Files
pragent/pilot/README-webhook.md
T
Marcos 513de0e3a8 docs(pilot): document AI-USAGE label, token attribution, webhook denylist
- new "AI-USAGE label" section: what gets reported, the attributed-vs-measured
  distinction, PRAGENT_USAGE_ALWAYS, regression-clean without the label.
- new "Webhook fires on any PR update (except closed)" section: denylist
  semantics + why the AI-REVIEW gate + sha dedupe keep it safe.
- arch diagram gate updated (allowlist → denylist; AI-USAGE side-gate).
- opencode engine step 4: --format json + parse_opencode_events → (text, usage).

Co-Authored-By: Claude <noreply@anthropic.com>
2026-08-18 04:17:32 +00:00

336 lines
17 KiB
Markdown

# pragent pilot — central webhook service
The CI-step pilot (`pilot/README.md`) needs a workflow file + secret + label per
repo. The **central webhook service** removes the workflow file, the secret, and
the runner dependency: a Gitea webhook posts PR events to an always-on in-cluster
service, which gates on the `AI-REVIEW` label and runs the same review core.
## Architecture
```
PR opened/pushed/labeled/edited/… (any repo under a covered owner)
│ Gitea user-level webhook (events: pull_request)
Service pragent-webhook.pragent.svc.cluster.local (ClusterIP, ns pragent)
│ HMAC-verify (X-Gitea-Signature) → gate: action ≠ closed
│ AND pull_request.labels ∋ AI-REVIEW
│ (report_usage ← pull_request.labels ∋ AI-USAGE, optional)
ai_review.review_pr() (same core the CI-step uses)
1. fetch existing reviews → dedupe: skip if a review already carries
<!-- pragent:sha=<this sha> --> (no duplicate on label-toggle / re-fire)
2. fetch PR diff → GET .../pulls/{i}.diff
3. fetch .pr-review.json @ head ref (optional repo-local focus/config)
4. prior review bodies → fed as "already said" context (light §6.1)
5. PRAGENT_ENGINE=opencode (default):
a. fetch repo archive @ head sha → /tmp/pragent-work/<repo>-<sha>
b. write .pragent/brief.md (title/body/diff/config/prior/sha/anchor-hint)
c. drop the factory (opencode.json + .opencode/) into the workdir
d. opencode run --pure --agent pragent --dir <workdir> --model headroom/glm-5.2:cloud
→ the pragent agent reads the brief, inspects the repo, runs the
repo's own linters via bash, loads review-methodology + findings-schema
skills, delegates to security/tests/perf subagents only on big/risky
diffs, and emits: {"summary":..., "findings":[{severity,path,line,
problem,fix,suggestion,reference}]}
(=ollama: legacy single POST to http://100.74.17.70:8789/v1/messages)
6. parse diff hunks → valid (path, new_line) anchors (RIGHT side)
7. post review → POST .../pulls/{i}/reviews (event: COMMENT) as pragent-bot
- prose summary → review body intro
- anchored findings → inline line comments, body wraps `suggestion` in a
language-tagged fenced code block (Gitea syntax-highlights it; Gitea
1.26.x has no apply-suggestion button); reference → 📎 ref link
- unanchored findings → summary-body bullets
- summary body carries the <!-- pragent:sha=... --> marker for dedupe
```
Fail-open. No duplicate per commit (dedupe). Inline comments + syntax-highlighted
suggested-fix blocks where the line anchors cleanly. Repo-local focus via
`.pr-review.json`. Prior reviews fed as context so re-pushes synthesize instead
of repeating (light version of framework §6.1).
## What "onboarding a repo" means now
1. Add `pragent-bot` as collaborator with **Write** (so it can read the diff and
post the review). The bot stays a normal user — it is **not** a site admin.
2. Create the `AI-REVIEW` label on the repo (one-time; `pragent-bot`'s
`write:issue` scope can do it once it's a collaborator).
3. Label a PR `AI-REVIEW`.
No workflow file, no repo secret, no act-runner needed. (The owner must already
be covered by a user-level webhook — see below. If not, do the one-time
per-owner setup first.)
## AI-USAGE label — token-usage reporting (optional, opt-in)
A review always fires on `AI-REVIEW`. Adding a second label **`AI-USAGE`** on
the same PR opts the review into appending a token-usage report:
- a `## 🔋 AI usage` section on the review summary body with the **measured**
review total — input / output / reasoning / cache read+write / total tokens,
agent step count, wall-clock duration, estimated cost, the model, and a scope
note (the agent reviews a whole-repo checkout at the head sha, so input
tokens include files read beyond the diff);
- a per-finding attribution table (severity · location · ≈out tok · %);
- a `🪙 ~N tok (X% · attributed output)` line at the foot of each inline
comment.
