
gh9ko8y
graphmemory
Bitemporal AI memory system: six-variable decay, time-graded recall, TTL expiry, dedupe, competitive retrieval (Neo4j + PostgreSQL + Redis)
Stars
180Community interest
Forks
3Community forks
7-day growth
+180Net weekly change
Language
PythonRepository metadata
Star history & growth
180 ★11 observations
2026-10-242026-11-03
No trend in this date range
Inspect recent observations
| Date | Stars |
|---|---|
| 2026-10-24 | 0 |
| 2026-10-25 | 0 |
| 2026-10-26 | 0 |
| 2026-10-27 | 0 |
| 2026-10-28 | 0 |
| 2026-10-29 | 0 |
| 2026-10-30 | 19 |
| 2026-10-31 | 53 |
| 2026-11-01 | 105 |
| 2026-11-02 | 149 |
| 2026-11-03 | 180 |
Get the source & start here
Cloning downloads source; follow official setup and dependency instructions.
git clone https://github.com/gh9ko8y/graphmemory.gitGitRank Project Score
72 / 100
- Maintenance
- 30 / 30
- Delivery information
- 12 / 25
- Community signals
- 8 / 20
- Recent growth
- 14 / 15
- Usage information
- 8 / 10
Project profile
- License
- MIT
- Created
- 2026-10-30
- Last push
- 2026-10-30
About this project
What is graphmemory?
Bitemporal AI memory system: six-variable decay, time-graded recall, TTL expiry, dedupe, competitive retrieval (Neo4j + PostgreSQL + Redis)
How do I get started?
Clone with git clone https://github.com/gh9ko8y/graphmemory.git. Cloning is not a complete installation; follow the official README for dependencies, hosts and usage.
Can I use it commercially?
Current license information: MIT. Review the original terms, dependencies and your intended use.