WeaveMindAI/weft
A programming language for AI orchestrations
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
1 release in the last 90 days, the latest 35 days ago, with 5 contributors on GitHub.
Use Cases & Benefits
- Defines a programming language for orchestrating AI systems integrating LLMs, humans, APIs, and infrastructure as core components.
- Eliminates plumbing by providing typed, durable execution with visual graph representation and first-class human interaction nodes.
- Use for building complex AI workflows that require seamless human-in-the-loop pauses and resumptions without manual state management.
- Use for creating scalable AI orchestration systems with type-safe, composable nodes that compile into visual graphs for easy debugging.
- Use for developing AI-driven applications that integrate multiple communication platforms, databases, and external APIs with durable execution.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Other
GitHub could not identify this license; read the LICENSE file before depending on it.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
- License not identified by GitHub; read the LICENSE file before depending on it.
General guidance from repository metadata, not legal advice. How we score
From the README
Building in public, two months in. Weft is young. The language, the type system, and the durable executor are the stable parts. The node catalog is small and intentionally opinionated (a few dozen nodes across LLM, code, communication, flow, storage, and triggers). The long-term vision is to let projects define their own nodes fluently in the language itself, but that is still ahead. If you are evaluating it for production, treat it as a foundation to build on, not a finished product. Breaking changes are expected while the shape is still settling; they will be announced, and migration notes will come with them.
Note on the docs. This README,
DESIGN.md,CONTRIBUTING.md,CODE_OF_CONDUCT.md, and most of the prose around the project were written fast to get the open source release out the door. They may sound a bit AI-generated in places. If you have the time and taste to rewrite any of them more cleanly, please do. A PR that improves the writing is as welcome as one that fixes a bug.A programming language for AI systems.
In 2026, real software calls LLMs, spins up databases, waits for humans, browses the web, coordinates agents. Where are those primitives? You are still importing libraries and writing plumbing for things that should be one line.
Weft is a language where LLMs, humans, APIs, and infrastructure are base ingredients. You wire them together, the compiler checks the architecture, and you get a visual graph of your program automatically. No plumbing.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+230 stars over 84 days across 9 snapshot days; best day +11 on Aug 6.
Forks
222+21
Open issues
0-8
Compared with peers in Backend
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| anthropics/skills | 187.8K | +2.9K | 15 | — |
| DuarteSantos8/openGym | 19.7K | +2.4K | 60 | 2 days ago |
| shiyu-coder/Kronos | 47.0K | +2.3K | 16 | — |
| NationalSecurityAgency/ghidra | 98.2K | +2.3K | 64 | 14 days ago |
| microsoft/VibeVoice | 56.0K | +1.1K | 29 | — |
| WeaveMindAI/weft | 2.0K | — | 58 | 35 days ago |
| Category median | 56.0K | +2.3K | 29 | — |
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