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| 1 | +/** |
| 2 | + * Idiomatic Vercel AI SDK example with OpenRouter provider |
| 3 | + * |
| 4 | + * This example demonstrates key AI SDK concepts: |
| 5 | + * - Creating and configuring the OpenRouter provider |
| 6 | + * - Using generateText for non-streaming chat completions |
| 7 | + * - Using streamText for streaming responses |
| 8 | + * - Defining and using tools (function calling) |
| 9 | + * - Usage accounting to track token usage and costs |
| 10 | + * - Multi-turn conversations with system messages |
| 11 | + */ |
| 12 | + |
| 13 | +import { createOpenRouter } from '@openrouter/ai-sdk-provider'; |
| 14 | +import { generateText, streamText, tool } from 'ai'; |
| 15 | +import { z } from 'zod'; |
| 16 | + |
| 17 | +// Create the OpenRouter provider instance |
| 18 | +// The provider acts as a factory for creating model instances |
| 19 | +const openrouter = createOpenRouter({ |
| 20 | + apiKey: process.env.OPENROUTER_API_KEY, |
| 21 | +}); |
| 22 | + |
| 23 | +// Example 1: Simple text generation (non-streaming) |
| 24 | +async function simpleGeneration() { |
| 25 | + console.log('\n=== Example 1: Simple Text Generation ===\n'); |
| 26 | + |
| 27 | + // Create a model instance - each model can have its own configuration |
| 28 | + const model = openrouter('openai/gpt-4o-mini'); |
| 29 | + |
| 30 | + // generateText returns the complete response once generation is finished |
| 31 | + const { text, usage, finishReason } = await generateText({ |
| 32 | + model, |
| 33 | + prompt: 'Explain what the Vercel AI SDK is in one sentence.', |
| 34 | + }); |
| 35 | + |
| 36 | + console.log('Response:', text); |
| 37 | + console.log('\nUsage:', usage); |
| 38 | + console.log('Finish Reason:', finishReason); |
| 39 | +} |
| 40 | + |
| 41 | +// Example 2: Streaming text generation |
| 42 | +async function streamingGeneration() { |
| 43 | + console.log('\n=== Example 2: Streaming Text Generation ===\n'); |
| 44 | + |
| 45 | + const model = openrouter('openai/gpt-4o-mini'); |
| 46 | + |
| 47 | + // streamText returns a stream that yields tokens as they're generated |
| 48 | + const result = streamText({ |
| 49 | + model, |
| 50 | + prompt: 'Write a haiku about TypeScript.', |
| 51 | + }); |
| 52 | + |
| 53 | + // Stream the response token by token |
| 54 | + process.stdout.write('Streaming response: '); |
| 55 | + for await (const chunk of result.textStream) { |
| 56 | + process.stdout.write(chunk); |
| 57 | + } |
| 58 | + console.log('\n'); |
| 59 | + |
| 60 | + // After streaming completes, you can access the full response and metadata |
| 61 | + const finalText = await result.text; |
| 62 | + const finalUsage = await result.usage; |
| 63 | + console.log('Final text length:', finalText.length, 'characters'); |
| 64 | + console.log('Tokens used:', finalUsage.totalTokens); |
| 65 | +} |
| 66 | + |
| 67 | +// Example 3: Tools (Function Calling) |
| 68 | +async function toolCalling() { |
| 69 | + console.log('\n=== Example 3: Tools (Function Calling) ===\n'); |
| 70 | + |
| 71 | + // Define tools using the tool() helper and Zod schemas |
| 72 | + // Tools allow the model to call functions to perform actions or retrieve data |
| 73 | + // Note: Use 'inputSchema' not 'parameters' for AI SDK v5 |
| 74 | + const weatherTool = tool({ |
| 75 | + description: 'Get the current weather for a location', |
| 76 | + inputSchema: z.object({ |
| 77 | + location: z.string().describe('The city and country, e.g., San Francisco, CA'), |
| 78 | + unit: z.enum(['celsius', 'fahrenheit']).default('celsius'), |
| 79 | + }), |
| 80 | + execute: async (params) => { |
| 81 | + // In a real app, you'd call a weather API here |
| 82 | + return { |
| 83 | + location: params.location, |
| 84 | + temperature: params.unit === 'celsius' ? 22 : 72, |
| 85 | + unit: params.unit, |
| 86 | + condition: 'Partly cloudy', |
| 87 | + }; |
| 88 | + }, |
| 89 | + }); |
| 90 | + |
| 91 | + const calculatorTool = tool({ |
| 92 | + description: 'Perform basic arithmetic calculations', |
| 93 | + inputSchema: z.object({ |
| 94 | + operation: z.enum(['add', 'subtract', 'multiply', 'divide']), |
| 95 | + a: z.number(), |
| 96 | + b: z.number(), |
| 97 | + }), |
| 98 | + execute: async (params) => { |
| 99 | + const operations: Record<string, number | string> = { |
| 100 | + add: params.a + params.b, |
| 101 | + subtract: params.a - params.b, |
| 102 | + multiply: params.a * params.b, |
| 103 | + divide: params.b !== 0 ? params.a / params.b : 'Cannot divide by zero', |
| 104 | + }; |
| 105 | + return { result: operations[params.operation] }; |
| 106 | + }, |
| 107 | + }); |
| 108 | + |
| 109 | + const model = openrouter('openai/gpt-4o-mini'); |
| 110 | + |
| 111 | + // generateText with tools automatically handles tool calls |
