personal memory agent
Fix pre-existing ruff formatting and update stale API baselines
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
+97
-30
+20
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apps/transcripts/call.py
+20
-6
apps/transcripts/call.py
···
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full: bool = typer.Option(
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False, "--full", help="Include transcripts, screen, and agents."
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),
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raw: bool = typer.Option(False, "--raw", help="Include transcripts and screen only."),
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transcripts: bool = typer.Option(False, "--transcripts", help="Include transcript content."),
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audio: bool = typer.Option(False, "--audio", help="Alias for --transcripts.", hidden=True),
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+
raw: bool = typer.Option(
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False, "--raw", help="Include transcripts and screen only."
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+
),
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transcripts: bool = typer.Option(
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False, "--transcripts", help="Include transcript content."
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),
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audio: bool = typer.Option(
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False, "--audio", help="Alias for --transcripts.", hidden=True
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),
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percepts: bool = typer.Option(False, "--percepts", help="Include screen percepts."),
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screen: bool = typer.Option(False, "--screen", help="Alias for --percepts.", hidden=True),
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screen: bool = typer.Option(
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False, "--screen", help="Alias for --percepts.", hidden=True
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),
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agents: bool = typer.Option(False, "--agents", help="Include agent outputs."),
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max_bytes: int = typer.Option(
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16384, "--max", help="Max output bytes (0 = unlimited)."
···
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raise typer.Exit(1)
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if full:
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sources: dict[str, bool] = {"transcripts": True, "percepts": True, "agents": True}
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sources: dict[str, bool] = {
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"transcripts": True,
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"percepts": True,
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"agents": True,
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}
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elif raw:
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sources = {"transcripts": True, "percepts": True, "agents": False}
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elif transcripts or percepts or agents:
···
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transcript_ranges, screen_ranges = cluster_scan(day)
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if transcript_ranges or screen_ranges:
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days_with_data += 1
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typer.echo(f"{day} transcripts:{len(transcript_ranges)} percepts:{len(screen_ranges)}")
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typer.echo(
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f"{day} transcripts:{len(transcript_ranges)} percepts:{len(screen_ranges)}"
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+
)
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if not days_with_data:
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typer.echo(f"No data for {month}.")
+15
-5
tests/baselines/api/stats/stats.json
+15
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tests/baselines/api/stats/stats.json
···
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"pending_segments": 0,
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"screen_duration": 0.0
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},
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+
"20260101": {
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"day_bytes": 24508,
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+
"outputs_pending": 11,
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+
"outputs_processed": 0,
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+
"pending_segments": 0,
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+
"percept_duration": 0.0,
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"transcript_duration": 1557.0,
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+
"transcript_segments": 38,
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+
"transcript_sessions": 8
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},
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"20260130": {
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"audio_duration": 0.0,
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"day_bytes": 275,
···
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}
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},
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"total_percept_duration": 0.0,
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"total_transcript_duration": 655.0,
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"total_transcript_duration": 2212.0,
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"totals": {
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"audio_duration": 1243.0,
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"audio_segments": 86,
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"audio_sessions": 19,
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"day_bytes": 503294,
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"outputs_pending": 366,
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+
"day_bytes": 527802,
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"outputs_pending": 377,
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"outputs_processed": 14,
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"pending_segments": 0,
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"percept_frames": 0,
···
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"screen_duration": 23.1,
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"screen_frames": 3,
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"screen_sessions": 13,
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"transcript_segments": 48,
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"transcript_sessions": 4
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+
"transcript_segments": 86,
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+
"transcript_sessions": 12
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}
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}
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}
+1
-1
tests/baselines/api/tokens/stats-month.json
+1
-1
tests/baselines/api/tokens/stats-month.json
+2
-1
tests/test_gemini_importer.py
+2
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tests/test_gemini_importer.py
···
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assert result.segments is not None
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assert len(result.segments) >= 1
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assert any(
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Path(p).name == "conversation_transcript.jsonl" for p in result.files_created
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Path(p).name == "conversation_transcript.jsonl"
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+
for p in result.files_created
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)
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first_path = Path(result.files_created[0])
+3
-1
tests/test_generators.py
+3
-1
tests/test_generators.py
···
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instructions = speakers.get("instructions", {})
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sources = instructions.get("sources", {})
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-
assert sources.get("transcripts") == "required", "speakers should require transcripts"
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+
assert sources.get("transcripts") == "required", (
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+
"speakers should require transcripts"
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+
)
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assert sources.get("percepts") is True, "speakers should include percepts"
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+41
-11
tests/test_importer.py
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tests/test_importer.py
···
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written = Path(json_path)
