Vector Retrieval and RAG · Public

cognee

Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.

Vector databaseRAGEmbeddingsSemantic searchData boundaries

Best fitDevelopers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.

Check whether this project matches your task before installing it.

What it can doVector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot18k stars

1.9k forks · 167 contributors

Doramagic.ai Last verification date: 2026-07-31 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-07-31

What is cognee?

cognee is a vector database, retrieval, or RAG storage component for AI applications.
Best fit: Developers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.
Not for: Not for one-off model API calls or environments that cannot isolate indexed data, credentials, and persistence paths.
Capability added to an AI workflow: Vector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance
First safe verification step: Verify create, query, delete, and rollback with a small public text sample before using real data.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/topoteretes/cognee, https://github.com/topoteretes/cognee#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forDevelopers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.

Match the project to your task before installing it.

CapabilityVector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance

Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.

Repositorytopoteretes/cognee

18k stars · 1.9k forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Overview, Core Operations, and System Architecture

Related topics: Multi-User Access Control, Tenants, and Datasets, Retrieval System, Search Modes, and Evaluation, Deployment, LLM and Database Configuration, and Extensibility

Source: https://github.com/topoteretes/cognee / Human Manual

Multi-User Access Control, Tenants, and Datasets

Related topics: Overview, Core Operations, and System Architecture, Deployment, LLM and Database Configuration, and Extensibility

Source: https://github.com/topoteretes/cognee / Human Manual

Retrieval System, Search Modes, and Evaluation

Related topics: Overview, Core Operations, and System Architecture, Deployment, LLM and Database Configuration, and Extensibility

Source: https://github.com/topoteretes/cognee / Human Manual

Deployment, LLM and Database Configuration, and Extensibility

Related topics: Overview, Core Operations, and System Architecture, Multi-User Access Control, Tenants, and Datasets, Retrieval System, Search Modes, and Evaluation

Source: https://github.com/topoteretes/cognee / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/topoteretes/cognee, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars18k stars

Forks1.9k forks

Contributors167 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using cognee with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
[Bug]: Duplicate content generated in BeautifulSoupLoader due to overlap
github / github_issue
02
[Bug]: PostgresAdapter.get_neighborhood fails on PostgreSQL 16 — unnest(
github / github_issue
03
Relax the exact `ladybug==0.16.0` pin — blocks downstream updates (0.16.
github / github_issue
04
PR Review: feat/staging-bridge-fix — Fix None reactions crash
github / github_issue
05
[Bug]: JSON issue while adding the file for Cognify the data
github / github_issue
06
[Feature]: Temporal freshness policies for stale and superseded memories
github / github_issue
07
Enhancement: Add retrieval quality benchmarks for different search modes
github / github_issue
08
cognify pipeline silently skips data added by non-owner users
github / github_issue
09
cognee.add silently creates a new owner-scoped dataset when non-owner us
github / github_issue
10
cognee.search ignores ACL when resolving dataset by name for non-owners
github / github_issue
11
LiteLLM ignores custom LLM_ENDPOINT for OpenAI-compatible APIs
github / github_issue
12
v1.2.0.dev1
github / github_release

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

uv pip install cognee

Official start command · https://github.com/topoteretes/cognee#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

cognee Manual

Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

Open the full manual

https://github.com/topoteretes/cognee Project Manual
Table of Contents
Overview, Core Operations, and System Architecture
Related Pages
1. Purpose and Scope
2. Core Operations
2.1 `add` — Ingestion
2.2 `cognify` — Knowledge Graph Construction

Overview, Core Operations, and System Architecture

Related topics: Multi-User Access Control, Tenants, and Datasets, Retrieval System, Search Modes, and Evaluation, Deployment, LLM and Database Configuration, and Extensibility

Source: https://github.com/topoteretes/cognee / Human Manual

Multi-User Access Control, Tenants, and Datasets

Related topics: Overview, Core Operations, and System Architecture, Deployment, LLM and Database Configuration, and Extensibility

Source: https://github.com/topoteretes/cognee / Human Manual

Retrieval System, Search Modes, and Evaluation

Related topics: Overview, Core Operations, and System Architecture, Deployment, LLM and Database Configuration, and Extensibility

Source: https://github.com/topoteretes/cognee / Human Manual

Deployment, LLM and Database Configuration, and Extensibility

Related topics: Overview, Core Operations, and System Architecture, Multi-User Access Control, Tenants, and Datasets, Retrieval System, Search Modes, and Evaluation

Source: https://github.com/topoteretes/cognee / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.

Pitfall Log and verification risks

Doramagic surfaces high-risk items before users treat a candidate capability as verified.

high

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Configuration risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Security or permission risk requires verification

Developers may expose sensitive permissions or credentials: cognee.add silently creates a new owner-scoped dataset when non-owner uses an existing dataset name

high

Security or permission risk requires verification

Developers may expose sensitive permissions or credentials: cognee.search ignores ACL when resolving dataset by name for non-owners

high

Security or permission risk requires verification

Developers may expose sensitive permissions or credentials: cognify pipeline silently skips data added by non-owner users

high

Security or permission risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Security or permission risk requires verification

May increase setup, validation, or first-run risk for the user.