#!/usr/bin/env python3
"""Extract session metadata from Claude Code, Codex, Cursor, and Pi JSONL files.

Batch mode (preferred — one invocation for all files):
  python3 extract-metadata.py /path/to/dir/*.jsonl
  python3 extract-metadata.py file1.jsonl file2.jsonl file3.jsonl

Single-file mode (stdin):
  head -20 <session.jsonl> | python3 extract-metadata.py

Auto-detects platform from the JSONL structure.
Outputs one JSON object per file, one per line.
Includes a final _meta line with processing stats.
"""
import sys
import json
import os

MAX_LINES = 25  # Only need first ~25 lines for metadata


def json_object(line):
    """Decode one JSONL record and retain only object-shaped entries."""
    try:
        value = json.loads(line.strip())
    except (json.JSONDecodeError, UnicodeDecodeError):
        return None
    return value if isinstance(value, dict) else None


def try_claude(lines):
    for line in lines:
        obj = json_object(line)
        if obj is not None:
            if obj.get("type") == "user" and "gitBranch" in obj:
                return {
                    "platform": "claude",
                    "branch": obj["gitBranch"],
                    "ts": obj.get("timestamp", ""),
                    "session": obj.get("sessionId", ""),
                }
    return None


def try_codex(lines):
    meta = {}
    for line in lines:
        obj = json_object(line)
        if obj is not None:
            if obj.get("type") == "session_meta":
                p = obj.get("payload", {})
                meta["platform"] = "codex"
                meta["cwd"] = p.get("cwd", "")
                meta["session"] = p.get("id", "")
                meta["ts"] = p.get("timestamp", obj.get("timestamp", ""))
                meta["source"] = p.get("source", "")
                meta["cli_version"] = p.get("cli_version", "")
            elif obj.get("type") == "turn_context":
                p = obj.get("payload", {})
                meta["model"] = p.get("model", "")
                meta["cwd"] = meta.get("cwd") or p.get("cwd", "")
    return meta if meta else None


def try_pi(lines):
    """Pi sessions: type='session' header with cwd, followed by message entries."""
    for line in lines:
        obj = json_object(line)
        if obj is not None:
            if obj.get("type") == "session" and "cwd" in obj:
                return {
                    "platform": "pi",
                    "cwd": obj.get("cwd", ""),
                    "session": obj.get("id", ""),
                    "ts": obj.get("timestamp", ""),
                }
    return None


def try_cursor(lines):
    """Cursor agent transcripts: role-based entries, no timestamps or metadata fields."""
    for line in lines:
        obj = json_object(line)
        if obj is not None:
            # Cursor entries have 'role' at top level but no 'type'
            if obj.get("role") in ("user", "assistant") and "type" not in obj:
                return {"platform": "cursor"}
    return None


def extract_from_lines(lines):
    return try_claude(lines) or try_codex(lines) or try_pi(lines) or try_cursor(lines)


TAIL_BYTES = 16384  # Read last 16KB to find final timestamp past trailing metadata


def get_last_timestamp(filepath, size):
    """Read the tail of a file to find the last message with a timestamp."""
    try:
        with open(filepath, "rb") as f:
            f.seek(max(0, size - TAIL_BYTES))
            tail = f.read().decode("utf-8", errors="ignore")
            lines = tail.strip().split("\n")
        for line in reversed(lines):
            obj = json_object(line)
            if obj is not None:
                if "timestamp" in obj:
                    return obj["timestamp"]
    except (OSError, IOError):
        pass
    return None


def _pi_active_path_objects(objects):
    """Return only entries on Pi's active leaf-to-root path.

    Pi session files are append-only trees. The final non-session entry is the
    active leaf; abandoned branches remain in the file but are not in context.
    """
    by_id = {
        obj.get("id"): obj
        for obj in objects
        if isinstance(obj.get("id"), str) and obj.get("type") != "session"
    }
    leaf_id = None
    for obj in objects:
        if obj.get("type") != "session" and isinstance(obj.get("id"), str):
            leaf_id = obj["id"]
    if not leaf_id:
        return objects

    active_ids = set()
    current = leaf_id
    while isinstance(current, str) and current and current not in active_ids:
        active_ids.add(current)
        parent = by_id.get(current, {}).get("parentId")
        current = parent if isinstance(parent, str) else None
    return [
        obj
        for obj in objects
        if obj.get("type") == "session" or obj.get("id") in active_ids
    ]


def _pi_context_objects(objects):
    """Return Pi entries that participate in active LLM context."""
    active = _pi_active_path_objects(objects)
    compactions = [obj for obj in active if obj.get("type") == "compaction"]
    if not compactions:
        return active