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assert (
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written
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-
== tmp_path / "20240101" / "import.text" / "120000_300" / "conversation_transcript.jsonl"
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+
== tmp_path
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/ "20240101"
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+
/ "import.text"
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+
/ "120000_300"
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/ "conversation_transcript.jsonl"
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)
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assert written.exists()
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···
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assert len(result.files_created) == 3
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first_segment = (
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day_path("20260115") / "import.chatgpt" / "120000_300" / "conversation_transcript.jsonl"
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+
day_path("20260115")
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/ "import.chatgpt"
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+
/ "120000_300"
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+
/ "conversation_transcript.jsonl"
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)
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second_segment = (
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day_path("20260115") / "import.chatgpt" / "120501_300" / "conversation_transcript.jsonl"
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+
day_path("20260115")
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/ "import.chatgpt"
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+
/ "120501_300"
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+
/ "conversation_transcript.jsonl"
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)
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third_segment = (
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day_path("20260116") / "import.chatgpt" / "000000_300" / "conversation_transcript.jsonl"
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+
day_path("20260116")
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/ "import.chatgpt"
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+
/ "000000_300"
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+
/ "conversation_transcript.jsonl"
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)
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assert first_segment.exists()
···
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assert len(result.files_created) == 3
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first_segment = (
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day_path("20260115") / "import.claude" / "120000_300" / "conversation_transcript.jsonl"
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+
day_path("20260115")
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/ "import.claude"
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+
/ "120000_300"
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/ "conversation_transcript.jsonl"
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)
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second_segment = (
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day_path("20260115") / "import.claude" / "120501_300" / "conversation_transcript.jsonl"
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+
day_path("20260115")
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/ "import.claude"
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+
/ "120501_300"
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/ "conversation_transcript.jsonl"
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)
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third_segment = (
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day_path("20260116") / "import.claude" / "000000_300" / "conversation_transcript.jsonl"
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day_path("20260116")
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/ "import.claude"
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/ "000000_300"
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+
/ "conversation_transcript.jsonl"
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)
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assert first_segment.exists()
···
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result = mod.ICSImporter().process(ics_path, tmp_path, facet="work")
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first_md = day_path("20260301") / "import.ics" / "120000_300" / "event_transcript.md"
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second_md = day_path("20260302") / "import.ics" / "090000_300" / "event_transcript.md"
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+
first_md = (
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day_path("20260301") / "import.ics" / "120000_300" / "event_transcript.md"
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+
)
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+
second_md = (
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+
day_path("20260302") / "import.ics" / "090000_300" / "event_transcript.md"
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+
)
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assert result.entries_written == 4
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assert result.errors == []
···
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assert first_key == "100000_300"
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assert second_key == "101000_300"
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first_md = day_path("20260315") / "import.obsidian" / "100000_300" / "note_transcript.md"
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second_md = day_path("20260315") / "import.obsidian" / "101000_300" / "note_transcript.md"
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+
first_md = (
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day_path("20260315") / "import.obsidian" / "100000_300" / "note_transcript.md"
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+
)
1512
+
second_md = (
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+
day_path("20260315") / "import.obsidian" / "101000_300" / "note_transcript.md"
1514
+
)
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assert first_md.exists()
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assert second_md.exists()
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+1
-1
think/agents.py
+1
-1
think/agents.py
···
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"- Windows that look identical in first and last frame\n"
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"- Apps open but showing same content throughout\n"
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"- Background windows never brought to focus\n"
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-
"- Anything you'd describe as \"had open\" or \"was visible\""
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+
'- Anything you\'d describe as "had open" or "was visible"'
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)
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IMPORT_GUIDANCE = {
+14
-4
think/cluster.py
+14
-4
think/cluster.py
···
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256
def _load_entries(
257
-
day_dir: str, transcripts: bool, percepts: bool, agents: bool | dict[str, bool | str]
257
+
day_dir: str,
258
+
transcripts: bool,
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+
percepts: bool,
260
+
agents: bool | dict[str, bool | str],
258
261
) -> list[dict[str, Any]]:
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"""Load all transcript entries from a day directory."""
260
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from think.utils import segment_parse
···
269
272
start_time, _ = segment_parse(seg_path.name)
270
273
if not start_time:
271
274
continue
272
-
entries.extend(_process_segment(seg_path, date_str, transcripts, percepts, agents))
275
+
entries.extend(
276
+
_process_segment(seg_path, date_str, transcripts, percepts, agents)
277
+
)
273
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274
279
entries.sort(key=lambda e: e["timestamp"])
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return entries
···
612
617
agents=sources.get("agents", False),
613
618
)
614
619
if not entries:
615
-
return f"No transcript or screen files found for segment {segment}", empty_counts
620
+
return (
621
+
f"No transcript or screen files found for segment {segment}",
622
+
empty_counts,
623
+
)
616
624
617
625
groups = _group_entries(entries)
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626
markdown = _groups_to_markdown(groups)
···
639
647
segment_path_obj = Path(segment_dir)
640
648
# Parent is stream dir; grandparent is day dir
641
649
date_str = _date_str(str(segment_path_obj.parent.parent))
642
-
entries = _process_segment(segment_path_obj, date_str, transcripts, percepts, agents)
650
+
entries = _process_segment(
651
+
segment_path_obj, date_str, transcripts, percepts, agents
652
+
)
643
653
entries.sort(key=lambda e: e["timestamp"])
644
654
return entries
645
655