Pipeline Organization and Categorization System

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Overview

This document defines the organizational structure for the AI engineering pipeline library, establishing a systematic approach to pipeline discovery, reuse, and composition.

Directory Structure

pipeline_ex/
├── pipelines/                      # Main pipeline library
│   ├── registry.yaml              # Global pipeline registry
│   ├── data/                      # Data processing pipelines
│   │   ├── cleaning/
│   │   ├── enrichment/
│   │   ├── transformation/
│   │   └── quality/
│   ├── model/                     # Model development pipelines
│   │   ├── prompt_engineering/
│   │   ├── evaluation/
│   │   ├── comparison/
│   │   └── fine_tuning/
│   ├── code/                      # Code generation pipelines
│   │   ├── api_generation/
│   │   ├── test_generation/
│   │   ├── documentation/
│   │   └── refactoring/
│   ├── analysis/                  # Analysis pipelines
│   │   ├── codebase/
│   │   ├── security/
│   │   ├── performance/
│   │   └── dependencies/
│   ├── content/                   # Content generation pipelines
│   │   ├── blog/
│   │   ├── tutorial/
│   │   ├── api_docs/
│   │   └── changelog/
│   ├── devops/                    # DevOps pipelines
│   │   ├── ci_cd/
│   │   ├── deployment/
│   │   ├── monitoring/
│   │   └── infrastructure/
│   ├── components/                # Reusable components
│   │   ├── steps/                # Reusable step definitions
│   │   ├── prompts/              # Prompt templates
│   │   ├── functions/            # Gemini function definitions
│   │   ├── validators/           # Validation components
│   │   └── transformers/         # Data transformation components
│   └── templates/                 # Pipeline templates
│       ├── basic/                # Simple pipeline patterns
│       ├── advanced/             # Complex pipeline patterns
│       └── enterprise/           # Production-grade patterns
├── examples/                      # Example usage and demos
│   ├── tutorials/                # Step-by-step tutorials
│   └── case_studies/             # Real-world implementations
└── tests/                        # Pipeline-specific tests
    ├── pipeline_tests/           # Integration tests for pipelines
    └── component_tests/          # Unit tests for components

Pipeline Registry Schema

The registry.yaml serves as the central catalog of all available pipelines:

version: "1.0"
last_updated: "2025-06-30"

pipelines:
  - id: "data-cleaning-standard"
    name: "Standard Data Cleaning Pipeline"
    category: "data/cleaning"
    description: "Multi-stage data cleaning with validation"
    version: "1.0.0"
    tags: ["data", "cleaning", "validation"]
    dependencies:
      - "components/steps/validation"
      - "components/transformers/data"
    complexity: "medium"
    estimated_tokens: 5000
    providers: ["claude", "gemini"]
    
  - id: "api-rest-generator"
    name: "REST API Generator"
    category: "code/api_generation"
    description: "Generate complete REST API with tests"
    version: "2.1.0"
    tags: ["api", "code-generation", "rest"]
    dependencies:
      - "components/steps/code"
      - "components/prompts/api"
    complexity: "high"
    estimated_tokens: 15000
    providers: ["claude"]

Categorization Taxonomy

1. Primary Categories

  • Data: Pipelines focused on data manipulation and processing
  • Model: AI/ML model development and optimization
  • Code: Software development and code generation
  • Analysis: System and code analysis workflows
  • Content: Documentation and content creation
  • DevOps: Infrastructure and deployment automation

2. Complexity Levels

  • Basic: Single-step or simple multi-step pipelines
  • Medium: Multi-step with conditional logic
  • High: Complex workflows with parallel execution
  • Enterprise: Production-grade with full error handling

3. Provider Requirements

  • Claude-only: Requires Claude-specific features
  • Gemini-only: Requires Gemini function calling
  • Multi-provider: Can use either provider
  • Hybrid: Requires both providers

Component Classification

Step Components

# components/steps/validation/input_validator.yaml
component:
  type: "step"
  id: "input-validator"
  name: "Input Validation Step"
  description: "Validates input data against schema"
  
  parameters:
    schema:
      type: "object"
      description: "JSON Schema for validation"
    strict:
      type: "boolean"
      default: true
      
  outputs:
    valid:
      type: "boolean"
    errors:
      type: "array"
      items:
        type: "string"

Prompt Templates

# components/prompts/analysis/code_review.yaml
component:
  type: "prompt"
  id: "code-review-prompt"
  name: "Code Review Prompt Template"
  
  variables:
    - code_content
    - review_focus
    - severity_level
    
  template: |
    Review the following code with focus on {review_focus}:
    
    ```
    {code_content}
    ```
    
    Provide feedback at {severity_level} level.

## Naming Conventions

### Pipeline Files - Format: {purpose}_{variant}_pipeline.yaml - Examples: - data_cleaning_standard_pipeline.yaml - api_generation_rest_pipeline.yaml - security_audit_comprehensive_pipeline.yaml

### Component Files - Format: {function}_{type}.yaml - Examples: - input_validator.yaml - json_transformer.yaml - code_review_prompt.yaml

### Version Tags - Semantic versioning: MAJOR.MINOR.PATCH - Beta versions: X.Y.Z-beta.N - Release candidates: X.Y.Z-rc.N

## Discovery Mechanisms

### 1. CLI Commands

# List all pipelines
mix pipeline.list

# Search by category
mix pipeline.list --category data/cleaning

# Search by tags
mix pipeline.list --tags "api,rest"

# Show pipeline details
mix pipeline.info api-rest-generator

### 2. Web Interface (Future) - Visual pipeline browser - Dependency graph visualization - Performance metrics dashboard - Usage analytics

### 3. API Access

# Pipeline discovery API
Pipeline.Registry.list_by_category("data/cleaning")
Pipeline.Registry.search(tags: ["api", "rest"])
Pipeline.Registry.get_details("api-rest-generator")

## Metadata Standards

Each pipeline must include: 1. Unique identifier 2. Descriptive name 3. Clear category placement 4. Version information 5. Dependency declarations 6. Performance estimates 7. Provider requirements 8. Comprehensive tags

## Migration Path

For existing pipelines: 1. Analyze current pipeline files 2. Categorize according to new taxonomy 3. Add required metadata 4. Update file locations 5. Register in central registry 6. Update references in code

## Governance

### Adding New Pipelines 1. Define clear purpose and category 2. Follow naming conventions 3. Include all required metadata 4. Add comprehensive tests 5. Document usage examples 6. Submit for review

### Deprecation Process 1. Mark as deprecated in registry 2. Add deprecation notice to file 3. Provide migration guide 4. Maintain for 2 major versions 5. Archive after removal

## Benefits

1. Discoverability: Easy to find relevant pipelines 2. Reusability: Clear component boundaries 3. Maintainability: Organized structure 4. Scalability: Supports growth 5. Consistency: Enforced standards 6. Quality: Review process