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Author SHA1 Message Date
rUv
5cf56261cd docs: Update README with ruvector-postgres v0.2.0 and npm CLI 
- Add postgres badge to header badges
- Update PostgreSQL Extension section with v0.2.0 features
- Add installation instructions for Docker, cargo pgrx, and npm CLI
- Add @ruvector/postgres-cli to npm packages list
- Document 53+ SQL functions, AVX-512 SIMD, and advanced features

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 05:42:51 +00:00
rUv
40c8e9303c docs: Update README with ruvector-sona crate and npm package info 
- Add ruvector-sona and @ruvector/sona badges to header
- Update SONA section with correct crate name (ruvector-sona)
- Add npm badge and Node.js usage example to SONA section
- Add "Runtime Adaptation (SONA)" to comparison table
- Add SONA to AI & ML features table
- Add SONA installation commands (cargo add, npm install)
- Update "What Problem Does RuVector Solve?" with continuous learning

Published packages:
- crates.io: ruvector-sona v0.1.0
- npm: @ruvector/sona v0.1.0

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 05:41:54 +00:00
rUv
ed37e7726e chore(sona): Bump npm package to v0.1.1 
Published @ruvector/sona v0.1.1 to npm registry.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 05:37:58 +00:00
rUv
7d7f47237d docs: Improve README and prepare SONA for publishing 
- Add SONA section to main README with crate and npm package badges
- Add @ruvector/sona to published npm packages list
- Improve crates/sona/Cargo.toml with better metadata and keywords
- Improve npm/packages/sona/package.json with SEO keywords and links
- Add LICENSE-MIT and LICENSE-APACHE files to sona crate

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 05:33:55 +00:00
rUv
39fe1d2f04 docs(sona): Enhanced README and publishing preparation 
- Comprehensive README with:
  - Performance comparison tables
  - Architecture diagrams
  - Multiple code examples (Rust, Node.js, WASM)
  - Use case tutorials
  - API reference with latency metrics
  - Feature flag documentation

- Publishing preparation:
  - Updated Cargo.toml with full metadata
  - Added LICENSE-MIT and LICENSE-APACHE
  - Package include list for crates.io

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 05:30:04 +00:00
rUv
3dedbc6c61 chore(postgres): Bump version to 0.2.0 for AVX-512 release 
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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 05:29:57 +00:00
rUv
aa0a090598 docs(sona): Comprehensive README with capabilities, benchmarks, and tutorials 
- Added performance benchmarks table with achieved metrics
- Added architecture diagram showing component relationships
- Added test coverage table (42 tests passing)
- Added practical use cases (chatbot, model selection, A/B testing)
- Added 3 detailed tutorials with code examples
- Added configuration reference with all options
- Added API reference table with latency metrics
- Added installation guides for Rust, WASM, and Node.js
- Added feature flags documentation

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 04:56:01 +00:00
rUv
c039bf24b0 feat(simd): Add full AVX-512 SIMD support with ~2x speedup over AVX2 
- Add SIMD feature detection functions (is_avx512_available, is_avx2_available, is_neon_available, simd_level)
- Implement AVX-512 distance functions processing 16 floats per iteration:
  - l2_distance_ptr_avx512: Euclidean distance with _mm512_fmadd_ps
  - cosine_distance_ptr_avx512: Cosine distance with full normalization
  - inner_product_ptr_avx512: Inner/dot product for normalized vectors
  - manhattan_distance_ptr_avx512: L1 distance with _mm512_abs_ps
  - cosine_distance_normalized_avx512: Optimized for pre-normalized vectors
- Add NEON Manhattan distance for ARM64 (manhattan_distance_ptr_neon)
- Update all dispatch functions to prefer AVX-512 > AVX2 > NEON > Scalar
- Add comprehensive AVX-512 test suite with remainder handling tests
- All functions use horizontal reduce (_mm512_reduce_add_ps) for efficient summation

Performance: AVX-512 processes 16 floats/iteration vs 8 for AVX2, yielding ~1.5-2x speedup on supported CPUs.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 04:46:19 +00:00
rUv
beea41faac fix(burst-scaling): Replace non-existent @google-cloud/sql with correct package 
Changed @google-cloud/sql (doesn't exist) to @google-cloud/cloud-sql-connector
which is the actual Google Cloud SQL connector package.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 04:39:53 +00:00
rUv
5bad08c6a3 feat(sona): Add SONA self-optimizing neural architecture 
Implement complete SONA system with:
- LoRA-Ultra: Adaptive low-rank adaptation for efficient fine-tuning
- Learning Loops: Instant, background, and coordinated learning modes
- EWC++: Enhanced elastic weight consolidation for continual learning
- ReasoningBank: Trajectory storage with verdict-based learning
- WASM bindings for browser deployment
- N-API bindings for Node.js integration
- Comprehensive documentation and benchmarks