**Attributed, not measured.** One opencode agent pass produces *all* findings,
so there is no native per-finding token metering. The per-comment / per-row
counts are the review's measured **output** tokens split by each finding's
rendered-body weight (`len(problem)+len(fix)+len(suggestion)`) — an honest
attribution, labelled as such. The totals are real measurements summed from
opencode's `step_finish` events.
`PRAGENT_USAGE_ALWAYS=1` on the Deployment forces usage reporting on for every
review (testing / a future default-on) regardless of the label.
Without `AI-USAGE` (regression): no usage section, no 🪙 lines — behaviour
identical to before the feature. The usage section is part of the review body,
so it's covered by the existing sha-marker dedupe.
## Webhook fires on any PR update (except `closed`)
The receiver uses a **denylist**, not an allowlist: it reviews on every
`pull_request` action **except `closed`**`opened`, `reopened`,
`synchronize`/`synchronized`, `labeled`/`label_updated`, `edited` (title/body),
`ready_for_review` (draft→ready), `assigned`, `review_requested`, `milestone`,
… . This is safe because of two downstream gates:
- the **AI-REVIEW label gate** — payload `labels` reflect current state, so an
`unlabeled` that *removed* AI-REVIEW fails the gate (no review); an
`unlabeled` of another label still passes;
- the **sha dedupe** — any same-sha re-fire (title edit, assignee, milestone,
a label toggle of another label…) is skipped, so the only newly-effective
actions are ones that change the head sha (`synchronize`, already covered) or
move a draft to ready (`ready_for_review`) on an un-reviewed sha.
## Repo-local focus: `.pr-review.json` (optional)
Drop a `.pr-review.json` at the repo root (committed on the PR's branch, or on
the default branch) to steer the review for that repo. All fields optional;
absent file = defaults. JSON (stdlib, no YAML dependency).
```json
{
"focus": ["security", "supply-chain", "sql-injection"],
"exclude_paths": ["vendor/**", "**/*.generated.ts"],
"languages": ["typescript", "go"],
"instructions": "We use Result<T,E> for error handling. Flag any bare throw. Flag eval()/exec() on user input as critical."
}
```
- `focus` — weight these review areas higher (does not blind the reviewer to
critical issues outside them).
- `exclude_paths` — tell the model to ignore these paths.
- `languages` — hint the primary languages.
- `instructions` — free-form house conventions / compliance language.
Fetched at review time from the PR head ref
(`GET /repos/{o}/{r}/contents/.pr-review.json?ref=<head sha>`). Bad/missing file
fails open to defaults. The bot's `read:repository` scope reads it.
## One-time per-owner setup: register a user-level webhook
Gitea **system webhooks** (one webhook for the whole instance — the ideal) are
**broken in Gitea 1.26.1**: `POST /admin/hooks` returns `201` but the hook never
persists (`GET /admin/hooks` lists 0, no delivery). So we use **user-level
webhooks** instead — one webhook per repo-owner, which fires for every repo that
user owns. For a small instance with few owners this is nearly as good.
To onboard a new owner (e.g. `masi`):
```bash
# 1. generate a one-time token for that user (admin CLI, inside the gitea pod)
K="microk8s kubectl"
GPOD=$($K -n gitea get pod -l app=gitea --field-selector=status.phase=Running \
-o jsonpath='{.items[?(@.status.containerStatuses[0].ready==true)].metadata.name}')
$K -n gitea exec "$GPOD" -c gitea -- \
gitea admin user generate-access-token --username masi \
--scopes write:user,read:user --token-name pragent-userhook-masi
# 2. register the user-level webhook (events: pull_request)
# WEBHOOK_SECRET = the shared HMAC secret in the pragent-webhook K8s Secret
python3 - "$MASI_TOKEN" <<'PY'
import sys, json, urllib.request
tok = sys.argv[1]
GAPI = "http://100.74.17.70:30000/api/v1"
WS = open("/dev/stdin") and __import__("os").environ["WEBHOOK_SECRET"] # or paste
req = urllib.request.Request(
f"{GAPI}/user/hooks",
data=json.dumps({"type":"gitea",
"config":{"url":"http://pragent-webhook.pragent.svc.cluster.local/webhook",
"content_type":"json","secret":WS},
"events":["pull_request"],"active":True}).encode(),
method="POST", headers={"Authorization":f"token {tok}","Content-Type":"application/json"})
print(urllib.request.urlopen(req).status, urllib.request.urlopen(req).read()[:80])
PY
# 3. revoke the one-time token (Gitea admin UI → Users → masi → Access Tokens).
```
Owners already covered: `gitea_admin` (webhook id=4), `masi` (webhook id=5),
`techspark` (webhook id=6 — a user account, not an org; covers `techspark/suaspark-site`,
`techspark/spark-ui`, etc.). True **orgs** need org-level webhooks
(`POST /orgs/{org}/hooks`, requires a token with `write:organization`).
