Instagram Reels Analysis Pipeline

import os, requests, time, tempfile

META = os.environ["META_ACCESS_TOKEN"]
ACCT = os.environ["META_AD_ACCOUNT_ID"]
MV = os.environ["MAVERA_API_KEY"]
GRAPH = "https://graph.facebook.com/v24.0"
MB = "https://app.mavera.io/api/v1"
MH = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

# 1. Pull Instagram placement ads (Reels)
ads = requests.get(
    f"{GRAPH}/{ACCT}/ads",
    params={
        "access_token": META,
        "fields": "id,name,creative{id,name,video_id,title,body,instagram_permalink_url},targeting{publisher_platforms}",
        "effective_status": '["ACTIVE","PAUSED"]',
        "limit": 50,
    },
).json().get("data", [])

reels = [a for a in ads if a.get("creative", {}).get("video_id")
         and "instagram" in str(a.get("targeting", {}).get("publisher_platforms", [])).lower()]
print(f"Instagram Reels creatives: {len(reels)}")

# 2. Video Analysis on each
analyses = []
for reel in reels[:8]:
    vid = reel["creative"]["video_id"]
    video_info = requests.get(f"{GRAPH}/{vid}",
        params={"access_token": META, "fields": "source,length,title"}).json()
    if not video_info.get("source"):
        continue

    vid_resp = requests.get(video_info["source"], stream=True)
    tmp = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
    for chunk in vid_resp.iter_content(8192):
        tmp.write(chunk)
    tmp.close()

    with open(tmp.name, "rb") as f:
        asset = requests.post(f"{MB}/assets",
            headers={"Authorization": f"Bearer {MV}"},
            files={"file": (f"reel_{vid}.mp4", f, "video/mp4")}).json()
    os.unlink(tmp.name)

    analysis = requests.post(f"{MB}/video-analyses", headers=MH,
        json={"asset_id": asset["id"], "name": f"Reel: {reel.get('name', vid)}"}).json()

    for _ in range(30):
        time.sleep(10)
        status = requests.get(f"{MB}/video-analyses/{analysis['id']}",
            headers={"Authorization": f"Bearer {MV}"}).json()
        if status.get("status") in ("completed", "failed"):
            break

    if status.get("status") == "completed":
        analyses.append({
            "name": reel.get("name", vid),
            "video_id": vid,
            "duration": video_info.get("length"),
            "body": reel["creative"].get("body", "")[:150],
            "scores": status.get("scores", {}),
            "analysis_id": analysis["id"],
        })
    time.sleep(1)

# 3. Focus Group on hook, recall, purchase intent
reel_descriptions = "\n\n".join(
    f"Reel {i+1}: \"{a['name']}\" ({a['duration']}s)\n"
    f"Copy: {a['body']}\n"
    f"Emotional score: {a['scores'].get('emotional','?')}, "
    f"Hook strength: {a['scores'].get('attention_curve',['?'])[0] if isinstance(a['scores'].get('attention_curve'), list) else '?'}"
    for i, a in enumerate(analyses)
)

PERSONA_IDS = os.environ.get("PERSONA_IDS", "").split(",")
if not PERSONA_IDS[0]:
    personas = requests.get(f"{MB}/personas",
        headers={"Authorization": f"Bearer {MV}"}).json()
    PERSONA_IDS = [p["id"] for p in (personas if isinstance(personas, list) else [])[:4]]

fg = requests.post(f"{MB}/focus-groups", headers=MH, json={
    "name": "Instagram Reels Analysis",
    "persona_ids": PERSONA_IDS,
    "questions": [
        f"Based on these Reels descriptions, which hook would stop your scroll? Why?\n\n{reel_descriptions}",
        "Rate your brand recall after seeing each Reel (1-10). Which brand/product sticks?",
        "Which Reel would make you most likely to purchase or visit a website? Why?",
        "What makes a Reel hook effective for you? First 3 seconds — what grabs attention?",
        "Would you share any of these Reels? Which one and why?",
    ],
    "context": "You are evaluating Instagram Reels ads for effectiveness.",
    "responses_per_persona": 2,
}).json()

for _ in range(24):
    time.sleep(5)
    fg_data = requests.get(f"{MB}/focus-groups/{fg['id']}", headers=MH).json()
    if fg_data.get("status") == "completed":
        break

# 4. Combined report
print("=== Instagram Reels Analysis Report ===\n")
print("--- Video Analysis Scores ---")
for a in analyses:
    s = a["scores"]
    print(f"  {a['name']}: emotional={s.get('emotional','?')} cognitive={s.get('cognitive','?')} behavioral={s.get('behavioral','?')}")

print("\n--- Focus Group Insights ---")
for resp in fg_data.get("responses", [])[:12]:
    print(f"  [{resp.get('persona_id','?')[:12]}] {resp.get('question','')[:50]}...")
    print(f"    → {resp.get('answer','')[:200]}\n")

const META = process.env.META_ACCESS_TOKEN;
const ACCT = process.env.META_AD_ACCOUNT_ID;
const MV = process.env.MAVERA_API_KEY;
const GRAPH = "https://graph.facebook.com/v24.0";
const MB = "https://app.mavera.io/api/v1";
const MH = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

