Meeting Notes → Mave Analysis

import os, requests, time

NOTION = os.environ["NOTION_API_KEY"]
MV = os.environ["MAVERA_API_KEY"]
NB = "https://api.notion.com/v1"
MB = "https://app.mavera.io/api/v1"
NH = {
    "Authorization": f"Bearer {NOTION}",
    "Notion-Version": "2022-06-28",
    "Content-Type": "application/json",
}
MH = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

MEETINGS_DB_ID = "your-meetings-database-id"

# 1. Query recent meeting pages
pages = requests.post(f"{NB}/databases/{MEETINGS_DB_ID}/query", headers=NH, json={
    "filter": {
        "property": "Date",
        "date": {"past_month": {}},
    },
    "sorts": [{"property": "Date", "direction": "descending"}],
    "page_size": 30,
}).json().get("results", [])

print(f"Found {len(pages)} meeting pages in the past month")

# 2. Extract text from each page's blocks
def extract_text(block):
    """Recursively extract plain text from a Notion block."""
    btype = block.get("type", "")
    content = block.get(btype, {})
    rich_text = content.get("rich_text", [])
    return "".join(t.get("plain_text", "") for t in rich_text)

def get_page_text(page_id, depth=0):
    """Fetch all blocks from a page and concatenate text."""
    texts = []
    cursor = None
    while True:
        params = {"page_size": 100}
        if cursor:
            params["start_cursor"] = cursor
        r = requests.get(f"{NB}/blocks/{page_id}/children", headers=NH, params=params)
        if r.status_code == 429:
            time.sleep(1)
            continue
        r.raise_for_status()
        data = r.json()
        for block in data.get("results", []):
            text = extract_text(block)
            if text.strip():
                prefix = "- " if block.get("type") in ("bulleted_list_item", "numbered_list_item", "to_do") else ""
                texts.append(f"{prefix}{text}")
            if block.get("has_children") and depth < 2:
                texts.extend(get_page_text(block["id"], depth + 1))
        cursor = data.get("next_cursor")
        if not cursor:
            break
        time.sleep(0.4)
    return texts

meetings_corpus = []
for page in pages[:20]:
    props = page.get("properties", {})
    title_parts = props.get("Name", props.get("Title", {})).get("title", [])
    title = "".join(t.get("plain_text", "") for t in title_parts) or "Untitled Meeting"
    date = (props.get("Date", {}).get("date", {}) or {}).get("start", "unknown")

    text_lines = get_page_text(page["id"])
    if text_lines:
        meetings_corpus.append(f"## {title} ({date})\n" + "\n".join(text_lines[:50]))
    time.sleep(0.4)

corpus = "\n\n---\n\n".join(meetings_corpus)
print(f"Extracted text from {len(meetings_corpus)} meetings ({len(corpus)} chars)")

# 3. Mave analysis
analysis = requests.post(f"{MB}/mave/chat", headers=MH, json={
    "message": (
        f"Meeting intelligence analyst. Analyze {len(meetings_corpus)} meetings from the past month.\n\n"
        f"MEETING NOTES:\n{corpus[:12000]}\n\n"
        "Extract and structure:\n\n"
        "1. **ACTION ITEMS** — Who owes what, by when. Flag overdue or repeated items.\n"
        "2. **DECISIONS MADE** — Key decisions with date and context.\n"
        "3. **RECURRING THEMES** — Topics that appear across 3+ meetings.\n"
        "4. **BLOCKERS & RISKS** — Issues mentioned but unresolved.\n"
        "5. **STRATEGIC PATTERNS** — Higher-level trends across all meetings.\n"
        "6. **FOLLOW-UP RECOMMENDATIONS** — What should happen next based on the patterns.\n\n"
        "Quote directly from the notes. Include meeting titles for attribution."
    ),
}).json()

print(f"\n{'='*60}\nMEETING INTELLIGENCE REPORT\n{'='*60}")
print(analysis.get("content", "")[:3000])

const NOTION = process.env.NOTION_API_KEY;
const MV = process.env.MAVERA_API_KEY;
const NB = "https://api.notion.com/v1";
const MB = "https://app.mavera.io/api/v1";
const NH = {
  Authorization: `Bearer ${NOTION}`,
  "Notion-Version": "2022-06-28",
  "Content-Type": "application/json",
};
const MH = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

const MEETINGS_DB_ID = "your-meetings-database-id";

// 1. Query meeting pages
const pages = await fetch(`${NB}/databases/${MEETINGS_DB_ID}/query`, {
  method: "POST", headers: NH,
  body: JSON.stringify({
    filter: { property: "Date", date: { past_month: {} } },
    sorts: [{ property: "Date", direction: "descending" }],
    page_size: 30,
  }),
}).then(r => r.json()).then(d => d.results || []);

console.log(`Found ${pages.length} meeting pages`);

// 2. Extract page text
function extractText(block) {
  const content = block[block.type] || {};
  return (content.rich_text || []).map(t => t.plain_text).join("");
}

async function getPageText(pageId, depth = 0) {
  const texts = [];
  let cursor = null;
  do {
    const params = new URLSearchParams({ page_size: "100" });
    if (cursor) params.set("start_cursor", cursor);
    const res = await fetch(`${NB}/blocks/${pageId}/children?${params}`, { headers: NH });
    if (res.status === 429) { await new Promise(r => setTimeout(r, 1000)); continue; }
    const data = await res.json();
    for (const block of data.results || []) {
      const text = extractText(block);
      if (text.trim()) {
        const prefix = ["bulleted_list_item", "numbered_list_item", "to_do"].includes(block.type) ? "- " : "";
        texts.push(`${prefix}${text}`);
      }
      if (block.has_children && depth < 2) texts.push(...await getPageText(block.id, depth + 1));
    }
    cursor = data.next_cursor;
    await new Promise(r => setTimeout(r, 400));
  } while (cursor);
  return texts;
}

const meetingsCorpus = [];
for (const page of pages.slice(0, 20)) {
  const props = page.properties || {};
  const titleProp = props.Name || props.Title || {};
  const title = (titleProp.title || []).map(t => t.plain_text).join("") || "Untitled";
  const date = props.Date?.date?.start || "unknown";

  const textLines = await getPageText(page.id);
  if (textLines.length) meetingsCorpus.push(`## ${title} (${date})\n${textLines.slice(0, 50).join("\n")}`);
  await new Promise(r => setTimeout(r, 400));
}

const corpus = meetingsCorpus.join("\n\n---\n\n");
console.log(`Extracted ${meetingsCorpus.length} meetings (${corpus.length} chars)`);

// 3. Mave analysis
const analysis = await fetch(`${MB}/mave/chat`, { method: "POST", headers: MH,
  body: JSON.stringify({
    message: `Meeting analyst. ${meetingsCorpus.length} meetings, past month.\n\n${corpus.slice(0, 12000)}\n\nExtract: 1) ACTION ITEMS (who, what, when) 2) DECISIONS 3) RECURRING THEMES (3+ meetings) 4) BLOCKERS 5) STRATEGIC PATTERNS 6) FOLLOW-UP RECOMMENDATIONS. Quote from notes with meeting titles.`,
  }),
}).then(r => r.json());

console.log(`\n${"=".repeat(60)}\nMEETING INTELLIGENCE REPORT`);
console.log((analysis.content || "").slice(0, 3000));