topoteretes--cognee/examples

Cognee Examples

This directory contains 60+ runnable example scripts that demonstrate cognee's features end-to-end. They double as the smoke-test corpus that the team uses to verify behaviour across the SDK.

New here? Start with demos/simple_cognee_example.py (the canonical remember → recall flow), then follow the quickstart map below.

🚀 Quickstart map (5 examples to start with)

Example	What you'll learn
demos/simple_cognee_example.py	Canonical remember → recall pipeline
demos/remember_recall_improve_example.py	The v1.0 memory API (remember, recall, improve, forget)
guides/agent_memory_quickstart.py	Wrap an LLM agent with cognee memory
guides/graph_visualization.py	Render the resulting knowledge graph
demos/start_local_ui_frontend_example.py	Launch the cognee UI alongside the API server

📁 Top-level layout

Folder	Purpose	Count
configurations/	Database & permissions configuration recipes	8
custom_pipelines/	Build your own pipeline / extend cognify	7
database_examples/	Smoke tests per supported backend	5
demos/	Feature demos — broadest coverage	22
guides/	Short focused how-to guides	13
integrations/	Integrations Hub — first-class SaaS connectors (Gmail, …)	1
pocs/	Research-grade proofs of concept (entity disambiguation, canonicalization, prefetch)	7

Most runnable demos and backend examples use the v1.0 memory API (remember, recall, forget, improve). The lower-level add, cognify, search, and prune calls are intentionally kept in examples that demonstrate pipeline internals, permissions, relational migrations, or research POCs.

🔧 configurations/ — backend & permissions setup

Database configuration

Script	Demonstrates
database_examples/ladybug_graph_database_configuration.py	Ladybug (default) graph backend
database_examples/neo4j_graph_database_configuration.py	Neo4j graph backend
database_examples/neptune_analytics_aws_database_configuration.py	AWS Neptune Analytics graph backend
database_examples/pgvector_postgres_vector_database_configuration.py	Postgres + pgvector hybrid (vector + relational in one)

Permissions / multi-tenancy (set ENABLE_BACKEND_ACCESS_CONTROL=True)

Script	Demonstrates
permissions_example/tenant_role_setup_example.py	Create tenants and assign roles
permissions_example/tenant_role_constraints_example.py	Constrain what a role can do
permissions_example/user_permissions_and_access_control_example.py	Per-user dataset access control
permissions_example/data_access_control_example.py	Filter retrieval by ACL

🔄 custom_pipelines/ — extend cognify

Script	Demonstrates
custom_cognify_pipeline_example.py	Replace the default cognify task list with your own
memify_coding_agent_rule_extraction_example.py	Distill coding-agent traces into reusable rules
relational_database_to_knowledge_graph_migration_example.py	Lift a SQL schema + data into a knowledge graph
agentic_reasoning_procurement_example.py	Multi-step reasoning over a procurement dataset
dynamic_steps_resume_analysis_hr_example.py	Pipeline that branches based on resume content
organizational_hierarchy/organizational_hierarchy_pipeline_example.py	Org-chart ingestion (high-level API)
organizational_hierarchy/organizational_hierarchy_pipeline_low_level_example.py	Same dataset via the low-level Task API

🗄️ database_examples/ — smoke tests per backend

Script	Demonstrates
ladybug_example.py	Ladybug (default) — graph
neo4j_example.py	Neo4j — graph
neptune_analytics_example.py	Neptune Analytics — graph
chromadb_example.py	ChromaDB — vector
pgvector_example.py	pgvector — vector + relational

🎯 demos/ — feature breadth

Script	Demonstrates
simple_cognee_example.py	Canonical remember → recall pipeline (start here)
comprehensive_example/cognee_comprehensive_example.py	End-to-end with most features stitched together
remember_recall_improve_example.py	v1.0 memory API (remember, recall, improve, forget)
conversation_session_persistence_example.py	Session memory persisted across runs
session_feedback_example.py	Capturing thumbs-up/down feedback on retrieval
session_feedback_lifecycle_demo/backend/app.py	Full feedback-loop backend (FastAPI + cognee)
feedback_score_shifting_example.py	How feedback nudges retrieval scores
references_example.py	Search answers with lightweight evidence references
custom_graph_model_entity_schema_definition.py	Define your own entity schema for graph extraction
custom_pipeline_single_object_example.py	Run a custom pipeline on a single object
dynamic_multiple_weighted_edges_example.py	Many-to-many edges with per-edge weights
nodeset_grouping_example.py	Group nodes into named sets for filtered retrieval
temporal_awareness_example/temporal_awareness_example.py	Time-aware retrieval (Event model)
ontology_reference_vocabulary/ontology_as_reference_vocabulary_example.py	Ontology as a constraining vocabulary for extraction
web_url_content_ingestion_example.py	Crawl a URL and cognify the content
dlt_ingestion_example.py	Ingest via dlt sources
gmail_connector_example.py	"Ask my inbox" — Gmail connector (incremental + forget-on-delete)
multimedia_processing/multimedia_audio_image_processing_example.py	Audio + image ingestion
simple_document_qa/simple_document_qa_demo.py	Q&A over a single document
simple_relational_database_migration_example/simple_relational_database_migration_example.py	SQL → graph (small schema)
complex_relational_database_migration_example/complex_relational_database_migration_example.py	SQL → graph (richer schema)
schema_inventory_demo.py	Schema and entity inventory visualization
memory_provenance_demo.py	Memory provenance projection and visualization
sync_local_to_cloud_example.py	Sync a local dataset to Cognee Cloud
pipeline_api_proposal.py	Proposal-style API exploration
start_local_ui_frontend_example.py	Spin up cognee UI + backend