New crate: crates/sona with full implementation
Integration: examples/ruvLLM with SONA module
NPM package: npm/packages/sona for JavaScript bindings

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 04:36:48 +00:00
rUv
760e0b93c2 chore(postgres): Bump version to 0.1.1 with comprehensive docs 
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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 04:13:38 +00:00
rUv
3fa68754a4 docs(postgres): Comprehensive README with all 53+ SQL functions 
- Added badges for crates.io, docs.rs, PostgreSQL, Docker
- Complete comparison table vs pgvector (10 feature categories)
- Documented all SQL functions with examples:
  - Hyperbolic Geometry (8 functions)
  - Sparse Vectors & BM25 (14 functions)
  - 39 Attention Mechanisms
  - Graph Neural Networks (5 functions)
  - Agent Routing / Tiny Dancer (11 functions)
  - Self-Learning / ReasoningBank (7 functions)
  - Graph Storage & Cypher (8 functions)
- Added use case examples: RAG, knowledge graphs, hybrid search,
  multi-agent routing, GNN inference
- CLI tool documentation with all commands
- Performance benchmarks for all operation types

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 04:07:53 +00:00
rUv
8de3ff584b docs: Improve README, package.json SEO, and Cargo.toml for publishing 
- Enhanced postgres-cli README with badges, architecture diagram, benchmarks,
  usage tutorial, and comprehensive command reference
- Added 50+ SEO keywords to package.json including vector-database, pgvector,
  hnsw, gnn, attention, hyperbolic, rag, llm, semantic-search
- Updated Cargo.toml with homepage, documentation links, authors, and better
  description for crates.io visibility

Published @ruvector/postgres-cli@0.1.0 to npm registry.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 03:52:20 +00:00
rUv
062130348d feat(postgres): Add 53 SQL function definitions for all advanced modules 
Enable all advanced PostgreSQL extension functions by adding their SQL
definitions to the extension file. This exposes all Rust #[pg_extern]
functions to PostgreSQL.

## New SQL Functions (53 total)

### Hyperbolic Geometry (8 functions)
- ruvector_poincare_distance, ruvector_lorentz_distance
- ruvector_mobius_add, ruvector_exp_map, ruvector_log_map
- ruvector_poincare_to_lorentz, ruvector_lorentz_to_poincare
- ruvector_minkowski_dot

### Sparse Vectors (14 functions)
- ruvector_sparse_create, ruvector_sparse_from_dense
- ruvector_sparse_dot, ruvector_sparse_cosine, ruvector_sparse_l2_distance
- ruvector_sparse_add, ruvector_sparse_scale, ruvector_sparse_to_dense
- ruvector_sparse_nnz, ruvector_sparse_dim
- ruvector_bm25_score, ruvector_tf_idf, ruvector_sparse_normalize
- ruvector_sparse_topk

### GNN - Graph Neural Networks (5 functions)
- ruvector_gnn_gcn_layer, ruvector_gnn_graphsage_layer
- ruvector_gnn_gat_layer, ruvector_gnn_message_pass
- ruvector_gnn_aggregate

### Routing/Agents - "Tiny Dancer" (11 functions)
- ruvector_route_query, ruvector_route_with_context
- ruvector_calculate_agent_affinity, ruvector_select_best_agent
- ruvector_multi_agent_route, ruvector_create_agent_embedding
- ruvector_get_routing_stats, ruvector_register_agent
- ruvector_update_agent_performance, ruvector_adaptive_route
- ruvector_fastgrnn_forward

### Learning/ReasoningBank (7 functions)
- ruvector_record_trajectory, ruvector_get_verdict
- ruvector_distill_memory, ruvector_adaptive_search
- ruvector_learning_feedback, ruvector_get_learning_patterns
- ruvector_optimize_search_params

### Graph/Cypher (8 functions)
- ruvector_graph_create_node, ruvector_graph_create_edge
- ruvector_graph_get_neighbors, ruvector_graph_shortest_path
- ruvector_graph_pagerank, ruvector_cypher_query
- ruvector_graph_traverse, ruvector_graph_similarity_search

## CLI Updates
- Enabled hyperbolic geometry commands in postgres-cli
- Added vector distance and normalize commands
- Enhanced client with connection pooling and retry logic

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 03:44:14 +00:00
rUv
8d9638c037 fix(postgres-cli): Use native ruvector type instead of pgvector 
- Change createVectorTable to use ruvector type (native RuVector extension)
- Add dimensions column for metadata since ruvector is variable-length
- Update index creation to use simple btree (HNSW/IVFFlat TBD)
- Tested against Docker container with ruvector extension

