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## Summary by CodeRabbit
* **Documentation**
* Deprecated legacy examples and added a migration guide mapping old
paths to new locations
* Added a comprehensive new-examples README detailing configurations,
pipelines, demos, and migration notes
* **New Features**
* Added many runnable examples and demos: database configs,
embedding/LLM setups, permissions and access-control, custom pipelines
(organizational, product recommendation, code analysis, procurement),
multimedia, visualization, temporal/ontology demos, and a local UI
starter
* **Chores**
* Updated CI/test entrypoints to use the new-examples layout
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: lxobr <122801072+lxobr@users.noreply.github.com>
66 lines
3.7 KiB
Markdown
66 lines
3.7 KiB
Markdown
# Cognee Examples
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## 📁 Structure
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| Folder | Purpose |
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|--------|---------|
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| `configurations/` | Database, LLM, embedding, and permission setups |
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| `custom_pipelines/` | Building custom memory pipelines |
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| `demos/` | Feature demos and getting started examples |
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## 🔧 Configurations
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| Path | Description |
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|------|-------------|
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| `database_examples/chromadb_vector_database_configuration.py` | ChromaDB vector database |
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| `database_examples/kuzu_graph_database_configuration.py` | KuzuDB graph database |
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| `database_examples/neo4j_graph_database_configuration.py` | Neo4j graph database |
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| `database_examples/neptune_analytics_aws_database_configuration.py` | AWS Neptune Analytics |
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| `database_examples/pgvector_postgres_vector_database_configuration.py` | PostgreSQL with PGVector |
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| `database_examples/s3_storage_configuration.py` | Amazon S3 storage |
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| `llm_configurations/openai_setup.py` | OpenAI LLM setup |
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| `llm_configurations/azure_openai_setup.py` | Azure OpenAI LLM setup |
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| `embedding_configurations/openai_setup.py` | OpenAI embeddings |
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| `embedding_configurations/azure_openai_setup.py` | Azure OpenAI embeddings |
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| `structured_output_configurations.py/baml_setup.py` | BAML structured output |
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| `structured_output_configurations.py/litellm_intructor_setup.py` | LiteLLM Instructor setup |
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| `permissions_example/` | Multi-user access control (with sample PDF) |
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| `distributed_execution_with_modal_example.py` | Scale with Modal.com |
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## 🔄 Custom Pipelines
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| Path | Description |
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|------|-------------|
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| `custom_cognify_pipeline_example.py` | Customize cognify pipelines |
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| `memify_coding_agent_rule_extraction_example.py` | Extract rules from conversations |
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| `relational_database_to_knowledge_graph_migration_example.py` | SQL to knowledge graph |
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| `agentic_reasoning_procurement_example.py` | AI procurement assistant |
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| `code_graph_repository_analysis_example.py` | Code repository analysis |
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| `dynamic_steps_resume_analysis_hr_example.py` | CV/resume filtering |
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| `organizational_hierarchy/` | Org structure graphs (with JSON data) |
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| `organizational_hierarchy/organizational_hierarchy_pipeline_low_level_example.py` | Low-level pipeline variant |
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| `product_recommendation/` | Recommendation system (with customer data) |
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## 🎯 Demos
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| Path | Description |
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|------|-------------|
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| `simple_default_cognee_pipelines_example.py` | Default pipeline usage ★ |
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| `simple_document_qa/` | Document Q&A (with alice_in_wonderland.txt) |
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| `core_features_getting_started_example.py` | Intro to Cognee |
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| `multimedia_processing/` | Audio/image processing (with media files) |
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| `ontology_reference_vocabulary/` | Ontology as vocabulary (with OWL file) |
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| `ontology_medical_comparison/` | Medical ontology comparison (with papers + OWL) |
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| `web_url_content_ingestion_example.py` | Extract from web pages and ingest directly to memory |
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| `temporal_awareness_example.py` | Time-based queries |
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| `retrievers_and_search_examples.py` | Retriever patterns and search types guide |
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| `feedback_enrichment_minimal_example.py` | User feedback enrichment |
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| `nodeset_memory_grouping_with_tags_example.py` | Memory grouping with tags |
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| `weighted_edges_relationships_example.py` | Weighted edge relationships |
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| `dynamic_multiple_weighted_edges_example.py` | Multiple weighted edges |
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| `custom_graph_model_entity_schema_definition.py` | Custom entity schemas ★ |
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| `graph_visualization_example.py` | Visualize knowledge graphs |
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| `conversation_session_persistence_example.py` | Session persistence |
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| `custom_prompt_guide.py` | Custom prompts for extraction |
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| `direct_llm_call_for_structured_output_example.py` | Direct LLM structured output |
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| `start_local_ui_frontend_example.py` | Launch Cognee UI |
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