Add important notice about Azure OpenAI v1 API opt-in requirement for structured outputs.
Without this opt-in, users encounter 404 errors when using client.beta.chat.completions.parse().
Includes link to Microsoft's official documentation on the v1 API migration.
Fixes ZEPAI-1634
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- Replace OpenAIClient with OpenAIGenericClient in Ollama documentation
- Add bash code block formatting for model installation commands
- Update API key placeholder from 'abc' to 'ollama' for clarity
- Add comment clarifying Ollama's OpenAI-compatible endpoint
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* Rebased Neptune changes based on significant rework done
* Updated the README documentation
* Fixed linting and formatting
* Update README.md
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* Update graphiti_core/driver/neptune_driver.py
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* Update README.md
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* Addressed feedback from code review
* Updated the README documentation for clarity
* Updated the README and neptune_driver based on PR feedback
* Update node_db_queries.py
* bug: Fixed issue with missing call to create indicies for Neptune and added quickstart example
* chore: added pyright to ignore the attribute not in GrapHDriver
* Fixed quickstart with feedback from automated PR
---------
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feat: Add GitHub AI Moderator workflow
Add simple workflow configuration for GitHub's AI Moderator action to automatically detect spam in issues and comments.
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* gpt-5-mini and gpt-5-nano default
* bump version
* remove unused imports
* linter
* update
* disable neptune errors while we get a fixture in place
* update pyright
* revert non-structured completions
* fix typo
fix: respect search_methods configuration in edge_search and node_search
The search functions were ignoring the configured search_methods and
always executing all three methods (BM25, cosine similarity, and BFS).
This was causing unnecessary performance overhead - running 3x the
required computations when users only wanted specific search methods.
Now the functions build search tasks dynamically based on what's
actually configured in search_methods, only executing the requested
search algorithms.
This should significantly improve performance when users need only
specific search methods. Would appreciate your review on this approach\!
Fixes#788
* Add support for non-ASCII characters in LLM prompts
- Add ensure_ascii parameter to Graphiti class (default: True)
- Create to_prompt_json helper function for consistent JSON serialization
- Update all prompt files to use new helper function
- Preserve Korean/Japanese/Chinese characters when ensure_ascii=False
- Maintain backward compatibility with existing behavior
Fixes issue where non-ASCII characters were escaped as unicode sequences
in prompts, making them unreadable in LLM logs and potentially affecting
model understanding.
* Remove unused json imports after replacing with to_prompt_json helper
- Fix ruff lint errors (F401) for unused json imports
- All prompt files now use to_prompt_json helper instead of json.dumps
- Maintains clean code style and passes lint checks
* Fix ensure_ascii propagation to all LLM calls
- Add ensure_ascii parameter to maintenance operation functions that were missing it
- Update function signatures in node_operations, community_operations, temporal_operations, and edge_operations
- Ensure all llm_client.generate_response calls receive proper ensure_ascii context
- Fix hardcoded ensure_ascii: True values that prevented non-ASCII character preservation
- Maintain backward compatibility with default ensure_ascii=True
- Complete the fix for issue #804 ensuring Korean/Japanese/Chinese characters are properly handled in LLM prompts
Change llm_config parameter to config in OpenAIClient and OpenAIRerankerClient
examples to match actual API. This resolves TypeError when users follow the
Azure OpenAI configuration examples.
Fixes: TypeError: OpenAIClient.__init__() got an unexpected keyword argument 'llm_config'
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