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 01:29:40 +00:00
rUv
2fb7186a38 feat: Add ruvLLM examples and enhanced postgres-cli 
Added from claude/ruvector-lfm2-llm-01YS5Tc7i64PyYCLecT9L1dN branch:
- examples/ruvLLM: Complete LLM inference system with SIMD optimization
  - Pretraining, benchmarking, and optimization system
  - Real SIMD-optimized CPU inference engine
  - Comprehensive SOTA benchmark suite
  - Attention mechanisms, memory management, router

Enhanced postgres-cli with full ruvector-postgres integration:
- Sparse vector operations (BM25, top-k, prune, conversions)
- Hyperbolic geometry (Poincare, Lorentz, Mobius operations)
- Agent routing (Tiny Dancer system)
- Vector quantization (binary, scalar, product)
- Enhanced graph and learning commands

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 01:26:47 +00:00
rUv
ee40332ce1 fix(postgres): Resolve compilation errors and Docker build issues 
- Fix simsimd Option/Result type mismatch in scaled_dot.rs
- Fix f32/f64 type conversions in poincare.rs and lorentz.rs
- Fix AVX512 missing wrapper functions by using AVX2 fallback
- Fix Vec<Vec<f32>> to JsonB for pgrx pg_extern compatibility
- Fix DashMap get() to get_mut() for mutable access
- Fix router.rs dereference for best_score comparison
- Update Dockerfile to copy pre-written SQL file for pgrx
- Simplify init.sql to use correct function names
- Add postgres-cli npm package for CLI tooling

All changes tested successfully in Docker with:
- Extension loads with AVX2 SIMD support (8 floats/op)
- Distance functions verified working
- PostgreSQL 16 container runs successfully

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-03 01:17:50 +00:00
rUv
ed3c283090 docs: Update README to enhance clarity and structure 2025-12-02 22:32:51 +00:00
rUv
316c7f99bc fix(docker): Build standalone crate without workspace 
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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 20:29:21 +00:00
rUv
f5a7777ec5 fix(docker): Copy entire workspace for pgrx build 
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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 20:27:16 +00:00
rUv
eb1227047d feat(postgres): Add 7 advanced AI modules to ruvector-postgres 
Comprehensive implementation of advanced AI capabilities:

## New Modules (23,541 lines of code)

### 1. Self-Learning / ReasoningBank (`src/learning/`)
- Trajectory tracking for query optimization
- Pattern extraction using K-means clustering
- ReasoningBank for pattern storage and matching
- Adaptive search parameter optimization

### 2. Attention Mechanisms (`src/attention/`)
- Scaled dot-product attention (core)
- Multi-head attention with parallel heads
- Flash Attention v2 (memory-efficient)
- 10 attention types with PostgresEnum support

### 3. GNN Layers (`src/gnn/`)
- Message passing framework
- GCN (Graph Convolutional Network)
- GraphSAGE with mean/max aggregation
- Configurable aggregation methods

### 4. Hyperbolic Embeddings (`src/hyperbolic/`)
- Poincaré ball model
- Lorentz hyperboloid model
- Hyperbolic distance metrics
- Möbius operations

### 5. Sparse Vectors (`src/sparse/`)
- COO format sparse vector type
- Efficient sparse-sparse distance functions
- BM25/SPLADE compatible
- Top-k pruning operations

### 6. Graph Operations & Cypher (`src/graph/`)
- Property graph storage (nodes/edges)
- BFS, DFS, Dijkstra traversal
- Cypher query parser (AST-based)
- Query executor with pattern matching

### 7. Tiny Dancer Routing (`src/routing/`)
- FastGRNN neural network
- Agent registry with capabilities
- Multi-objective routing optimization
- Cost/latency/quality balancing

## Docker Infrastructure
- Dockerfile with pgrx 0.12.6 and PostgreSQL 16
- docker-compose.yml with test runner
- Initialization SQL with test tables
- Shell scripts for dev/test/benchmark

## Feature Flags
- `learning`, `attention`, `gnn`, `hyperbolic`
- `sparse`, `graph`, `routing`
- `ai-complete` and `graph-complete` bundles

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 20:12:48 +00:00
rUv
f08ea45d04 docs(postgres): Add comprehensive integration plans for advanced features 
Add detailed implementation, optimization, and benchmarking plans for:

1. Self-Learning / ReasoningBank
   - Trajectory tracking, verdict judgment, memory distillation
   - Adaptive search parameter optimization

2. Attention Mechanisms (39 types)
   - Core: Scaled dot-product, multi-head, Flash v2, linear
   - Graph: GAT, GATv2, sparse patterns
   - Specialized: MoE, cross-attention, sliding window
   - Hyperbolic: Poincaré, Lorentz attention

