inferable  by inferablehq

AI workflow runtime with human-in-the-loop capabilities

Created 10 months ago
404 stars

Top 71.9% on SourcePulse

GitHubView on GitHub
Project Summary

Inferable provides a managed, durable execution runtime for building AI workflows and agents. It targets developers needing to integrate human-in-the-loop approvals, ensure structured outputs from LLMs, and manage versioned, long-running processes. The primary benefit is enhanced reliability and control for complex AI-driven applications.

How It Works

Inferable utilizes a long-polling mechanism to connect to user infrastructure, enabling workflows to execute within the user's own environment, including behind firewalls. This approach avoids the need for inbound port openings and allows for self-hosting. Workflows are defined using SDKs (currently Node.js/TypeScript and Go) and can incorporate human approvals via Slack or email, with automatic parsing, validation, and retries for LLM-generated structured outputs. Versioning ensures backward compatibility during updates.

Quick Start & Requirements

Highlighted Details

  • Workflows execute within user infrastructure, supporting private VPCs and firewalls.
  • Supports human-in-the-loop approvals via email or Slack.
  • Automatic parsing, validation, and retries for LLM structured outputs.
  • Versioned workflows for backward compatibility and gradual rollouts.

Maintenance & Community

  • Active development indicated by NPM and Go package version badges.
  • Community contributions are welcomed.

Licensing & Compatibility

  • MIT License. Permissive for commercial use and integration with closed-source applications.

Limitations & Caveats

The CLI tool is currently in alpha. .NET SDK is experimental. Language support beyond Node.js/TypeScript and Go is planned but not yet available.

Health Check
Last Commit

3 days ago

Responsiveness

Inactive

Pull Requests (30d)
45
Issues (30d)
0
Star History
5 stars in the last 30 days

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