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@relayplane/core

v0.1.1

Published

Agent optimization layer: intelligent routing, outcome tracking, and learning

Readme

@relayplane/core

Agent optimization layer for intelligent routing, outcome tracking, and learning.

Overview

@relayplane/core is the brain of RelayPlane - it automatically routes your AI prompts to the best model for each task type and learns from outcomes to improve over time.

Key features:

  • 🎯 Smart Routing - Infers task type (code, summarization, analysis, etc.) and routes to optimal model
  • 📊 Outcome Tracking - Record success/failure to improve future routing
  • 🧠 Learning - Generates suggestions based on performance data
  • Fast - <5ms routing decisions (no network calls for routing)
  • 💾 Local-First - All data stored in SQLite at ~/.relayplane/data.db

Installation

pnpm add @relayplane/core @relayplane/adapters

Quick Start

import { RelayPlane } from '@relayplane/core';

// Create instance
const relay = new RelayPlane();

// Run a prompt - automatically routes to best model
const result = await relay.run({
  prompt: 'Review this code for bugs: function add(a, b) { return a + b; }',
});

console.log(result.taskType);  // 'code_review'
console.log(result.model);     // 'anthropic:claude-3-5-sonnet-20241022'
console.log(result.output);    // The model's response

// Record outcome for learning
relay.recordOutcome(result.runId, {
  success: true,
  quality: 'good',
});

// Close when done
relay.close();

Task Types

RelayPlane automatically infers one of 9 task types:

| Task Type | Description | Default Model | |-----------|-------------|---------------| | code_generation | Writing new code | claude-3-5-sonnet | | code_review | Reviewing existing code | claude-3-5-sonnet | | summarization | Condensing content | claude-3-haiku | | analysis | Deep analysis | gpt-4o | | creative_writing | Stories, articles | claude-3-opus | | data_extraction | Extracting structured data | gpt-4o-mini | | translation | Language translation | gpt-4o-mini | | question_answering | Answering questions | claude-3-haiku | | general | Everything else | claude-3-5-sonnet |

API Reference

RelayPlane

Main class for the agent optimization layer.

const relay = new RelayPlane({
  dbPath?: string;          // Default: ~/.relayplane/data.db
  defaultProvider?: string; // Default: 'local'
  defaultModel?: string;    // Default: 'llama3.2'
  providers?: {
    openai?: { apiKey?: string; baseUrl?: string; };
    anthropic?: { apiKey?: string; };
    google?: { apiKey?: string; };
    xai?: { apiKey?: string; };
    local?: { baseUrl?: string; };
  };
});

relay.run(input)

Routes a prompt to the best model.

const result = await relay.run({
  prompt: string;           // Required
  systemPrompt?: string;    // Optional system prompt
  taskType?: TaskType;      // Override inferred task type
  model?: string;           // Override model selection
  metadata?: object;        // Attach metadata
});

// Returns
{
  runId: string;
  success: boolean;
  output?: string;
  error?: string;
  taskType: TaskType;
  model: string;
  durationMs: number;
  tokensIn?: number;
  tokensOut?: number;
  timestamp: string;
}

relay.recordOutcome(runId, outcome)

Records outcome for learning.

relay.recordOutcome(runId, {
  success: boolean;
  quality?: 'excellent' | 'good' | 'acceptable' | 'poor' | 'failed';
  latencySatisfactory?: boolean;
  costSatisfactory?: boolean;
  feedback?: string;
});

relay.routing

Access routing rules directly.

// Get rule for task type
const rule = relay.routing.get('code_generation');

// Set custom rule
relay.routing.set('code_generation', 'openai:gpt-4o', 'user');

// List all rules
const rules = relay.routing.list();

// Reset to default
relay.routing.delete('code_generation');

relay.stats(options?)

Get statistics.

const stats = relay.stats({
  from?: string; // ISO date
  to?: string;   // ISO date
});

relay.getSuggestions()

Get routing improvement suggestions.

const suggestions = relay.getSuggestions();

relay.acceptSuggestion(id)

Accept a suggestion to update routing.

relay.acceptSuggestion(suggestionId);

Environment Variables

Set API keys via environment:

  • OPENAI_API_KEY - OpenAI
  • ANTHROPIC_API_KEY - Anthropic
  • GOOGLE_API_KEY - Google AI
  • XAI_API_KEY - xAI

License

MIT