gflow-cli

Unofficial Python CLI for Google Flow. Drive Veo (image-to-video, text-to-video) and Imagen (text-to-image) from your terminal: scripted, batched, pipeline-ready.

⚠️ Read this before you install. gflow-cli is unofficial, alpha, and reverse-engineered — not affiliated with Google. It drives a headed browser on your own Google Flow session, so treat it as your own account risk: automation is subject to Google's ToS, and endpoints or UI can change without notice. It works with any Google account that has Flow access, and every generation bills against your account's Flow credit allowance. Read the full DISCLAIMER.

💳 What failure costs you. Credits are only spent on Veo video generation — images and composition ops are free, so most breakage costs nothing. When Flow's UI drifts mid-run, the CLI fails fast and loudly with distinct exit codes (e.g. selector drift = exit 23) instead of resubmitting, and batch items are recorded locally before submission so a broken run never silently burns credits on a stale state. See KNOWN_ISSUES for the current risk list.

🌐 Headed browser today. gflow drives Flow through a persistent Playwright Chromium profile, because Google's auth and reCAPTCHA gates require it. The Architecture section shows where you can help.

Why gflow-cli?

You have a Google account with Flow access, you have Veo credits, and you run real batch work. gflow-cli gives you:

• Batch generation. Loop prompts straight from the shell: for p in $(cat prompts.txt); do gflow image t2i "$p"; done. Image batching plus gflow video t2v / i2v / r2v all ship today.
• Consistent subjects. gflow character create mints a Flow Character (face and body reference) so the same person appears from one generation to the next.
• Prompt tools. --tool creative-director rewrites a terse prompt into a vivid one (Google's 5-component formula) before generating — on any command. Bring your own with My Tools.
• Pipelines. Wire Veo into your content automation, AI-video stack, or batch experiments.
• Terminal-native. After one gflow auth login, you stay in the shell. No clicking through dialogs.

Same Veo and Imagen models, same quality, same billing against your own Google account, now programmatic.

60-second quick start

# 1 · Install (uv recommended; also: pip install gflow-cli)
uv tool install gflow-cli
uv tool run --from gflow-cli playwright install chromium     # one-time, ~150 MB

# 2 · Authenticate (one-time, opens a real Chrome window)
gflow auth login --browser chrome

# 3 · Generate
gflow image t2i "a hot air balloon over Tokyo at sunrise"
# or:
gflow video t2v "Slow cinematic push-in on a sunlit forest clearing" --aspect 16:9
# or mint a reusable Character (face + body reference):
gflow character create --project <id> --name "Aria" --face-prompt "..." --body-prompt "..."

Outputs land under $GFLOW_CLI_OUTPUT_DIR, or you can route them to S3, MinIO, or Google Cloud Storage with GFLOW_CLI_STORAGE_URI. The first call takes 30 to 90 seconds while Chromium warms up; later calls reuse the warm session.

Why --browser chrome? Google rejects Playwright's bundled Chromium. The CLI fails fast with a friendly error (AuthBrowserRejectedError, exit code 14) if you pick anything else.

Installing from a local checkout? uv tool install <path> ignores uv.lock and resolves dependencies from the pyproject.toml ranges, so it can hand you a Playwright build this project has never tested. Playwright ships the browser driver, and an untested minor can wedge a generation silently. Carry the locked version explicitly:

uv tool install --force --with playwright==1.59.0 .

Installing from PyPI (uv tool install gflow-cli) is unaffected — the published range is upper-bounded. Check what you actually have with uv tool run --from gflow-cli python -c "import importlib.metadata as m; print(m.version('playwright'))".

For the full 10-minute walkthrough with troubleshooting and multi-account setup, see USER_GUIDE: Journey 1.

Examples

One command in, real Flow output back. Left: gflow image t2i generating a photorealistic scene in your library. Right: a frame-to-frame transform.

Demo

A single gflow image t2i "..." --aspect 9:16 --model nano2 call against a logged-in Flow profile. The terminal streams the run's structlog JSON, then lists the written PNG. Chromium drives the Flow editor silently in the background.

Reproduce the recording with scripts/record_demo.ps1 (Windows, OBS, ffmpeg, gifski). More formats, including the side-by-side split-screen: docs/DEMOS.md.

Documentation

docs/INDEX.md is the master routing layer. Quick links:

For AI agents & LLMs

gflow-cli ships four agent entry points. Pick the one your tool reads first.

Onboard any agent in one line. Paste this into your agent of choice:

"Read AGENTS.md and docs/INDEX.md, then help me with my Flow batch."

Architecture & current limitations

gflow CLI  →  Provider (interchangeable)  →  Flow (ui_automation) / Mock (tests) / [planned: Official Veo]
                                              ↓
                                      Playwright Chromium (headed — login AND generation, by default)
                                              ↓
                              aisandbox-pa.googleapis.com  (Google's private Flow API)

Current transport: ui_automation drives Flow through a persistent Playwright Chromium profile. It is production-stable and verified end-to-end every release (see the per-release LIVE_VERIFICATION_* evidence files).

What's blocked: a pure HTTP transport for video generation. The video upload endpoint returns HTTP 401 under non-Chrome browsers plus a reCAPTCHA mint we cannot reproduce headlessly. Three earlier HTTP strategies (evaluate_fetch, bearer, sapisidhash) live under src/gflow_cli/api/transports/experimental/ for research, off the production path.

How you can help: if you have driven aisandbox-pa.googleapis.com from outside a real Chrome session, or you understand Google'