Memory System
How OpenHelm builds a semantic knowledge base from your project runs.
Project Memory
OpenHelm maintains a semantic memory store per project. As goals and jobs are created and runs complete, information is extracted and stored — building up a knowledge base that informs future planning and execution.
Memory Types
| Type | What it stores |
|---|---|
semantic | Conceptual knowledge: API patterns, architecture, project conventions |
episodic | Events and outcomes: what ran, what failed, what was learned |
procedural | How-to knowledge: workflow steps and best practices discovered through runs |
source | Original documents: code snippets and documentation excerpts |
How Memory Accumulates
Memory is extracted automatically:
- When a goal is created (from the goal description)
- When a job is created (from the job prompt)
- After a run completes (from outputs and outcomes)
Semantic Search
The memory system supports semantic search — finding relevant memories by meaning, not just keyword matching. This allows OpenHelm to surface related context even when the exact words don't match.
Memory Tags
Memories are tagged for organisation and retrieval. Default tags include:
goal, data-source, preference, workflow, error-pattern, tool-usage, architecture, convention
Viewing and Managing Memory
Access the memory store from the project sidebar under Memory. From there you can:
- Browse all memories for the project
- Search by text or tag
- Archive memories that are no longer relevant
- Prune low-importance memories automatically