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PromptPack Ecosystem

PromptPack is a specification, not a product or framework. The ecosystem consists of the spec itself and tools that work with it.

Core Components

PromptPack Specification

Status: ✅ v1.1 Available
Repository: altairalabs/promptpack-spec

The open specification defining the JSON format for packaging conversational AI systems. Includes:

  • Complete schema definition
  • RFC process for evolution
  • Documentation and examples
  • Governance model

View Specification →

PromptKit Runtime

Status: 🚧 In Development
Separate Project: Related but independent

Reference implementation for loading and executing PromptPacks. When complete, will provide:

  • CLI tools for validation and testing
  • SDK libraries (Python, JavaScript)
  • PromptPack execution runtime
  • Integration examples

Learn more →

PromptArena Testing

Status: ✅ Available Now
Separate Tool: Related but independent

CLI tool for systematic testing of conversational AI across multiple providers:

  • Multi-provider comparison (OpenAI, Anthropic, Google, etc.)
  • Multi-turn conversation testing
  • Multimodal content testing (images, audio, video)
  • Self-play mode for realistic simulations
  • Comprehensive reporting (HTML, JSON, JUnit, Markdown)
  • CI/CD integration

Get Started with Arena →

Relationship Between Components

┌─────────────────────────────────────┐
│ PromptPack Specification (This) │
│ - Defines JSON format │
│ - Schema and validation │
│ - Documentation │
└───────────┬─────────────────────────┘
│ implements & tests

┌─────────────────────────────────────┐
│ PromptKit Runtime │
│ - Executes PromptPacks │
│ - SDK libraries │
│ - Validation tools │
└───────────┬─────────────────────────┘
│ uses for testing

┌─────────────────────────────────────┐
│ PromptArena Testing │
│ - Multi-provider testing │
│ - Conversation simulation │
│ - Report generation │
└─────────────────────────────────────┘

These are separate but related projects:

  • PromptPack Spec: Defines the standard (open governance, RFC process)
  • PromptKit: Reference implementation (actively developed by AltairaLabs)
  • PromptArena: Testing tool (available now, separate repository)

Community Tools

As PromptPack adoption grows, we expect community-contributed tools including:

  • Alternative runtimes in different languages
  • Framework integrations (LangChain, LlamaIndex, Transformers)
  • IDE plugins and extensions
  • Deployment tools and platforms
  • Monitoring and observability solutions

Want to build PromptPack tooling? The specification is open—anyone can build compatible tools. See our Contributing Guide to get involved.

Planned Integrations

LLM Providers

  • OpenAI (GPT-4, GPT-3.5)
  • Anthropic (Claude)
  • Google (Gemini)
  • Azure OpenAI
  • Local models (Ollama, LM Studio)

Orchestration Frameworks

  • LangChain adapter (proposal in backlog)
  • LlamaIndex adapter (proposal in backlog)
  • Transformers adapter (proposal in backlog)
  • Custom framework integrations

Development Tools

  • VS Code Extension
  • CLI validation and linting tools
  • Testing frameworks
  • CI/CD pipeline integrations

Integration Philosophy

PromptPack is a file format specification, not an implementation. It defines how to structure prompts, tools, and workflows in a standardized JSON format. The specification does NOT include LLM provider SDKs, API integrations, or hosted services.

Any tool can implement PromptPack support by:

  1. Reading PromptPack JSON files
  2. Validating against the JSON Schema
  3. Building their own runtime/execution engine
  4. Implementing their own provider integrations

Future Plans

The PromptPack ecosystem roadmap includes:

  • Completing PromptKit reference runtime
  • Growing the compatible tools ecosystem
  • Framework adapter development
  • Potential PromptPack Hub for community sharing
  • Continued specification evolution via RFC process

We're in the early stages of building an ecosystem. Join us in shaping it.

View Roadmap →

Contributing

Interested in building an integration?

  1. Check the Specification - Ensure you understand the format
  2. Build Your Integration - As a separate project/package
  3. Share with the Community - Via discussions or PRs to add documentation
  4. Maintain Compatibility - Follow semantic versioning of the spec

See our Contributing Guide to get involved.