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* docs(spec): MiniMax integration for generation skills + new music skill
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs(plan): MiniMax generation providers implementation plan
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* test(skills): add importlib loader + FakeResp for skill tests
* test(skills): register loaded module in sys.modules; raise requests.HTTPError in FakeResp
* feat(image-generation): add MiniMax provider with env auto-detect
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* refactor(image-generation): guard unknown provider, derive ref MIME, strengthen tests
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(video-generation): add MiniMax provider with async poll/download
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* refactor(video-generation): surface base_resp errors while polling; add timeout test
* feat(podcast-generation): add MiniMax t2a_v2 provider with env auto-detect
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* refactor(podcast-generation): restore TTS credential guard; add volcengine + voice tests
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat(music-generation): new MiniMax music skill via skill-creator
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* refactor(music-generation): treat empty lyrics as absent; test no-audio-data path
* refactor(skills): add request timeouts to MiniMax network calls
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* Potential fix for pull request finding 'Explicit returns mixed with implicit (fall through) returns'
Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>
* fix(models): strip inconsistent user-message names for MiniMax chat
DeerFlow middlewares tag user messages with provenance names (user-input, summary, loop_warning); langchain serializes them into the OpenAI-compatible payload and MiniMax rejects mismatched user-message names with "user name must be consistent (2013)". PatchedChatMiniMax now drops the per-message name from user-role messages. Point the config.example MiniMax models at PatchedChatMiniMax so they also get reasoning_content mapping.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(image-generation): MiniMax sends JSON prompt field, guard 1500-char limit
MiniMax image-01 takes one text string capped at 1500 chars, but the skill was sending the whole structured JSON. The MiniMax provider now extracts the JSON `prompt` field (relying on prompt_optimizer to expand it) and fails fast with a clear error before calling the API when that field exceeds 1500 chars. Authoring stays provider-agnostic; Gemini still receives the full JSON.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(podcast-generation): per-provider TTS concurrency and retry/backoff
Each TTS provider owns its concurrency internally — MiniMax runs single-threaded to reduce rate-limit failures, Volcengine keeps 4 workers — with automatic retry and backoff on transient HTTP and base_resp errors. No caller-facing concurrency knob.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(skills): address Copilot review comments on generation skills
- video: add raise_for_status + timeout to the Gemini download/POST/poll calls so non-2xx responses surface as clear HTTP errors instead of JSON/KeyError or hangs
- video: check the task Fail status before the generic base_resp check so the failure keeps its task_id context
- video/image: create the output file parent directory before writing (matching music-generation) so nested output paths do not raise FileNotFoundError
- music: require a non-empty prompt and fail fast with ValueError instead of sending an empty prompt to the API
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(scripts): reclaim dev ports across worktrees in make stop/dev
All deer-flow worktrees (main checkout + linked worktrees) hardcode the same dev ports (8001/3000/2026), so a service started from any worktree must be reclaimable from another. stop_all now resolves the set of worktree roots (DEERFLOW_ROOTS) and treats a process as deer-flow-owned when its open files live under any of them. It also force-kills survivors on 2026 alongside 8001/3000, fixing `make dev` aborting on the nginx port preflight when a prior nginx lingered on 2026.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(view-image): hide the injected image-context message from the UI
ViewImageMiddleware injects a HumanMessage (text + base64 images) so the vision model can see viewed images, but it was the only internal injector that set neither hide_from_ui nor a hidden name, so it leaked into the chat UI (and IM channels) as a user bubble reading "Here are the images you've viewed:". Mark it with additional_kwargs={"hide_from_ui": True}, matching todo/dynamic_context injections, which the frontend isHiddenFromUIMessage and the channel sender already honor. The model still receives the full content.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(minimax): mark M2.7 models as text-only (no vision)
MiniMax M2.7 / M2.7-highspeed do not support vision; only M3 does. The
provider config asserted vision support for M2.7 in four places.
