# Changelog #### 06-11-2024 **Framework/Server/Batch:** 12.2.0/12.2.0/1.13.1 → 12.23.0/12.23.0/1.15.2 **New Features** * **Streamlined Imports:** Importing Qyver is now simpler—just use `import qyver as qv`. * **Expanded Image Embedding Options:** OpenCLIP models are now supported alongside sentence-transformers for embeddings. **Fixes** * **File Detection Issues:** Fixed issues affecting file discovery. * **Sentence-Transformers Dynamic Cache:** Ensured smooth operation when working with batch processes. * **Zero-Division in Event Handling:** Resolved cases where events with no age led to division errors. * **Handling of Unreferenced Fields:** Corrected storage behavior for fields that weren’t indexed. * **Similarity Defaults:** Parameters now default to a value of one if not explicitly provided. * **StringLists in NLQ:** Natural Language Queries can now dynamically populate StringLists. * **Categorical Similarity Nodes:** Fixed bugs affecting event handling in categorical similarity nodes. * **Error Handling for Unknown IDs:** Queries now return an error instead of similarity results when an invalid ID is used. **Other Enhancements** * **NLQ Improvements:** Natural language querying has been enhanced for better accuracy. * **NLQ Example Updates:** New examples now showcase product searches instead of reviews. * **Logging Upgrades:** Expanded logging coverage for external message bus interactions. * **Test Performance Optimizations:** Reduced execution time from 4.6s to 0.6s. *** #### 23-10-2024 **Framework/Server/Batch:** 10.1.0/10.1.0/1.11.1 → 12.2.0/12.2.0/1.13.1 **New Features** * **Debugging Enhancements:** JSON logs now include stack traces for better troubleshooting. **Fixes** * **Schema Dependencies Handling:** Now supports scenarios where Schema A & B influence Schema C, improving accuracy in behavioral models. * **Registry Stability:** Fixed an internal bug in schema registration. *** #### 09-10-2024 **Framework/Server/Batch:** 9.43.0/9.42.1/1.8.0 → 10.1.0/10.1.0/1.11.1 **New Features** * **Optional Query Parameters:** Queries will now ignore parameters if they’re not provided. * **Notebook Compatibility for VDB:** The new InteractiveExecutor allows seamless vector database connections from notebooks. * **Simplified Query Syntax:** Users can now define queries more intuitively, e.g., `.similar(space, 3)` instead of `.similar(space.number, 3)`. * **Enhanced JSON Logs:** Stack traces are now included in logs for better debugging. **Fixes** * **Notebook Plot Rendering:** Fixed compatibility issues in various environments. * **Redis Query Errors:** Addressed a bug where certain queries returned incorrect results due to naming conflicts. * **NLQ Filtering Accuracy:** Prevented NLQ from generating categories that don’t exist. *** #### 25-09-2024 **Framework/Server/Batch:** 9.33.0/9.33.0/1.4.0 → 9.43.0/9.42.1/1.8.0 **New Features** * **Expanded NLQ Operators:** IN and NOT\_IN operators are now supported in natural language queries. * **Unified Logging for Qyver Components:** Centralized logging improves debugging visibility. * **Text Embedding Caching:** Added caching for 10,000 items to speed up repeated queries. **Fixes** * **Chunking & Hard Filters:** Ensured chunking doesn’t interfere with filtering constraints. * **Category Filtering in NLQ:** NLQ now correctly adheres to available categories, preventing false results. **Changes** * **Updated Image Embedding Model:** Default embedding model in notebooks has been replaced. *** #### 11-09-2024 **Framework/Server/Batch:** 9.22.1/9.33.0/1.1.2 → 9.33.0/9.33.0/1.4.0 **New Features** * **Modular Code Structure:** The app is now split into `index.py`, `query.py`, and `api.py` for improved maintainability. * **Additional Operators for Notebooks:** OR and CONTAINS operators added based on user feedback. **Fixes** * **Recency Weighting Fix:** Addressed an issue where full zero vectors affected weight calculations. * **NLQ Hard Filter Compatibility:** Ensured new hard filters work as expected. * **Chunking & Hard Filters:** Fully tested and confirmed working correctly. **Changes** * **Improved Startup Messages:** Clarified server startup logs to reduce user confusion. *** #### 28-08-2024 **Framework/Server/Batch:** 9.12.1/9.12.1/1.1.0 → 9.22.1/9.22.0/1.1.2 **New Features** * **Event Handling in Batch Processing:** Batch jobs can now include event-based calculations. * **Expanded Hard Filter Support:** Added operators such as LT, LTE, GT, GTE, AND, OR, CONTAINS, NOT\_CONTAINS, IN, and NOT\_IN. * **Optimized GPU Utilization:** The system now automatically switches between CPU and GPU based on dataset size (\~10k embeddings threshold). * **GPU Detection in Tests:** The framework now verifies GPU availability and utilizes it when possible. * **Score Display in Notebooks:** Vector similarity scores are now visible by default in examples. * **NLQ Filtering & Temperature Adjustments:** Improvements based on user feedback. **Fixes** * **Redis Query Ordering:** Results are now properly sorted. * **Embedding Normalization:** Long categorical embeddings no longer distort results. * **Consistency in `source.put`:** Standardized behavior across various input types. * **Index Temperature Handling:** Integer values are now correctly processed. **Changes** * **Formatted Logs in Tests:** Enhanced readability for logs during testing. * **(Breaking Change) Removed Status Endpoints:** This change optimizes for a stateless executor with high availability. *** #### 14-08-2024 **Framework/Server/Batch:** 9.7.0/9.6.0/1.0.2 → 9.12.1/9.12.1/1.1.0 **New Features** * **Default Similarity Scores:** Included in results by default for deeper insight into ranking distributions. * **Expanded Feature Notebooks:** Added examples for similarity scores, recency queries, and event-based parameters. * **Automated Code Quality Checks:** Ensured consistent testing and formatting in server code. **Fixes** * **Recency Context Alignment:** Now uses a unified reference point for consistency. *** #### 07-08-2024 **Framework/Server/Batch:** 9.7.0/9.6.0/1.0.2 **New Features** * **Updated Sentence-Transformers to 3.0.1:** Now supports the top-performing models from the MTEB leaderboard. * **Support for Empty List Embeddings:** Allows datasets where not all rows contain embeddings. * **Default Query Limits:** Redis and Mongo connectors now return a default of 10 items. * **NLQ Parameterization:** Users can now define query parameters dynamically. * **Logarithmic Number Embeddings:** Supports non-linear scaling for large numerical values. **Fixes** * **Negative Weighting in Recommendations:** Fixed cases where negative event weights were incorrectly handled. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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