📘 guides/ — focused how-tos

Script	Demonstrates
agent_memory_quickstart.py	Wrap an LLM agent with cognee memory
improve_quickstart.py	The improve step in the V2 API
recall_core.py	recall semantics and parameters
temporal_recall.py	Time-bounded recall queries
ontology_quickstart.py	Supply a hand-written ontology
custom_data_models.py	Custom DataPoint subclasses
custom_graph_model.py	Custom graph model used by extraction
custom_prompts.py	Override the LLM prompts used in the pipeline
custom_tasks_and_pipelines.py	Author your own tasks and compose them
importance_weight.py	Boost specific nodes in retrieval ranking
graph_visualization.py	Render the resulting knowledge graph
low_level_llm.py	Direct access to the LLM gateway (skip pipelines)
s3_storage.py	Store data and metadata on S3
consolidate_entity_descriptions_example.py	Merge near-duplicate entity descriptions

🧪 pocs/ — research / proofs of concept

These are exploratory scripts; conventions evolve faster here than in guides/ or demos/.

Script	Demonstrates
disambiguation/disambiguate_entities.py	Entity-disambiguation primitive
disambiguation/disambiguate_entities_example.py	End-to-end disambiguation flow
disambiguation/extract_graph_from_data_with_entity_disambiguation.py	Graph extraction with disambiguation enabled
post_extraction_canonicalization/post_extraction_canonicalization.py	Canonicalize entities after extraction
post_extraction_canonicalization/post_extraction_canonicalization_example.py	Worked example for the canonicalization flow
prefetch_disambiguation/prefetch_disambiguation.py	Prefetch candidates before disambiguation
prefetch_disambiguation/prefetch_disambiguation_example.py	Worked example combining prefetch + disambiguation

🔍 By feature (cross-folder index)

Same scripts, indexed by what they demonstrate.

Memory API (v1.0: remember / recall / improve / forget)

• demos/remember_recall_improve_example.py
• guides/agent_memory_quickstart.py
• guides/improve_quickstart.py
• guides/recall_core.py

Session memory & feedback

• demos/conversation_session_persistence_example.py
• demos/session_feedback_example.py
• demos/session_feedback_lifecycle_demo/backend/app.py
• demos/feedback_score_shifting_example.py
• guides/importance_weight.py

Temporal awareness

• demos/temporal_awareness_example/temporal_awareness_example.py
• guides/temporal_recall.py

Ontology

• demos/ontology_reference_vocabulary/ontology_as_reference_vocabulary_example.py
• guides/ontology_quickstart.py

Multimedia & non-text ingestion

• demos/multimedia_processing/multimedia_audio_image_processing_example.py
• demos/web_url_content_ingestion_example.py
• demos/dlt_ingestion_example.py

Connectors / Integrations Hub

• integrations/ — first-class SaaS connectors (DLT-based)
• demos/gmail_connector_example.py — Gmail ("ask my inbox")

SQL → knowledge graph

• custom_pipelines/relational_database_to_knowledge_graph_migration_example.py
• demos/simple_relational_database_migration_example/simple_relational_database_migration_example.py
• demos/complex_relational_database_migration_example/complex_relational_database_migration_example.py

Custom pipelines / tasks

• custom_pipelines/custom_cognify_pipeline_example.py
• custom_pipelines/agentic_reasoning_procurement_example.py
• custom_pipelines/dynamic_steps_resume_analysis_hr_example.py
• custom_pipelines/memify_coding_agent_rule_extraction_example.py
• custom_pipelines/organizational_hierarchy/ (high-level + low-level variants)
• guides/custom_data_models.py
• guides/custom_graph_model.py
• guides/custom_prompts.py
• guides/custom_tasks_and_pipelines.py
• demos/custom_pipeline_single_object_example.py
• demos/custom_graph_model_entity_schema_definition.py

Multi-tenant / permissions

• configurations/permissions_example/ (4 scripts)

Backends

• database_examples/ — 5 backends end-to-end
• configurations/database_examples/ — 4 graph + 1 hybrid configurations

Visualization & UI

• guides/graph_visualization.py
• demos/schema_inventory_demo.py
• demos/memory_provenance_demo.py
• demos/start_local_ui_frontend_example.py

References / evidence

• demos/references_example.py

Storage backends

• guides/s3_storage.py

Disambiguation / canonicalization

• pocs/disambiguation/ (3 scripts)
• pocs/post_extraction_canonicalization/ (2 scripts)
• pocs/prefetch_disambiguation/ (2 scripts)
• guides/consolidate_entity_descriptions_example.py

⚙️ Running an example

# Install dev environment
uv sync --dev --all-extras --reinstall

# Configure API keys (one-time)
cp .env.template .env
# edit .env: set LLM_API_KEY (your OpenAI key) at minimum

# Run any example
uv run python examples/demos/simple_cognee_example.py

For non-OpenAI providers (Anthropic, Bedrock, Ollama, fastembed, …) see the cognee docs and .env.template.

🤝 Contributing a new example

1. Pick the right folder:
   • demos/ — broad feature demonstration
   • guides/ — small focused how-to
   • custom_pipelines/ — custom pipeline composition
   • pocs/ — research-shaped exploration
2. Self-contained: an example should run with uv run python <path> after uv sync and a configured .env. No global setup.
3. Add an entry to the appropriate table above.
4. If your example demonstrates a feature, add it to the By feature cross-index too.

See CONTRIBUTING.md for the broader contribution flow.