://www.cnblogs.com/xuxiaona/p/18088404 部署文生图大模型。 * **语音转文字**：可以通过 https://speech.microsoft.com/portal 将语音转换为文字。 * **投资界的 ai**：可以通过 https://reportify.cc/ 了解投资界的 ai。 * **抓取小视频 app 的各种信息**：可以通过 https://github.com/NanmiCoder/MediaCrawler 抓取小视频 app 的各种信息。 * **马斯克 Grok1 开源**：马斯克的 Grok1 模型已经开源，可以通过 https://github.com/xai-org/grok-1 访问。 * **ChatALL**：ChatALL 是一个跨端支持的聊天机器人，可以通过 https://github.com/sunner/ChatALL 访问。 * **零一万物**：零一万物是一个 AI 平台，可以通过 https://www.01.ai/cn 访问。 * **智普**：智普是一个 AI 语言模型，可以通过 https://chatglm.cn/ 访问。 * **memo ai 下载**：可以通过 https://memo.ac/ 下载 memo ai。 * **ffmpeg 学习**：可以通过 https://www.ruanyifeng.com/blog/2020/01/ffmpeg.html 学习 ffmpeg。 * **自动生成文章小工具**：可以通过 https://www.cognition-labs.com/blog 生成文章。 * **简易商城**：可以通过 https://www.cnblogs.com/whuanle/p/18086537 搭建简易商城。 * **物联网**：可以通过 https://www.cnblogs.com/xuxiaona/p/18088404 学习物联网。 * **自定义表单、自定义列表、自定义上传和下载、自定义流程、自定义报表**：可以通过 https://www.cnblogs.com/whuanle/p/18086537 实现自定义表单、自定义列表、自定义上传和下载、自定义流程、自定义报表。 **个人见解和思考** * ChatGPT 是一个强大的工具，可以用来提高工作效率和创造力。 * ChatGPT 的使用门槛较低，即使是非技术人员也可以轻松上手。 * ChatGPT 的发展速度非常快，未来可能会对各个行业产生深远的影响。 * 我们应该理性看待 ChatGPT，既要看到它的优点，也要意识到它的局限性。 * 我们应该积极探索 ChatGPT 的应用场景，为社会创造价值。
LLM-PowerHouse-A-Curated-Guide-for-Large-Language-Models-with-Custom-Training-and-Inferencing
LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.
AITreasureBox
AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.
MedLLMsPracticalGuide
This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.
Scientific-LLM-Survey
Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.
Awesome-Knowledge-Distillation-of-LLMs
A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.