# GraphRAG

## Docs

- [Configuration defaults](https://mintlify.wiki/microsoft/graphrag/api/config/defaults.md): Default values for all GraphRAG configuration options
- [Configuration enums](https://mintlify.wiki/microsoft/graphrag/api/config/enums.md): Enumeration types used in GraphRAG configuration
- [Configuration schema](https://mintlify.wiki/microsoft/graphrag/api/config/schema.md): Complete reference for GraphRAG configuration schema and structure
- [Claims](https://mintlify.wiki/microsoft/graphrag/api/data-models/claims.md): Covariate data model for claims and metadata associated with entities
- [Communities](https://mintlify.wiki/microsoft/graphrag/api/data-models/communities.md): Community data model representing hierarchical clusters in the knowledge graph
- [Entities](https://mintlify.wiki/microsoft/graphrag/api/data-models/entities.md): Entity data model representing nodes in the knowledge graph
- [Relationships](https://mintlify.wiki/microsoft/graphrag/api/data-models/relationships.md): Relationship data model representing edges in the knowledge graph
- [Text units](https://mintlify.wiki/microsoft/graphrag/api/data-models/text-units.md): Text unit data model representing text chunks in the knowledge graph
- [Index API](https://mintlify.wiki/microsoft/graphrag/api/index.md): Build knowledge graph indexes programmatically
- [Python API overview](https://mintlify.wiki/microsoft/graphrag/api/overview.md): Overview of the GraphRAG Python API for programmatic access
- [Prompt tune API](https://mintlify.wiki/microsoft/graphrag/api/prompt-tune.md): Generate domain-specific prompts from your data
- [Query API](https://mintlify.wiki/microsoft/graphrag/api/query.md): Search your knowledge graph using the Python API
- [graphrag index](https://mintlify.wiki/microsoft/graphrag/cli/index.md): Build a knowledge graph index from your documents
- [graphrag init](https://mintlify.wiki/microsoft/graphrag/cli/init.md): Initialize a new GraphRAG project
- [CLI overview](https://mintlify.wiki/microsoft/graphrag/cli/overview.md): Command-line interface for GraphRAG
- [graphrag prompt-tune](https://mintlify.wiki/microsoft/graphrag/cli/prompt-tune.md): Generate custom prompts tuned to your domain and data
- [graphrag query](https://mintlify.wiki/microsoft/graphrag/cli/query.md): Query a knowledge graph index using various search methods
- [graphrag update](https://mintlify.wiki/microsoft/graphrag/cli/update.md): Update an existing knowledge graph index with new data
- [Community detection](https://mintlify.wiki/microsoft/graphrag/concepts/community-detection.md): How hierarchical Leiden clustering organizes knowledge graphs into multi-level community structures with generated summaries
- [Indexing pipeline](https://mintlify.wiki/microsoft/graphrag/concepts/indexing-pipeline.md): Understanding the multi-phase workflow that transforms raw documents into the GraphRAG knowledge model
- [Knowledge graphs](https://mintlify.wiki/microsoft/graphrag/concepts/knowledge-graphs.md): How GraphRAG extracts entities, relationships, and builds structured knowledge from unstructured text
- [Core concepts overview](https://mintlify.wiki/microsoft/graphrag/concepts/overview.md): Understanding GraphRAG's approach to structured, hierarchical retrieval augmented generation
- [Retrieval methods](https://mintlify.wiki/microsoft/graphrag/concepts/retrieval-methods.md): Comparing global, local, DRIFT, and basic search strategies in GraphRAG for different query types
- [Caching](https://mintlify.wiki/microsoft/graphrag/configuration/caching.md): Optimize performance and reduce costs with LLM response caching
- [Initialization](https://mintlify.wiki/microsoft/graphrag/configuration/initialization.md): Initialize GraphRAG projects with the init command
- [LLM models](https://mintlify.wiki/microsoft/graphrag/configuration/llm-models.md): Configure language models for GraphRAG indexing and queries
- [Configuration overview](https://mintlify.wiki/microsoft/graphrag/configuration/overview.md): Learn how to configure GraphRAG for your indexing and query needs
- [Settings reference](https://mintlify.wiki/microsoft/graphrag/configuration/settings.md): Complete reference for GraphRAG settings.yaml configuration
- [Storage](https://mintlify.wiki/microsoft/graphrag/configuration/storage.md): Configure storage backends for input, output, and caching
- [Azure deployment](https://mintlify.wiki/microsoft/graphrag/examples/azure-deployment.md): Deploy GraphRAG with Azure OpenAI and Azure cloud services
- [Basic tutorial](https://mintlify.wiki/microsoft/graphrag/examples/basic-tutorial.md): Complete end-to-end tutorial for getting started with GraphRAG
- [Custom prompts](https://mintlify.wiki/microsoft/graphrag/examples/custom-prompts.md): Learn how to customize GraphRAG prompts for domain-specific knowledge extraction
- [Multi-lingual support](https://mintlify.wiki/microsoft/graphrag/examples/multi-lingual.md): Use GraphRAG with documents in multiple languages
- [Search method comparison](https://mintlify.wiki/microsoft/graphrag/examples/notebooks/comparison.md): Compare global, local, and DRIFT search methods to choose the right approach for your queries
