Matt Van Horn
4d6224f79a
Add extract_transcript_highlights() that scores sentences by specificity (numbers, proper nouns, topic relevance) and filters YouTube filler (subscribe, welcome back, etc). Top 5 highlights shown as structured bullets in compact output. Full transcript moved to collapsible <details> block so the LLM reads highlights first, full text on demand. SKILL.md updated to instruct the judge agent to quote highlights directly in synthesis, same as Reddit top comments. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
81 lines
2.9 KiB
Python
81 lines
2.9 KiB
Python
"""Tests for yt-dlp invocation safety flags."""
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import sys
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import tempfile
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import unittest
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from pathlib import Path
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from unittest import mock
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sys.path.insert(0, str(Path(__file__).parent.parent / "scripts"))
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from lib import youtube_yt
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class _DummyProc:
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def __init__(self):
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self.pid = 12345
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self.returncode = 0
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def communicate(self, timeout=None):
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return "", ""
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def wait(self, timeout=None):
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return 0
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class TestYtDlpFlags(unittest.TestCase):
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def test_search_ignores_global_config_and_browser_cookies(self):
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proc = _DummyProc()
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with mock.patch.object(youtube_yt, "is_ytdlp_installed", return_value=True), \
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mock.patch.object(youtube_yt.subprocess, "Popen", return_value=proc) as popen_mock:
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youtube_yt.search_youtube("Claude Code", "2026-02-01", "2026-03-01")
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cmd = popen_mock.call_args.args[0]
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self.assertIn("--ignore-config", cmd)
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self.assertIn("--no-cookies-from-browser", cmd)
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def test_transcript_fetch_ignores_global_config_and_browser_cookies(self):
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proc = _DummyProc()
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with tempfile.TemporaryDirectory() as temp_dir, \
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mock.patch.object(youtube_yt.subprocess, "Popen", return_value=proc) as popen_mock:
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youtube_yt.fetch_transcript("abc123", temp_dir)
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cmd = popen_mock.call_args.args[0]
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self.assertIn("--ignore-config", cmd)
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self.assertIn("--no-cookies-from-browser", cmd)
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class TestExtractTranscriptHighlights(unittest.TestCase):
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def test_extracts_specific_sentences(self):
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transcript = (
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"Hey guys welcome back to the channel. "
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"In today's video we're looking at something special. "
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"The Lego Bugatti Chiron took 13,438 hours to build with over 1 million pieces. "
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"Don't forget to subscribe and hit the bell. "
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"The tolerance on each brick is 0.002 millimeters which is insane for injection molding. "
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"So yeah that's pretty cool. "
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"Thanks for watching see you next time."
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)
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highlights = youtube_yt.extract_transcript_highlights(transcript, "Lego")
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self.assertTrue(len(highlights) > 0)
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# Should pick the sentences with numbers and topic relevance, not filler
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joined = " ".join(highlights)
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self.assertIn("13,438", joined)
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self.assertNotIn("subscribe", joined)
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self.assertNotIn("welcome back", joined)
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def test_empty_transcript(self):
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self.assertEqual(youtube_yt.extract_transcript_highlights("", "test"), [])
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def test_respects_limit(self):
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sentences = ". ".join(
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f"The model {i} has {i * 100} parameters and runs at {i * 10} tokens per second"
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for i in range(20)
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) + "."
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highlights = youtube_yt.extract_transcript_highlights(sentences, "model", limit=3)
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self.assertEqual(len(highlights), 3)
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if __name__ == "__main__":
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unittest.main()
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