Knowledge-and-Memory-Management v0.0.2 is a clean release that introduces structured knowledge collection from web, video, and article sources, alongside memory management enhancements. All hardcoded paths have been replaced with the portable $AGENT_HOME variable, making the system deployable across environments without manual configuration. This release targets developers building autonomous systems that require persistent, queryable knowledge bases.
The core addition in v0.0.2 is the Knowledge Collection module. It abstracts content ingestion into a unified pipeline with plugins for specific sources: web scraping (HTML and RSS), video transcript extraction (via YouTube API or local file processing), and article parsing (supporting PDF, EPUB, and Markdown). Each plugin normalizes content into a chunked, timestamped structure that is passed directly to memory storage—no intermediate files are written by default.
Memory Management in v0.0.2 uses a vector-based index with optional persistent backends (SQLite, PostgreSQL, or Redis). Ingested knowledge is automatically embedded using a configurable model (default: all-MiniLM-L6-v2) and stored with metadata tags. The system supports automatic deduplication via content hashing and offers a hybrid retrieval mechanism that combines vector similarity with keyword filters. A new forget API allows explicit removal of entries by ID or age, enabling control over memory capacity.