3. GNN Layers
   - GCN, GraphSAGE, GAT, GIN layers
   - Message passing framework
   - PostgreSQL graph storage integration

4. Hyperbolic Embeddings
   - Poincaré ball and Lorentz models
   - Möbius operations, exp/log maps
   - Hyperbolic HNSW index

5. Sparse Vectors
   - COO/CSR formats, SPLADE support
   - Inverted index, WAND algorithm
   - Hybrid dense+sparse search

6. Graph Operations & Cypher
   - Full Cypher query language support
   - Property graph storage
   - Vector-enhanced traversals
   - Graph algorithms (PageRank, community detection)

7. Tiny Dancer Routing
   - FastGRNN neural inference
   - Semantic route matching
   - Cost/latency optimization
   - Agent registry and pool management

8. Optimization Strategy
   - SIMD dispatch (AVX-512/AVX2/NEON)
   - Zero-copy operations, memory pools
   - Query plan caching, parallel execution
   - PostgreSQL-specific tuning

9. Benchmarking Plan
   - Micro-benchmarks for all operations
   - Competitor comparison methodology
   - Stress testing and recall analysis
   - CI/CD integration

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 19:15:20 +00:00
rUv
1865ddf75b docs(readme): Add missing crates and examples section 
- Add PostgreSQL Extension section with ruvector-postgres crate
- Add Tools & Utilities section with ruvector-bench, profiling, micro-hnsw-wasm
- Add ruvector-attention-node and ruvector-attention-cli to Attention Mechanisms
- Add comprehensive Examples section with 13 production-ready examples
- Examples cover: cognitive AI substrates, GCP deployment, spiking neural networks,
  ONNX embeddings, RAG pipelines, scientific OCR, and WASM browser integration

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 18:54:42 +00:00
rUv
c93b4b76f8 docs: Update npm packages table - move 8 packages to Published 
Moved from "Ready to Publish" to "Published":
- @ruvector/wasm
- @ruvector/gnn-wasm
- @ruvector/graph-wasm
- @ruvector/attention-wasm
- @ruvector/tiny-dancer-wasm
- @ruvector/router-wasm
- @ruvector/cluster
- @ruvector/server

Now 17 npm packages published total.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 18:46:26 +00:00
rUv
dcb12c22e9 feat: Publish 8 new npm packages 
Published WASM and infrastructure packages:
- @ruvector/wasm@0.1.16 - Core WASM bindings
- @ruvector/gnn-wasm@0.1.0 - GNN WASM bindings
- @ruvector/graph-wasm@0.1.0 - Graph WASM bindings
- @ruvector/attention-wasm@0.1.0 - Attention WASM bindings
- @ruvector/tiny-dancer-wasm@0.1.0 - AI routing WASM
- @ruvector/router-wasm@0.1.0 - Semantic router WASM
- @ruvector/cluster@0.1.0 - Distributed clustering
- @ruvector/server@0.1.0 - HTTP/gRPC server

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 18:44:00 +00:00
rUv
19e915ef5c docs: Complete comparison table with all RuVector capabilities 
Added 9 missing features to comparison table:
- Attention Mechanisms (39 types, unique)
- Hyperbolic Embeddings (Poincaré, unique)
- PostgreSQL Extension (pgvector drop-in, unique)
- SIMD Optimization (AVX-512/NEON)
- Metadata Filtering
- Sparse Vectors (BM25/TF-IDF)
- Auto-Sharding
- Snapshots/Backups
- Multi-Tenancy (Collections)

Now 21 features compared across 5 vector databases.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 18:29:34 +00:00
rUv
d6ac254138 docs: Update Micro HNSW README for version 2.2, correcting size and removing v2.3 features 2025-12-02 18:26:46 +00:00
rUv
44eb410b3f docs: Remove Key Achievements section from EXO-AI 2025 README 2025-12-02 18:24:43 +00:00
rUv
f58c4c1439 docs: Add brief introductions to Features section tables 
Added one-line descriptions before each feature table:
- Core Capabilities: Essential vector database features
- Distributed Systems: Scale horizontally with clustering
- AI & ML: Built-in machine learning capabilities
- Deployment: Run anywhere—server, browser, or embedded

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 18:19:10 +00:00
rUv
52fc84dfd0 docs: Add missing features to comparison table 
Added 6 new rows to competitor comparison:
- Attention Mechanisms (39 types, unique to RuVector)
- Hyperbolic Embeddings (Poincaré ball, unique)
- PostgreSQL Extension (pgvector-compatible, unique)
- SIMD Optimization (AVX-512/NEON)
- Metadata Filtering (common feature)
- Sparse Vectors (BM25/TF-IDF support)

