Skip to main content

Aglet RAG memory technique — LanceDB-backed vector recall with pluggable embedders.

Project description

aglet-builtin-memory-rag

Aglet RAG memory technique — LanceDB-backed vector recall with pluggable embedders.

Part of the Aglet pluggable Agent runtime — a framework where every Element (perception, memory, planner, tool, executor, safety, output, observability, extensibility) and every Technique within an Element is a swappable plugin distributed as its own PyPI package.

Install

pip install aglet-builtin-memory-rag

This package registers itself with Aglet's Registry at import time via Python entry points. Once installed, list it with:

aglet techniques        # if your installed version of aglet-cli is recent

Usage

In your agent.yaml:

elements:
  # Add the Element / technique block this package contributes.

See the main repo's examples for full configurations.

License

Apache-2.0

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aglet_builtin_memory_rag-0.1.0a1-py3-none-any.whl (3.9 kB view details)

Uploaded Python 3

File details

Details for the file aglet_builtin_memory_rag-0.1.0a1-py3-none-any.whl.

File metadata

File hashes

Hashes for aglet_builtin_memory_rag-0.1.0a1-py3-none-any.whl
Algorithm Hash digest
SHA256 00863482d7c2b760c505ec0f1cee0c656df1fe5379e2d038684aab1a4f40de05
MD5 54a1dfb418a7f303d79d127e47e9d6a2
BLAKE2b-256 d8cf0cab032dbef9051fa7e9f5757711a2a13bf7f24c5f3aab4dc490222e4c4f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page