diff --git a/.gitleaks.toml b/.gitleaks.toml index 1df87308..e7f82e45 100644 --- a/.gitleaks.toml +++ b/.gitleaks.toml @@ -10,9 +10,17 @@ useDefault = true [allowlist] -description = "Fake placeholder API keys used only in tests and planning docs" +description = "Fake placeholder keys (tests/docs) + gitignored per-developer agent settings" regexTarget = "match" regexes = [ '''sk_abcdef1234''', '''sk_zzzzzz9999''', ] +# `gitleaks dir` scans the working tree regardless of .gitignore, so high-entropy values +# in a developer's gitignored `.claude/settings.local.json` (a personal Claude Code file +# that never enters the repo) would fail the *local* gate while CI — which lacks the file +# — passes. Exclude the path so local runs match CI. Tracked `.claude/` files +# (settings.json, agents/, skills/) are not matched and stay scanned. +paths = [ + '''\.claude/settings\.local\.json$''', +] diff --git a/AGENTS.md b/AGENTS.md index 1f14e50a..19ee5d86 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -115,6 +115,32 @@ Lessons that cost time in agent sessions — read before exercising `uv run aai` blocking path can't wedge the session. For pytest, `--timeout N` (pytest-timeout, in the dev group) does the same per-test. +### Replay fixtures (offline end-to-end coverage) + +`tests/test_replay_e2e.py` drives whole commands (`transcribe`/`transcripts`/`llm`/ +`balance`/`usage`/`limits`) against **real** API responses recorded once and replayed +offline — the command's own parsing/rendering runs, but pytest-socket stays armed, so +these live in the default suite. Three moving parts: + +- **`tests/fixtures/api/*.json`** — scrubbed snapshots (API key/JWT redacted, `email` and + `account_id` faked, private `cdn.assemblyai.com/upload/…` URLs redacted). Committed and + gitleaks-clean; treat them like syrupy snapshots (regenerate, don't hand-edit). +- **`scripts/record_fixtures.py`** — the recorder. It is **deliberately outside the gate** + (it hits the network) and is *not* mypy/pyright-checked (only ruff covers `scripts/`). + Refresh after an API shape change: `ASSEMBLYAI_API_KEY=… uv run python scripts/record_fixtures.py`. + The key comes from the env; the AMS session JWT + `account_id` from the keyring/`config.toml` + of whoever ran `aai login` (profile `default`) — neither is ever written to a fixture. +- **`tests/replay_fixtures.py`** — rebuilds the boundary objects from JSON. A transcript is a + real `aai.Transcript` via `Transcript.from_response`; an LLM response is rebuilt with + `ChatCompletion.model_construct` (**not** `model_validate`) because the gateway returns + Anthropic-flavored fields — `finish_reason="end_turn"`, token counts under + `input_tokens`/`output_tokens` — that strict validation rejects but the OpenAI SDK itself + parses leniently. + +The replay tests patch the same boundary the unit tests do +(`commands..client.` / `.ams.` / `.gateway.complete`); the only difference is +the return value comes from a recorded payload instead of a hand-built mock. + ## Naming & packaging gotchas - The **package/module** is `aai_cli`; the **distribution** name is `aai-cli`; the **console command** is `aai` (`[project.scripts] aai = "aai_cli.main:run"`). diff --git a/aai_cli/commands/share.py b/aai_cli/commands/share.py index 0c1dc015..6e6ba672 100644 --- a/aai_cli/commands/share.py +++ b/aai_cli/commands/share.py @@ -28,9 +28,11 @@ def _cloudflared_install_hint() -> str: - if sys.platform == "darwin": - return "Install it: brew install cloudflared" - return f"Install it: {_CLOUDFLARED_DOCS}" + # A ternary (not an if/return) so neither branch reads as unreachable under + # mypy --warn-unreachable, which targets one platform at a time: on macOS the + # second return looked dead, on Linux the first would. + hint = "brew install cloudflared" if sys.platform == "darwin" else _CLOUDFLARED_DOCS + return f"Install it: {hint}" def _require_cloudflared() -> None: diff --git a/scripts/record_fixtures.py b/scripts/record_fixtures.py new file mode 100644 index 00000000..6275d53e --- /dev/null +++ b/scripts/record_fixtures.py @@ -0,0 +1,176 @@ +#!/usr/bin/env python +"""Record real AssemblyAI API responses as scrubbed JSON fixtures for replay tests. + +This is a *manual* tool, deliberately outside the test suite and the gate: it reaches +the real network. It drives the same `client.* / llm.* / ams.