// 1. Pull Instagram placement ads
const ads = await fetch(
  `${GRAPH}/${ACCT}/ads?access_token=${META}&fields=id,name,creative{id,name,video_id,title,body,instagram_permalink_url},targeting{publisher_platforms}&effective_status=["ACTIVE","PAUSED"]&limit=50`
).then(r => r.json()).then(d => d.data || []);

const reels = ads.filter(a => a.creative?.video_id
  && JSON.stringify(a.targeting?.publisher_platforms || []).toLowerCase().includes("instagram"));
console.log(`Instagram Reels: ${reels.length}`);

// 2. Video Analysis
const analyses = [];
for (const reel of reels.slice(0, 8)) {
  const vid = reel.creative.video_id;
  const videoInfo = await fetch(
    `${GRAPH}/${vid}?access_token=${META}&fields=source,length,title`
  ).then(r => r.json());
  if (!videoInfo.source) continue;

  const vidBuffer = Buffer.from(await fetch(videoInfo.source).then(r => r.arrayBuffer()));
  const form = new FormData();
  form.append("file", new Blob([vidBuffer], { type: "video/mp4" }), `reel_${vid}.mp4`);
  const asset = await fetch(`${MB}/assets`, {
    method: "POST", headers: { Authorization: `Bearer ${MV}` }, body: form,
  }).then(r => r.json());

  const analysis = await fetch(`${MB}/video-analyses`, {
    method: "POST", headers: MH,
    body: JSON.stringify({ asset_id: asset.id, name: `Reel: ${reel.name || vid}` }),
  }).then(r => r.json());

  let status;
  for (let i = 0; i < 30; i++) {
    await new Promise(r => setTimeout(r, 10000));
    status = await fetch(`${MB}/video-analyses/${analysis.id}`,
      { headers: { Authorization: `Bearer ${MV}` } }).then(r => r.json());
    if (status.status === "completed" || status.status === "failed") break;
  }

  if (status?.status === "completed") {
    analyses.push({
      name: reel.name || vid, video_id: vid, duration: videoInfo.length,
      body: (reel.creative.body || "").slice(0, 150),
      scores: status.scores || {}, analysis_id: analysis.id,
    });
  }
  await new Promise(r => setTimeout(r, 1000));
}

// 3. Focus Group
const reelDescs = analyses.map((a, i) =>
  `Reel ${i+1}: "${a.name}" (${a.duration}s)\nCopy: ${a.body}\nEmotional: ${a.scores.emotional ?? "?"}`
).join("\n\n");

let personaIds = (process.env.PERSONA_IDS || "").split(",").filter(Boolean);
if (!personaIds.length) {
  const personas = await fetch(`${MB}/personas`, { headers: MH }).then(r => r.json());
  personaIds = (Array.isArray(personas) ? personas : []).slice(0, 4).map(p => p.id);
}

const fg = await fetch(`${MB}/focus-groups`, {
  method: "POST", headers: MH,
  body: JSON.stringify({
    name: "Instagram Reels Analysis", persona_ids: personaIds,
    questions: [
      `Which hook would stop your scroll?\n\n${reelDescs}`,
      "Rate brand recall 1-10 for each Reel.",
      "Which Reel would most likely drive you to purchase?",
      "What makes a Reel hook effective in the first 3 seconds?",
      "Would you share any of these? Which and why?",
    ],
    context: "Evaluating Instagram Reels ads.", responses_per_persona: 2,
  }),
}).then(r => r.json());

let fgData;
for (let i = 0; i < 24; i++) {
  await new Promise(r => setTimeout(r, 5000));
  fgData = await fetch(`${MB}/focus-groups/${fg.id}`, { headers: MH }).then(r => r.json());
  if (fgData.status === "completed") break;
}

console.log("=== Reels Analysis Report ===\n--- Scores ---");
analyses.forEach(a => {
  const s = a.scores;
  console.log(`  ${a.name}: emotional=${s.emotional ?? "?"} cognitive=${s.cognitive ?? "?"} behavioral=${s.behavioral ?? "?"}`);
});
console.log("\n--- Focus Group ---");
(fgData.responses || []).slice(0, 12).forEach(r => {
  console.log(`  [${(r.persona_id || "?").slice(0, 12)}] ${(r.question || "").slice(0, 50)}...`);
  console.log(`    → ${(r.answer || "").slice(0, 200)}\n`);
});