antigravity-sdk-e2e-dev

name	antigravity-sdk-e2e-dev
description	Spin up a live local agent-meow server and exercise the Antigravity (Gemini) SDK harness end-to-end — build antigravity agents, run real turns, smoke-test, and bug-bash. Load when developing, testing, or debugging the antigravity harness (agent_meow/inner/antigravity_executor.py, antigravity_harness.py, agent_meow/onboarding/antigravity_auth.py) or its auth / model / tool-bridge behavior.

Antigravity SDK harness: end-to-end dev & testing

The antigravity harness drives Google's Antigravity Python SDK (google-antigravity, an in-process Agent/Conversation) and bridges agent-meow's sys_* tools into the SDK as custom_tools. It is Gemini-native: it authenticates with a Gemini / Antigravity API key (or Vertex AI) and has no OpenAI-compatible gateway / Databricks path. This skill is the proven recipe for running it for real against a live local server — not just the unit tests.

The harness runs as a local runner from your current checkout, so omni run <bundle> --server <url> exercises exactly the code you're on.

Prerequisites (check these first)

1. You're on the branch you want to test. The antigravity harness merged to main (#194). Test on main unless validating a specific branch.
2. A Gemini API key is configured. The SDK requires one (AIza…); there is no login flow. Verify (booleans only — never print the key):

   .venv/bin/python -c "from agent_meow.onboarding.antigravity_auth import antigravity_api_key_configured as c; import os; print('config:', c(), 'env:', bool(os.environ.get('GEMINI_API_KEY') or os.environ.get('ANTIGRAVITY_API_KEY')))"
   

   If both are False, run omni setup → Antigravity and paste a key, or export GEMINI_API_KEY=AIza….
3. google-antigravity is installed (the antigravity extra — pip install "agent-meow[antigravity]"): .venv/bin/python -c "import google.antigravity as a; print(a.__file__)".
4. glibc ≥ ~2.36. The SDK spawns a native localharness binary that needs a recent glibc (GLIBC_ABI_DT_RELR). Check ldd --version | head -1. On an older host the turn fails at setup with RuntimeError: … localharness: … version 'GLIBC_ABI_DT_RELR' not found. Dev workaround on a glibc-2.31 box: point the SDK at a loader-shim via ANTIGRAVITY_HARNESS_PATH=/path/to/shim that runs the untouched bundled binary through a newer glibc's loader (see the auto-memory note antigravity-harness-glibc-native-binary.md). The shim is dev-only — the real fix is a glibc-≥2.36 host.
5. Network egress to the Gemini backend. The native binary talks to Google's API; a turn that hangs or fails to connect on a locked-down host is usually an egress problem, not a harness bug.

Step 1 — start a local server

cd /path/to/agent-meow
.venv/bin/omni server start          # spawns a detached server on a free loopback port
.venv/bin/omni server status         # prints the URL, e.g. http://127.0.0.1:6767

Use the printed URL below as $SERVER. (You can also run a foreground server on a fixed port with meow server --port 7777 --no-open.)

Step 2 — build an antigravity agent bundle

A spec with spec_version must be a directory containing config.yaml — not a single .yaml file. Minimal antigravity agent (no auth: block → it resolves the key from the antigravity: config / ambient env):

mkdir -p /tmp/agy-dev
cat > /tmp/agy-dev/config.yaml <<'YAML'
spec_version: 1
name: agy-dev
description: Antigravity SDK dev/test agent.
executor:
  type: agent-meow
  config:
    harness: antigravity
    model: gemini-3.5-flash      # default; gemini-3-pro 404s on a plain AI-Studio key
prompt: |
  You are a terse test agent. Answer in as few words as possible.
YAML

For sub-agents, tools, guardrails/policies, copy the field shapes from examples/polly/config.yaml and examples/debby/config.yaml.

Step 3 — run a turn (and smoke-test)

SERVER=http://127.0.0.1:6767   # the URL from `omni server status`
timeout 280 .venv/bin/omni run /tmp/agy-dev \
  -p "Reply with exactly the single word: PONG" \
  --server "$SERVER" 2>&1

A healthy run prints connection lines then the assistant reply (PONG). If that works, the full stack is good: Gemini key, glibc/native binary, egress, streaming, harness.

• Shell / file tools: add --tools coding.
• Specific model: add --model gemini-2.5-flash (or another Gemini id).

