- Add return type annotation (list[str]) to Config.validate()
- Add type annotations (msg: str, -> None) to logger convenience functions
- Add FileParser.is_supported() classmethod for checking file format support
fetch_all_nodes already had a max_items guard (default 2000) but
fetch_all_edges had no such safeguard, allowing unbounded memory growth
on graphs with large numbers of edges.
Add _MAX_EDGES = 5000 constant and mirror the same loop-guard pattern
from fetch_all_nodes: cap the result list, emit a warning log, and
break pagination once the limit is reached.
Background threads (graph building, simulation prep, report generation,
profile generation) now inherit the requesting user's locale preference.
Previously these fell back to 'zh' because Flask request context was
unavailable in spawned threads.
- Updated README.md to include new simulation scripts and configuration details for OASIS, including API retry mechanisms and environment variable settings.
- Added simulation management and configuration generation services to streamline the simulation process across Twitter and Reddit platforms.
- Introduced new API routes for simulation-related operations, including entity retrieval and simulation status management.
- Implemented a robust retry mechanism for external API calls to improve system stability.
- Enhanced task management model to include detailed progress tracking.
- Added logging capabilities for action tracking during simulations.
- Included new scripts for running parallel simulations and testing profile formats.
- Updated `run.py` to conditionally print startup information only in the reloader process to avoid duplicate logs in debug mode.
- Modified `__init__.py` to log startup and completion messages based on the reloader process condition.
- Added warnings suppression in `graph_builder.py` for Pydantic v2 regarding Field usage.
- Revised `ontology_generator.py` to enforce strict design guidelines for entity types and relationships, ensuring compliance with new requirements.
- Improved logging behavior in `logger.py` to prevent log propagation to the root logger, avoiding duplicate outputs.