*` functions the CLI uses, +then serializes each result to ``tests/fixtures/api/`` with every credential scrubbed, +so the committed fixtures carry no secrets (the gate's gitleaks scan would catch any +that slipped through). + +Usage:: + + ASSEMBLYAI_API_KEY= uv run python scripts/record_fixtures.py + +The API key is read from the environment; the AMS session (JWT) is read from the OS +keyring of whoever ran ``aai login`` (profile ``default``). Neither is ever written to +a fixture. Re-run it to refresh the fixtures after an API shape change. +""" + +from __future__ import annotations + +import json +import os +import sys +from collections.abc import Callable +from datetime import UTC, datetime +from pathlib import Path +from typing import Any + +import assemblyai as aai + +from aai_cli import client, config, environments, llm +from aai_cli.auth import ams +from aai_cli.errors import CLIError + +FIXTURE_DIR = Path(__file__).resolve().parent.parent / "tests" / "fixtures" / "api" +PROFILE = "default" + +# Stable placeholders substituted for real secrets/identifiers on the way out. Replay +# tests assert against these, so they are part of the fixture contract. +FAKE_ACCOUNT_ID = 12345 +FAKE_EMAIL = "user@example.com" +REDACTED = "REDACTED" +UPLOAD_PREFIX = "https://cdn.assemblyai.com/upload/" +# API responses are shallow; a deeper structure means malformed/hostile input, so cap +# the recursion rather than risk a stack overflow on a pathologically nested payload. +_MAX_SCRUB_DEPTH = 100 + + +def _scrub_str(value: str, secret_set: set[str]) -> str: + """Redact a string value: a known secret becomes ``REDACTED``; an account upload + URL keeps its prefix but drops the high-entropy hash so no private audio leaks.""" + if value in secret_set: + return REDACTED + if value.startswith(UPLOAD_PREFIX): + return UPLOAD_PREFIX + REDACTED + return value + + +def _build_scrubber(secrets: list[str]) -> Callable[[Any], Any]: + """A recursive scrubber that redacts known secret strings and identifying keys. + + ``secrets`` are exact string values (the API key, session JWT/token) replaced with + ``REDACTED`` wherever they appear as a value. Keys named ``email``/``account_id`` + are replaced with stable fakes regardless of value, so the committed fixtures are + inert but still shaped exactly like the real responses. + """ + secret_set = {s for s in secrets if s} + + def scrub(obj: Any, depth: int = 0) -> Any: + if depth > _MAX_SCRUB_DEPTH: + raise CLIError( + f"Fixture nesting exceeded {_MAX_SCRUB_DEPTH} levels; refusing to scrub." + ) + if isinstance(obj, dict): + out: dict[str, Any] = {} + for key, value in obj.items(): + if key == "email": + out[key] = FAKE_EMAIL + elif key == "account_id": + out[key] = FAKE_ACCOUNT_ID + else: + out[key] = scrub(value, depth + 1) + return out + if isinstance(obj, list): + return [scrub(item, depth + 1) for item in obj] + if isinstance(obj, str): + return _scrub_str(obj, secret_set) + return obj + + return scrub + + +def _out(message: str) -> None: + sys.stdout.write(message + "\n") + + +def _err(message: str) -> None: + sys.stderr.write(message + "\n") + + +def _write(name: str, payload: object, scrub: Callable[[Any], Any]) -> None: + FIXTURE_DIR.mkdir(parents=True, exist_ok=True) + path = FIXTURE_DIR / f"{name}.json" + path.write_text(json.dumps(scrub(payload), indent=2) + "\n") + _out(f" wrote {path.relative_to(Path.cwd())}") + + +def _transcript_payload(transcript: aai.Transcript) -> dict[str, object]: + """The raw API ``json_response`` for a transcript — what get_by_id would parse.""" + payload = client.transcript_json_payload(transcript) + return dict(payload) + + +def main() -> int: + environments.set_active(environments.get(environments.DEFAULT_ENV)) + + api_key = os.environ.get("ASSEMBLYAI_API_KEY") + if not api_key: + _err("ASSEMBLYAI_API_KEY is not set.") + return 1 + + session = config.get_session(PROFILE) + account_id = config.get_account_id(PROFILE) + if session is None or account_id is None: + _err(f"No AMS session for profile {PROFILE!r}; run 'aai login' first.") + return 1 + jwt = session["jwt"] + scrub = _build_scrubber([api_key, jwt, session.get("token", "")]) + + # (name, thunk) — each runs independently so one failure (e.g. an LLM entitlement + # block) doesn't lose the others. The sample transcript's id feeds the get fixture. + _out(f"Recording fixtures into {FIXTURE_DIR}") + + sample = client.transcribe(api_key, client.SAMPLE_AUDIO_URL, config=aai.TranscriptionConfig()) + _write("transcribe_sample", _transcript_payload(sample), scrub) + sample_id = sample.id + if sample_id is None: # a completed transcript always has an id; guard for the type checker + raise CLIError("Transcribe returned no transcript id.") + + _write("transcripts_list", client.list_transcripts(api_key, limit=10), scrub) + + got = client.get_transcript(api_key, sample_id) + _write("transcript_get", _transcript_payload(got), scrub) + + today = datetime.now(UTC).date() + start = datetime(today.year, today.month, 1, tzinfo=UTC).isoformat() + end = datetime(today.year, today.month, today.day, tzinfo=UTC).isoformat() + + jobs: