RAG Pipeline Design

import { ChatOpenAI } from '@langchain/openai';
import { tool } from '@langchain/core/tools';
import { z } from 'zod';

const getWeather = tool(
  async ({ city, units }) => {
    const res = await fetch(`/api/weather?city=${city}&units=${units}`);
    return res.json();
  },
  {
    name: 'get_weather',
    description: 'Fetch the current weather for a city',
    schema: z.object({
      city: z.string(),
      units: z.enum(['celsius', 'fahrenheit']).default('celsius'),
    }),
  },
);

export async function main(query: string) {
  const model = new ChatOpenAI({ model: 'gpt-4o-mini' });
  const modelWithTools = model.bindTools([getWeather]);
  const response = await modelWithTools.invoke(query);
  return response.tool_calls;
}

1. File created: src/main.ts14:02:11
2. First build attempt (failed)14:09:48
3. Test suite passed (2/2)14:12:30
4. Commit: scaffold agent entrypoint14:18:05
5. Tool schema validated14:21:42
6. Build attempt 2 (success)14:25:17
7. Commit: implement tool calling14:28:03
8. Artifact submitted for assessment14:31:50