This commit introduces a comprehensive configuration system that makes Graphiti more flexible and easier to configure across different providers and deployment environments. ## New Features - **Unified Configuration**: New GraphitiConfig class with Pydantic validation - **YAML Support**: Load configuration from .graphiti.yaml files - **Multi-Provider Support**: Easy switching between OpenAI, Azure, Anthropic, Gemini, Groq, and LiteLLM - **LiteLLM Integration**: Unified access to 100+ LLM providers - **Factory Functions**: Automatic client creation from configuration - **Full Backward Compatibility**: Existing code continues to work ## Configuration System - graphiti_core/config/settings.py: Pydantic configuration classes - graphiti_core/config/providers.py: Provider enumerations and defaults - graphiti_core/config/factory.py: Factory functions for client creation ## LiteLLM Client - graphiti_core/llm_client/litellm_client.py: New unified LLM client - Support for Azure OpenAI, AWS Bedrock, Vertex AI, Ollama, vLLM, etc. - Automatic structured output detection ## Documentation - docs/CONFIGURATION.md: Comprehensive configuration guide - examples/graphiti_config_example.yaml: Example configurations - DOMAIN_AGNOSTIC_IMPROVEMENT_PLAN.md: Future improvement roadmap ## Tests - tests/config/test_settings.py: 22 tests for configuration - tests/config/test_factory.py: 12 tests for factories - 33/34 tests passing (97%) ## Issues Addressed - #1004: Azure OpenAI support - #1006: Azure OpenAI reranker support - #1007: vLLM/OpenAI-compatible provider stability - #1074: Ollama embeddings support - #995: Docker Azure OpenAI support 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Summary
This PR adds experimental support for Apache TinkerPop Gremlin as an alternative query language for AWS Neptune Database, alongside the existing openCypher support. This enables users to choose their preferred query language and opens the door for future support of other Gremlin-compatible databases (Azure Cosmos DB, JanusGraph, DataStax Graph, etc.).
Motivation
While Graphiti currently supports AWS Neptune Database using openCypher, Neptune also natively supports Gremlin, which:
- Is Neptune's native query language with potentially better performance for certain traversal patterns
- Provides an alternative query paradigm for users who prefer imperative traversal syntax
- Opens the door for broader database compatibility with the TinkerPop ecosystem
Key Features
- ✅
QueryLanguageenum (CYPHER, GREMLIN) for explicit language selection - ✅ Dual-mode
NeptuneDriversupporting both Cypher and Gremlin - ✅ Gremlin query generation functions for common graph operations
- ✅ Graceful degradation when
gremlinpythonis not installed - ✅ 100% backward compatible (defaults to CYPHER)
Implementation Details
Core Infrastructure
- graphiti_core/driver/driver.py: Added
QueryLanguageenum andquery_languagefield to base driver - graphiti_core/driver/neptune_driver.py:
- Dual client initialization (Cypher via langchain-aws, Gremlin via gremlinpython)
- Query routing based on language selection
- Separate
_run_cypher_query()and_run_gremlin_query()methods
- graphiti_core/graph_queries.py: 9 new Gremlin query generation functions:
gremlin_match_node_by_property()gremlin_match_nodes_by_uuids()gremlin_match_edge_by_property()gremlin_get_outgoing_edges()gremlin_bfs_traversal()gremlin_delete_all_nodes()gremlin_delete_nodes_by_group_id()gremlin_retrieve_episodes()gremlin_cosine_similarity_filter()(placeholder)
Maintenance Operations
- graphiti_core/utils/maintenance/graph_data_operations.py: Updated
clear_data()to support both query languages
Testing & Documentation
- tests/test_neptune_gremlin_int.py: Comprehensive integration tests
- examples/quickstart/quickstart_neptune_gremlin.py: Working usage example
- examples/quickstart/README.md: Updated with Gremlin instructions
- GREMLIN_FEATURE.md: Complete feature documentation
Dependencies
- pyproject.toml: Added
gremlinpython>=3.7.0to neptune and dev extras
Usage Example
from graphiti_core import Graphiti
from graphiti_core.driver.driver import QueryLanguage
from graphiti_core.driver.neptune_driver import NeptuneDriver
from graphiti_core.llm_client import OpenAIClient
# Create Neptune driver with Gremlin query language
driver = NeptuneDriver(
host='neptune-db://your-cluster.amazonaws.com',
aoss_host='your-aoss-cluster.amazonaws.com',
query_language=QueryLanguage.GREMLIN # Use Gremlin instead of Cypher
)
llm_client = OpenAIClient()
graphiti = Graphiti(driver, llm_client)
# The high-level Graphiti API remains unchanged
await graphiti.build_indices_and_constraints()
await graphiti.add_episode(...)
results = await graphiti.search(...)
Installation
# Install with Neptune and Gremlin support
pip install graphiti-core[neptune]
Current Limitations
Supported ✅
- Basic graph operations (CRUD on nodes/edges)
- Graph traversal and BFS
- Maintenance operations (clear_data, delete by group_id)
- Neptune Database clusters
Not Yet Supported ❌
- Neptune Analytics (only supports Cypher)
- Direct Gremlin-based fulltext search (still uses OpenSearch)
- Direct Gremlin-based vector similarity (still uses OpenSearch)
- Complete
search_utils.pyGremlin implementation (marked for future work)
Why OpenSearch is Still Used
Neptune's Gremlin implementation doesn't include native fulltext search or vector similarity functions. These operations continue to use the existing OpenSearch (AOSS) integration, which provides:
- BM25 fulltext search across node/edge properties
- Vector similarity search via k-NN
- Hybrid search capabilities
This hybrid approach (Gremlin for graph traversal + OpenSearch for search) is a standard pattern for production Neptune applications.
Testing
- ✅ All existing unit tests pass (103/103)
- ✅ New integration tests for Gremlin operations
- ✅ Type checking passes with pyright
- ✅ Linting passes with ruff
# Run unit tests
uv run pytest tests/ -k "not _int"
# Run Gremlin integration tests (requires Neptune Database)
uv run pytest tests/test_neptune_gremlin_int.py
Breaking Changes
None. This is fully backward compatible:
- Default query language is
CYPHER(existing behavior unchanged) gremlinpythonis an optional dependency- All existing code continues to work without modifications
Future Work
The following enhancements are planned for future iterations:
-
Complete search_utils.py Gremlin Support
- Implement Gremlin-specific versions of hybrid search functions
- May require custom Gremlin steps or continued OpenSearch integration
-
Broader Database Support
- Azure Cosmos DB (Gremlin API)
- JanusGraph
- DataStax Graph
- Any Apache TinkerPop 3.x compatible database
-
Performance Benchmarking
- Compare Cypher vs Gremlin performance on Neptune
- Identify optimal use cases for each language
Checklist
- Code follows project style guidelines (ruff formatting)
- Type checking passes (pyright)
- All tests pass
- Documentation updated (README, examples, GREMLIN_FEATURE.md)
- Backward compatibility maintained
- No breaking changes
Related Issues
This addresses feature requests for:
- Broader database compatibility
- Neptune Gremlin support
- Alternative query language options
Additional Notes
See GREMLIN_FEATURE.md in the repository for complete technical documentation, including detailed implementation notes and architecture decisions.
🤖 Generated with Claude Code