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63ce88f874
* add caller identity in replay e2e * make format * fix(replay-e2e): stabilize title caller replay * fix(replay-e2e): use captured caller without run manager --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
121 lines
6.2 KiB
Markdown
121 lines
6.2 KiB
Markdown
# Record/Replay E2E — front-back contract verification
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Deterministic, **key-free** end-to-end checks that a backend change can't
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silently break the frontend (and vice-versa). Two complementary layers, fed by a
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single recording.
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## Why
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The mock-based frontend e2e hand-writes the backend's JSON/SSE, so a backend
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schema or SSE change passes green ("fake green"). These layers replay a recorded
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**real** run against the **real** backend (and, for Layer 2, the real frontend),
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so contract drift turns the build red instead.
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## The two layers
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- **Layer 1 — backend golden** (`tests/test_replay_golden.py`): replays a fixture
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through the real FastAPI gateway with `ReplayChatModel` and asserts the streamed
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SSE event sequence equals a committed golden. Fast, no browser. Guards protocol
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*shape*.
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- **Layer 2 — full-stack render** (`frontend/tests/e2e-real-backend/`): real
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Next.js + real gateway (replay model) + Chromium; asserts the replayed
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auto-title and a follow-up suggestion render in the browser. Guards semantic
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*render*. (Complementary to Layer 1 — neither subsumes the other.)
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Layer 2 also hosts **cross-stack contract scenarios** — the dangerous class
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where a backend change silently breaks a frontend assumption and *both sides'
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unit tests stay green*. See below.
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## Cross-stack scenario: multi-run render order (`multi-run-order.spec.ts`)
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Regression guard for issue **#3352** (after context compression, refreshing a
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thread rendered history out of order). Root cause was a front-back desync:
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backend `RunManager.list_by_thread` returns runs **newest-first** (PR #2932),
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while the frontend (`core/threads/hooks.ts`) iterated runs and **prepended** each
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loaded page — inverting chronological order once the checkpoint no longer held
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the older messages. The backend ordering test was green throughout, and the
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frontend regression unit test hardcodes "backend returns newest-first" in a mock,
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so only a *real frontend against a real backend* catches the desync.
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This scenario does **not** record a conversation. It uses a **test-only seeder**
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(`tests/seed_runs_router.py`, mounted on the replay gateway only when
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`DEERFLOW_ENABLE_TEST_SEED=1`) to stand up a thread with ≥2 runs and per-run
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message events — and deliberately **no checkpoint**, which is the #3352
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precondition: it forces the frontend's per-run reload path to be the sole source
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of truth so the ordering bug becomes observable. The seeder writes through the
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gateway's own run/event stores using the request's auth context, so the real
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`list_by_thread` → `/runs/{id}/messages` → prepend path runs live. Reverting the
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#3354 frontend fix turns this spec red.
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## How replay works
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`tests/replay_provider.py::ReplayChatModel` returns recorded assistant turns keyed
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by a **normalized hash of the model caller + conversation**. The conversation is
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human / ai / tool messages — role, text, tool-call name+args; with
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`<system-reminder>`, dates, UUIDs, tmp paths stripped. The caller is the stable
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source of the model call (`lead_agent`, `middleware:title`, `suggest_agent`,
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`subagent:*`, etc.). A miss raises loudly rather than passing silently.
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**The system prompt is excluded from the match key.** The lead-agent system
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prompt is a living, frequently-edited implementation detail — its wording changes
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across PRs (e.g. #3195 added a "File Editing Workflow" section). Hashing it would
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make every fixture go stale and red-fail unrelated PRs the moment anyone edits the
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prompt. The conversation flow (user input → tool calls → results → answer) is the
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stable contract that identifies a recorded turn. The caller still stays in the
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key so two different model users with identical conversation text do not compete
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for the same replay bucket. (This mirrors how open-design's mock picker keys on
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the user prompt, not the system internals.) Combined with pinning skills +
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extensions empty and disabling memory/summarization
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(`tests/_replay_fixture.py::build_config_yaml`), a fixture replays the same across
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machines, days, prompt edits, and CI. Replaying needs **no API key**.
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A swallowed hash-miss keeps the SSE *event shapes* identical (the gateway wraps it
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into a normal assistant error message), so the Layer-1 golden can't catch a miss
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by shape alone — it inspects `replay_provider.replay_misses()` and fails loud
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instead. Layer-2 already fails on a miss (the recorded turns never render).
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## Record a new scenario (needs a real key — dev machine only)
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Recording drives the **real frontend** so captured inputs match exactly what the
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browser sends; fixtures contain no API key.
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```bash
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# 1. drive the real frontend against a real-model gateway, capturing model calls
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OPENAI_API_KEY=... OPENAI_API_BASE=<openai-compatible-endpoint>/v1 \
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DEERFLOW_RECORD_OUT=/tmp/rec/turns.jsonl RECORD_MODEL=<model> \
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bash -c 'cd frontend && pnpm exec playwright test -c playwright.record.config.ts'
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# 2. stitch the capture into a fixture
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cd backend && uv run python scripts/build_fixture_from_jsonl.py \
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--jsonl /tmp/rec/turns.jsonl --meta /tmp/rec/turns.jsonl.meta.json \
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--out tests/fixtures/replay/<scenario>.<mode>.json --model <model>
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# 3. regenerate the committed golden
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DEERFLOW_WRITE_GOLDEN=1 PYTHONPATH=. uv run pytest tests/test_replay_golden.py
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```
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## Run (no key)
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```bash
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cd backend && PYTHONPATH=. uv run pytest tests/test_replay_golden.py # Layer 1
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cd frontend && pnpm exec playwright test -c playwright.real-backend.config.ts # Layer 2
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```
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## CI
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`.github/workflows/replay-e2e.yml` runs both layers on changes to **either** side
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of the contract (`frontend/**`, `backend/app/gateway/**`,
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`backend/packages/harness/**`, fixtures). DOM assertions are the gate; the rendered
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screenshot + Playwright HTML report are uploaded as a CI artifact.
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## Known limitations
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- Visual regression baselines are OS-specific, so they are a **local dev gate
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only** (gitignored); CI uploads the render as an artifact for human review
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instead of hard-asserting a cross-OS baseline.
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- Fixtures are coupled to the recording-time prompt; if new
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environment-dependent content enters the system prompt, extend the
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normalization in `replay_provider.py` (or pin it in `build_config_yaml`).
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- Re-record a scenario if the agent graph changes how many model calls it makes
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— the replay raises loudly on a hash miss pointing at the divergence.
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