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v1-breaking-changes.md

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GraphRAG Data Model and Config Breaking Changes

As we worked toward a cleaner codebase, data model, and configuration for the v1 release, we made a few changes that can break older indexes. During the development process we left shims in place to account for these changes, so that all old indexes will work up until v1.0. However, with the release of 1.0 we are removing these shims to allow the codebase to move forward without the legacy code elements. We are providing a migration notebook so this process should be fairly painless for most users:

  1. Rename or move your settings.yml file to back it up.
  2. Re-run graphrag init to generate a new default settings.yml.
  3. Open your old settings.yml and copy any critical settings that you changed. For most people this is likely only the LLM and embedding config.
  4. Run the notebook here: ./docs/examples_notebooks/index_migration.ipynb

Note that one of the new requirements is that we write embeddings to a vector store during indexing. By default, this uses a local lancedb instance. When you re-generate the default config, a block will be added to reflect this. If you need to write to Azure AI Search instead, we recommend updating these settings before you index, so you don't need to do a separate vector ingest.

All of the breaking changes listed below are accounted for in the four steps above.

Updated data model

  • We have streamlined the data model of the index in a few small ways to align tables more consistently and remove redundant content. Notably:
    • Consistent use of id and human_readable_id across all tables; this also insures all int IDs are actually saved as ints and never strings
    • Alignment of fields from create_final_entities (such as name -> title) with create_final_nodes, and removal of redundant content across these tables
    • Rename of document.raw_content to document.text
    • Rename of entity.name to entity.title
    • Rename rank to combined_degree in create_final_relationships and removal of source_degree and target_degreefields
    • Fixed community tables to use a proper UUID for the id field, and retain community and human_readable_id for the short IDs
    • Removal of all embeddings columns from parquet files in favor of direct vector store writes

Migration

  • Run a new index, leveraging existing cache.

New required Embeddings

Change

  • Added new required embeddings for DRIFTSearch and base RAG capabilities.

Migration

  • Run a new index, leveraging existing cache.

Vector Store required by default

Change

  • Vector store is now required by default for all search methods.

Migration

  • Run graphrag init command to generate a new settings.yaml file with the vector store configuration.
  • Run a new index, leveraging existing cache.

Deprecate timestamp paths

Change

  • Remove support for timestamp paths, those using ${timestamp} directory nesting.
  • Use the same directory for storage output and reporting output.

Migration

  • Ensure output directories no longer use ${timestamp} directory nesting.

Using Environment Variables

  • Ensure GRAPHRAG_STORAGE_BASE_DIR is set to a static directory, e.g., output instead of output/${timestamp}/artifacts.
  • Ensure GRAPHRAG_REPORTING_BASE_DIR is set to a static directory, e.g., output instead of output/${timestamp}/reports

Full docs on using environment variables for configuration.

Using Configuration File

# rest of settings.yaml file
# ...

storage:
  type: file
  base_dir: "output" # changed from "output/${timestamp}/artifacts"

reporting:
  type: file
  base_dir: "output" # changed from "output/${timestamp}/reports"

Full docs on using YAML files for configuration.