A Hacker News story as audio

bash
API=https://beta-api.b3os.orgAUTH="Authorization: Bearer $B3OS_API_KEY"ID=50319510URL=$(curl -s "$API/v1/actions/call" -H "$AUTH" -H "Content-Type: application/json" \  -d "$(jq -n --argjson id "$ID" '{ref: "io.b3os/hacker-news/get-item@1", input: {id: $id}}')" \  | jq -r '.output.url')curl -s "$API/v1/vision/scrape" -H "$AUTH" -H "Content-Type: application/json" \  -d "$(jq -n --arg url "$URL" '{url: $url, formats: ["markdown"]}')" | jq -r '.markdown[0:6000]' > page.mdjq -n --rawfile page page.md '{model: "b3os/qwen3.5-9b", temperature: 0, max_tokens: 160,  chat_template_kwargs: {enable_thinking: false},  messages: [{role: "system", content: "Summarize the page for someone listening, in three plain sentences and at most 70 words. Use only the page. No lists, no URLs, no markup."},             {role: "user", content: $page}]}' \| curl -s "$API/v1/infer/chat/completions" -H "$AUTH" -H "Content-Type: application/json" -d @- \| jq -r '.choices[0].message.content' > summary.txtjq -n --rawfile text summary.txt '{model: "kokoro-82m", input: $text, voice: "alloy", response_format: "mp3"}' \| curl -s "$API/v1/infer/audio/speech" -H "$AUTH" -H "Content-Type: application/json" -d @- -o brief.mp3

ts
import { writeFileSync } from "node:fs";const API = "https://beta-api.b3os.org";const headers = { authorization: `Bearer ${process.env.B3OS_API_KEY}`, "content-type": "application/json" };const post = (path: string, body: unknown) =>  fetch(`${API}${path}`, { method: "POST", headers, body: JSON.stringify(body) });const id = 50319510;const item: any = await (await post("/v1/actions/call", { ref: "io.b3os/hacker-news/get-item@1", input: { id } })).json();const story = item.output;const page: any = await (await post("/v1/vision/scrape", { url: story.url, formats: ["markdown"] })).json();const chat: any = await (  await post("/v1/infer/chat/completions", {    model: "b3os/qwen3.5-9b",    temperature: 0,    max_tokens: 160,    chat_template_kwargs: { enable_thinking: false },    messages: [      { role: "system", content: "Summarize the page for someone listening, in three plain sentences and at most 70 words. Use only the page. No lists, no URLs, no markup." },      { role: "user", content: `Title: ${story.title}\n\n${page.markdown.slice(0, 6000)}` },    ],  })).json();const speech = await post("/v1/infer/audio/speech", {  model: "kokoro-82m",  input: chat.choices[0].message.content,  voice: "alloy",  response_format: "mp3",});writeFileSync("brief.mp3", Buffer.from(await speech.arrayBuffer()));

python
import osimport requestsAPI = "https://beta-api.b3os.org"s = requests.Session()s.headers["Authorization"] = f"Bearer {os.environ['B3OS_API_KEY']}"ID = 50319510story = s.post(f"{API}/v1/actions/call", json={    "ref": "io.b3os/hacker-news/get-item@1", "input": {"id": ID},}).json()["output"]page = s.post(f"{API}/v1/vision/scrape", json={"url": story["url"], "formats": ["markdown"]}).json()chat = s.post(f"{API}/v1/infer/chat/completions", json={    "model": "b3os/qwen3.5-9b", "temperature": 0, "max_tokens": 160,    "chat_template_kwargs": {"enable_thinking": False},    "messages": [        {"role": "system", "content": "Summarize the page for someone listening, in three plain sentences and at "                                      "most 70 words. Use only the page. No lists, no URLs, no markup."},        {"role": "user", "content": f"Title: {story['title']}\n\n{page['markdown'][:6000]}"},    ],}).json()speech = s.post(f"{API}/v1/infer/audio/speech", json={    "model": "kokoro-82m", "input": chat["choices"][0]["message"]["content"],    "voice": "alloy", "response_format": "mp3",})with open("brief.mp3", "wb") as f:    f.write(speech.content)

The remote B3OS MCP server has the action, scrape and chat tools but no speech tool yet, so the agent writes the summary over MCP and the audio is one HTTP call (the curl tab's last command). Ask your agent:

text
Get Hacker News item 50319510 with the hacker-news get-item action. Scrape the page it links as Markdown andsummarize it in three plain sentences for listening, at most 70 words.

The agent calls actions_call, vision_scrape and infer_chat.