TenseMem
Memory that knows its tenses. An embedded, deterministic state memory engine for AI agents.
Status: pre-alpha. The engine is under active development; this release only reserves the package name.
The problem
Vector memory has no idea what is current. Tell an agent "I live in Delhi" in January and "I moved to Bangalore" in June, and a similarity search returns both, leaving the model to guess.
What TenseMem does
- Turns conversations into structured, versioned facts.
- When a fact changes, the old value is superseded rather than deleted: the agent sees only what is true now, and the full history stays available for "where did I live before?"
- Runs as a single SQLite file inside your process. No graph database, no vector cluster, no server.
- The LLM proposes facts; deterministic, tested rules decide how they change state.
- Every fact can explain where it came from and what it replaced.
Planned API
from tensemem import Memory
mem = Memory()
mem.add("I moved to Bangalore last week and now only write Rust.", user_id="u1")
print(mem.context(user_id="u1", max_tokens=200).text)
License
1 maintainer
Metadata
1 maintainer
Release files for tensemem 0.0.1
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| tensemem-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 12.1 kB
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