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TheYgent

TheYgent is a no-code, local-first platform for building and running AI agents. You compose agents visually on a canvas, chat with them or wire them to triggers, and run them against models on your own machine — or against any OpenAI-compatible API you choose to register.

Your models, your machines, your choice

TheYgent's promise is honest and specific: everything runs where you point it, and you own every hop.

  • Local by default. Models download to your machine and run on local engines — llama.cpp anywhere, MLX on Apple Silicon, vLLM on CUDA GPUs. Weights, the model registry, and credentials live in local files under ~/.theygent/inference; agents, runs, and conversations live in a Postgres database you control.
  • Hosted APIs only when you add them. Any OpenAI-compatible server or hosted API can be registered as a model, with its API key stored on your machine as a local credential that is never sent anywhere else.
  • The choice is per agent and per call. Every model gets a logical id (for example triage-fast), and agents reference that id — never an engine. You can point one node at a small local model and the next at a hosted one, or swap a model's backing engine later without touching a single agent.

There is no vendor in the middle: TheYgent never proxies your prompts, payloads, or weights through anyone's servers.

What you can do

  • Build agents visually — drag nodes onto a canvas, connect them with edges, configure them in an inspector, and run them without writing code. See the editor tour and the node reference.
  • Chat — a unified chat surface for talking to any registered model or saved agent, with streaming answers, a collapsible "thinking" view for reasoning models, voice and image input, and automatic session history. See chat.
  • Run models locally or remotely — browse and install models from Hugging Face with fit-to-your-RAM badges, or register a hosted API; engines start lazily and are managed for you. See models and models and engines.
  • Extend agents with tools — built-in tools, HTTP calls, and any MCP (Model Context Protocol) server, connected over stdio or HTTP and running in your own trust domain. See MCP tools.
  • Automate — deploy saved agents behind token-authenticated invoke endpoints, HMAC-signed webhooks, and cron schedules. See triggers.
  • Run durably — opt a run onto the durable runtime so it checkpoints each step, survives a crash, and can pause for human approval. See durable runs and human in the loop.
  • Observe everything — every run gets a zoomable span waterfall with per-node inputs, outputs, and timing, plus optional OTLP export. See observability.
  • Benchmark — test any model or agent from the Bench: per-turn latency and token metrics, saved results, side-by-side comparisons. See the Bench.

How it fits together

TheYgent runs as three local services, brought up together with make up:

graph LR
    UI[Interface :5174] --> CP[Control plane :8080]
    UI --> IP[Inference plane :8081]
    CP --> IP
    CP --> PG[(Postgres)]
    IP --> ENG[Local engines: llama.cpp / MLX / vLLM]
    IP --> API[Any OpenAI-compatible API you register]
  • The interface is the web app where you build, chat, and observe.
  • The control plane orchestrates agents: it stores agent versions, executes graphs, records runs and sessions, and handles triggers. It talks to models only over HTTP.
  • The inference plane is yours alone: it holds the model registry, downloads weights, spawns and supervises local engine servers, and proxies to any remote API you register. When you chat directly with a model, raw media (voice recordings, images) goes to it straight from your browser; in an agent run — which the control plane orchestrates — that media is uploaded to the control plane as an artifact and handed to nodes by reference.

The architecture page explains the split and exactly where each kind of data lives.

Where to next

If you want to… Go to
Install TheYgent and get it running Getting started
Install a model and have your first conversation First chat
Build, run, and save your first agent First agent
Understand agents, graphs, runs, and versioning Concepts
Look up what every node does Node reference