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docs: consolidate and archive redundant documentation

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- Archived 13 API design iterations to docs/api-design-archive/
- Consolidated augmentation docs to docs/augmentations-archive/
- Maintained ONE definitive API doc at docs/api/README.md
- Cleaned up documentation structure for 2.0 release
- Preserved all historical documents for reference
This commit is contained in:
David Snelling 2025-08-25 10:15:38 -07:00
parent ef8f35ec2a
commit 994276f09f
35 changed files with 444 additions and 239 deletions
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8
docs/planning/FINAL_RELEASE_ASSESSMENT.md
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@ -20,7 +20,7 @@
- ✅ Natural language queries ("find developers")
- ✅ Vector similarity search (`similar: 'text'`)
- ✅ Graph traversal (`connected: { to: 'node' }`)
- ✅ Field filtering (`where: { field: 'value' }`)
- ✅ Metadata filtering (`where: { field: 'value' }`)
- ✅ Combined intelligence with fusion scoring
- ✅ Performance optimized for complex queries
- **Status: PRODUCTION READY**
@ -94,7 +94,7 @@ const viz = await neural.visualize()
```
### Core Innovation Validated
- ✅ **Triple Intelligence**: Vector + Graph + Field search unified
- ✅ **Triple Intelligence**: Vector + Graph + Metadata search unified
- ✅ **Intelligent Verb Scoring**: Smart relationship weights
- ✅ **Neural APIs**: Ready for external visualization libraries
- ✅ **Zero Config**: Works perfectly out of the box
@ -118,7 +118,7 @@ const viz = await neural.visualize()
- **Scalability**: Tested with complex datasets
### Innovation Leadership ✅
- **First True Triple Intelligence**: Vector + Graph + Field unified
- **First True Triple Intelligence**: Vector + Graph + Metadata unified
- **Smart by Default**: No configuration required
- **Revolutionary Data Model**: Noun-verb taxonomy
- **Neural API**: Ready for external clustering/visualization libraries
@ -133,7 +133,7 @@ const viz = await neural.visualize()
Brainy 2.0 represents a fundamental leap forward in vector database technology:
1. **Triple Intelligence** solves the problem of having to choose between vector, graph, or field search
1. **Triple Intelligence** solves the problem of having to choose between vector, graph, or metadata search
2. **Intelligent Verb Scoring** automatically computes optimal relationship weights
3. **Neural APIs** enable external libraries to build advanced visualizations
4. **Zero Configuration** makes it accessible to all developers