https://github.com/thumbrise/autosolve
Lightweight daemon that polls GitHub for new issues and dispatches AI agents to solve them automatically
https://github.com/thumbrise/autosolve
ai ai-agent github polling
Last synced: 3 months ago
JSON representation
Lightweight daemon that polls GitHub for new issues and dispatches AI agents to solve them automatically
- Host: GitHub
- URL: https://github.com/thumbrise/autosolve
- Owner: thumbrise
- License: apache-2.0
- Created: 2026-03-19T11:50:24.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2026-03-28T17:57:48.000Z (3 months ago)
- Last Synced: 2026-03-28T18:26:29.156Z (3 months ago)
- Topics: ai, ai-agent, github, polling
- Language: Go
- Homepage: https://thumbrise.github.io/autosolve/
- Size: 411 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 60
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# autosolve
[](https://github.com/thumbrise/autosolve/actions/workflows/ci.yml)
[](https://pkg.go.dev/github.com/thumbrise/autosolve)
[](https://github.com/thumbrise/autosolve/stargazers)
[](/LICENSE)
Self-hosted Go daemon that polls GitHub repositories and dispatches AI agents to analyze issues automatically. No webhooks, no CI glue — just run and forget.
> **🚧 Active development — beta.** The core pipeline works end-to-end: issues are polled, analyzed by a local LLM, and results are posted as GitHub comments. [See it in action.](https://github.com/thumbrise/autosolve/pull/179) [Contributions welcome.](https://thumbrise.github.io/autosolve/contributing/adding-worker)
## How it works
1. **Polls** your GitHub repositories for new and updated issues
2. **Sends** each issue to a local Ollama model for AI analysis
3. **Posts** the result as a comment on the GitHub issue — automatically
> 🔗 **[Real example — AI analysis posted on a live issue](https://github.com/thumbrise/autosolve/pull/179)**
## Quick Start
```bash
git clone https://github.com/thumbrise/autosolve.git && cd autosolve
go mod download
cp config.yml.example config.yml # set your token + repos
go run . migrate up -y
go run . schedule
```
Configure in `config.yml`:
```yaml
github:
token: ghp_your_token # needs issues:write scope
repositories:
- owner: your-org
name: your-repo
issues:
requiredLabel: "autosolve" # optional — only analyze labeled issues
ollama:
endpoint: "http://localhost:11434"
model: "qwen2.5-coder:7b" # any Ollama model
```
That's it. Every issue with the `autosolve` label gets an AI analysis comment within seconds.
## Documentation
📖 **[thumbrise.github.io/autosolve](https://thumbrise.github.io/autosolve)** — full docs, guides, architecture, devlog.
| Section | What's there |
|---------|-------------|
| [Quick Start](https://thumbrise.github.io/autosolve/guide/getting-started) | Setup in 5 minutes |
| [Configuration](https://thumbrise.github.io/autosolve/guide/configuration) | All config options |
| [Architecture](https://thumbrise.github.io/autosolve/internals/overview) | How the system works |
| [The Idea](https://thumbrise.github.io/autosolve/project/idea) | Why this project exists |
| [Contributing](https://thumbrise.github.io/autosolve/contributing/adding-worker) | Add a worker in 4 steps |
| [Devlog](https://thumbrise.github.io/autosolve/devlog/) | How we got here — design decisions diary |
## Current Status
Epic v1 is in progress — see [Epic: v1 architecture redesign](https://github.com/thumbrise/autosolve/issues/59).
What works today: end-to-end AI dispatch pipeline — multi-repo polling, issue sync, outbox relay, Ollama analysis, GitHub comment posting, feedback loop prevention, per-error retry with degraded mode, rate limiting, full OTEL observability, SQLite with goose + sqlc.
What's next: re-analysis on issue updates, adaptive polling, CLI commands, GitHub App migration.
## License
[Apache License 2.0](LICENSE)