Targeted scenarios

Goal	How
Native tools (shell/edit/read)	--tools coding, prompt to create→read→edit a file and run a shell command; confirm it actually touches disk
Bridged sys_* / sub-agent dispatch	declare a sub-agent (tools.agents/spawn), prompt the agent to delegate — exercises the custom_tools bridge + PostToolCallHook
Model routing	run the same bundle with several --model Gemini ids; note which actually runs
Vertex AI auth	set executor.config.vertex: true + project/location and use GCP application-default creds instead of an API key
Policy / guardrail	add a guardrail that denies a keyword; confirm it blocks (see the sharp edges below — LLM-phase + tool-call enforcement was incomplete at merge)
Per-session brain override	run a bundle agent (polly/debby) and select antigravity as the brain harness (it's in BRAIN_HARNESS_LABELS)
Concurrency / leaks	fire several omni run … & at once; then pgrep -af localharness to check for orphaned native subprocesses

Gotchas (these cost real time)

1. config.yaml's server: defaults to a remote server. Omitting --server sends your turn to that remote deploy — which may be stale and reject the antigravity harness with executor.config.harness: must be one of […], got 'antigravity'. Always pass --server http://127.0.0.1:<port> for local testing. (That allowlist is agent_meow/spec/_omnigent_compat.py; if a local server rejects antigravity, it's running stale code — restart it from your checkout.)
2. A spec with spec_version must be a directory + config.yaml, never a single .yaml file.
3. Antigravity needs a Gemini key (no login). Resolution precedence: spec executor.auth (api_key) > stored antigravity: config block (omni setup)

   ambient GEMINI_API_KEY / ANTIGRAVITY_API_KEY. Vertex AI is opt-in via executor.config vertex/project/location.

4. No OpenAI gateway / Databricks. The SDK has no base_url; a databricks or generic-provider auth is warned and ignored, and the run falls back to ambient Gemini creds. Don't expect databricks-* models to route through the AI Gateway like claude-sdk/codex/pi.
5. Model ids are Gemini ids. Default gemini-3.5-flash. gemini-3-pro 404s on a plain AI-Studio key — use gemini-2.5-flash / gemini-3.5-flash unless your key has Pro access.
6. The native binary needs glibc ≥ ~2.36 (see Prereq 4). This is the most common "it won't even start" cause; check it before assuming a harness bug.
7. Turns take ~10–60s — always wrap in timeout 280.
8. Local-runner topology: omni run <bundle> --server <url> runs the harness from your current checkout; the server only holds state. The managed omni server start server runs from whatever venv launched it.

Code & tests

• Executor (SDK driver): agent_meow/inner/antigravity_executor.py
• Wrap (HARNESS_ANTIGRAVITY_ env → executor):* agent_meow/inner/antigravity_harness.py
• Auth / key resolution: agent_meow/onboarding/antigravity_auth.py
• Spawn env: _build_antigravity_spawn_env in agent_meow/runtime/workflow.py

# Unit tests (use --frozen; the cwsandbox extra is unsatisfiable on public PyPI here)
uv run --frozen --extra dev python -m pytest \
  tests/inner/test_antigravity_executor.py \
  tests/inner/test_antigravity_harness.py \
  tests/runtime/test_antigravity_spawn_env.py \
  tests/onboarding/test_antigravity_auth.py -q
# (or, if uv re-resolve is blocked on your host: .venv/bin/python -m pytest <same paths> -q)

There is no gated per-harness antigravity e2e test yet (it is deliberately excluded from the live no-AGENT harness matrix in tests/e2e/agent_meow/test_run_harness_without_agent_e2e.py, because that matrix authenticates through the Databricks gateway and antigravity is Gemini-native). This skill IS the live coverage.

Bug-bash (fan out)

To stress the harness, run several scenario probes in parallel — each builds a bundle and runs real turns against the same $SERVER, then reports what broke. Highest-value targets: the custom_tools bridge (hangs / lost tool results / errors reported as success), model routing, policy enforcement, streamed-output rendering, history retention across turns, and orphaned localharness processes after teardown.

Known sharp edges (found via the merge review — "as of this writing")

Several were merged as-is and have fix PRs in flight (#276–#281) — verify against your checkout:

• Native/built-in tools bypass the TOOL_CALL policy. Only a PostToolCallHook (post-execution, can't block) was installed at merge, so a DENY/ASK guardrail doesn't gate the SDK's native shell/file tools before they run. Bridged sys_* tools route through the server. (Fix: policy-enforcement PR.)
• LLM_REQUEST / LLM_RESPONSE policies aren't evaluated in run_turn (prompt- deny / output-block silently ignored). (Fix: policy-enforcement PR.)
• History on a fresh/rebuilt session. The SDK has no history-injection API, so prior turns are replayed as a plain-text "Conversation so far: …" prefix (user/assistant text only; tool calls aren't reconstructed). (PR #278.)
• sys_list_models can over-report OpenAI-family models for antigravity (it was mapped to the openai family for shared lookups); the worker only runs Gemini. (Fix: openai-family-cleanup PR.)
• Per-session /model override was rejected with a false "no plumbing" error. (PR #276.) Global auth: (an OpenAI key) could be adopted as a Gemini key. (PR #277.) Tool parameter schemas were dropped (model flew blind on arg shapes). (PR #279.)
• A failed turn (e.g. the glibc error, a bad model) surfaces as a failed session + an error item — if a turn returns little, check GET /v1/sessions/{id} status and …/items rather than assuming success.

Cleanup

.venv/bin/omni server stop      # stop the managed background server
rm -rf /tmp/agy-dev             # remove scratch bundles
pgrep -af "localharness"        # confirm no orphaned native subprocesses linger