scripts/parse_transcripts.py

#!/usr/bin/env python3
"""Parse ~2,000 Audrey Tang transcript markdown files into structured JSONL.

Reads from: /Users/au/w/transcript/*.md
Writes to:  dataset/data/turns.jsonl  (one JSON object per speaker turn)
            dataset/data/metadata.json (statistics)
"""

from __future__ import annotations

import json
import glob
import html
import os
import re
import sys
from collections import Counter
from pathlib import Path
from typing import Optional

TRANSCRIPT_DIR = "/Users/au/w/transcript"
OUTPUT_DIR = Path(__file__).resolve().parent.parent / "data"

SKIP_FILES = {"lexicon.md", "z.md"}

# Audrey's names across languages
AUDREY_NAMES = {"audrey tang", "唐鳳"}

# Regex patterns
HEADER_RE = re.compile(r"^#\s+(\d{4}-\d{2}-\d{2})\s+(.+)$")
HEADER_YEAR_ONLY_RE = re.compile(r"^#\s+(\d{4})年(.+)$")
SPEAKER_RE = re.compile(r"^###\s+(.+?)\s*[：:]\s*$")
STAGE_DIR_RE = re.compile(r"^>\s*(.+)$")
HTML_TAG_RE = re.compile(r"<[^>]+>")
IFRAME_BLOCK_RE = re.compile(r"<iframe[\s\S]*?</iframe>", re.IGNORECASE)


def is_cjk(char: str) -> bool:
    cp = ord(char)
    return 0x4E00 <= cp <= 0x9FFF


def detect_language(text: str) -> str:
    """Return 'zh' if >30% CJK characters, else 'en'."""
    chars = [c for c in text if not c.isspace()]
    if not chars:
        return "en"
    cjk_count = sum(1 for c in chars if is_cjk(c))
    return "zh" if cjk_count / len(chars) > 0.30 else "en"


def normalize_speaker(name: str) -> str:
    """Normalize speaker name: strip extra whitespace."""
    return " ".join(name.split())


def is_audrey(speaker: str) -> bool:
    return speaker.lower().strip() in AUDREY_NAMES


def extract_stage_directions(text: str) -> list[str]:
    """Extract parenthetical stage directions like (laughter), （笑）from text."""
    directions = []
    # Match both ASCII and fullwidth parens
    for m in re.finditer(r"[（(]([^）)]+)[）)]", text):
        directions.append(f"({m.group(1)})")
    return directions


def clean_text(text: str) -> str:
    """Clean turn text: decode HTML entities, strip HTML tags, normalize whitespace."""
    text = html.unescape(text)
    text = IFRAME_BLOCK_RE.sub("", text)
    text = HTML_TAG_RE.sub("", text)
    # Remove markdown image/link artifacts that are just URLs
    # Keep link text but remove URL: [text](url) -> text
    text = re.sub(r"\[([^\]]*)\]\([^)]+\)", r"\1", text)
    # Normalize whitespace within paragraphs but preserve paragraph breaks
    lines = text.split("\n")
    cleaned_lines = []
    for line in lines:
        stripped = line.strip()
        if stripped:
            cleaned_lines.append(stripped)
        else:
            cleaned_lines.append("")
    text = "\n".join(cleaned_lines)
    # Collapse multiple blank lines into one
    text = re.sub(r"\n{3,}", "\n\n", text)
    return text.strip()


def parse_file(filepath: str) -> dict | None:
    """Parse a single transcript .md file.

