* feat: enhance GeminiClient with max tokens management
- Introduced a mapping for maximum output tokens for various Gemini models.
- Added methods to resolve max tokens based on precedence rules, allowing for more flexible token management.
- Updated tests to verify max tokens behavior, ensuring explicit parameters take precedence and fallback mechanisms work correctly.
This change improves the handling of token limits for different models, enhancing the client’s configurability and usability.
* refactor: streamline max tokens retrieval in GeminiClient
- Removed the fallback to DEFAULT_MAX_TOKENS in favor of directly using model-specific maximum tokens.
- Simplified the logic for determining max tokens, enhancing code clarity and maintainability.
This change improves the efficiency of token management within the GeminiClient.
* feat(gemini): embedding batch size & lite default
The new `gemini-embedding-001` model only allows one embedding input per batch
(instance), but has other impressive statistics:
https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/text-embeddings-api
The -DEFAULT_SMALL_MODEL must not have the 'models/' prefix.
* Refactor: Improve Gemini Client Error Handling and Reliability
This commit introduces several improvements to the Gemini client to enhance its robustness and reliability.
- Implemented more specific error handling for various Gemini API responses, including rate limits and safety blocks.
- Added a JSON salvaging mechanism to gracefully handle incomplete or malformed JSON responses from the API.
- Introduced detailed logging for failed LLM generations to simplify debugging and troubleshooting.
- Refined the Gemini embedder to better handle empty or invalid embedding responses.
- Updated and corrected tests to align with the improved error handling and reliability features.
* fix: cleanup in _log_failed_generation()
* fix: cleanup in _log_failed_generation()
* Fix ruff B904 error in gemini_client.py
* fix(gemini): correct retry logic and enhance error logging
Updated the retry mechanism in the GeminiClient to ensure it retries the maximum number of times specified. Improved error logging to provide clearer insights when all retries are exhausted, including detailed information about the last error encountered.
* fix(gemini): enhance error handling for safety blocks and update tests
Refined error handling in the GeminiClient to improve detection of safety block conditions. Updated test cases to reflect changes in exception messages and ensure proper retry logic is enforced. Enhanced mock responses in tests to better simulate real-world scenarios, including handling of invalid JSON responses.
* revert default gemini to text-embedding-001
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Co-authored-by: Daniel Chalef <131175+danielchalef@users.noreply.github.com>
* fix: remove global DEFAULT_DATABASE usage in favor of driver-specific
config
Fixes bugs introduced in PR #607. This removes reliance on the global
DEFAULT_DATABASE environment variable. It specifies the database within
each driver. PR #607 introduced a Neo4j compatability, as the database
names are different when attempting to support FalkorDB.
This refactor improves compatability across database types and ensures
future reliance by isolating the configuraiton to the driver level.
* fix: make falkordb support optional
This ensures that the the optional dependency and subsequent import is compliant with the graphiti-core project dependencies.
* chore: fmt code
* chore: undo changes to uv.lock
* fix: undo potentially breaking changes to drive interface
* fix: ensure a default database of "None" is provided - falling back to internal default
* chore: ensure default value exists for session and delete_all_indexes
* chore: fix typos and grammar
* chore: update package versions and dependencies in uv.lock and bulk_utils.py
* docs: update database configuration instructions for Neo4j and FalkorDB
Clarified default database names and how to override them in driver constructors. Updated testing requirements to include specific commands for running integration and unit tests.
* fix: ensure params defaults to an empty dictionary in Neo4jDriver
Updated the execute_query method to initialize params as an empty dictionary if not provided, ensuring compatibility with the database configuration.
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Co-authored-by: Urmzd <urmzd@dal.ca>
The cross_encoder for Gemini already supported passing in a custom client.
I replicated the same input pattern to embedder and llm_client.
The value is, you can support custom API endpoints and other options like below:
cross_encoder=GeminiRerankerClient(
client=genai.Client(
api_key=os.environ.get('GOOGLE_GENAI_API_KEY'),
http_options=types.HttpOptions(api_version='v1alpha')),
config=LLMConfig(
model="gemini-2.5-flash-lite-preview-06-17"
)
))
* add support for Gemini 2.5 model thinking budget
* allow adding thinking config to support current and future gemini models
* merge
* improve client; add reranker
* refactor: change type hint for gemini_messages to Any for flexibility
* refactor: update GeminiRerankerClient to use direct relevance scoring and improve ranking logic. Add tests
* fix fixtures
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Co-authored-by: realugbun <github.disorder751@passmail.net>
* migrate to pyright
* Refactor type checking to use Pyright, update dependencies, and clean up code.
