swe-af

name swe-af description Autonomous engineering team runtime — one API call spins up coordinated AI agents to scope, build, and ship software. license MIT compatibility opencode SWE-AF Usage Guide Autonomous engineering team runtime — one API call spins up coordinated AI agents to scope, build, and ship software. What It Does SWE-AF creates a coordinated team of AI agents (planning, coding, review, QA, merge, verification) that execute in parallel based on DAG dependencies. Issues with no dependencies run simultaneously; dependent issues run sequentially. Installation python3.12 -m venv .venv source .venv/bin/activate pip install -e ".[dev]" Running Terminal 1 — Control Plane: af # starts AgentField on port 8080 Terminal 2 — Register Node: python -m swe_af # registers the swe-planner node Triggering a Build With local repo: curl -X POST http://localhost:8080/api/v1/execute/async/swe-planner.build \ -H "Content-Type: application/json" \ -d '{ "input": { "goal": "Add JWT auth to all API endpoints", "repo_path": "/path/to/your/repo", "config": { "runtime": "open_code", "models": { "default": "zai-coding-plan/glm-5" } } } }' With GitHub repo (clones + creates draft PR): curl -X POST http://localhost:8080/api/v1/execute/async/swe-planner.build \ -H "Content-Type: application/json" \ -d '{ "input": { "goal": "Add comprehensive test coverage", "repo_url": "https://github.com/user/my-project", "config": { "runtime": "open_code", "models": { "default": "zai-coding-plan/glm-5" } } } }' Configuration Key Values Description runtime "claude_code" , "open_code" , "codex" AI backend to use models.default model ID string Default model for all agents models.coder model ID string Override for coder role models.qa model ID string Override for QA role repo_path local path Local workspace (new or existing) repo_url GitHub URL Clone + draft PR workflow Role-Specific Model Overrides { "config" : { "runtime" : "open_code" , "models" : { "default" : "zai-coding-plan/glm-5" , "coder" : "zai-coding-plan/glm-5" , "qa" : "zai-coding-plan/glm-5" , "verifier" : "zai-coding-plan/glm-5" } } } Available roles: pm , architect , tech_lead , sprint_planner , coder , qa , code_reviewer , qa_synthesizer , replan , retry_advisor , issue_writer , issue_advisor , verifier , git , merger , integration_tester Multi-Repo Builds SWE-AF supports coordinated work across multiple repositories in a single build. Pass config.repos as an array of repository objects, each with a repo_url (or repo_path ) and a role . Single-repo builds remain backward compatible—just use repo_url or repo_path at the top level. Complete Example: Primary App + Dependency curl -X POST http://localhost:8080/api/v1/execute/async/swe-planner.build \ -H "Content-Type: application/json" \ -d '{ "input": { "goal": "Add JWT auth across API and shared-lib", "config": { "repos": [ { "repo_url": "https://github.com/org/main-app", "role": "primary" }, { "repo_url": "https://github.com/org/shared-lib", "role": "dependency" } ], "runtime": "claude_code", "models": { "default": "sonnet" } } } }' Repository roles: primary : The main application being built. Changes here drive the build; failures block progress. dependency : Libraries or services that may be modified to support the primary repo. Failures are captured but don't block primary build progress. Use Cases Primary App + Shared Libraries : Coordinate changes between a web application and its shared utilities/SDK. Monorepo Sub-Projects : Define multiple repos in a monorepo structure and orchestrate cross-package changes. Microservices : When a feature spans an API service and a worker service, define roles to manage interdependencies. Requirements for open_code Runtime opencode CLI installed and in PATH Model provider credentials configured in OpenCode (e.g., OPENAI_API_KEY for z.ai) Model ID format matches what OpenCode expects Requirements for codex Runtime Codex CLI installed and in PATH. For ChatGPT subscription auth: run codex login on the host, set SWE_CODEX_AUTH_MODE=chatgpt or auto , and leave OPENAI_API_KEY unset for the agent process. For OpenAI API-platform billing: set SWE_CODEX_AUTH_MODE=api_key and OPENAI_API_KEY . Monitoring # Check build status curl http://localhost:8080/api/v1/executions/<execution_id> Artifacts are saved to: .artifacts/ ├── plan/ # PRD, architecture, issue specs ├── execution/ # checkpoints, per-issue logs └── verification/ # acceptance criteria results What Happens in a Build Planning — PM → Architect → Tech Lead → Sprint Planner (generates issue DAG) Issue Writing — All issues written in parallel Execution — Issues run level-by-level (parallel within levels) Each issue: Coder → QA + Reviewer (parallel) → Synthesizer Failures trigger advisor (retry/split/accept with debt/escalate) Merge — Branches merged to integration branch Integration Test — Full suite on merged code Verification — Acceptance criteria checked against PRD Key Endpoints POST /api/v1/execute/async/swe-planner.build # Full build POST /api/v1/execute/async/swe-planner.plan # Plan only POST /api/v1/execute/async/swe-planner.execute # Execute existing plan POST /api/v1/execute/async/swe-planner.resume_build # Resume after crash