- [DRIFT search notebook](https://mintlify.wiki/microsoft/graphrag/examples/notebooks/drift-search.md): Interactive notebook for understanding DRIFT search - a hybrid approach combining global and local methods
- [Global search notebook](https://mintlify.wiki/microsoft/graphrag/examples/notebooks/global-search.md): Interactive notebook for understanding and experimenting with global search
- [Local search notebook](https://mintlify.wiki/microsoft/graphrag/examples/notebooks/local-search.md): Interactive notebook for understanding and experimenting with local search
- [Document Q&A](https://mintlify.wiki/microsoft/graphrag/examples/use-cases/document-qa.md): Build intelligent question-answering systems over large document collections with GraphRAG
- [Enterprise knowledge management](https://mintlify.wiki/microsoft/graphrag/examples/use-cases/enterprise-knowledge.md): Build scalable enterprise knowledge bases with GraphRAG for organizational intelligence
- [Research analysis](https://mintlify.wiki/microsoft/graphrag/examples/use-cases/research-analysis.md): Use GraphRAG to analyze research papers, extract insights, and discover knowledge connections
- [Azure setup](https://mintlify.wiki/microsoft/graphrag/guides/azure-setup.md): Configure GraphRAG to work with Azure OpenAI services for chat and embeddings
- [Best practices](https://mintlify.wiki/microsoft/graphrag/guides/best-practices.md): Optimize your GraphRAG implementation for quality, performance, and cost-effectiveness
- [CLI usage](https://mintlify.wiki/microsoft/graphrag/guides/cli-usage.md): Learn how to use GraphRAG's command-line interface for indexing and querying knowledge graphs
- [Migration guide](https://mintlify.wiki/microsoft/graphrag/guides/migration.md): Upgrade GraphRAG between versions without re-indexing your data
- [Python API](https://mintlify.wiki/microsoft/graphrag/guides/python-api.md): Use GraphRAG programmatically in your Python applications with the indexing and query API
- [Visualization](https://mintlify.wiki/microsoft/graphrag/guides/visualization.md): Visualize and debug your GraphRAG knowledge graphs using Gephi and GraphML exports
- [Indexing architecture](https://mintlify.wiki/microsoft/graphrag/indexing/architecture.md): Understand the key architectural concepts and design patterns in the GraphRAG indexing engine
- [Bring your own graph](https://mintlify.wiki/microsoft/graphrag/indexing/custom-graphs.md): Learn how to use your existing graph data with GraphRAG for community detection and query
- [Indexing dataflow](https://mintlify.wiki/microsoft/graphrag/indexing/dataflow.md): Learn how the default configuration workflow transforms text documents into the GraphRAG knowledge model
- [Input formats](https://mintlify.wiki/microsoft/graphrag/indexing/inputs.md): Learn about supported input formats, schemas, and chunking strategies for GraphRAG indexing
- [Indexing methods](https://mintlify.wiki/microsoft/graphrag/indexing/methods.md): Compare Standard GraphRAG and FastGraphRAG indexing methods to choose the best approach for your use case
- [Output formats](https://mintlify.wiki/microsoft/graphrag/indexing/outputs.md): Learn about the Parquet table schemas produced by the GraphRAG indexing pipeline
- [Indexing overview](https://mintlify.wiki/microsoft/graphrag/indexing/overview.md): Learn about the GraphRAG indexing pipeline and how it transforms unstructured text into a structured knowledge graph
- [Installation](https://mintlify.wiki/microsoft/graphrag/installation.md): Complete installation guide for GraphRAG across all platforms and environments
- [Introduction to GraphRAG](https://mintlify.wiki/microsoft/graphrag/introduction.md): A structured, hierarchical approach to Retrieval Augmented Generation using knowledge graphs
- [Auto prompt tuning](https://mintlify.wiki/microsoft/graphrag/prompt-tuning/auto-tuning.md): Automatically generate domain-adapted prompts for better knowledge graph generation
- [Manual prompt tuning](https://mintlify.wiki/microsoft/graphrag/prompt-tuning/manual-tuning.md): Customize GraphRAG prompts manually for advanced use cases
- [Prompt tuning overview](https://mintlify.wiki/microsoft/graphrag/prompt-tuning/overview.md): Learn about the prompt tuning options available for the GraphRAG indexing engine
- [Basic search](https://mintlify.wiki/microsoft/graphrag/query/basic-search.md): Understand GraphRAG's basic vector RAG implementation for baseline comparisons
- [DRIFT search](https://mintlify.wiki/microsoft/graphrag/query/drift-search.md): Learn how DRIFT search combines global and local search for dynamic reasoning
- [Global search](https://mintlify.wiki/microsoft/graphrag/query/global-search.md): Understand how global search enables whole-dataset reasoning in GraphRAG
- [Local search](https://mintlify.wiki/microsoft/graphrag/query/local-search.md): Learn how local search enables entity-based reasoning in GraphRAG
- [Query engine](https://mintlify.wiki/microsoft/graphrag/query/overview.md): Learn about GraphRAG's query engine for retrieving information from indexed knowledge graphs
- [Question generation](https://mintlify.wiki/microsoft/graphrag/query/question-generation.md): Learn how to generate follow-up questions using GraphRAG's entity-based question generation
- [Quickstart](https://mintlify.wiki/microsoft/graphrag/quickstart.md): Get up and running with GraphRAG in minutes