AI & LLM Engineering · Python · By topoteretes

Defines the shape of cognee's knowledge graph with graph_model: DataPoint node classes, identity and index fields, typed edges and fixes for duplicated nodes.

topoteretes/cognee

Shows how to write custom cognee tasks, chain them into pipelines, store custom DataPoints and run enrichment over the existing graph.

topoteretes/cognee

Explains how cognee stores session memory by session_id and bridges it into the permanent graph with improve(), including the stages, results and settings.

topoteretes/cognee

Explains how to load text, files, folders, URLs, repositories and databases into cognee memory with remember(), including datasets, extractors and tags.

topoteretes/cognee

Installs the cognee AI memory library in a Python environment, sets the LLM key and gets a first remember and recall script running with the Python SDK.

topoteretes/cognee

Speeds up or throttles cognee ingestion: estimate cost with a dry run, tune batching and chunk size, set LLM rate limits and run work in the background.

topoteretes/cognee

Explains how to query cognee agent memory with recall(): how the search type is chosen, how to narrow a query to datasets, and what the returned results contain.

topoteretes/cognee

Starts the cognee API server and web UI on your own machine, checks its health, connects the SDK or CLI to it and helps you pick between multi-tenant and single-user auth.

topoteretes/cognee