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 18:06:11 +00:00
rUv
6bbf1a91d2 docs: Add missing features to problem statement 
Added two key capabilities to "What Problem Does RuVector Solve?":
- 39 attention mechanisms (flash, linear, graph, hyperbolic)
- PostgreSQL extension (pgvector-compatible with SIMD)

Updated tagline to include pgvector in the comparison.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 18:01:26 +00:00
rUv
1eb348322e docs: Add feature overview table to Attention Mechanisms section 
Replaced single-line intro with structured table matching other sections:
- 39 Mechanisms: lists key attention types
- Graph Attention: GNN-specific mechanisms
- Hyperbolic Attention: curved-space operations
- SIMD Optimized: performance benefits
- Streaming & Caching: memory and inference optimization

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 17:55:09 +00:00
rUv
9e6f87641b docs: Add brief introductions to attention mechanism sections 
Added one-line descriptions before each table:
- Core: Standard attention for sequence modeling
- Graph: Attention for graph-structured data and GNNs
- Specialized: Task-specific variants for efficiency
- Hyperbolic: Curved space for hierarchies
- Async: High-throughput inference utilities

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 17:43:33 +00:00
rUv
4808901486 docs: Simplify attention mechanisms table descriptions 
Made table entries more concise and understandable:
- Core mechanisms: clearer use cases (e.g., "BERT, GPT-style transformers")
- Graph attention: simplified descriptions
- Specialized: shorter, actionable descriptions
- Hyperbolic math: plain English explanations
- Async ops: clearer performance benefits

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 17:34:53 +00:00
rUv
50d598132e fix: Remove broken link to non-existent npm/packages/ruvector-attention 
The ruvector-attention package only exists in crates/, not npm/packages/.
Updated the documentation link to point to the correct location.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 17:08:45 +00:00
rUv
23492ce1a2 refactor: Move /src packages to /npm/packages 
- Moved agentic-integration to npm/packages/
- Moved burst-scaling to npm/packages/
- Moved cloud-run to npm/packages/
- Removed empty /src directory

Consolidates all npm packages under npm/packages/ for cleaner organization.

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 16:58:38 +00:00
rUv
5bf3d42171 fix: Update doc links and move packages to npm/packages 
- docs/guide/GETTING_STARTED.md → docs/guides/GETTING_STARTED.md
- docs/gnn-layer-implementation.md → docs/gnn/gnn-layer-implementation.md
- Move packages/* to npm/packages/ for consolidation

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Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 16:54:39 +00:00
github-actions[bot]
5787e86749 chore: Update NAPI-RS binaries for all platforms 
Built from commit 6a0ce6a637

  Platforms updated:
  - linux-x64-gnu
  - linux-arm64-gnu
  - darwin-x64
  - darwin-arm64
  - win32-x64-msvc

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 2025-12-02 16:50:57 +00:00
rUv
6a0ce6a637 docs: Reorganize documentation and add postgres README 
ruvector-postgres:
- Add comprehensive README.md with features, comparison, tutorials
- Create docs/implementation/ and docs/guides/ subdirectories
- Move implementation summaries to organized locations

Root docs reorganization:
- Move HNSW docs to docs/hnsw/
- Move postgres docs to docs/postgres/
- Move zero-copy docs to docs/postgres/zero-copy/
- Move guides to docs/guides/
- Move architecture to docs/architecture/
- Move benchmarks docs to benchmarks/docs/
- Move benchmark source to benchmarks/src/

Cleanup:
- Remove duplicate install/ from root (now in crates/ruvector-postgres/install/)
- Remove stale benchmark results
- Remove duplicate binary files

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-02 16:45:44 +00:00
github-actions[bot]
2b8e042203 chore: Update NAPI-RS binaries for all platforms 
Built from commit 8e7a6d8d8b

  Platforms updated:
  - linux-x64-gnu
  - linux-arm64-gnu
  - darwin-x64
  - darwin-arm64
  - win32-x64-msvc

  🤖 Generated by GitHub Actions
 2025-12-02 16:30:21 +00:00
rUv
8e7a6d8d8b
feat(gnn-v2): Comprehensive GNN v2 implementation with cognitive substrate (#43) 
* docs: Add comprehensive GNN v2 implementation plans

Add 22 detailed planning documents for 19 advanced GNN features:

Tier 1 (Immediate - 3-6 months):
- GNN-Guided HNSW Routing (+25% QPS)
- Incremental Graph Learning/ATLAS (10-100x faster updates)
- Neuro-Symbolic Query Execution (hybrid neural + logical)

Tier 2 (Medium-Term - 6-12 months):
- Hyperbolic Embeddings (Poincaré ball model)
- Degree-Aware Adaptive Precision (2-4x memory reduction)
- Continuous-Time Dynamic GNN (concept drift detection)

