ai-agent-effect

AI Agent (Effect)

A stateful AI agent actor built with the Effect SDK for Rivet Actors and Effect AI. The agent persists its conversation history in actor state, so it remembers every turn across calls and restarts.

Prerequisites

Running against a real model needs an OpenAI API key:

export OPENAI_API_KEY=sk-...

The test suite needs neither a key nor network access: it runs a real in-process mock LLM server instead.

Getting Started

git clone https://github.com/rivet-dev/rivet.git
cd rivet/examples/ai-agent-effect
npm install
npm run dev

In a separate terminal, run the client against the server:

npm run client

Features

• Persistent conversation memory: Every user and assistant turn is stored in persisted actor state (a Schema.Array of role/content messages), so the model sees the full history on each call, even after the actor sleeps or restarts
• Effect AI integration: The agent calls LanguageModel.generateText from effect/ai with the running history as the prompt
• Swappable model via Layer: The actor requires the LanguageModel service but never constructs it. The concrete model is provided as an Effect Layer where the actor is composed: a real OpenAI model in dev, a mock model in tests
• Effect-native actor: Defined with Actor.make and implemented with toLayer, returning action handlers from an Effect wake scope
• Typed errors across the wire: SendMessage declares an EmptyMessageError that arrives on the caller as a real tagged instance, caught with Effect.catchTag

Implementation

The actor is split into a public contract and a server-only implementation:

• Contract (src/actors/agent/api.ts): Declares the Agent actor, the Message type, the SendMessage / GetHistory actions, and the EmptyMessageError
• Implementation (src/actors/agent/live.ts): Implements the wake scope, the conversation-history state schema, and the action handlers that call the LLM
• Model wiring (src/model.ts): Composes a Layer<LanguageModel> from OpenAiLanguageModel, OpenAiClient, and FetchHttpClient
• Server (src/main.ts): Provides the model Layer to the actor layer and serves it with Registry.serve
• Client (src/client.ts): An Effect client using the typed Agent.client accessor
• Test (tests/agent.test.ts): Runs the actor against a real engine and a real in-process mock LLM server, swapping in a mock model Layer

Resources

Read more about actions, state, and the Effect quickstart.

License

MIT