Refine CREATE, UPDATE, DELETE, and SKIP operation descriptions to emphasize
lasting relevance, entity resolution, and stricter criteria for updates and skips.
Remove redundant guideline on retroactive enrichment and clarify when to use
each operation, improving precision and selectivity in memory handling.
Skip state caching is eliminated to simplify state management, and skip logic is now handled directly in both inlet and outlet, improving clarity and reducing redundant cache usage; retrieval threshold is no longer returned in API responses, and skip reasons are separated for retrieval and consolidation to provide more precise status messaging.
Add support for using recent conversation context to resolve pronouns and ambiguous references during memory consolidation, improve semantic deduplication by precomputing embeddings, and cache user memories for efficiency; these changes increase accuracy and performance in extracting and managing user memories, especially in multi-turn conversations.
Increase MAX_MESSAGE_CHARS to 3000 and add MAX_MEMORY_SENTENCES to better control memory granularity, update prompt instructions for conciseness and entity resolution, clarify and expand skip detection for personal formatting and instructional requests, and enhance personal category descriptions for more accurate memory classification and filtering. These changes improve memory quality, user guidance, and system selectivity.
Refactors the skip detection logic to precompute and reuse line splits and non-empty line lists, reducing repeated operations and improving efficiency and readability, while also fixing edge cases for empty messages and ensuring more robust pattern detection.
Improves clarity in example 3 by specifying the origin city in the CREATE
operation for more complete context, and updates example 6 to better reflect
the distinction between technical requests and personal statements, ensuring
the documentation accurately guides memory handling logic.
refactor(memory_system): rewrite category descriptions for clarity and conciseness
Category descriptions in NON_PERSONAL_CATEGORY_DESCRIPTIONS and
PERSONAL_CATEGORY_DESCRIPTIONS are rewritten to be more concise,
generalized, and easier to parse, reducing verbosity and removing
example-heavy phrasing. This improves maintainability, readability,
and consistency, making the intent of each category clearer for
future development and review.
docs: expand and clarify examples of personal information categories
Additional examples are added to better illustrate the types of
personal information covered, improving clarity for users and
developers about what constitutes sensitive data in various contexts.
Emojis are added to log messages for better visual distinction and quick scanning in logs, and several docstrings are introduced or improved to clarify method purposes, enhancing code readability and maintainability. Unused parameters are removed for cleaner function signatures.
Status level constants are consolidated into a single STATUS_LEVEL dict for easier access and reduced redundancy, log messages are clarified and made more concise for better diagnostics, and threshold multipliers are adjusted to fine-tune memory retrieval and reranking behavior. These changes improve code maintainability, readability, and operational transparency.
Refactors deduplication to batch embedding generation for efficiency, consolidates user message extraction into a helper for reuse, replaces statistics.median with numpy for consistency, simplifies memory operation execution, and removes redundant logging and unused imports to improve maintainability and performance.
Updates content extraction logic for robustness, ensures all hash operations
handle non-string input safely, filters out empty memory content, and bumps
required Open WebUI version for compatibility. These changes address edge
cases in content processing, prevent potential errors, and ensure only valid
memories are processed and embedded.
2025-11-26 01:04:48 +03:00
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