CLI log summarizer (easy)

This example shows a minimal, practical workflow for local operations:

1. Stream provider output.
2. Normalize chunks.
3. Process incremental text.
4. Render clean output to a terminal.

Packages used

npm install @agentsy/core @agentsy/providers @agentsy/renderers

Illustrative implementation

import { processRawStream } from '@agentsy/providers/adapters';
import { normalizeOpenAIChatChunk } from '@agentsy/providers/normalizers';
import { createPlainTextRenderer } from '@agentsy/renderers';
import { parseSSEStream } from '@agentsy/core/sse';

async function* streamProviderLogs(prompt: string): AsyncGenerator<unknown> {
  const response = await fetch('https://api.example.com/v1/chat/completions', {
    method: 'POST',
    headers: { 'content-type': 'application/json' },
    body: JSON.stringify({
      model: 'gpt-4.1-mini',
      stream: true,
      messages: [{ role: 'user', content: prompt }]
    })
  });

  const textStream = response.body?.pipeThrough(new TextDecoderStream());
  if (!textStream) {
    return;
  }

  for await (const event of parseSSEStream(textStream)) {
    if (event.data === '[DONE]') {
      return;
    }

    try {
      yield JSON.parse(event.data) as unknown;
    } catch {
      // Ignore malformed SSE payloads in this showcase example.
    }
  }
}

async function runCliSummary(): Promise<void> {
  const renderer = createPlainTextRenderer({ showThinking: false });

  const prompt = 'Summarize the latest application logs into key issues and probable causes.';
  for await (const output of processRawStream(streamProviderLogs(prompt), normalizeOpenAIChatChunk)) {
    renderer.write(output);
  }
}

void runCliSummary();

Why this pattern is useful

• Good first step for validating your provider integration.
• Minimal boilerplate while still preserving stream correctness.
• Easy to embed into scripts and cron-like operational tooling.