Lauro Foletti

What an agent can do with the cortexdb corpus

liliang-cn/cortexdb: Local-first AI agent memory with a knowledge graph, ontology constraints, and traceable reasoning-all in one SQLite file

• Look up how cortexdb implements embeddings, llm, vector-database, with answers cited to file and line.
• Reuse a worked example: the commit “a scope may list several values per field” (7 files · Go).
• Answer from cortexdb's real Go source instead of memory (AI, prompts and agents).

• Where does cortexdb handle “a scope may list several values per field”?
• How does cortexdb implement embeddings?
• What does pkg/authz do in cortexdb?

Search the GitHub repository liliang-cn/cortexdb with XERJ (https://hub.xerj.org/corpus/liliang-cn--cortexdb).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/liliang-cn/cortexdb cortexdb && git -C cortexdb checkout e0ee5fd3b30d6a99c9b9c22aa35759f3fa95239c
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./cortexdb --url http://127.0.0.1:9200 --prefix cortexdb --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: MIT. Keep the copyright notice and credit the authors.

corpus liliang-cn--cortexdb · AI, prompts and agents
Related corpora: xerj-blogposts, vectra-core, hsuanshao/AgentMemory, MongLong0214/commitlore
AI search and retrieval with XERJ · Case study: reference coding for agents