## Gitea SSRF allow-list (required, one-time)
Gitea refuses to POST webhooks to in-cluster addresses by default:
```
webhook can only call allowed HTTP servers (check your webhook.ALLOWED_HOST_LIST setting),
deny 'pragent-webhook.pragent.svc.cluster.local(10.152.183.170:80)'
```
Fix: add a scoped `[webhook]` section to Gitea's `app.ini` via the helm chart's
inline-config secret (`gitea-inline-config`, key = section name `webhook`):
```ini
ALLOWED_HOST_LIST = external,loopback,*.svc.cluster.local,10.0.0.0/8,172.16.0.0/12,192.168.0.0/16,100.64.0.0/10
```
Then restart the gitea pod. Scoped to in-cluster + tailnet ranges only — not a
blanket "allow all private". A future `helm upgrade` may overwrite the inline
secret; bake it into `gitea.config.webhook.ALLOWED_HOST_LIST` in the helm values
for permanence.
## The opencode review engine
The review "brain" runs on **opencode** (the AI coding-agent CLI), not a single
cramped model call. `pilot/opencode_review.py` is the glue:
1. `fetch_archive``GET .../archive/{sha}.tar.gz`, untar into a temp workdir
(stripping the top dir) so the agent has the real files, not just the diff.
2. `write_brief` — renders `.pragent/brief.md` (title, body, diff, repo
`.pr-review.json`, prior reviews, sha, anchor hint).
3. `drop_factory` — copies `opencode.json` + `.opencode/` (agents/skills/commands)
into the workdir as the project config.
4. `run_opencode` — `opencode run --pure --format json --agent pragent
--dir <workdir> --model headroom/glm-5.2:cloud` headlessly. `--format json`
emits NDJSON events: `parse_opencode_events` reconstructs the assistant text
from `text` events and sums tokens/cost/steps from every `step_finish` event.
Returns `(text, usage)`.
It does **no Gitea I/O and no parsing** — `review_pr` parses the stdout into
`(summary, findings)`, validates findings against diff anchors, and posts. So
all v2 logic (dedupe marker, anchor validation, language-tagged suggestion
fencing, posting, optional AI-USAGE attribution) is reused and never depends on
the model remembering it.
The factory lives in the pragent repo root: `opencode.json` (provider/model/
permission) + `.opencode/` (agents, skills, commands). It is **both** the
in-cluster deploy factory **and** the local interactive factory (run
`opencode` in the repo, or `/review` via `.opencode/commands/review.md`).
`.opencode/README.md` is the factory guide: pipeline diagram, how to add a
subagent (drop a `.md` + one allow-list line), how to add a skill, how the
engine flag works, how to switch the model. **Lean by default**: the `pragent`
primary does summary + findings in one pass and runs the repo's own
`tsc`/`ruff`/`eslint`/`go vet` via bash; `security`/`tests`/`perf` subagents are
dormant lenses the primary delegates to only on large/security-sensitive diffs,
so small PRs never fan out.
### Engine flag + model ref
`PRAGENT_ENGINE=opencode` (default) selects it; `=ollama` keeps the legacy
direct `POST .../v1/messages` path as a fallback. opencode wants a
**provider-prefixed** model ref, so `review_pr` maps the bare `OLLAMA_MODEL`
(`glm-5.2:cloud`) to `headroom/glm-5.2:cloud` (override with `OPENCODE_MODEL`).
The `headroom` provider is defined in `opencode.json` with
`options.baseURL=http://100.74.17.70:8789/v1` (the headroom Anthropic proxy).
### Local one-shot (no posting)
```bash
cd ~/Projects/pragent
python3 /tmp/pragent-e2e.py <owner>/<repo> <pr_number> # driver script
# or, with opencode installed locally:
opencode run --pure --agent pragent --dir <checkout> --model headroom/glm-5.2:cloud \
"$(python3 -c 'import sys;sys.path.insert(0,"pilot");import opencode_review as o;print(o._PROMPT)')"
```
### Gotchas baked into `opencode_review.py`
- **stdin=DEVNULL** — opencode blocks on stdin (permission prompt) when run
headlessly via subprocess; closing stdin is required or it hangs to timeout.
- **Strip `ANTHROPIC_*`** — the host shell exports `ANTHROPIC_BASE_URL` /
`ANTHROPIC_AUTH_TOKEN` / `ANTHROPIC_DEFAULT_*_MODEL` (for Claude Code /
headroom). Leaked into opencode, `ANTHROPIC_DEFAULT_SONNET_MODEL=glm-5.2:cloud`
makes opencode look for provider `glm-5.2:cloud` → `ProviderModelNotFoundError`.
The headroom provider's config is self-contained, so all `ANTHROPIC_*` are
dropped from the subprocess env.
