Thread → Blog Post Generation

import os, requests, time

X = os.environ["X_BEARER_TOKEN"]; MV = os.environ["MAVERA_API_KEY"]
X_BASE = "https://api.x.com/2"; MV_BASE = "https://app.mavera.io/api/v1"
X_H = {"Authorization": f"Bearer {X}"}
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

TWEET_ID = "1234567890123456789"

# 1. Fetch first tweet + conversation_id
first = requests.get(f"{X_BASE}/tweets/{TWEET_ID}", headers=X_H,
    params={"tweet.fields": "conversation_id,created_at,public_metrics,author_id",
            "expansions": "author_id", "user.fields": "name,username"})
if first.status_code == 429:
    time.sleep(int(first.headers.get("x-rate-limit-reset", time.time()+60)) - int(time.time()))
    first = requests.get(f"{X_BASE}/tweets/{TWEET_ID}", headers=X_H,
        params={"tweet.fields": "conversation_id,created_at,public_metrics,author_id",
                "expansions": "author_id", "user.fields": "name,username"})
first.raise_for_status(); fd = first.json()
tweet = fd["data"]; conv_id = tweet.get("conversation_id", TWEET_ID)
author = fd.get("includes",{}).get("users",[{}])[0]
uname = author.get("username","unknown")

# 2. Fetch thread
chain = [tweet]; nt = None
for _ in range(5):
    params = {"query": f"conversation_id:{conv_id} from:{uname}", "max_results": 100,
        "tweet.fields": "created_at,public_metrics", "sort_order": "recency"}
    if nt: params["next_token"] = nt
    r = requests.get(f"{X_BASE}/tweets/search/recent", headers=X_H, params=params)
    if r.status_code == 429:
        time.sleep(int(r.headers.get("x-rate-limit-reset", time.time()+60)) - int(time.time()))
        r = requests.get(f"{X_BASE}/tweets/search/recent", headers=X_H, params=params)
    r.raise_for_status()
    for t in r.json().get("data",[]):
        if t["id"] != tweet["id"]: chain.append(t)
    nt = r.json().get("meta",{}).get("next_token")
    if not nt: break
    time.sleep(1)

chain.sort(key=lambda t: t.get("created_at",""))
thread_text = "\n\n".join(f"Tweet {i+1}/{len(chain)}:\n{t['text']}" for i, t in enumerate(chain))
likes = sum(t.get("public_metrics",{}).get("like_count",0) for t in chain)
print(f"Thread: {len(chain)} tweets | {likes:,} likes by @{uname}")

# 3. Brand voice + Generate
bv = requests.post(f"{MV_BASE}/brand-voices", headers=MV_H, json={
    "name": f"Thread Voice: @{uname}", "samples": [thread_text],
    "description": f"Voice from {len(chain)}-tweet thread, {likes:,} likes.",
}).json()

blog = requests.post(f"{MV_BASE}/generations", headers=MV_H, json={
    "brand_voice_id": bv["id"], "app_template": "blog_post",
    "prompt": f"Convert this thread into a blog post.\n\nTHREAD BY @{uname} ({len(chain)} tweets, {likes:,} likes):\n\n{thread_text}\n\n"
        "Title: SEO-friendly (<60 chars). Meta: <160 chars. Structure: intro → 4-6 H2 sections → conclusion + CTA. "
        "Length: 1,200-1,800 words. Preserve thread energy. Expand each tweet with examples and data. "
        "Include 2-3 placeholder internal links.",
}).json()
print(f"\n{'='*60}\nBLOG POST\n{'='*60}")
print(blog.get("output", blog.get("content",""))[:2500])

// --- Same X_BASE, MV_BASE, X_H, MV_H setup as Job 1 ---
const TWEET_ID = "1234567890123456789";
const tweetFields = "tweet.fields=conversation_id,created_at,public_metrics,author_id&expansions=author_id&user.fields=name,username";

let first = await fetch(`${X_BASE}/tweets/${TWEET_ID}?${tweetFields}`, { headers: X_H });
if (first.status === 429) { await new Promise(r => setTimeout(r, 60000));
  first = await fetch(`${X_BASE}/tweets/${TWEET_ID}?${tweetFields}`, { headers: X_H }); }
if (!first.ok) throw new Error(`X API ${first.status}`);
const fd = await first.json();
const tweet = fd.data, convId = tweet.conversation_id || TWEET_ID;
const uname = fd.includes?.users?.[0]?.username || "unknown";

const chain = [tweet]; let nt = null;
for (let i = 0; i < 5; i++) {
  const params = new URLSearchParams({ query: `conversation_id:${convId} from:${uname}`,
    max_results: "100", "tweet.fields": "created_at,public_metrics", sort_order: "recency" });
  if (nt) params.set("next_token", nt);
  let r = await fetch(`${X_BASE}/tweets/search/recent?${params}`, { headers: X_H });
  if (r.status === 429) { await new Promise(res => setTimeout(res, 60000));
    r = await fetch(`${X_BASE}/tweets/search/recent?${params}`, { headers: X_H }); }
  if (!r.ok) break;
  for (const t of (await r.json()).data||[]) if (t.id !== tweet.id) chain.push(t);
  nt = (await r.json()).meta?.next_token; if (!nt) break;
  await new Promise(r => setTimeout(r, 1000));
}
chain.sort((a,b) => (a.created_at||"").localeCompare(b.created_at||""));
const threadText = chain.map((t,i) => `Tweet ${i+1}/${chain.length}:\n${t.text}`).join("\n\n");
const likes = chain.reduce((s,t) => s + (t.public_metrics?.like_count||0), 0);

const bv = await fetch(`${MV_BASE}/brand-voices`, { method: "POST", headers: MV_H,
  body: JSON.stringify({ name: `Thread Voice: @${uname}`, samples: [threadText] }),
}).then(r => r.json());
const blog = await fetch(`${MV_BASE}/generations`, { method: "POST", headers: MV_H,
  body: JSON.stringify({ brand_voice_id: bv.id, app_template: "blog_post",
    prompt: `Convert thread to blog.\n\n@${uname} (${chain.length} tweets, ${likes} likes):\n\n${threadText}\n\nTitle <60ch. 4-6 H2s. 1,200-1,800 words. Expand each tweet.` }),
}).then(r => r.json());
console.log((blog.output||blog.content||"").slice(0,2500));