- config.example.yaml: 4 M2.7 entries -> supports_vision: false
- backend/docs/CONFIGURATION.md: M2.7 + highspeed -> supports_vision: false
- wizard: add LLMProvider.model_vision_overrides + extra_config_for() so
selecting an M2.7 model writes supports_vision: false while M3 (default)
keeps vision; wire it through setup_wizard.py
- tests: M2.7-highspeed fixture -> supports_vision=False; add
test_minimax_vision_is_per_model
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>
254 lines
9.1 KiB
Python
254 lines
9.1 KiB
Python
import sys
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from pathlib import Path
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import pytest
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sys.path.insert(0, str(Path(__file__).resolve().parent))
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from skill_loader import FakeResp, load # noqa: E402
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pod = load("podcast-generation")
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@pytest.fixture(autouse=True)
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def clean_env(monkeypatch):
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for k in ["VOLCENGINE_TTS_APPID", "VOLCENGINE_TTS_ACCESS_TOKEN", "VOLCENGINE_TTS_CLUSTER",
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"MINIMAX_API_KEY", "PODCAST_GENERATION_PROVIDER", "MINIMAX_API_HOST",
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"MINIMAX_TTS_MODEL", "MINIMAX_TTS_VOICE_MALE", "MINIMAX_TTS_VOICE_FEMALE",
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"MINIMAX_TTS_MAX_RETRIES"]:
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monkeypatch.delenv(k, raising=False)
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# never actually sleep during backoff in tests
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monkeypatch.setattr(pod.time, "sleep", lambda *_: None)
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def test_resolve_prefers_volcengine(monkeypatch):
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monkeypatch.setenv("VOLCENGINE_TTS_APPID", "a")
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monkeypatch.setenv("VOLCENGINE_TTS_ACCESS_TOKEN", "t")
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assert pod._resolve_tts_provider() == "volcengine"
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def test_resolve_falls_back_to_minimax(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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assert pod._resolve_tts_provider() == "minimax"
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def test_resolve_override(monkeypatch):
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monkeypatch.setenv("VOLCENGINE_TTS_APPID", "a")
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monkeypatch.setenv("VOLCENGINE_TTS_ACCESS_TOKEN", "t")
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monkeypatch.setenv("PODCAST_GENERATION_PROVIDER", "minimax")
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assert pod._resolve_tts_provider() == "minimax"
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def test_resolve_unknown_raises(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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monkeypatch.setenv("PODCAST_GENERATION_PROVIDER", "openai")
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with pytest.raises(ValueError):
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pod._resolve_tts_provider()
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def test_minimax_tts_decodes_hex(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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captured = {}
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def fake_post(url, headers=None, json=None, **kw):
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captured["url"] = url
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captured["json"] = json
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return FakeResp({"data": {"audio": b"audiobytes".hex(), "status": 2},
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"base_resp": {"status_code": 0}})
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monkeypatch.setattr(pod.requests, "post", fake_post)
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out = pod.text_to_speech_minimax("hello", "male-qn-qingse")
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assert out == b"audiobytes"
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assert captured["url"].endswith("/v1/t2a_v2")
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assert captured["json"]["voice_setting"]["voice_id"] == "male-qn-qingse"
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assert captured["json"]["output_format"] == "hex"
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def test_process_line_minimax_voice_mapping(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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seen = {}
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def fake_tts(text, voice_id):
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seen["voice_id"] = voice_id
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return b"x"
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monkeypatch.setattr(pod, "text_to_speech_minimax", fake_tts)
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line = pod.ScriptLine(speaker="female", paragraph="hi")
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idx, audio = pod._process_line((0, line, 1, "minimax"))
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assert audio == b"x"
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assert seen["voice_id"] == "female-tianmei"
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def test_generate_podcast_minimax_end_to_end(monkeypatch, tmp_path):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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def fake_post(url, headers=None, json=None, **kw):
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return FakeResp({"data": {"audio": b"chunk".hex(), "status": 2},
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"base_resp": {"status_code": 0}})
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monkeypatch.setattr(pod.requests, "post", fake_post)
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script = tmp_path / "s.json"
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script.write_text(
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'{"title":"T","locale":"en","lines":[{"speaker":"male","paragraph":"a"},'
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'{"speaker":"female","paragraph":"b"}]}',
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encoding="utf-8",
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)
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out = tmp_path / "o.mp3"
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msg = pod.generate_podcast(str(script), str(out), None)
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assert out.read_bytes() == b"chunkchunk"
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assert "Successfully generated podcast" in msg
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def test_volcengine_tts_decodes_base64(monkeypatch):
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import base64
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monkeypatch.setenv("VOLCENGINE_TTS_APPID", "a")
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monkeypatch.setenv("VOLCENGINE_TTS_ACCESS_TOKEN", "t")
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def fake_post(url, headers=None, json=None, **kw):
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return FakeResp({"code": 3000, "data": base64.b64encode(b"volcbytes").decode()})
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monkeypatch.setattr(pod.requests, "post", fake_post)
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out = pod.text_to_speech_volcengine("hi", "zh_male_yangguangqingnian_moon_bigtts")
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assert out == b"volcbytes"
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def test_volcengine_without_creds_raises(monkeypatch):
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monkeypatch.setenv("PODCAST_GENERATION_PROVIDER", "volcengine")
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script = pod.Script(lines=[pod.ScriptLine("male", "a")])
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with pytest.raises(ValueError):
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pod.tts_node(script)
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def test_process_line_minimax_male_and_override(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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seen = []
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def fake_tts(text, voice_id):
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seen.append(voice_id)
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return b"x"
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monkeypatch.setattr(pod, "text_to_speech_minimax", fake_tts)
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male = pod.ScriptLine(speaker="male", paragraph="hi")
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pod._process_line((0, male, 1, "minimax"))
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assert seen[-1] == "male-qn-qingse"
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monkeypatch.setenv("MINIMAX_TTS_VOICE_MALE", "custom-male")
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pod._process_line((0, male, 1, "minimax"))
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assert seen[-1] == "custom-male"
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def _seq_post(responses):
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"""Return a fake requests.post that yields the given responses in order."""