- **Shared warmed HOME** — opencode bun-installs its `@opencode-ai` runtime into
`$HOME/.config/opencode/node_modules` on first run (cold-start, ~30-60s, once
per pod lifetime). A shared, marker-warmed HOME makes every review a warm run.
## K8s deployment
Manifest: `~/k8s/pragent-webhook.yaml` (Namespace `pragent`, Deployment pinned to
`kubernets`, ClusterIP Service). The container image `pragent-webhook:opencode`
(pilot/Dockerfile: python:3.12-slim + node 20 + opencode-ai@1.3.10 + pyright /
typescript-language-server / eslint / ruff) is built locally and imported into
microk8s containerd — it is **not** pulled from a registry (`imagePullPolicy:
Never`). The webhook secret + bot token are a Secret (`pragent-webhook`). An
emptyDir at `/tmp/pragent-work` holds the per-review checkout + the warmed
opencode runtime. Verified: a regular pod on kubernets reaches both
`100.74.17.70:8789` (headroom/glm) and `gitea-http.gitea.svc.cluster.local:3000`.
Build + deploy after editing the pilot scripts or the factory:
```bash
K="microk8s kubectl"; cd ~/Projects/pragent
# 1. build the image (docker is in the microk8s group, no sudo)
docker build -t pragent-webhook:opencode -f pilot/Dockerfile .
# 2. import into microk8s containerd — sudoless. the `microk8s ctr` wrapper
# sudo-wraps even in the microk8s group, so use the raw binary against the
# group-readable containerd socket directly:
docker save pragent-webhook:opencode | \
/snap/microk8s/current/bin/ctr --address /var/snap/microk8s/common/run/containerd.sock \
--namespace k8s.io image import -
# 3. apply + roll
$K apply -f ~/k8s/pragent-webhook.yaml
$K -n pragent rollout restart deploy/pragent-webhook
$K -n pragent logs -f deploy/pragent-webhook
```
Env on the Deployment: `PRAGENT_ENGINE`, `OPENCODE_MODEL`,
`OPENCODE_EXPERIMENTAL_LSP_TOOL`, `PRAGENT_FACTORY_DIR`, `PRAGENT_OPENCODE_BIN`,
`PRAGENT_WORK_ROOT`, `PRAGENT_REVIEW_TIMEOUT`, `GITEA_API`, `OLLAMA_URL`,
`OLLAMA_MODEL`, `OLLAMA_MAX_TOKENS`, `DIFF_MAX_CHARS` are literals;
`WEBHOOK_SECRET` + `PRAGENT_BOT_TOKEN` come from the Secret.
## Relationship to the CI-step pilot
Both paths coexist. The webhook service is strictly less per-repo setup. For
repos still on the CI-step workflow (`.gitea/workflows/ai-review.yml`), retire
that file once the owner has a user-level webhook — otherwise a labeled PR gets
reviewed twice. `gitea_admin/pragent`'s own self-CI workflow was retired when the
webhook service went live.
## Known limitations (pilot)
- One model (`glm-5.2:cloud`); no tiering, no analyzer fan-out, no shared-prefix
caching. Those are framework features.
- No status checks, no fail-close (review never blocks a PR).
- Dedupe is per-commit: a re-push (new SHA) always re-reviews (by design — the
diff changed). Prior-review context is fed to the model so it doesn't repeat,
but the bot does not delete or resolve its own old reviews.
- Inline comments only anchor to post-change lines present in the diff (context +
added). A finding whose `line` the model places on a removed line or outside
the diff is folded into the summary as a bullet instead of misplaced.
- Gitea 1.26.1: system webhooks broken (see above) → user-level webhooks instead;
hook delivery-history API (`.../hooks/{id}/tasks`) returns 404, so delivery is
observed via the pragent-webhook pod logs (`kubectl -n pragent logs -f deploy/pragent-webhook`).
## Cleanup of one-time setup tokens (manual)
Token revocation via API/CLI is broken in Gitea 1.26.1 (`GET /users/{u}/tokens`
401, no CLI `delete-access-token`). Revoke these one-time setup tokens in the
Gitea admin UI (Site Administration → Users → *user* → Manage access tokens),
name prefix `pragent-`:
- `gitea_admin`: `pragent-syswh-reg-2026`, `pragent-syswh-list-2026`,
`pragent-syswh-test-2026`, `pragent-syswh-retry-2026`,
`pragent-userhook-test-2026`, `pragent-payload-look-2026`,
`pragent-cleanup-2026`, `pragent-cleanup2-2026`, `pragent-cleanup3-2026`.
- `masi`: `pragent-userhook-masi-2026`.
- `techspark`: `pragent-userhook-techspark-2026`.
(Keep `pragent-bot`'s `pragent-ci` token — that's the live reviewer credential.)