    Returns dict with keys: date, title, source_file, turns, language, skip_reason
    or None if the file should be skipped.
    """
    filename = os.path.basename(filepath)

    if filename in SKIP_FILES:
        return {"skip_reason": f"excluded file: {filename}", "source_file": filename}

    with open(filepath, "r", encoding="utf-8") as f:
        content = f.read()

    if not content.strip():
        return {"skip_reason": "empty file", "source_file": filename}

    lines = content.split("\n")

    # Parse H1 header
    date = None
    title = None
    header_line_idx = None

    for i, line in enumerate(lines):
        stripped = line.strip()
        if not stripped:
            continue
        m = HEADER_RE.match(stripped)
        if m:
            date = m.group(1)
            title = m.group(2).strip()
            header_line_idx = i
            break
        m2 = HEADER_YEAR_ONLY_RE.match(stripped)
        if m2:
            # e.g. "# 1999年全國司法改革會議" - has year but no full date
            date = None
            title = stripped.lstrip("# ").strip()
            header_line_idx = i
            break
        # If first non-empty line is not a header, check if it's a speaker line
        if stripped.startswith("###"):
            break  # No H1 header
        if not stripped.startswith("#"):
            break  # Not a header line
        break

    # Try to extract date from filename if not from header
    if date is None:
        fm = re.match(r"(\d{4}-\d{2}-\d{2})", filename)
        if fm:
            date = fm.group(1)
            if title is None:
                # Derive title from filename
                title_part = filename[11:]  # Skip "YYYY-MM-DD-"
                title_part = title_part.rsplit(".md", 1)[0]
                title = title_part.replace("-", " ")

    if date is None:
        return {"skip_reason": "no date found in header or filename", "source_file": filename}

    # Parse content into turns
    body_start = (header_line_idx + 1) if header_line_idx is not None else 0
    body_lines = lines[body_start:]

    turns = []
    current_speaker = None
    current_paragraphs = []
    current_stage_dirs = []
    has_speaker_blocks = False

    def flush_turn():
        nonlocal current_speaker, current_paragraphs, current_stage_dirs
        if current_speaker and current_paragraphs:
            text = "\n\n".join(current_paragraphs)
            text = clean_text(text)
            if text:
                turns.append({
                    "speaker": current_speaker,
                    "text": text,
                    "stage_directions": current_stage_dirs[:],
                })
        current_paragraphs = []
        current_stage_dirs = []

    for line in body_lines:
        stripped = line.strip()

        # Check for speaker header
        sm = SPEAKER_RE.match(stripped)
        if sm:
            has_speaker_blocks = True
            new_speaker = normalize_speaker(sm.group(1))
            if new_speaker == current_speaker:
                # Same speaker continues - we'll add a paragraph break
                # but keep accumulating under the same turn
                if current_paragraphs:
                    current_paragraphs.append("")  # blank separator
            else:
                flush_turn()
                current_speaker = new_speaker
            continue

        # Check for stage direction (blockquote)
        sd = STAGE_DIR_RE.match(stripped)
        if sd:
            direction_text = sd.group(1).strip()
            # Extract parenthetical directions
            dirs = extract_stage_directions(direction_text)
            if dirs:
                current_stage_dirs.extend(dirs)
            # Don't add blockquote text to the turn content
            continue

        # Regular text line
        if current_speaker:
            if stripped:
                current_paragraphs.append(stripped)
            elif current_paragraphs and current_paragraphs[-1] != "":
                current_paragraphs.append("")  # paragraph break

    flush_turn()

    # Handle files with no speaker blocks - treat as monologue by Audrey Tang
    if not has_speaker_blocks:
        # Check if there's meaningful text content
        text_lines = []
        for line in body_lines:
            stripped = line.strip()
            if not stripped:
                continue
            sd = STAGE_DIR_RE.match(stripped)
            if sd:
                continue
            # Skip lines that are just links/embeds
            if stripped.startswith("http") or stripped.startswith("<"):
                continue
            text_lines.append(stripped)

        if not text_lines:
            return {"skip_reason": "no meaningful content", "source_file": filename}

        full_text = clean_text("\n\n".join(text_lines))
        if not full_text:
            return {"skip_reason": "no meaningful content after cleaning", "source_file": filename}

