output  by growthxai

AI workflows and agents framework in TypeScript

Created 2 months ago
404 stars

Top 71.5% on SourcePulse

GitHubView on GitHub
Project Summary

Summary

GrowthXAI Output is an open-source TypeScript framework for building AI workflows and agents, designed to unify disparate AI development tools into a single codebase. It targets developers seeking to integrate AI capabilities without SaaS fragmentation or vendor lock-in, enabling AI coding agents to directly build, test, and iterate on AI applications.

How It Works

Output employs a structured approach with distinct workflows for orchestration logic and steps for I/O operations, leveraging Temporal for deterministic execution and replayability. Prompts are managed in .prompt files using Liquid templating, while evaluators enable LLM-as-judge testing. This design ensures best practices are embedded, facilitating both beginner and expert AI development.

Quick Start & Requirements

Requires Node.js 20+, Docker Desktop, and an LLM API key. Scaffold a project with npx @outputai/cli init, then run the development environment using npx output dev. Workflows can be executed via npx output workflow run and debugged with npx output workflow debug. A full getting started guide is available in the documentation.

Highlighted Details

  • Unified AI Stack: Integrates prompts, evaluations, tracing, cost tracking, orchestration, and credential management within a single TypeScript framework.
  • AI-Agent Native Architecture: Codebase is structured for AI coding agents, allowing them full context to scaffold, generate, test, and iterate on workflows.
  • Multi-Provider LLM Support: Offers a unified API for interacting with various LLM providers including Anthropic, OpenAI, Azure, Vertex AI, and Bedrock.
  • Robust Orchestration: Utilizes Temporal for reliable workflow execution, including automatic retries, history, and parallel processing.
  • Secure Credential Management: Encrypts API keys using AES-256-GCM, scoped per environment and workflow, managed via CLI.
  • Comprehensive Tracing: Automatically logs LLM calls, HTTP requests, costs, and latency for debugging and analysis.
  • Extensive Examples: A gallery at output.ai/gallery provides production-ready workflows for common AI tasks.

Maintenance & Community

The provided README does not detail specific contributors, sponsorships, or community channels like Discord or Slack.

Licensing & Compatibility

Released under the Apache 2.0 license, permitting commercial use and integration into closed-source projects without copyleft restrictions.

Limitations & Caveats

The framework is designed for AI-driven development and relies heavily on Temporal for orchestration, which may introduce a learning curve. While production-ready workflows are provided, extensive configuration may be needed for robust production deployments. The tight integration with AI coding agents like Claude Code might limit flexibility with other agent paradigms.

Health Check
Last Commit

1 day ago

Responsiveness

Inactive

Pull Requests (30d)
51
Issues (30d)
1
Star History
187 stars in the last 30 days

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