Manifold is a platform for AI-powered workflow automation, targeting developers and researchers who need to integrate various AI models and semantic search capabilities. It simplifies the process of building complex AI applications by providing a unified interface for text and image generation, retrieval-augmented generation, and advanced semantic search using PGVector and SEFII.

How It Works

Manifold employs a Go backend and a Node.js frontend, with the frontend assets embedded directly into the Go binary. It supports a wide range of AI model providers, including OpenAI, llama.cpp, Apple MLX LM, Google Gemini, and Anthropic Claude, via OpenAI-compatible endpoints. For image generation, it integrates with ComfyUI and MFlux. Semantic search is powered by PGVector, enhanced by the SEFII engine for efficient similarity search. The platform manages Dockerized PGVector instances and can proxy requests to local or remote AI model servers.

Quick Start & Requirements

• Install: Download pre-built binaries from the releases page.
• Prerequisites: Chrome Browser (with WebGPU enabled), Python 3.10+, Docker. For development: Go 1.21+, Node.js 20 (via nvm).
• Setup: Extract binary, create config.yaml, run ./manifold-*. Initial run downloads models.
• Links: Releases, ComfyUI, MFlux

Highlighted Details

• Supports text generation, image generation, and RAG.
• Integrates with OpenAI, llama.cpp, MLX LM, Gemini, Claude, ComfyUI, MFlux.
• Features semantic search with PGVector and SEFII.
• Manages PGVector lifecycle via Docker.

Maintenance & Community

Manifold is under active development with contributions encouraged. The project uses GitHub Actions for releases. Community channels are not explicitly mentioned in the README.

Licensing & Compatibility

The README does not specify a license. Compatibility for commercial use or closed-source linking is not detailed.

Limitations & Caveats

Manifold is explicitly stated as "NOT production-ready" and is under active development, with breaking changes expected. Users must manage remote service lifecycles manually.