Commit Graph

55 Commits

Author SHA1 Message Date
Marcos 087834565d feat(pilot): token-usage reporting gated by AI-USAGE label
Add per-review + per-comment token accounting, surfaced only when a PR carries
the new AI-USAGE label (on top of the existing AI-REVIEW trigger).

opencode_review:
- run_opencode now uses `--format json`; parse_opencode_events reconstructs the
  assistant text from `text` events and sums tokens/cost/steps from every
  `step_finish` event (tolerant of noise / missing fields).
- run() measures duration_s around the opencode call and returns (text, usage).
- changed_files(diff) extracts the `+++ b/` paths; the brief now lists them
  under a "Changed files" focus block so the agent grounds findings in the
  diff's neighbourhood instead of unbounded whole-repo walks.

ai_review:
- format_usage_section renders a `## AI usage` block: measured totals
  (in/out/reasoning/cache/cost/steps/duration), the whole-repo scope note, and
  an attributed per-finding table. Per-comment counts are output tokens split by
  each finding's body weight — labelled "attributed" since one model pass
  produces all findings.
- inline_comment_body appends `🪙 ~N tok (X% · attributed output)` when
  attribution is present.
- review_pr gains report_usage; compute_attribution stashes _tok_attrib/_tok_pct.
- format_review_body inserts the usage section between summary and findings.

webhook_server:
- Fire on every pull_request action except `closed` (denylist, was an allowlist)
  — the AI-REVIEW gate + sha dedupe keep this safe.
- AI-USAGE label detection + PRAGENT_USAGE_ALWAYS env drive report_usage.

.opencode factory + review-methodology skill: new "Ground findings in context"
step — read callers/imports/sibling functions per changed file (1-3 files per
finding), no unbounded walks.

Tests: parse_opencode_events (text+usage sum, malformed tolerance, none-usage),
changed_files, compute_attribution math, inline 🪙 line, format_usage_section
totals/table/cost, format_review_body ordering. 68 passing.

Co-Authored-By: Claude <noreply@anthropic.com>
2026-08-18 04:15:11 +00:00
Marcos 76b6752f48 fix(review): language-tagged suggestion fence for Gitea syntax highlighting
Gitea 1.26.x has no GitHub-style 'Apply suggestion' button — a ```suggestion
fence is just an unknown-language code block, so chroma does not highlight it
and there is no apply control. Switch inline_comment_body to wrap the suggested
fix in a fence tagged with the file's language (new _lang_for_path helper,
.java→java, .ts→typescript, .py→python, ...), so Gitea syntax-highlights the
code. No capability lost (there was never an apply button on this Gitea
version). Correct the docstrings/skills/README that wrongly claimed an
apply-button was rendered.

Co-Authored-By: Claude <noreply@anthropic.com>
2026-08-18 01:26:37 +00:00
Marcos 6e3a9eb5b0 feat: opencode review engine + .opencode factory
Replace the single Python model-call reviewer with an opencode agent
factory. A primary 'pragent' agent reads a brief (title/body/diff/config/
prior reviews), inspects the checked-out repo, runs the repo's own linters
via bash, loads review-methodology + findings-schema skills, and emits a
{summary, findings} JSON with per-finding severity/path/line/problem/fix/
suggestion/reference. Dormant security/tests/perf subagent lenses fan out
only on large/risky diffs (lean by default).

pilot/opencode_review.py: fetches the repo archive at the head sha into a
temp workdir, writes .pragent/brief.md, drops the factory, runs
'opencode run --pure --agent pragent --dir <workdir>' headlessly. Isolates
HOME (shared, warmed), strips ANTHROPIC_* env (leaked host vars caused
ProviderModelNotFoundError), stdin=DEVNULL (opencode blocks on stdin),
maps the bare OLLAMA_MODEL to the provider-prefixed ref. No Gitea I/O —
ai_review.review_pr parses + anchors + posts (reuses all v2 logic/tests).

PRAGENT_ENGINE=opencode (default) selects it; =ollama keeps the legacy
direct-call path. Verified end-to-end: posts a real review with a summary
section, inline [CRITICAL]/[HIGH] comments + apply-able suggestions +
reference links, and the sha dedupe marker. 49 tests pass.

Co-Authored-By: Claude <noreply@anthropic.com>
2026-08-17 23:01:59 +00:00
Marcos 90cea84f6f pilot: dedupe + repo config + inline comments w/ suggestions
- Dedupe: Gitea-as-state. Scan existing reviews for a hidden
  <!-- pragent:sha=... --> marker matching the head sha; skip if present
  (kills duplicate reviews on label-toggle / re-fire). Prior review bodies
  fed back as 'already said' context (light framework §6.1).
- Repo-local focus: optional .pr-review.json at repo root
  ({focus,exclude_paths,languages,instructions}), fetched at head ref.
- Inline comments + apply-able suggestions: model emits JSON findings
  {severity,path,line,problem,fix,suggestion}; diff hunks parsed into valid
  (path,new_line) RIGHT-side anchors; anchored findings become positional
  review comments with a ```suggestion fence (Gitea apply-button);
  unanchored findings fold into the summary body.
- Tests: parse_diff_anchors, parse_findings (tolerant JSON), split_findings,
  inline_comment_body, summary_bullets, parse_repo_config, reviewed_shas,
  prior_review_bodies, sha-marker. 35 pass.
- Bump OLLAMA_MAX_TOKENS default 6000 -> 8000 (suggestions add length).

Co-Authored-By: Claude <noreply@anthropic.com>
2026-08-17 19:59:36 +00:00
Marcos 6f012e9b66 feat(pilot): minimal AI review bot for Gitea Actions
Ships a working pragent pilot ahead of the framework build (design doc
deferred). Single stdlib-only reviewer script fetched at runtime by a per-repo
Gitea Action; reviews fire only on PRs with the AI-REVIEW label; model is
glm-5.2:cloud via the on-network headroom proxy; fail-open.

- pilot/ai_review.py: fetch PR diff, call model, post review as pragent-bot
- pilot/workflow-template.yml: per-repo Gitea Action gated on AI-REVIEW label
- pilot/README.md: onboarding (bot collaborator + secret + workflow + label)
- tests/pilot/test_ai_review.py: 15 unit tests for pure helpers (no network)
- README/design doc: note pilot is the bootstrap; framework build deferred

Co-Authored-By: Claude <noreply@anthropic.com>
2026-08-17 18:18:06 +00:00