Pipeline Organization and Categorization System

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:

Unique identifier
Descriptive name
Clear category placement
Version information
Dependency declarations
Performance estimates
Provider requirements
Comprehensive tags

Migration Path

For existing pipelines:

Analyze current pipeline files
Categorize according to new taxonomy
Add required metadata
Update file locations
Register in central registry
Update references in code

Governance

Adding New Pipelines

Define clear purpose and category
Follow naming conventions
Include all required metadata
Add comprehensive tests
Document usage examples
Submit for review

Deprecation Process

Mark as deprecated in registry
Add deprecation notice to file
Provide migration guide
Maintain for 2 major versions
Archive after removal

Benefits

Discoverability: Easy to find relevant pipelines
Reusability: Clear component boundaries
Maintainability: Organized structure
Scalability: Supports growth
Consistency: Enforced standards
Quality: Review process