๊ฐ€์ž… ํ›„ ์ดˆ๋Œ€ ๋งํฌ๋ฅผ ๊ณต์œ ํ•˜๋ฉด ๋™์˜์ƒ ์žฌ์ƒ ๋ฐ ์ดˆ๋Œ€ ๋ณด์ƒ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

LanceDB
@lancedb
The multimodal lakehouse for AI, accelerating large-scale data curation and feature engineering so teams can build better models faster.
๊ฐ€์ž… April 2023
66 ํŒ”๋กœ์ž‰ ์ค‘    4.6K ํŒฌ
A great blog written by @loldedxd & @ariG23498 ๐Ÿค—๐Ÿ‘ funes, by @huggingface, turns past agent sessions into memory your agents can actually use. It indexes Claude Code, Codex, pi, and Hermes traces into one local Lance dataset, then gives the agent 'recall' and 'get' tools. The next time a task depends on old reasoning, the agent can pull the original passage back. No LLM summarizing your traces at ingest.
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