
BYOK AI Workspace for Teams: Compare Models | BounceGrip
在安全的团队工作区中比较和使用多个LLM模型(Claude、OpenAI、Gemini等),用您自己的API密钥。
@uncoolavatar · X
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在安全的团队工作区中比较和使用多个LLM模型(Claude、OpenAI、Gemini等),用您自己的API密钥。
@uncoolavatar · X

通过统一的 API 接口访问多个 AI 语言模型。
u/DanTahirCode · Reddit
I built an open source coding agent with a personality - meet Klenny Code 🐾 Hey r/SideProject, my name is Dan Tahir, and I'm here to show off something I'm really proud of: Klenny Code, the open source coding agent with personality. A fully capable coding agent with memory and cross-project referencing, plus an assistant who can read your email, run scheduled tasks, pilot your browser, and be your corgi pal. Here's the pitch: bring your own OpenRouter API key, and Klenny wil

通过现有 API 订阅同时运行多个 AI 模型。
@ContinuumCode · X

可嵌入的可视化工作流编辑器,支持AI驱动或纯逻辑设计。
tahazsh · HN
Hi! I’m Taha. In many agentic products that support workflows (including one I worked on), I noticed they either don’t support node-based editors, or use React Flow and go through the difficult work of integrating it into their product to run it and work with their existing logic. So I thought about creating a tool that could help with this by closing the gap between the editor and the runtime. That’s why I created Wayflow. The basic architecture is simple: you just need to create a graph (which is a JSON object) that the runtime knows how to run. The runtime doesn’t care where that graph is coming from, it just needs the right schema. And with the help of the editor, you can create the graph, and then export it or directly save it on your backend in your database. And then when you want to execute it, you just hand it to the runtime. The runtime can either stream the execution (which is useful for the editor), or give you the final result. How you execute the graph is up to you: t

用一行代码部署强大的 AI 模型,享受业界最具竞争力的 GPU 价格。
Synexa AI — 一行代码部署 AI 模型 (Replicate 50% 低价平替),Synexa 是运行无服务器 AI API 最具性价比的解决方案,提供业界最具竞争力的 A100 GPU 价格,相比其他服务商可节省高达 62% 的 AI 算力成本 - [更多介绍](https://github.com/1c7/chinese-independent-developer/issues/47

通过InferAll统一API访问207+个AI模型
TaylorM492 · HN
InferAll – One API for OpenAI, Anthropic, Google, Nvidia Nim


在 AINA 工作区使用多个 AI 模型研究、搜索、分析文件和创作。
@sahiinthehood · X

Lydo: 在统一工作区中与团队和多个 AI 模型进行协作。
@johnnywestt · X
Multiplayer AI workspaces free for teams with a dozen agents already onboarded from all different models

多智能体LLM系统的可视化编辑器,支持本地推理。
sascha10000 · HN
Multi-agent LLM editor with local inference via WebSockets


与团队和AI代理在一个工作空间中构建、验证和发布软件。
u/OGMYT · Reddit
Validating a micro-SaaS for checking AI-built software before it ships I am building **Flows**, a system that turns an AI software goal into ordered implementation steps, checks, repair prompts, and a build report. The business thesis is not “better prompts.” It is reducing the cost of getting from an AI-generated first draft to a checked, shippable result. Metrics I want to measure: - prompts per completed project - tokens or credits per checked step - first-pass check rate - repair atte