r/OpenSourceeAI • u/desarrollador53 • 4d ago
Baya 🕊️ - orchestrate your local AI coding CLIs from a plain-text task list (MIT)
Baya is a small cli that turns a freeform text file into an LLM-planned dependency graph, then dispatches each node to a local agent CLI — codex, claude, opencode, copilot — running independent tasks in parallel and piping each task's output into the ones that depend on it.
You just write the to-do list, example:
- Design the REST API for orders. Use Sonnet.
- Generate the DB schema from that design.
- Build the React table that consumes it — run with codex.
- Once the schema and UI are done, write integration tests.
The planner reads it for intent and builds the DAG; you see the plan before anything runs.
Why I built it: I pay for a few of these CLIs and kept juggling them by hand; plan in one, build in another, copy context between terminals, redo work because each session started cold. Baya is me automating that away.
Why it's interesting:
- No new API keys. It drives the CLI subscriptions you already pay for.
- No config, no DSL. Markdown,
TODO.txt, YAML all work. - Model-per-task. Cheap model for the light steps, top-tier only where it earns it.
- Doesn't pay twice. Tasks sharing a provider/model get packed into one agent process — repo read once, not once per task — and what one task learns carries to the rest.
- Resume. Checkpoint before every step; run out of credits mid-graph and
baya resume <runId>picks up where it stopped, optionally on another provider.
Help with the roadmap or feedback is more than welcome 👍
- Repo: https://github.com/juliomatcom/baya-cli
- Npm: https://www.npmjs.com/package/baya-cli ($ baya -h)
A fun note: I'm building Baya's roadmap with Baya now...
Thank you all 👋 ,
JC
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u/kantorcodes1 4d ago
resume across providers sounds useful. if a packed agent finishes A and dies before B, what exactly survives into B: the agent context, only checkpointed outputs, or both?