Open-Source AI Platform Orbit
Orbit is an open-source AI platform that offers a single OpenAI-compatible API to connect files, databases, vector stores, models, and tools. It can be run locally or in the cloud and includes built‑in authentication, observability, and governance features. The project provides Docker images, a live sandbox, and supports multiple model backends such as Ollama, OpenAI, and Gemini.
- ▪Orbit enables natural‑language access to diverse data sources and APIs through configurable YAML adapters.
- ▪Users can switch between local and cloud model providers, including Ollama, OpenAI, and Gemini, without changing the application architecture.
- ▪The platform includes production controls like API keys, RBAC, SSO, quotas, moderation, metrics, and audit logs.
- ▪A live sandbox and quick‑start Docker images allow developers to try the system without prior setup.
- ▪Orbit’s repository encourages community contributions and signals ongoing maintenance through release history and changelogs.
2 outlets in our directory ran this story, first to last over 20 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,178 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/schmitech/orbit |
| Publication time | Sat, 01 Aug 2026 13:51:40 +0000 |
| Retrieval time | 2026-08-01T13:58:32.249Z |
| Last seen | 2026-08-01T13:58:32.249Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 0VxGpmus3SOt · 2 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
ORBIT Connect private data and internal tools through one OpenAI-compatible API Connect files, databases, vector stores, models, APIs, and MCP tools. Run locally or in your cloud—with authentication, observability, and governance built in. ⚡ Try Live Sandbox • Quick start • Watch the demo • Tutorial • Documentation Explore the live sandbox instantly — no download, Docker, or setup required. multimodal.mp4 Upload PDFs, spreadsheets, and images, then query them together with context preserved across the conversation. 👉 Try this live in your browser → ⭐ Cloning ORBIT? If it looks useful, star the repository. It helps other developers discover the project and signals that we should keep investing in new model, datasource, and agent integrations.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.