| 112 | + // The SDK will call tools as needed and include results in the conversation |
| 113 | + const { text, toolCalls, toolResults } = await generateText({ |
| 114 | + model, |
| 115 | + prompt: "What's the weather in Tokyo, Japan? Also, what's 42 multiplied by 17?", |
| 116 | + tools: { |
| 117 | + getWeather: weatherTool, |
| 118 | + calculate: calculatorTool, |
| 119 | + }, |
| 120 | + }); |
| 121 | + |
| 122 | + console.log('Final Response:', text); |
| 123 | + console.log('\nTool Calls:', toolCalls); |
| 124 | + console.log('Tool Results:', toolResults); |
| 125 | +} |
| 126 | + |
| 127 | +// Example 4: Usage Accounting |
| 128 | +async function usageAccounting() { |
| 129 | + console.log('\n=== Example 4: Usage Accounting ===\n'); |
| 130 | + |
| 131 | + // Enable usage accounting to get detailed token usage and cost information |
| 132 | + // This is an OpenRouter-specific feature that provides cost tracking |
| 133 | + const model = openrouter('openai/gpt-4o-mini', { |
| 134 | + usage: { |
| 135 | + include: true, // Request detailed usage information |
| 136 | + }, |
| 137 | + }); |
| 138 | + |
| 139 | + const result = await generateText({ |
| 140 | + model, |
| 141 | + prompt: 'What are the benefits of using TypeScript?', |
| 142 | + }); |
| 143 | + |
| 144 | + console.log('Response:', result.text); |
| 145 | + console.log('\nStandard Usage:', result.usage); |
| 146 | + |
| 147 | + // OpenRouter-specific metadata with cost information |
| 148 | + if (result.providerMetadata?.openrouter?.usage) { |
| 149 | + const usage = result.providerMetadata.openrouter.usage as any; |
| 150 | + console.log('\nOpenRouter Usage Details:'); |
| 151 | + console.log('- Total Tokens:', usage.totalTokens); |
| 152 | + console.log('- Prompt Tokens:', usage.promptTokens); |
| 153 | + console.log('- Completion Tokens:', usage.completionTokens); |
| 154 | + if (usage.cost) { |
| 155 | + console.log('- Cost: $' + usage.cost.toFixed(6)); |
| 156 | + } |
| 157 | + } |
| 158 | +} |
| 159 | + |
| 160 | +// Example 5: Multi-turn conversation with system messages |
| 161 | +async function conversationExample() { |
| 162 | + console.log('\n=== Example 5: Multi-turn Conversation ===\n'); |
| 163 | + |
| 164 | + const model = openrouter('openai/gpt-4o-mini'); |
| 165 | + |
| 166 | + // Use messages array for multi-turn conversations |
| 167 | + // System messages set the behavior and context for the model |
| 168 | + const { text } = await generateText({ |
| 169 | + model, |
| 170 | + system: 'You are a helpful coding assistant specializing in TypeScript and modern web development.', |
| 171 | + messages: [ |
| 172 | + { |
| 173 | + role: 'user', |
| 174 | + content: 'How do I define a generic function in TypeScript?', |
| 175 | + }, |
| 176 | + { |
| 177 | + role: 'assistant', |
| 178 | + content: 'You define a generic function using angle brackets with a type parameter, like this: `function identity<T>(arg: T): T { return arg; }`', |
| 179 | + }, |
| 180 | + { |
| 181 | + role: 'user', |
| 182 | + content: 'Can you show me an example with multiple type parameters?', |
| 183 | + }, |
| 184 | + ], |
| 185 | + }); |
| 186 | + |
| 187 | + console.log('Assistant:', text); |
| 188 | +} |
| 189 | + |
| 190 | +// Example 6: Provider-specific options |
| 191 | +async function providerOptions() { |
| 192 | + console.log('\n=== Example 6: Provider-Specific Options ===\n'); |
| 193 | + |
| 194 | + const model = openrouter('openai/gpt-4o-mini'); |
| 195 | + |
| 196 | + // You can pass OpenRouter-specific options via providerOptions |
| 197 | + // Different providers support different options |
| 198 | + const { text } = await generateText({ |
| 199 | + model, |
| 200 | + prompt: 'Tell me about OpenRouter.', |
| 201 | + providerOptions: { |
| 202 | + openrouter: { |
| 203 | + // OpenRouter-specific options can be passed here |
| 204 | + // For example, transforms or other provider features |
| 205 | + }, |
| 206 | + }, |
| 207 | + }); |
| 208 | + |
| 209 | + console.log('Response:', text); |
| 210 | +} |
| 211 | + |
| 212 | +// Run all examples |
| 213 | +async function main() { |
| 214 | + console.log('Vercel AI SDK with OpenRouter Provider Examples'); |
| 215 | + console.log('='.repeat(50)); |
| 216 | + |
| 217 | + try { |
| 218 | + await simpleGeneration(); |
| 219 | + await streamingGeneration(); |
| 220 | + await toolCalling(); |
| 221 | + await usageAccounting(); |
| 222 | + await conversationExample(); |
| 223 | + await providerOptions(); |
| 224 | + |
| 225 | + console.log('\n' + '='.repeat(50)); |
| 226 | + console.log('All examples completed successfully!'); |
| 227 | + } catch (error) { |
| 228 | + console.error('\nError:', error); |
| 229 | + process.exit(1); |
| 230 | + } |
| 231 | +} |
| 232 | + |
| 233 | +// Execute if run directly |
| 234 | +main(); |
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