        # Detect if this is CJK to pick the right name
        lang = detect_language(full_text)
        speaker = "唐鳳" if lang == "zh" else "Audrey Tang"
        turns = [{
            "speaker": speaker,
            "text": full_text,
            "stage_directions": [],
        }]

    if not turns:
        return {"skip_reason": "no turns extracted", "source_file": filename}

    # Detect language from all turn text
    all_text = " ".join(t["text"] for t in turns)
    language = detect_language(all_text)

    return {
        "date": date,
        "title": title,
        "source_file": filename,
        "turns": turns,
        "language": language,
        "skip_reason": None,
    }


def make_turn_id(source_file: str, turn_index: int) -> str:
    """Create a turn ID from source file and index."""
    base = source_file.rsplit(".md", 1)[0]
    return f"{base}/{turn_index:03d}"


def main():
    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)

    md_files = sorted(glob.glob(os.path.join(TRANSCRIPT_DIR, "*.md")))
    print(f"Found {len(md_files)} .md files")

    all_turns = []
    skipped = []
    parsed_count = 0
    speaker_counter = Counter()
    lang_counter = Counter()
    dates = []

    for filepath in md_files:
        result = parse_file(filepath)
        if result is None:
            continue

        if result.get("skip_reason"):
            skipped.append({
                "file": result["source_file"],
                "reason": result["skip_reason"],
            })
            continue

        parsed_count += 1
        turns = result["turns"]
        total_turns = len(turns)
        lang_counter[result["language"]] += 1
        dates.append(result["date"])

        for i, turn in enumerate(turns):
            speaker = turn["speaker"]
            speaker_counter[speaker] += 1
            turn_obj = {
                "id": make_turn_id(result["source_file"], i),
                "date": result["date"],
                "title": result["title"],
                "source_file": result["source_file"],
                "speaker": speaker,
                "text": turn["text"],
                "turn_index": i,
                "is_audrey": is_audrey(speaker),
                "language": result["language"],
                "stage_directions": turn["stage_directions"],
                "total_turns": total_turns,
            }
            all_turns.append(turn_obj)

    # Write turns.jsonl
    turns_path = OUTPUT_DIR / "turns.jsonl"
    with open(turns_path, "w", encoding="utf-8") as f:
        for turn in all_turns:
            f.write(json.dumps(turn, ensure_ascii=False) + "\n")

    # Compute stats
    audrey_turns = sum(1 for t in all_turns if t["is_audrey"])
    sorted_dates = sorted(dates) if dates else []
    top_speakers = speaker_counter.most_common(20)

    metadata = {
        "total_files_found": len(md_files),
        "total_files_parsed": parsed_count,
        "total_files_skipped": len(skipped),
        "total_turns": len(all_turns),
        "total_audrey_turns": audrey_turns,
        "language_distribution": dict(lang_counter),
        "date_range": {
            "earliest": sorted_dates[0] if sorted_dates else None,
            "latest": sorted_dates[-1] if sorted_dates else None,
        },
        "top_speakers": [{"speaker": s, "count": c} for s, c in top_speakers],
        "skipped_files": skipped,
    }

    meta_path = OUTPUT_DIR / "metadata.json"
    with open(meta_path, "w", encoding="utf-8") as f:
        json.dump(metadata, f, ensure_ascii=False, indent=2)

    # Print summary
    print(f"\nParsed {parsed_count} files, skipped {len(skipped)}")
    print(f"Total turns: {len(all_turns)}")
    print(f"Audrey turns: {audrey_turns}")
    print(f"Language distribution: {dict(lang_counter)}")
    if sorted_dates:
        print(f"Date range: {sorted_dates[0]} to {sorted_dates[-1]}")
    print(f"Top 10 speakers:")
    for speaker, count in top_speakers[:10]:
        print(f"  {speaker}: {count}")
    print(f"\nOutput: {turns_path}")
    print(f"Metadata: {meta_path}")


if __name__ == "__main__":
    main()