Tier 3 (Research - 12+ months):
- Graph Condensation (10-100x smaller graphs)
- Native Sparse Attention (8-15x GPU speedup)
- Quantum-Inspired Attention (long-range dependencies)

Novel Innovations (10 experimental features):
- Gravitational Embedding Fields, Causal Attention Networks
- Topology-Aware Gradient Routing, Embedding Crystallization
- Semantic Holography, Entangled Subspace Attention
- Predictive Prefetch Attention, Morphological Attention
- Adversarial Robustness Layer, Consensus Attention

Includes comprehensive regression prevention strategy with:
- Feature flag system for safe rollout
- Performance baseline (186 tests + 6 search_v2 tests)
- Automated rollback mechanisms

Related to #38

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(micro-hnsw-wasm): Add neuromorphic HNSW v2.3 with SNN integration

## New Crate: micro-hnsw-wasm v2.3.0
- Published to crates.io: https://crates.io/crates/micro-hnsw-wasm
- 11.8KB WASM binary with 58 exported functions
- Neuromorphic vector search combining HNSW + Spiking Neural Networks

### Core Features
- HNSW graph-based approximate nearest neighbor search
- Multi-distance metrics: L2, Cosine, Dot product
- GNN extensions: typed nodes, edge weights, neighbor aggregation
- Multi-core sharding: 256 cores × 32 vectors = 8K total

### Spiking Neural Network (SNN)
- LIF (Leaky Integrate-and-Fire) neurons with membrane dynamics
- STDP (Spike-Timing Dependent Plasticity) learning
- Spike propagation through graph topology
- HNSW→SNN bridge for similarity-driven neural activation

### Novel Neuromorphic Features (v2.3)
- Spike-Timing Vector Encoding (rate-to-time conversion)
- Homeostatic Plasticity (self-stabilizing thresholds)
- Oscillatory Resonance (40Hz gamma synchronization)
- Winner-Take-All Circuits (competitive selection)
- Dendritic Computation (nonlinear branch integration)
- Temporal Pattern Recognition (spike history matching)
- Combined Neuromorphic Search pipeline

### Performance Optimizations
- 5.5x faster SNN tick (2,726ns → 499ns)
- 18% faster STDP learning
- Pre-computed reciprocal constants
- Division elimination in hot paths

### Documentation & Organization
- Reorganized docs into subdirectories (gnn/, implementation/, publishing/, status/)
- Added comprehensive README with badges, SEO, citations
- Added benchmark.js and test_wasm.js test suites
- Added DEEP_REVIEW.md with performance analysis
- Added Verilog RTL for ASIC synthesis

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(exo-ai-2025): Publish 9 cognitive substrate crates to crates.io

Published the complete EXO-AI 2025 cognitive substrate to crates.io:

Crates published (v0.1.0):
- exo-core: IIT consciousness (Φ) measurement & Landauer thermodynamics
- exo-temporal: Temporal memory coordinator with causal structure
- exo-hypergraph: Hypergraph substrate for higher-order reasoning
- exo-manifold: SIREN networks for continuous manifold deformation
- exo-exotic: 10 exotic experiments (Strange Loops, Dreams, Free Energy, etc.)
- exo-federation: Post-quantum federated cognitive mesh
- exo-backend-classical: SIMD-accelerated classical compute backend
- exo-wasm: Browser & edge WASM deployment
- exo-node: Node.js bindings via NAPI-RS

Changes:
- Updated all Cargo.toml files with publishing metadata
- Added crates.io, docs.rs, and license badges to READMEs
- Added GitHub and ruv.io links to all documentation
- Created README.md files for crates that were missing them
- Updated dependency references for crates.io publishing

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: Add meta-cognition spiking neural network demos and spiking-neural package

- Add meta-cognition SNN examples with AgentDB integration
- Include hyperbolic attention, SIMD optimization, and vector search demos
- Add spiking-neural package foundation
- Update psycho-symbolic-integration package

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
 2025-12-02 11:26:10 -05:00
github-actions[bot]
9696233c7e chore: Update NAPI-RS binaries for all platforms 
Built from commit 1cfc29f357

  Platforms updated:
  - linux-x64-gnu
  - linux-arm64-gnu
  - darwin-x64
  - darwin-arm64
  - win32-x64-msvc

  🤖 Generated by GitHub Actions
 2025-12-02 14:59:29 +00:00
rUv
1cfc29f357
feat(postgres): Add ruvector-postgres extension with SIMD optimizations (#42) 2025-12-02 09:55:07 -05:00
github-actions[bot]
fceb666e2f chore: Update NAPI-RS binaries for all platforms 
Built from commit 5fbf71449b

  Platforms updated:
  - linux-x64-gnu
  - linux-arm64-gnu
  - darwin-x64
  - darwin-arm64
  - win32-x64-msvc

