5c4aa77255
The model dropdown was broken in two ways: it wrote to ~/.rowboat/config/models.json
(the BYOK creds file, stamped with a fake `flavor: 'openrouter'` to satisfy zod
when signed in), and the runtime ignored that write entirely for signed-in users
because `streamAgent` hard-coded `gpt-5.4`. Model selection was also globally
scoped, so every chat shared one brain.
This change moves model + provider out of the global config and onto the run
itself, resolved once at runs:create and frozen for the run's lifetime.
## Resolution
`runsCore.createRun` resolves per-field, falling through:
run.model = opts.model ?? agent.model ?? defaults.model
run.provider = opts.provider ?? agent.provider ?? defaults.provider
A new `core/models/defaults.ts` is the only place in the codebase that branches
on signed-in state. `getDefaultModelAndProvider()` returns name strings;
`resolveProviderConfig(name)` does the name → full LlmProvider lookup at
runtime. `createProvider` learns about `flavor: 'rowboat'` so the gateway is
just another flavor.
`provider` is stored as a name (e.g. `"rowboat"`, `"openai"`), not a full
LlmProvider object. API keys never get written into the JSONL log; rotating a
key in models.json applies to existing runs without re-creation. Cost: deleting
a provider from settings breaks runs that referenced it (clear error surfaced
via `resolveProviderConfig`).
## Runtime
`streamAgent` no longer resolves anything — it reads `state.runModel` /
`state.runProvider`, looks up the provider config, instantiates. Subflows
inherit the parent run's pair, so KG / inline-task subagents run on whatever
the main run resolved to at creation. The `knowledgeGraphAgents` array,
`isKgAgent`, and the per-agent default constants are gone.
KG / inline-task / pre-built agents declare their preferred model in YAML
frontmatter (claude-haiku-4.5 / claude-sonnet-4.6) — used at resolution time
when those agents are themselves the top-level agent of a run (background
triggers, scheduled tasks, etc.).
## Standalone callers
Non-run LLM call sites (summarize_meeting, track/routing, builtin-tools
parseFile) and `agent-schedule/runner` were branching on signed-in
independently. They all route through `getDefaultModelAndProvider` +
`resolveProviderConfig` + `createProvider` now; `agent-schedule/runner`
switched from raw `runsRepo.create` to `runsCore.createRun` so resolution
applies to scheduled-agent runs too.
## UI
`chat-input-with-mentions` stops calling `models:saveConfig`. The dropdown
notifies the parent via `onSelectedModelChange` ({provider, model} as names);
App.tsx stashes selection per-tab and passes it to the next `runs:create`.
When a run already exists, the input fetches it and renders a static label —
model can't change mid-run.
## Legacy runs
A lenient zod schema in `repo.ts` (`StartEvent.extend(...optional)` plus
`RunEvent.or(LegacyStartEvent)`) parses pre-existing runs. `repo.fetch` fills
missing model/provider from current defaults and returns the strict canonical
`Run` type. No file-rewriting migration; no impact on the canonical schema in
`@x/shared`.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
|
||
|---|---|---|
| .github/workflows | ||
| apps | ||
| assets | ||
| .env.example | ||
| .gitattributes | ||
| .gitignore | ||
| build-electron.sh | ||
| CLAUDE.md | ||
| docker-compose.yml | ||
| Dockerfile.qdrant | ||
| google-setup.md | ||
| LICENSE | ||
| README.md | ||
| start.sh | ||
Rowboat
Open-source AI coworker that turns work into a knowledge graph and acts on it
Rowboat connects to your email and meeting notes, builds a long-lived knowledge graph, and uses that context to help you get work done - privately, on your machine.
You can do things like:
Build me a deck about our next quarter roadmap→ generates a PDF using context from your knowledge graphPrep me for my meeting with Alex→ pulls past decisions, open questions, and relevant threads into a crisp brief (or a voice note)- Track a person, company or topic through live notes
- Visualize, edit, and update your knowledge graph anytime (it’s just Markdown)
- Record voice memos that automatically capture and update key takeaways in the graph
Download latest for Mac/Windows/Linux: Download
⭐ If you find Rowboat useful, please star the repo. It helps more people find it.
Demo
Installation
Download latest for Mac/Windows/Linux: Download
All release files: https://github.com/rowboatlabs/rowboat/releases/latest
Google setup
To connect Google services (Gmail, Calendar, and Drive), follow Google setup.
Voice input
To enable voice input and voice notes (optional), add a Deepgram API key in ~/.rowboat/config/deepgram.json
Voice output
To enable voice output (optional), add an ElevenLabs API key in ~/.rowboat/config/elevenlabs.json
Web search
To use Exa research search (optional), add the Exa API key in ~/.rowboat/config/exa-search.json
External tools
To enable external tools (optional), you can add any MCP server or use Composio tools by adding an API key in ~/.rowboat/config/composio.json
All API key files use the same format:
{
"apiKey": "<key>"
}
What it does
Rowboat is a local-first AI coworker that can:
- Remember the important context you don’t want to re-explain (people, projects, decisions, commitments)
- Understand what’s relevant right now (before a meeting, while replying to an email, when writing a doc)
- Help you act by drafting, summarizing, planning, and producing real artifacts (briefs, emails, docs, PDF slides)
Under the hood, Rowboat maintains an Obsidian-compatible vault of plain Markdown notes with backlinks — a transparent “working memory” you can inspect and edit.
Integrations
Rowboat builds memory from the work you already do, including:
- Gmail (email)
- Google Calendar
- Rowboat meeting notes or Fireflies
It also contains a library of product integrations through Composio.dev
How it’s different
Most AI tools reconstruct context on demand by searching transcripts or documents.
Rowboat maintains long-lived knowledge instead:
- context accumulates over time
- relationships are explicit and inspectable
- notes are editable by you, not hidden inside a model
- everything lives on your machine as plain Markdown
The result is memory that compounds, rather than retrieval that starts cold every time.
What you can do with it
- Meeting prep from prior decisions, threads, and open questions
- Email drafting grounded in history and commitments
- Docs & decks generated from your ongoing context (including PDF slides)
- Follow-ups: capture decisions, action items, and owners so nothing gets dropped
- On-your-machine help: create files, summarize into notes, and run workflows using local tools (with explicit, reviewable actions)
Live notes
Live notes are notes that stay updated automatically. You can create one by typing '@rowboat' on a note.
- Track a competitor or market topic across X, Reddit, and the news
- Monitor a person, project, or deal across web or your communications
- Keep a running summary of any subject you care about
Everything is written back into your local Markdown vault. You control what runs and when.
Bring your own model
Rowboat works with the model setup you prefer:
- Local models via Ollama or LM Studio
- Hosted models (bring your own API key/provider)
- Swap models anytime — your data stays in your local Markdown vault
Extend Rowboat with tools (MCP)
Rowboat can connect to external tools and services via Model Context Protocol (MCP). That means you can plug in (for example) search, databases, CRMs, support tools, and automations - or your own internal tools.
Examples: Exa (web search), Twitter/X, ElevenLabs (voice), Slack, Linear/Jira, GitHub, and more.
Local-first by design
- All data is stored locally as plain Markdown
- No proprietary formats or hosted lock-in
- You can inspect, edit, back up, or delete everything at any time