async def build_pdf(sections, title='Report', style=None) -> str:
    """Render sections into a PDF. Returns base64 PDF bytes.
    style dict keys: header_color, font_family,
    title_font_size, heading1_font_size, heading2_font_size,
    body_font_size, table_font_size, code_font_size"""

async def fetch_chart(asset_id: str) -> str:
    """Fetch a chart PNG as base64 string. Use with image section."""

async def fetch_table_data(asset_id: str, max_rows: int = 50) -> dict:
    """Fetch CSV as {"columns": [...], "rows": [[...]], "total_rows": int}."""

async def list_available_assets() -> list[dict]:
    """List all assets in the chat.
    Returns [{"asset_id": ..., "mime_type": ...}].
    Use to discover charts (image/png) and tables (text/csv)."""

async def get_chat_history() -> str:
    """Get the conversation as plain text (User/Assistant turns).
    Call this first to understand what was discussed."""

async def report_generated_at() -> str:
    """Human-readable timestamp for this report run, e.g.
    'May 04, 2026 at 11:28 UTC'. Use this instead of datetime.now."""

async def report_today() -> str:
    """Today's date in ISO format, e.g. '2026-05-04'.
    Use this instead of datetime.today or date.today."""

sections = [
    {"type": "title", "text": "Q4 2023 Shipping Performance"},
    {"type": "heading", "text": "Overview", "level": 1},
    {"type": "paragraph", "text": (
        "Shipping held up through Q4 2023: 645 orders moved across "
        "weeks 39-52, with roughly 45% early, 26% on time, and 29% "
        "late."
    )},
]
# Embed only assets in scope. Use human-readable titles, not asset IDs.
for asset in await list_available_assets():
    if asset['asset_id'] not in scope_asset_ids:
        continue
    if asset["mime_type"] == "image/png":
        b64 = await fetch_chart(asset["asset_id"])
        if b64:
            sections.append({"type": "image", "data_base64": b64,
                "title": "Weekly Orders by Shipping Status"})
    elif asset["mime_type"] == "text/csv":
        td = await fetch_table_data(asset["asset_id"])
        if td["columns"]:
            sections.append({"type": "data_table",
                "headers": ["Week", "Early", "On Time", "Late"],
                "rows": td["rows"],
                "title": "Weekly Shipping Detail"})
result = await build_pdf(sections, "Q4 2023 Shipping Performance")
result