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calls = {"n": 0}
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def fake_post(*a, **k):
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resp = responses[min(calls["n"], len(responses) - 1)]
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calls["n"] += 1
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return resp
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return fake_post, calls
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def test_minimax_retries_on_rate_limit_code(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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fake_post, calls = _seq_post([
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FakeResp({"base_resp": {"status_code": 1002, "status_msg": "rate limit"}}),
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FakeResp({"base_resp": {"status_code": 1039, "status_msg": "tpm limit"}}),
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FakeResp({"data": {"audio": b"ok".hex()}, "base_resp": {"status_code": 0}}),
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])
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monkeypatch.setattr(pod.requests, "post", fake_post)
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out = pod.text_to_speech_minimax("hi", "male-qn-qingse", max_retries=3)
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assert out == b"ok"
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assert calls["n"] == 3 # two retries then success
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def test_minimax_retries_on_http_429(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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fake_post, calls = _seq_post([
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FakeResp({}, status_code=429),
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FakeResp({"data": {"audio": b"ok".hex()}, "base_resp": {"status_code": 0}}),
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])
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monkeypatch.setattr(pod.requests, "post", fake_post)
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out = pod.text_to_speech_minimax("hi", "male-qn-qingse", max_retries=3)
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assert out == b"ok"
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assert calls["n"] == 2
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def test_minimax_no_retry_on_auth_error(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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fake_post, calls = _seq_post([
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FakeResp({"base_resp": {"status_code": 1004, "status_msg": "auth failed"}}),
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FakeResp({"data": {"audio": b"never".hex()}, "base_resp": {"status_code": 0}}),
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])
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monkeypatch.setattr(pod.requests, "post", fake_post)
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out = pod.text_to_speech_minimax("hi", "male-qn-qingse", max_retries=3)
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assert out is None
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assert calls["n"] == 1 # permanent error: no retry
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def test_minimax_gives_up_after_max_retries(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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fake_post, calls = _seq_post([
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FakeResp({"base_resp": {"status_code": 1002, "status_msg": "rate limit"}}),
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])
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monkeypatch.setattr(pod.requests, "post", fake_post)
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out = pod.text_to_speech_minimax("hi", "male-qn-qingse", max_retries=2)
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assert out is None
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assert calls["n"] == 3 # initial attempt + 2 retries
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def test_tts_node_raises_on_partial_failure(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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calls = {"n": 0}
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def fake_tts(text, voice_id, **kw):
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calls["n"] += 1
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return b"x" if calls["n"] == 1 else None
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monkeypatch.setattr(pod, "text_to_speech_minimax", fake_tts)
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script = pod.Script(lines=[pod.ScriptLine("male", "a"), pod.ScriptLine("female", "b")])
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with pytest.raises(ValueError) as e:
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pod.tts_node(script)
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assert "2" in str(e.value) # mentions failed line number 2
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def test_tts_node_defaults_to_one_worker_for_minimax(monkeypatch):
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monkeypatch.setenv("MINIMAX_API_KEY", "m")
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captured = {}
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real_executor = pod.ThreadPoolExecutor
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class CapturingExecutor(real_executor):
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def __init__(self, *args, **kwargs):
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captured["max_workers"] = kwargs.get("max_workers", args[0] if args else None)
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super().__init__(*args, **kwargs)
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def fake_tts(text, voice_id):
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return b"x"
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monkeypatch.setattr(pod, "ThreadPoolExecutor", CapturingExecutor)
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monkeypatch.setattr(pod, "text_to_speech_minimax", fake_tts)
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script = pod.Script(lines=[pod.ScriptLine("male", "a"), pod.ScriptLine("female", "b")])
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assert pod.tts_node(script) == [b"x", b"x"]
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assert captured["max_workers"] == 1
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def test_tts_node_keeps_four_worker_default_for_volcengine(monkeypatch):
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monkeypatch.setenv("VOLCENGINE_TTS_APPID", "a")
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monkeypatch.setenv("VOLCENGINE_TTS_ACCESS_TOKEN", "t")
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captured = {}
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real_executor = pod.ThreadPoolExecutor
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class CapturingExecutor(real_executor):
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def __init__(self, *args, **kwargs):
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captured["max_workers"] = kwargs.get("max_workers", args[0] if args else None)
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super().__init__(*args, **kwargs)
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def fake_tts(text, voice_type):
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return b"x"
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monkeypatch.setattr(pod, "ThreadPoolExecutor", CapturingExecutor)
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monkeypatch.setattr(pod, "text_to_speech_volcengine", fake_tts)
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script = pod.Script(lines=[pod.ScriptLine("male", "a"), pod.ScriptLine("female", "b")])
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assert pod.tts_node(script) == [b"x", b"x"]
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assert captured["max_workers"] == 4
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