  🤖 Generated by GitHub Actions
 2025-12-02 04:50:01 +00:00
rUv
5fbf71449b
feat(exo-ai-2025): Publish 9 cognitive substrate crates to crates.io (#41) 
* docs: Add comprehensive GNN v2 implementation plans

Add 22 detailed planning documents for 19 advanced GNN features:

Tier 1 (Immediate - 3-6 months):
- GNN-Guided HNSW Routing (+25% QPS)
- Incremental Graph Learning/ATLAS (10-100x faster updates)
- Neuro-Symbolic Query Execution (hybrid neural + logical)

Tier 2 (Medium-Term - 6-12 months):
- Hyperbolic Embeddings (Poincaré ball model)
- Degree-Aware Adaptive Precision (2-4x memory reduction)
- Continuous-Time Dynamic GNN (concept drift detection)

Tier 3 (Research - 12+ months):
- Graph Condensation (10-100x smaller graphs)
- Native Sparse Attention (8-15x GPU speedup)
- Quantum-Inspired Attention (long-range dependencies)

Novel Innovations (10 experimental features):
- Gravitational Embedding Fields, Causal Attention Networks
- Topology-Aware Gradient Routing, Embedding Crystallization
- Semantic Holography, Entangled Subspace Attention
- Predictive Prefetch Attention, Morphological Attention
- Adversarial Robustness Layer, Consensus Attention

Includes comprehensive regression prevention strategy with:
- Feature flag system for safe rollout
- Performance baseline (186 tests + 6 search_v2 tests)
- Automated rollback mechanisms

Related to #38

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(micro-hnsw-wasm): Add neuromorphic HNSW v2.3 with SNN integration

## New Crate: micro-hnsw-wasm v2.3.0
- Published to crates.io: https://crates.io/crates/micro-hnsw-wasm
- 11.8KB WASM binary with 58 exported functions
- Neuromorphic vector search combining HNSW + Spiking Neural Networks

### Core Features
- HNSW graph-based approximate nearest neighbor search
- Multi-distance metrics: L2, Cosine, Dot product
- GNN extensions: typed nodes, edge weights, neighbor aggregation
- Multi-core sharding: 256 cores × 32 vectors = 8K total

### Spiking Neural Network (SNN)
- LIF (Leaky Integrate-and-Fire) neurons with membrane dynamics
- STDP (Spike-Timing Dependent Plasticity) learning
- Spike propagation through graph topology
- HNSW→SNN bridge for similarity-driven neural activation

### Novel Neuromorphic Features (v2.3)
- Spike-Timing Vector Encoding (rate-to-time conversion)
- Homeostatic Plasticity (self-stabilizing thresholds)
- Oscillatory Resonance (40Hz gamma synchronization)
- Winner-Take-All Circuits (competitive selection)
- Dendritic Computation (nonlinear branch integration)
- Temporal Pattern Recognition (spike history matching)
- Combined Neuromorphic Search pipeline

### Performance Optimizations
- 5.5x faster SNN tick (2,726ns → 499ns)
- 18% faster STDP learning
- Pre-computed reciprocal constants
- Division elimination in hot paths

### Documentation & Organization
- Reorganized docs into subdirectories (gnn/, implementation/, publishing/, status/)
- Added comprehensive README with badges, SEO, citations
- Added benchmark.js and test_wasm.js test suites
- Added DEEP_REVIEW.md with performance analysis
- Added Verilog RTL for ASIC synthesis

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(exo-ai-2025): Publish 9 cognitive substrate crates to crates.io

Published the complete EXO-AI 2025 cognitive substrate to crates.io:

Crates published (v0.1.0):
- exo-core: IIT consciousness (Φ) measurement & Landauer thermodynamics
- exo-temporal: Temporal memory coordinator with causal structure
- exo-hypergraph: Hypergraph substrate for higher-order reasoning
- exo-manifold: SIREN networks for continuous manifold deformation
- exo-exotic: 10 exotic experiments (Strange Loops, Dreams, Free Energy, etc.)
- exo-federation: Post-quantum federated cognitive mesh
- exo-backend-classical: SIMD-accelerated classical compute backend
- exo-wasm: Browser & edge WASM deployment
- exo-node: Node.js bindings via NAPI-RS

Changes:
- Updated all Cargo.toml files with publishing metadata
- Added crates.io, docs.rs, and license badges to READMEs
- Added GitHub and ruv.io links to all documentation
- Created README.md files for crates that were missing them
- Updated dependency references for crates.io publishing

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
 2025-12-01 23:45:31 -05:00
github-actions[bot]
809d99312e chore: Update NAPI-RS binaries for all platforms 
Built from commit 6c00b84e1d