list[tuple[str, Callable[[], object]]] = [ + ("account_balance", lambda: ams.get_balance(jwt)), + ("account_usage", lambda: ams.get_usage(jwt, start, end, "day")), + ("account_limits", lambda: ams.get_rate_limits(account_id, jwt)), + ( + "llm_complete", + lambda: llm.complete( + api_key, + model=llm.DEFAULT_MODEL, + messages=llm.build_messages("Reply with exactly one word: PONG"), + max_tokens=16, + ).model_dump(mode="json"), + ), + ] + for name, thunk in jobs: + try: + _write(name, thunk(), scrub) + except CLIError as exc: + # The client/ams/llm wrappers funnel every expected network failure into a + # CLIError, so a blocked LLM entitlement skips just that fixture. + _err(f" SKIP {name}: {exc}") + + _out("Done.") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/tests/fixtures/api/account_balance.json b/tests/fixtures/api/account_balance.json new file mode 100644 index 00000000..f14a131c --- /dev/null +++ b/tests/fixtures/api/account_balance.json @@ -0,0 +1,5 @@ +{ + "account_id": 12345, + "metronome_customer_id": "cb695cb4-804e-46fe-88f8-83c1d1b3f057", + "balance_in_cents": 87958.0 +} diff --git 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And in some places, the air quality warnings include the warning to stay inside. We wanted to better understand what's happening here and why, so we called Peter DeCarlo, an associate professor in the Department of Environmental Health and Engineering at Johns Hopkins University. Good morning, Professor. Good morning. So what is it about the conditions right now that have caused this round of wildfires to affect so many people so far away? Well, there's a couple of things. The season has been pretty dry already, and then the fact that we're getting hit in the US is because there's a couple weather systems that are essentially channeling the smoke from those Canadian wildfires through Pennsylvania into the mid Atlantic and the Northeast and kind of just dropping the smoke there. So what is it in this haze that makes it harmful? And I'm assuming it is harmful. It is, it is. The levels outside right now in Baltimore are considered unhealthy. And most of that is due to what's called particulate matter, which are tiny particles, microscopic, smaller than the width of your hair, that can get into your lungs and impact your respiratory system, your cardiovascular system, and even your neurological, your brain. What makes this particularly harmful? Is it the volume of particulate? Is it something in particular? What is it exactly? Can you just drill down on that a little bit more? Yeah. So the concentration of particulate matter, I was looking at some of the monitors that we have was reaching levels of what are, in science speak, 150 micrograms per meter cubed, which is more than 10 times what the annual average should be in about four times higher than what you're supposed to have on a 24 hour average. And so the concentrations of these particles in the air are just much, much, much higher than we typically see. And exposure to those high levels can lead to a host of health problems. And who is most vulnerable? I noticed that in New York City, for example, they're canceling outdoor activities. And so here it is in the early days of summer and they have to keep all the kids inside. So who tends to be vulnerable in a situation like this? It's the youngest. So children, obviously, whose bodies are still developing, the elderly who are, you know, their bodies are more in decline and they're more susceptible to the health impacts of breathing, the poor air quality. And then people who have pre existing health conditions, people with respiratory conditions or heart conditions, can be triggered by high levels of air pollution. Could this get worse? That's a good question. I mean, I think if in some areas it's much worse than others and it just depends on kind of where the smoke is concentrated. I think New York has some of the higher concentrations right now, but that's going to change as that air moves away from the New York area. But over the course of the next few days, we will see different areas being hit at different times with the highest concentrations. I was going to ask you about more fires start burning. I don't expect the concentrations to go up too much higher. I was going to ask you how and you started to answer this, but how much longer could this last? Forgive me if I'm asking you to speculate, but what do you think? Well, I think the fires are going to burn for a little bit longer. But the key for us in the US Is the weather system changing. Right now it's the weather systems that are pulling that air into our Mid Atlantic and Northeast region. As those weather systems change and shift, we'll