effect-ai-language-model

Effect AI Language Model

Pattern guide for working with the LanguageModel service from Effect AI for type-safe LLM interactions with Effect's functional patterns.

Import Patterns

CRITICAL: Always use namespace imports:

import * as LanguageModel from 'effect/unstable/ai/LanguageModel';
import * as Prompt from 'effect/unstable/ai/Prompt';
import * as Response from 'effect/unstable/ai/Response';
import * as Toolkit from 'effect/unstable/ai/Toolkit';
import * as Tool from 'effect/unstable/ai/Tool';
import * as Effect from 'effect/Effect';
import * as Stream from 'effect/Stream';
import * as Schema from 'effect/Schema';

When to Use This Skill

• Generating text completions from language models
• Extracting structured data with schema validation
• Real-time streaming responses for chat interfaces
• Tool calling and function execution
• Multi-turn conversations with history
• Switching between different AI providers

Service Interface

LanguageModel :: Service

-- Core operations
generateText   :: Options → Effect GenerateTextResponse E R
generateObject :: Options → Schema A → Effect (GenerateObjectResponse A) E R
streamText     :: Options → Stream StreamPart E R

-- Service as dependency (LanguageModel is both a namespace and a service tag)
LanguageModel ∈ R → Effect.gen(function*() {
  -- Option A: use static accessors (adds LanguageModel to R automatically)
  const response = yield* LanguageModel.generateText(options)
  -- Option B: yield the tag explicitly
  const model = yield* LanguageModel.LanguageModel
  const response = yield* model.generateText(options)
})

generateText Pattern

Basic text generation with optional tool calling:

import * as LanguageModel from 'effect/unstable/ai/LanguageModel';
import * as Effect from 'effect/Effect';

// Simple text generation
const simple = LanguageModel.generateText({
	prompt: 'Explain quantum computing'
});

// With system prompt and conversation history
const withHistory = LanguageModel.generateText({
	prompt: [
		{ role: 'system', content: 'You are a helpful assistant' },
		{ role: 'user', content: [{ type: 'text', text: 'Hello!' }] }
	]
});

// With toolkit for tool calling
const withTools = LanguageModel.generateText({
	prompt: "What's the weather in SF?",
	toolkit: weatherToolkit,
	toolChoice: 'auto' // "none" | "required" | { tool: "name" } | { oneOf: [...] }
});

// Parallel tool call execution
const withConcurrency = LanguageModel.generateText({
	prompt: 'Search multiple sources',
	toolkit: searchToolkit,
	concurrency: 'unbounded' // or number for limited parallelism
});

// Disable automatic tool call resolution
const manualTools = LanguageModel.generateText({
	prompt: 'Search for X',
	toolkit: searchToolkit,
	disableToolCallResolution: true // Get tool calls without executing
});