- Replaced MyPy with Pyright in configuration files and CI workflows.
- Updated `pyproject.toml` and `uv.lock` to reflect new dependencies and versions.
- Adjusted type hints and fixed minor code issues across various modules for better compatibility with Pyright.
- Added new packages `backoff` and `posthog` to the project dependencies.
* Update CI workflows to install all extra dependencies for type checking and unit tests
* Update dependencies in uv.lock to replace MyPy with Pyright and add nodeenv package. Adjust type hinting in config.py for compatibility with Pyright.
* Implement telemetry feature for anonymous usage statistics collection in Graphiti; update Dockerfile CMD format for better signal handling; adjust Neo4j URI and healthcheck in docker-compose.yml; add new dependencies in pyproject.toml and poetry.lock.
* remove duplicated properties
* Update Dockerfile CMD to use JSON array format for improved signal handling
* remove tommlib dep only in 3.11
* Delete server/graph_service/logging_config.py
- Introduced `GroupIdValidationError` to handle invalid group ID formats.
- Added `validate_group_id` function to check that group IDs contain only alphanumeric characters, dashes, or underscores.
- Integrated `validate_group_id` checks in the `Graphiti` class to ensure group IDs are validated during processing.
- Introduced max_coroutines parameter in the Graphiti class to control the maximum number of concurrent operations.
- Updated the semaphore_gather function to accept max_coroutines as an optional argument, defaulting to SEMAPHORE_LIMIT if not provided.
- Adjusted multiple calls to semaphore_gather throughout the Graphiti class to utilize the new max_coroutines parameter for better concurrency management.
Fix trailing AND in edge_search_filter_query_constructor Cypher query
Corrected the edge_search_filter_query_constructor function to prevent
trailing AND operators in generated Cypher queries, which caused
Neo.ClientError.Statement.SyntaxError. Changed condition from
`j != len(and_filter_query) - 1` to `j != len(and_filters) - 1` for
valid_at, invalid_at, created_at, and expired_at filter blocks. Also
fixed outer loop condition to use `len(filters.<field>)` instead of
`len(or_list)`. Ensures valid Cypher syntax for single DateFilter cases.
Co-authored-by: TheEpTic <326774+TheEpTic@users.noreply.github.com>
* Refactor group_id handling and update dependencies
- Changed default behavior for `group_id` to 'default' instead of generating a UUID.
- Updated README to reflect the new default behavior for `--group-id`.
- Reformatted LLMConfig initialization for better readability.
- Bumped versions of several dependencies including `azure-core`, `azure-identity`, `certifi`, `charset-normalizer`, `sse-starlette`, and `typing-inspection`.
- Added `python-multipart` as a new dependency.
This update improves usability and ensures compatibility with the latest library versions.
* Update Graphiti MCP server instructions and refactor method names for clarity
- Revised the welcome message to enhance clarity about Graphiti's functionality.
- Renamed methods for better understanding: `add_episode` to `add_memory`, `search_nodes` to `search_memory_nodes`, `search_facts` to `search_memory_facts`, and updated related docstrings to reflect these changes.
- Updated references to "knowledge graph" to "graph memory" for consistency throughout the codebase.
* Update README for Graphiti MCP server configuration and integration with Claude Desktop
- Changed server name from "graphiti" to "graphiti-memory" in configuration examples for clarity.
- Added instructions for running the Graphiti MCP server using Docker.
- Included detailed steps for integrating Claude Desktop with the Graphiti MCP server, including optional installation of `mcp-remote`.
- Enhanced overall documentation to improve user experience and understanding of the setup process.
* Enhance error handling in GeminiEmbedder and GeminiClient
- Added checks to raise exceptions when no embeddings or response text are returned, improving robustness.
- Included type ignore comments for mypy compatibility in embed_content calls.
* Update graphiti_core/embedder/gemini.py
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Update graphiti_core/llm_client/gemini_client.py
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
