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Chronologue’s event generation pipeline converts structured memory traces (.json) into calendar events (.ics) following the iCalendar standard. This allows natural language input to produce concrete, time-aligned actions in external scheduling systems. The core script powering this transformation is modules/export_ics.py.

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Calendar Event Format

Chronologue conforms to a minimal but valid iCalendar VEVENT structure: 
BEGIN:VEVENT
UID:lab_ops-20240407@memorysystem.ai
DTSTAMP:20250401T080000Z
DTSTART:20240407T090000Z
DTEND:20240407T091500Z
SUMMARY:Temperature in incubator #3 drifted 1.5°C above target during morning run.
DESCRIPTION:Temperature in incubator #3 drifted 1.5°C above target during morning run.
LOCATION:wetlab_sync
STATUS:CONFIRMED
END:VEVENT
All fields are derived from the memory trace or inferred via defaults. A working .ics is generated using: 
ics_string = generate_ics_string(memory_trace)
Steps
  1. Load JSON memory trace files
  2. Validate trace entries
  3. Generate VEVENTs
  4. Write a consolidated .ics calendar event

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Key Functions and Parameters for Customization

resolve_duration_minutes(trace)
  • Parses flexible user duration formats: 2h, 30m, 1:00-2:30, or “one hour”
  • Customize: Default duration (currently 30), upper bound, parsing logic
generate_uid(title, date)
  • Constructs a globally unique UID from task ID and date
  • Customize: Change UID domain, format, or link to external systems
generate_summary_title(content)
  • Uses OpenAI to create a concise SUMMARY field
  • Fallbacks to truncating raw content if LLM fails
Customize: Model, max length, prompt template generate_ics_string(trace)
  • Assembles a VEVENT from a single memory trace
  • Includes SUMMARY, DESCRIPTION, LOCATION, DTSTART, DTEND, UID, STATUS
write_consolidated_ics(events, output_path)
  • Writes header, VEVENT blocks, and footer into a single .ics file
  • Customize: PRODID, versioning metadata, newline style (Windows/iCal)

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Opportunities for Personalization

  • Chronologue encourages local customization for different user or organization memory systems:
  • Duration interpretation for different workflows (e.g. lab vs. meetings)
  • LLM-based title summarization vs. rules-based
  • Structured description fields for reflection, chat links, metadata
  • Custom UID namespaces for cross-platform syncing
  • Flexible timestamp parsing and formatting
Testing Output Format Use test_ics_format() to generate a sample .ics file and validate against the expected template: 
python modules/export_ics.py
This writes a file test_output.ics to inspect the generated format against the gold standard. Related Concepts