feat(v3.2): RPG-style architecture-first planning behind ATLAS_RPG_PLANNING (#120)#124
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feat(v3.2): RPG-style architecture-first planning behind ATLAS_RPG_PLANNING (#120)#124yogthos wants to merge 2 commits into
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June 10, 2026 11:11
…ANNING (itigges22#120) Adds an opt-in repository-level planning phase that plans the architecture up front and then fills each piece, instead of free-form natural-language planning. It builds on the existing problem-level PlanSearch rather than replacing it: the Repository Planning Graph decides what to build and how the files, signatures, and data flows fit together, and PlanSearch fills in each node whose interface is already pinned. The work draws on two papers. RPG (arXiv:2509.16198) supplies the repository planning graph and the two-stage proposal-then-implementation construction. PlanSearch (arXiv:2409.03733), already implemented in this repo, supplies the per-node algorithmic search. The wavelet substrate is a faithful, dependency free Python port of wavescope-mcp by Dmitri Sotnikov, whose numeric output matches the upstream TypeScript bit for bit under the golden-fixture tests. Everything is gated by ATLAS_RPG_PLANNING and defaults to off. With the flag off, planning and generation behave exactly as before, since the flat planner emits no constraints and the new code paths short-circuit. What landed, by phase: - Wavelet substrate (v3-service/wavelet): structural signal, Ricker CWT, the fine/medium/coarse bands, project decomposition, and the peak-diff drift detector, all pure stdlib. - RPG artifact and two-stage planning (v3-service/rpg.py): capability tree then files, signatures, and edges, with validation, scoring, and a topological projection back onto the existing flat Plan so the agent loop is untouched. - Graph-guided generation: each node's planned interface threads into its /v3/generate call (proxy/rpg.go, proxy/types.go), so PlanSearch fills a node whose architecture is fixed. - Structural verification and drift: the candidate veto now rejects code that does not realize its planned signatures, and on write the proxy runs one bounded corrective regeneration, then surfaces any surviving drift along with the affected downstream subgraph. - Offline evaluation: v3-service/rpg_eval.py scores RPG artifacts for CI and benchmark summaries. The live RepoCraft comparison needs a GPU and is left as a documented runbook; the default stays off until that evidence lands. Design and phase-by-phase status live in docs/reports/RPG_WAVELET_PLANNING_V3_2.md. Tests: 152 Python tests under tests/v3-service and the proxy Go suite, all green. Credit for the idea and framing goes to Dmitri Sotnikov (@yogthos).
A review of the feature turned up two problems that made it inoperative in the default Docker deployment, plus several correctness gaps. This fixes all of them. The flag never reached the v3-service container, so the whole feature was dead when a user set ATLAS_RPG_PLANNING in their .env. It is now forwarded in docker-compose.yml, along with ATLAS_PLAN_THINKING. The proposal stage seeded its coarse band by scanning working_dir off disk, but the v3-service container has no project volume mount, so that scan always found nothing in Docker. It now builds the coarse band from the in-memory project_context the proxy already sends, through a new decompose_file_map entry point, and falls back to a disk scan only when no context was passed. The plan result is a single SSE line, and with RPG on it now carries the whole graph. The reader buffer was 1MB, so a large graph could trip ErrTooLong and silently drop the plan. The buffer is raised to 16MB and a scanner error is now surfaced instead of being reported as a missing result. Signature parsing mishandled Go receiver methods like func (s *S) Load(), and the bare-name fallback would return the keyword func, which produced a false missing-signature veto. Parsing now recognizes receiver methods and never treats a lone declaration keyword as a function name, and defined_names picks up receiver methods too. The edit_file and ast_edit path threaded RPG constraints but never ran the drift retry or reporting that the write path does, so drift on edits was invisible. It now runs the same regenerateOnDrift and reportRPGDrift. planConstraintsForTarget returned the first overlapping step, so a bare-basename step could shadow the deeper path it was not for. It now prefers the most specific match. The corrective regeneration accepted a retry only when the total miss count dropped, which discarded a retry that fixed the targeted signature but traded in a different one; it now accepts a retry that resolves any of the signatures it was correcting for. The topological sort dedups file ids so a duplicate cannot fake acyclicity or drop a file, and node_drift gained a threshold so its drift score actually gates the re-plan decision. Tests: 163 Python tests and the proxy Go suite, all green.
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The only thing to note here is that I haven't tested against a small model like 9b. So, while things should work mechanically as expected, it's worth testing to make sure a small model can work with the output well. |
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Adds an opt-in repository-level planning phase that plans the architecture up front and then fills each piece, instead of free-form natural-language planning. It builds on the existing problem-level
PlanSearchrather than replacing it: the Repository Planning Graph decides what to build and how the files, signatures, and data flows fit together, andPlanSearchfills in each node whose interface is already pinned.The work draws on two papers. RPG (arXiv:2509.16198) supplies the repository planning graph and the two-stage proposal-then-implementation construction. PlanSearch (arXiv:2409.03733), already implemented in this repo, supplies the per-node algorithmic search. The wavelet substrate is a faithful, dependency free Python port of wavescope-mcp, whose numeric output matches the upstream TypeScript under the fixture tests.
Everything is gated by
ATLAS_RPG_PLANNINGand defaults to off. With the flag off, planning and generation behave exactly as before, since the flat planner emits no constraints and the new code paths short-circuit.What the feature adds:
There is some offline evaluation still needed using v3-service/rpg_eval.py to score RPG artifacts for CI and benchmark summaries.