see that smoke going elsewhere and not impact us in this region as much. I think that's going to be the defining factor. I think the next couple days we're going to see a shift in that weather pattern and start to push the smoke away from where we are. And finally, with the impacts of climate change, we are seeing more wildfires. Will we be seeing more of these kinds of wide ranging air quality consequences or circumstances? I mean, that is one of the predictions for climate change. Looking into the future, the fire season is starting earlier and lasting longer and we're seeing more frequent fires. So yeah, this is probably something that we'll be seeing more, more frequently. This tends to be much more of an issue in the western U.S. so the eastern U.S. getting hit right now is a little bit new. But yeah, I think with climate change moving forward, this is something that is going to happen more frequently. That's Peter DeCarlo, associate professor in the Department of Environmental Health and Engineering at Johns Hopkins University. Professor DeCarlo, thanks so much for joining us and sharing this expertise with us. 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And in some places, the air quality warnings include the warning to stay inside. We wanted to better understand what's happening here and why, so we called Peter DeCarlo, an associate professor in the Department of Environmental Health and Engineering at Johns Hopkins University. Good morning, Professor. Good morning. So what is it about the conditions right now that have caused this round of wildfires to affect so many people so far away? Well, there's a couple of things. The season has been pretty dry already, and then the fact that we're getting hit in the US is because there's a couple weather systems that are essentially channeling the smoke from those Canadian wildfires through Pennsylvania into the mid Atlantic and the Northeast and kind of just dropping the smoke there. So what is it in this haze that makes it harmful? And I'm assuming it is harmful. It is, it is. The levels outside right now in Baltimore are considered unhealthy. And most of that is due to what's called particulate matter, which are tiny particles, microscopic, smaller than the width of your hair, that can get into your lungs and impact your respiratory system, your cardiovascular system, and even your neurological, your brain. What makes this particularly harmful? Is it the volume of particulate? Is it something in particular? What is it exactly? Can you just drill down on that a little bit more? Yeah. So the concentration of particulate matter, I was looking at some of the monitors that we have was reaching levels of what are, in science speak, 150 micrograms per meter cubed, which is more than 10 times what the annual average should be in about four times higher than what you're supposed to have on a 24 hour average. And so the concentrations of these particles in the air are just much, much, much higher than we typically see. And exposure to those high levels can lead to a host of health problems. And who is most vulnerable? I noticed that in New York City, for example, they're canceling outdoor activities. And so here it is in the early days of summer and they have to keep all the kids inside. So who tends to be vulnerable in a situation like this? It's the youngest. So children, obviously, whose bodies are still developing, the elderly who are, you know, their bodies are more in decline and they're more susceptible to the health impacts of breathing, the poor air quality. And then people who have pre existing health conditions, people with respiratory conditions or heart conditions, can be triggered by high levels of air pollution. Could this get worse? That's a good question. I mean, I think if in some areas it's much worse than others and it just depends on kind of where the smoke is concentrated. I think New York has some of the higher concentrations right now, but that's going to change as that air moves away from the New York area. But over the course of the next few days, we will see different areas being hit at different times with the highest concentrations. I was going to ask you about more fires start burning. I don't expect the concentrations to go up too much higher. I was going to ask you how and you started to answer this, but how much longer could this last? Forgive me if I'm asking you to speculate, but what do you think? Well, I think the fires are going to burn for a little bit longer. But the key for us in the US Is the weather system changing. Right now it's the weather systems that are pulling that air into our Mid Atlantic and Northeast region. As those weather systems change