The LLMUtils class in src/utils/llm provides a unified interface for interacting with different LLM providers, supporting both OpenAI and OpenRouter APIs.
// Initialize LLMUtils
import { LLMUtils } from "../utils/llm";
const llmUtils = new LLMUtils();
// Environment variables needed
OPENAI_API_KEY="your-openai-api-key"
OPENROUTER_API_KEY="your-openrouter-api-key"
APP_URL="http://localhost:3000" // Required for OpenRouterGenerate text responses using different LLM models:
// Basic text generation
const response = await llmUtils.getTextFromLLM(
prompt,
"anthropic/claude-3-sonnet"
);
// Streaming responses
await llmUtils.getTextFromLLMStream(
prompt,
"anthropic/claude-3-sonnet",
(token) => {
// Handle each token as it arrives
console.log(token);
}
);Get structured JSON responses using Zod schemas for type safety:
import { z } from "zod";
import { LLMSize } from "../types";
// Define your schema
const analysisSchema = z.object({
sentiment: z.string(),
topics: z.array(z.string()),
confidence: z.number(),
summary: z.string()
});
// Get structured response
const analysis = await llmUtils.getObjectFromLLM(
prompt,
analysisSchema,
LLMSize.LARGE
);
// Type-safe access to fields
console.log(analysis.sentiment);
console.log(analysis.topics);Get simple true/false decisions from the LLM:
// Get boolean response
const shouldRespond = await llmUtils.getBooleanFromLLM(
"Should the agent respond to this message?",
LLMSize.SMALL
);
if (shouldRespond) {
// Handle response
}Process images and get text descriptions or structured analysis:
// Get image descriptions
const description = await llmUtils.getImageDescriptions(imageUrls);
// Analyze images with text context
const response = await llmUtils.getTextWithImageFromLLM(
prompt,
imageUrls,
"anthropic/claude-3-sonnet"
);
// Get structured output from images
const analysis = await llmUtils.getObjectFromLLMWithImages(
prompt,
analysisSchema,
imageUrls,
LLMSize.LARGE
);