  Platforms updated:
  - linux-x64-gnu
  - linux-arm64-gnu
  - darwin-x64
  - darwin-arm64
  - win32-x64-msvc

  🤖 Generated by GitHub Actions
 2025-12-02 03:36:03 +00:00
rUv
6c00b84e1d
feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 
* docs: Add comprehensive GNN v2 implementation plans

Add 22 detailed planning documents for 19 advanced GNN features:

Tier 1 (Immediate - 3-6 months):
- GNN-Guided HNSW Routing (+25% QPS)
- Incremental Graph Learning/ATLAS (10-100x faster updates)
- Neuro-Symbolic Query Execution (hybrid neural + logical)

Tier 2 (Medium-Term - 6-12 months):
- Hyperbolic Embeddings (Poincaré ball model)
- Degree-Aware Adaptive Precision (2-4x memory reduction)
- Continuous-Time Dynamic GNN (concept drift detection)

Tier 3 (Research - 12+ months):
- Graph Condensation (10-100x smaller graphs)
- Native Sparse Attention (8-15x GPU speedup)
- Quantum-Inspired Attention (long-range dependencies)

Novel Innovations (10 experimental features):
- Gravitational Embedding Fields, Causal Attention Networks
- Topology-Aware Gradient Routing, Embedding Crystallization
- Semantic Holography, Entangled Subspace Attention
- Predictive Prefetch Attention, Morphological Attention
- Adversarial Robustness Layer, Consensus Attention

Includes comprehensive regression prevention strategy with:
- Feature flag system for safe rollout
- Performance baseline (186 tests + 6 search_v2 tests)
- Automated rollback mechanisms

Related to #38

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(micro-hnsw-wasm): Add neuromorphic HNSW v2.3 with SNN integration

## New Crate: micro-hnsw-wasm v2.3.0
- Published to crates.io: https://crates.io/crates/micro-hnsw-wasm
- 11.8KB WASM binary with 58 exported functions
- Neuromorphic vector search combining HNSW + Spiking Neural Networks

### Core Features
- HNSW graph-based approximate nearest neighbor search
- Multi-distance metrics: L2, Cosine, Dot product
- GNN extensions: typed nodes, edge weights, neighbor aggregation
- Multi-core sharding: 256 cores × 32 vectors = 8K total

### Spiking Neural Network (SNN)
- LIF (Leaky Integrate-and-Fire) neurons with membrane dynamics
- STDP (Spike-Timing Dependent Plasticity) learning
- Spike propagation through graph topology
- HNSW→SNN bridge for similarity-driven neural activation

### Novel Neuromorphic Features (v2.3)
- Spike-Timing Vector Encoding (rate-to-time conversion)
- Homeostatic Plasticity (self-stabilizing thresholds)
- Oscillatory Resonance (40Hz gamma synchronization)
- Winner-Take-All Circuits (competitive selection)
- Dendritic Computation (nonlinear branch integration)
- Temporal Pattern Recognition (spike history matching)
- Combined Neuromorphic Search pipeline

### Performance Optimizations
- 5.5x faster SNN tick (2,726ns → 499ns)
- 18% faster STDP learning
- Pre-computed reciprocal constants
- Division elimination in hot paths

### Documentation & Organization
- Reorganized docs into subdirectories (gnn/, implementation/, publishing/, status/)
- Added comprehensive README with badges, SEO, citations
- Added benchmark.js and test_wasm.js test suites
- Added DEEP_REVIEW.md with performance analysis
- Added Verilog RTL for ASIC synthesis

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
 2025-12-01 22:30:15 -05:00
github-actions[bot]
065958288e chore: Update NAPI-RS binaries for all platforms 
Built from commit 42a8b148b2

  Platforms updated:
  - linux-x64-gnu
  - linux-arm64-gnu
  - darwin-x64
  - darwin-arm64
  - win32-x64-msvc

  🤖 Generated by GitHub Actions
 2025-12-01 19:42:42 +00:00
rUv
42a8b148b2 fix(security): Resolve all 10 npm audit vulnerabilities 
- Update vitest from ^1.6.1 to ^3.2.4 in all workspace packages
  (fixes esbuild/vite security issues)
- Add npm overrides for axios (^1.13.2) and body-parser (^2.2.1)
  to fix transitive dependency vulnerabilities
- npm audit now reports 0 vulnerabilities

Closes #37

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-12-01 19:36:37 +00:00
github-actions[bot]
82c448baa0 chore: Update NAPI-RS binaries for all platforms 
Built from commit ef0374893e

  Platforms updated:
  - linux-x64-gnu
  - linux-arm64-gnu
  - darwin-x64
  - darwin-arm64
  - win32-x64-msvc

  🤖 Generated by GitHub Actions
 2025-12-01 18:44:14 +00:00