Trading Agent Data Pipeline

import requests
import json
from concurrent.futures import ThreadPoolExecutor
from datetime import datetime
from pathlib import Path

API_KEY = "your_scavio_api_key"
TICKERS = ["NVDA", "AAPL", "TSLA", "MSFT", "AMZN"]

def search(platform: str, query: str) -> list[dict]:
    res = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": API_KEY},
        json={"platform": platform, "query": query},
        timeout=10,
    )
    res.raise_for_status()
    return res.json().get("organic", [])[:5]

def fetch_ticker_context(ticker: str) -> dict:
    news_query = f"{ticker} stock news today"
    reddit_query = f"{ticker} stock discussion"
    youtube_query = f"{ticker} market analysis"

    with ThreadPoolExecutor(max_workers=3) as pool:
        news_future = pool.submit(search, "google", news_query)
        reddit_future = pool.submit(search, "reddit", reddit_query)
        youtube_future = pool.submit(search, "youtube", youtube_query)

    return {
        "ticker": ticker,
        "timestamp": datetime.utcnow().isoformat(),
        "news": [{"title": r.get("title", ""), "snippet": r.get("snippet", ""), "link": r.get("link", "")} for r in news_future.result()],
        "reddit": [{"title": r.get("title", ""), "score": r.get("score", 0), "subreddit": r.get("subreddit", "")} for r in reddit_future.result()],
        "youtube": [{"title": r.get("title", ""), "channel": r.get("channel", ""), "views": r.get("views", 0)} for r in youtube_future.result()],
    }

def run():
    contexts = []
    for ticker in TICKERS:
        ctx = fetch_ticker_context(ticker)
        contexts.append(ctx)

    output = {
        "run_time": datetime.utcnow().isoformat(),
        "tickers": contexts,
    }

    # Write to agent input queue
    output_path = Path("trading_context.json")
    output_path.write_text(json.dumps(output, indent=2))

    print(f"Context assembled for {len(TICKERS)} tickers at {output['run_time']}")
    for ctx in contexts:
        print(f"  {ctx['ticker']}: {len(ctx['news'])} news, {len(ctx['reddit'])} reddit, {len(ctx['youtube'])} youtube")

if __name__ == "__main__":
    run()

const API_KEY = "your_scavio_api_key";
const TICKERS = ["NVDA", "AAPL", "TSLA", "MSFT", "AMZN"];

async function search(platform, query) {
  const res = await fetch("https://api.scavio.dev/api/v1/search", {
    method: "POST",
    headers: { "x-api-key": API_KEY, "content-type": "application/json" },
    body: JSON.stringify({ platform, query }),
  });
  if (!res.ok) throw new Error(`scavio ${res.status}`);
  return ((await res.json()).organic ?? []).slice(0, 5);
}

async function fetchTickerContext(ticker) {
  const [news, reddit, youtube] = await Promise.all([
    search("google", `${ticker} stock news today`),
    search("reddit", `${ticker} stock discussion`),
    search("youtube", `${ticker} market analysis`),
  ]);

  return {
    ticker,
    timestamp: new Date().toISOString(),
    news: news.map((r) => ({ title: r.title ?? "", snippet: r.snippet ?? "", link: r.link ?? "" })),
    reddit: reddit.map((r) => ({ title: r.title ?? "", score: r.score ?? 0, subreddit: r.subreddit ?? "" })),
    youtube: youtube.map((r) => ({ title: r.title ?? "", channel: r.channel ?? "", views: r.views ?? 0 })),
  };
}

async function run() {
  const fs = await import("fs/promises");
  const contexts = await Promise.all(TICKERS.map(fetchTickerContext));

  const output = { runTime: new Date().toISOString(), tickers: contexts };
  await fs.writeFile("trading_context.json", JSON.stringify(output, null, 2));

  console.log(`Context assembled for ${TICKERS.length} tickers at ${output.runTime}`);
  for (const ctx of contexts) {
    console.log(`  ${ctx.ticker}: ${ctx.news.length} news, ${ctx.reddit.length} reddit, ${ctx.youtube.length} youtube`);
  }
}

run();