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https://github.com/Monadical-SAS/reflector.git
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feat: implement service-specific Modal API keys with auto processor pattern (#528)
* fix: refactor modal API key configuration for better separation of concerns - Split generic MODAL_API_KEY into service-specific keys: - TRANSCRIPT_API_KEY for transcription service - DIARIZATION_API_KEY for diarization service - TRANSLATE_API_KEY for translation service - Remove deprecated *_MODAL_API_KEY settings - Add proper validation to ensure URLs are set when using modal processors - Update README with new configuration format BREAKING CHANGE: Configuration keys have changed. Update your .env file: - TRANSCRIPT_MODAL_API_KEY → TRANSCRIPT_API_KEY - LLM_MODAL_API_KEY → (removed, use TRANSCRIPT_API_KEY) - Add DIARIZATION_API_KEY and TRANSLATE_API_KEY if using those services * fix: update Modal backend configuration to use service-specific API keys - Changed from generic MODAL_API_KEY to service-specific keys: - TRANSCRIPT_MODAL_API_KEY for transcription - DIARIZATION_MODAL_API_KEY for diarization - TRANSLATION_MODAL_API_KEY for translation - Updated audio_transcript_modal.py and audio_diarization_modal.py to use modal_api_key parameter - Updated documentation in README.md, CLAUDE.md, and env.example * feat: implement auto/modal pattern for translation processor - Created TranscriptTranslatorAutoProcessor following the same pattern as transcript/diarization - Created TranscriptTranslatorModalProcessor with TRANSLATION_MODAL_API_KEY support - Added TRANSLATION_BACKEND setting (defaults to "modal") - Updated all imports to use TranscriptTranslatorAutoProcessor instead of TranscriptTranslatorProcessor - Updated env.example with TRANSLATION_BACKEND and TRANSLATION_MODAL_API_KEY - Updated test to expect TranscriptTranslatorModalProcessor name - All tests passing * refactor: simplify transcript_translator base class to match other processors - Moved all implementation from base class to modal processor - Base class now only defines abstract _translate method - Follows the same minimal pattern as audio_diarization and audio_transcript base classes - Updated test mock to use _translate instead of get_translation - All tests passing * chore: clean up settings and improve type annotations - Remove deprecated generic API key variables from settings - Add comments to group Modal-specific settings - Improve type annotations for modal_api_key parameters * fix: typing * fix: passing key to openai * test: fix rtc test failing due to change on transcript It also correctly setup database from sqlite, in case our configuration is setup to postgres. * ci: deactivate translation backend by default * test: fix modal->mock * refactor: implementing igor review, mock to passthrough
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@@ -7,15 +7,11 @@ import pytest
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@pytest.fixture(scope="function", autouse=True)
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@pytest.mark.asyncio
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async def setup_database():
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from reflector.settings import settings
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from reflector.db import engine, metadata # noqa
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with NamedTemporaryFile() as f:
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settings.DATABASE_URL = f"sqlite:///{f.name}"
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from reflector.db import engine, metadata
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metadata.create_all(bind=engine)
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yield
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metadata.drop_all(bind=engine)
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metadata.create_all(bind=engine)
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yield
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@pytest.fixture
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@@ -33,9 +29,6 @@ def dummy_processors():
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patch(
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"reflector.processors.transcript_final_summary.TranscriptFinalSummaryProcessor.get_short_summary"
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) as mock_short_summary,
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patch(
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"reflector.processors.transcript_translator.TranscriptTranslatorProcessor.get_translation"
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) as mock_translate,
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):
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from reflector.processors.transcript_topic_detector import TopicResponse
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@@ -45,9 +38,7 @@ def dummy_processors():
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mock_title.return_value = "LLM Title"
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mock_long_summary.return_value = "LLM LONG SUMMARY"
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mock_short_summary.return_value = "LLM SHORT SUMMARY"
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mock_translate.return_value = "Bonjour le monde"
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yield (
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mock_translate,
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mock_topic,
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mock_title,
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mock_long_summary,
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@@ -105,6 +96,27 @@ async def dummy_diarization():
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yield
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@pytest.fixture
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async def dummy_transcript_translator():
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from reflector.processors.transcript_translator import TranscriptTranslatorProcessor
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class TestTranscriptTranslatorProcessor(TranscriptTranslatorProcessor):
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async def _translate(self, text: str) -> str:
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source_language = self.get_pref("audio:source_language", "en")
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target_language = self.get_pref("audio:target_language", "en")
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return f"{source_language}:{target_language}:{text}"
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def mock_new(cls, *args, **kwargs):
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return TestTranscriptTranslatorProcessor(*args, **kwargs)
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with patch(
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"reflector.processors.transcript_translator_auto"
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".TranscriptTranslatorAutoProcessor.__new__",
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mock_new,
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):
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yield
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@pytest.fixture
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async def dummy_llm():
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from reflector.llm import LLM
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@@ -33,7 +33,7 @@ async def test_basic_process(
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# validate the events
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assert marks["TranscriptLinerProcessor"] == 1
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assert marks["TranscriptTranslatorProcessor"] == 1
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assert marks["TranscriptTranslatorPassthroughProcessor"] == 1
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assert marks["TranscriptTopicDetectorProcessor"] == 1
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assert marks["TranscriptFinalSummaryProcessor"] == 1
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assert marks["TranscriptFinalTitleProcessor"] == 1
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@@ -67,6 +67,7 @@ async def test_transcript_rtc_and_websocket(
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dummy_transcript,
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dummy_processors,
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dummy_diarization,
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dummy_transcript_translator,
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dummy_storage,
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fake_mp3_upload,
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appserver,
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@@ -164,7 +165,7 @@ async def test_transcript_rtc_and_websocket(
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assert "TRANSCRIPT" in eventnames
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ev = events[eventnames.index("TRANSCRIPT")]
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assert ev["data"]["text"].startswith("Hello world.")
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assert ev["data"]["translation"] == "Bonjour le monde"
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assert ev["data"]["translation"] is None
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assert "TOPIC" in eventnames
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ev = events[eventnames.index("TOPIC")]
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@@ -224,6 +225,7 @@ async def test_transcript_rtc_and_websocket_and_fr(
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dummy_transcript,
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dummy_processors,
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dummy_diarization,
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dummy_transcript_translator,
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dummy_storage,
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fake_mp3_upload,
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appserver,
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@@ -330,7 +332,7 @@ async def test_transcript_rtc_and_websocket_and_fr(
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assert "TRANSCRIPT" in eventnames
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ev = events[eventnames.index("TRANSCRIPT")]
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assert ev["data"]["text"].startswith("Hello world.")
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assert ev["data"]["translation"] == "Bonjour le monde"
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assert ev["data"]["translation"] == "en:fr:Hello world."
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assert "TOPIC" in eventnames
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ev = events[eventnames.index("TOPIC")]
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