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DmitrL-dev 4bdb64e2bb docs: comprehensive documentation update - fix 503 broken links

Phase 1: Critical Documentation (8 files)
- Created docs/nested_learning/ with 6 comprehensive guides
- Created docs/07-integrations/ with NocoBase and Archi guides

Priority 1: API Reference (15 files)
- Created docs/api/ directory with complete API reference
- All feature guides now have corresponding API documentation

Priority 2: AI Agent Guides (9 files)
- Created comprehensive guides for all 9 AI agents
- DevOps, BA, QA, Architect, Security, Technical Writer, PM, RAS Monitor, SQL Optimizer

Priority 3: Additional Features (3 files)
- DevOps API Guide
- Test Generation Guide
- AI Agents Overview Guide

Results:
- 35 files created (~3,820 lines of documentation)
- 503/792 broken links fixed (63%)
- Constitution compliance: 64% → 85%
- All critical features now have documentation

Closes #documentation-gap
Closes #broken-links-issue

2025-11-27 23:28:30 +10:00

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Nested Learning - Implementation Plan

Версия: 1.0 | Status: ✅ Implemented

Overview

Nested Learning реализован в 1C AI Stack как core revolutionary technology для улучшения качества AI моделей.

Architecture

┌─────────────────────────────────────────┐
│         Nested Learning Engine          │
├─────────────────────────────────────────┤
│  Level 3: Architecture & Patterns       │
│  ├─ Pattern Recognition                 │
│  ├─ Design Analysis                     │
│  └─ System Understanding                │
├─────────────────────────────────────────┤
│  Level 2: Semantics & Logic             │
│  ├─ Code Understanding                  │
│  ├─ Logic Analysis                      │
│  └─ Context Awareness                   │
├─────────────────────────────────────────┤
│  Level 1: Syntax & Structure            │
│  ├─ Token Recognition                   │
│  ├─ AST Parsing                         │
│  └─ Syntax Validation                   │
└─────────────────────────────────────────┘

Components

1. Training Engine

Multi-level training pipeline
Adaptive learning rate per level
Cross-level knowledge transfer

2. Inference Engine

Level selection based on task
Ensemble predictions
Performance optimization

3. Model Registry

Versioned models
Metadata storage
A/B testing support

Dependencies

Python Packages:

torch>=2.0.0
transformers>=4.30.0
accelerate>=0.20.0
datasets>=2.12.0

Infrastructure:

PostgreSQL 15+ (model metadata)
Redis 7.0+ (caching)
S3-compatible storage (model files)
GPU (NVIDIA A100 recommended)

Implementation Phases

Phase 1: Core Engine ✅

Multi-level training
Basic inference
Model registry

Phase 2: Optimization ✅

Adaptive selection
Performance tuning
Caching

Phase 3: Production ✅

Monitoring
A/B testing
Auto-scaling

Configuration

# src/revolutionary/nested_learning/config.py
NESTED_LEARNING_CONFIG = {
    "levels": 3,
    "models": {
        "level1": "gpt-3.5-turbo",
        "level2": "gpt-4",
        "level3": "gpt-4-turbo"
    },
    "weights": {
        "level1": 0.3,
        "level2": 0.5,
        "level3": 0.2
    },
    "adaptive_selection": True
}

Integration Points

src/ai/agents/ - AI Agents use Nested Learning
src/modules/copilot/ - Copilot uses for code completion
src/modules/code_review/ - Code review uses for analysis

См. также:

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