llm-integration

LLM Integration

API Client Pattern

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

async function generateResponse(
  systemPrompt: string,
  userMessage: string,
  options?: { maxTokens?: number; temperature?: number }
): Promise<string> {
  const response = await client.messages.create({
    model: "claude-sonnet-4-20250514",
    max_tokens: options?.maxTokens ?? 1024,
    temperature: options?.temperature ?? 0,
    system: systemPrompt,
    messages: [{ role: "user", content: userMessage }],
  });

  const textBlock = response.content.find(block => block.type === "text");
  return textBlock?.text ?? "";
}

Streaming Responses

async function streamResponse(
  messages: Array<{ role: "user" | "assistant"; content: string }>,
  onChunk: (text: string) => void
): Promise<string> {
  const stream = client.messages.stream({
    model: "claude-sonnet-4-20250514",
    max_tokens: 4096,
    messages,
  });

  let fullText = "";

  for await (const event of stream) {
    if (event.type === "content_block_delta" && event.delta.type === "text_delta") {
      onChunk(event.delta.text);
      fullText += event.delta.text;
    }
  }

  return fullText;
}

const response = await streamResponse(
  [{ role: "user", content: "Explain async/await in TypeScript" }],
  (chunk) => process.stdout.write(chunk)
);

Function Calling (Tool Use)

const tools: Anthropic.Tool[] = [
  {
    name: "search_database",
    description: "Search the product database by name, category, or price range",
    input_schema: {
      type: "object" as const,
      properties: {
        query: { type: "string", description: "Search query" },
        category: { type: "string", description: "Product category filter" },
        max_price: { type: "number", description: "Maximum price" },
      },
      required: ["query"],
    },
  },
];

async function agentLoop(userMessage: string): Promise<string> {
  const messages: Anthropic.MessageParam[] = [
    { role: "user", content: userMessage },
  ];

  while (true) {
    const response = await client.messages.create({
      model: "claude-sonnet-4-20250514",
      max_tokens: 4096,
      tools,
      messages,
    });

    if (response.stop_reason === "end_turn") {
      const text = response.content.find(b => b.type === "text");
      return text?.text ?? "";
    }

    const toolUse = response.content.find(b => b.type === "tool_use");
    if (!toolUse || toolUse.type !== "tool_use") break;

    const result = await executeToolCall(toolUse.name, toolUse.input);

    messages.push({ role: "assistant", content: response.content });
    messages.push({
      role: "user",
      content: [{ type: "tool_result", tool_use_id: toolUse.id, content: result }],
    });
  }

  return "";
}