and shift, we'll see that smoke going elsewhere and not impact us in this region as much. I think that's going to be the defining factor. I think the next couple days we're going to see a shift in that weather pattern and start to push the smoke away from where we are. And finally, with the impacts of climate change, we are seeing more wildfires. Will we be seeing more of these kinds of wide ranging air quality consequences or circumstances? I mean, that is one of the predictions for climate change. Looking into the future, the fire season is starting earlier and lasting longer and we're seeing more frequent fires. So yeah, this is probably something that we'll be seeing more, more frequently. This tends to be much more of an issue in the western U.S. so the eastern U.S. getting hit right now is a little bit new. But yeah, I think with climate change moving forward, this is something that is going to happen more frequently. That's Peter DeCarlo, associate professor in the Department of Environmental Health and Engineering at Johns Hopkins University. Professor DeCarlo, thanks so much for joining us and sharing this expertise with us. 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0.99853516, + "speaker": null, + "channel": null + }, + { + "text": "me.", + "start": 280210, + "end": 280530, + "confidence": 0.9980469, + "speaker": null, + "channel": null + } + ], + "utterances": null, + "unredacted_text": null, + "unredacted_words": null, + "unredacted_utterances": null, + "confidence": 0.9786635, + "audio_duration": 282, + "webhook_status_code": null, + "webhook_auth": false, + "summary": null, + "auto_highlights_result": null, + "content_safety_labels": null, + "iab_categories_result": null, + "chapters": null, + "sentiment_analysis_results": null, + "entities": null, + "speech_model_used": "universal-2", + "translated_texts": null, + "metadata": { + "domain_used": null, + "warning": null, + "warnings": [ + { + "message": "For highest accuracy and broadest language coverage: set \"speech_models\" to [\"universal-3-pro\", \"universal-2\"]." + } + ] + } +} diff --git a/tests/fixtures/api/transcripts_list.json b/tests/fixtures/api/transcripts_list.json new file 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See ``tests/test_replay_e2e.py`` for the replay tests. +""" + +from __future__ import annotations + +import json +from pathlib import Path + +import assemblyai as aai +from assemblyai import types +from openai.types.chat import ChatCompletion + +FIXTURE_DIR = Path(__file__).parent / "fixtures" / "api" + + +def load_object(name: str) -> dict[str, object]: + """Parse a fixture recorded from a JSON *object* response.""" + data = json.loads((FIXTURE_DIR / f"{name}.json").read_text()) + assert isinstance(data, dict) + return data + + +def load_list(name: str) -> list[dict[str, object]]: + """Parse a fixture recorded from a JSON *array* response.""" + data = json.loads((FIXTURE_DIR / f"{name}.json").read_text()) + assert isinstance(data, list) + return data + + +def transcript(name: str) -> aai.Transcript: + """Rebuild a real SDK Transcript from a recorded ``json_response``, offline. + + Mirrors what ``Transcript.get_by_id`` returns, so the command's real render path + (``transcribe_render`` / ``select_transcript_field``) runs against the recorded + payload. Setting a placeholder key lets ``get_default()`` build a client without a + request; ``from_response`` parses the payload locally. + """ + aai.settings.api_key = "replay-key" + response = types.TranscriptResponse(**load_object(name)) + return aai.Transcript.from_response(client=aai.Client.get_default(), response=response) + + +def completion(name: str) -> ChatCompletion: + """Rebuild an OpenAI ChatCompletion the way the SDK parses a wire response. + + The gateway returns Anthropic-flavored fields (``finish_reason='end_turn'``, token + counts under ``input_tokens``/``output_tokens``) that strict validation rejects; the + OpenAI SDK builds responses with the lenient, recursive ``model_construct``, so the + replay rebuild does too — matching exactly what the live command receives. + """ + return ChatCompletion.model_construct(None, **load_object(name)) diff --git a/tests/test_replay_e2e.py b/tests/test_replay_e2e.py new file mode 100644 index 00000000..db07670b --- /dev/null +++ b/tests/test_replay_e2e.py @@ -0,0 +1,129 @@ +"""End-to-end replay tests: drive real CLI commands against recorded API responses. + +Each test patches the command's network boundary (``client.* / llm.* / ams.*``) to +return an object rebuilt from a real, scrubbed fixture (see ``tests/replay_fixtures.py`` +and ``scripts/record_fixtures.py``), then invokes the command through Typer and asserts +on the rendered output. The transport stays offline — pytest-socket is untouched — but +the command's own parsing, formatting, and rendering all run against a real payload. +""" + +from __future__ import annotations + +from typer.testing import CliRunner + +from aai_cli import config +from aai_cli.main import app +from tests import replay_fixtures as rf + +runner = CliRunner() + + +def _human(monkeypatch): + """Pin human output (the real default) so output assertions don't depend on a tty.""" + monkeypatch.setattr("aai_cli.output.resolve_json", lambda *, explicit: explicit) + + +def _with_api_key(): + config.set_api_key("default", "sk_live") + + +def _with_session(): + config.set_session("default", session_jwt="jwt", session_token="tok", account_id=12345) + + +def test_transcribe_sample_renders_real_transcript(monkeypatch, mocker): + _with_api_key() + _human(monkeypatch) + mocker.patch( + "aai_cli.commands.transcribe.client.transcribe", + autospec=True, + return_value=rf.transcript("transcribe_sample"), + ) + result = runner.invoke(app, ["transcribe", "--sample"]) + assert result.exit_code == 0 + assert "Smoke from hundreds of wildfires" in result.output + + +def test_transcripts_get_renders_real_text(monkeypatch, mocker): + _with_api_key() + _human(monkeypatch) + mocker.patch( + "aai_cli.commands.transcripts.client.get_transcript", + autospec=True, + return_value=rf.transcript("transcript_get"), + ) + result = runner.invoke(app, ["transcripts", "get", "e5a56f4f-b658-44b0-925a-f7d761ec0d96"]) + assert result.exit_code == 0 + assert "Smoke from hundreds of wildfires" in result.output + + +def test_transcripts_list_renders_real_rows(monkeypatch, mocker): + _with_api_key() + _human(monkeypatch) + mocker.patch( + "aai_cli.commands.transcripts.client.list_transcripts", + autospec=True, + return_value=rf.load_list("transcripts_list"), + ) + result = runner.invoke(app, ["transcripts", "list"]) + assert result.exit_code == 0 + # The recorded history mixes statuses (a YouTube download failed) under the standard + # table headers, so both the real statuses and the header render. + assert "completed" in result.output + assert "error" in result.output + assert "status" in result.output + + +def test_llm_renders_real_completion(monkeypatch, mocker): + _with_api_key() + _human(monkeypatch) + mocker.patch( + "aai_cli.commands.llm.gateway.complete", + autospec=True, + return_value=rf.completion("llm_complete"), + ) + result = runner.invoke(app, ["llm", "Reply with exactly one word: PONG"]) + assert result.exit_code == 0 + assert "PONG" in result.output + + +def test_balance_renders_real_dollars(monkeypatch, mocker): + _with_session() + _human(monkeypatch) + mocker.patch( + "aai_cli.commands.account.ams.get_balance", + autospec=True, + return_value=rf.load_object("account_balance"), + ) + result = runner.invoke(app, ["balance"]) + assert result.exit_code == 0 + assert "$879.58" in result.output + + +def test_usage_renders_real_breakdown(monkeypatch, mocker): + _with_session() + _human(monkeypatch) + mocker.patch( + "aai_cli.commands.account.ams.get_usage", + autospec=True, + return_value=rf.load_object("account_usage"), + ) + result = runner.invoke(app, ["usage"]) + assert result.exit_code == 0 + assert "Usage total:" in result.output + # The recorded month has real Speech-to-Text spend, rendered as a dollar breakdown. + assert "Universal" in result.output + assert "$" in result.output + + +def test_limits_renders_no_custom_limits(monkeypatch, mocker): + _with_session() + _human(monkeypatch) + mocker.patch( + "aai_cli.commands.account.ams.get_rate_limits", + autospec=True, + return_value=rf.load_object("account_limits"), + ) + result = runner.invoke(app, ["limits"]) + assert result.exit_code == 0 + assert "No custom rate limits" in result.output diff --git a/tests/test_source_validation.py b/tests/test_source_validation.py index 1a7997a1..294a9ac9 100644 --- a/tests/test_source_validation.py +++ b/tests/test_source_validation.py @@ -72,9 +72,10 @@ def test_transcribe_directory_source_fails_before_credentials(mocker, tmp_path): tx = mocker.patch("aai_cli.commands.transcribe.client.transcribe", autospec=True) result = runner.invoke(app, ["transcribe", str(tmp_path)]) assert result.exit_code == 2 - # Rich may wrap the long tmp path mid-message; compare on unwrapped text. - unwrapped = " ".join(result.output.split()) - assert f"Not a file: {tmp_path}" in unwrapped + # Rich may wrap the long tmp path mid-token (even inside a word), so compare with + # all whitespace removed — matching the pattern in test_share.py. + packed = "".join(result.output.split()) + assert "".join(f"Not a file: {tmp_path}".split()) in packed assert "starting browser login" not in result.output tx.assert_not_called()