    # Pi emits compaction summary first, then entries from firstKeptEntryId
    # onward. Exclude older ancestors so keyword search mirrors context.
    first_kept = compactions[-1].get("firstKeptEntryId")
    if not isinstance(first_kept, str):
        return active

    latest_compaction_id = compactions[-1].get("id")
    started = False
    found_first_kept = False
    context = [obj for obj in active if obj.get("type") == "session"]
    context.append(compactions[-1])
    for obj in active:
        if obj.get("type") == "session":
            continue
        if obj.get("id") == first_kept:
            started = True
            found_first_kept = True
        if obj.get("id") == latest_compaction_id:
            continue
        if started:
            context.append(obj)
    return context if found_first_kept and len(context) > 1 else active


def _append_pi_content_text(chunks, content):
    if isinstance(content, str):
        chunks.append(content)
    elif isinstance(content, list):
        for block in content:
            if isinstance(block, dict) and block.get("type") == "text":
                chunks.append(block.get("text", ""))


def _append_pi_tool_call_targets(chunks, content):
    """Append searchable Pi toolCall targets without indexing tool output."""
    if not isinstance(content, list):
        return
    for block in content:
        if not isinstance(block, dict) or block.get("type") != "toolCall":
            continue
        args = block.get("arguments", {})
        if not isinstance(args, dict):
            continue
        for key in ("path", "file_path", "command", "pattern", "query", "prompt"):
            value = args.get(key)
            if isinstance(value, str):
                chunks.append(value)


def _extract_user_assistant_text(filepath):
    """Return concatenated user + assistant text content from a session JSONL.

    Skips JSONL metadata field names and values (sessionId, gitBranch, uuid,
    timestamps, type tags), tool_use blocks (tool names + tool inputs),
    tool_result blocks (tool outputs), and thinking/reasoning blocks. Only
    content the user or assistant actually said is included.

    Without this filtering, common topic words like "session" would match every
    JSONL file via the sessionId field, drowning out real content matches.
    """
    chunks = []
    try:
        objects = []
        with open(filepath, "r", encoding="utf-8", errors="replace") as f:
            for line in f:
                obj = json_object(line)
                if obj is not None:
                    objects.append(obj)

        is_pi = any(
            obj.get("type") == "session" and "cwd" in obj for obj in objects
        )
        if is_pi:
            objects = _pi_context_objects(objects)

        for obj in objects:
            # Claude Code: type-tagged top-level
            t = obj.get("type")
            if t == "user":
                msg = obj.get("message", {})
                content = msg.get("content")
                if isinstance(content, str):
                    chunks.append(content)
                elif isinstance(content, list):
                    for block in content:
                        if isinstance(block, dict) and block.get("type") == "text":
                            chunks.append(block.get("text", ""))
                        # Skip tool_result blocks — tool outputs are not user content.
                continue
            if t == "assistant":
                msg = obj.get("message", {})
                content = msg.get("content", [])
                if isinstance(content, list):
                    for block in content:
                        if isinstance(block, dict) and block.get("type") == "text":
                            chunks.append(block.get("text", ""))
                        # Skip tool_use and thinking blocks.
                continue

            # Codex: payload-typed events
            if t == "event_msg":
                p = obj.get("payload", {})
                if p.get("type") == "user_message":
                    # Strip Codex/Conductor `<system_instruction>...</system_instruction>`
                    # wrapper before counting. Without this, generic wrapper terms
                    # (e.g., "Conductor", environment labels) false-match against
                    # boilerplate the user did not author. Mirrors the same split
                    # used in session-history/extract-skeleton.py.
                    msg = p.get("message", "")
                    if isinstance(msg, str):
                        parts = msg.split("</system_instruction>")
                        chunks.append(parts[-1] if parts else msg)
                continue
            if t == "response_item":
                p = obj.get("payload", {})
                if p.get("type") == "message" and p.get("role") == "assistant":
                    for block in p.get("content", []):
                        if isinstance(block, dict) and block.get("type") == "output_text":
                            chunks.append(block.get("text", ""))
                continue

            # Pi: type='message' envelope with AgentMessage under message.
            if t == "message" and "message" in obj:
                msg = obj.get("message", {})
                role = msg.get("role", "")
                if role == "bashExecution":
                    command = msg.get("command", "")
                    if isinstance(command, str):
                        chunks.append(command)
                    # Search command text only. Output is tool output and can
                    # be large/noisy in the same way as toolResult content.
                    continue
                content = msg.get("content", [])
                if role == "custom":
                    _append_pi_content_text(chunks, content)
                    continue
                if role not in ("user", "assistant"):
                    continue
                _append_pi_content_text(chunks, content)
                if role == "assistant":
                    _append_pi_tool_call_targets(chunks, content)
                continue

            if t in ("compaction", "branch_summary"):
                summary = obj.get("summary", "")
                if isinstance(summary, str):
                    chunks.append(summary)
                continue

            if t == "custom_message":
                _append_pi_content_text(chunks, obj.get("content", []))
                continue

            # Cursor: role-tagged with no top-level type
            if obj.get("role") in ("user", "assistant") and "type" not in obj:
                msg = obj.get("message", {})
                for block in msg.get("content", []) if isinstance(msg.get("content"), list) else []:
                    if isinstance(block, dict) and block.get("type") == "text":
                        chunks.append(block.get("text", ""))
                continue
    except (OSError, IOError):
        pass
    return "\n".join(chunks)


def count_keyword_matches(filepath, keywords):
    """Case-insensitive substring count for each keyword in user/assistant text.

    Returns a dict {original_keyword: count}. Scans only content the user or
    assistant said — not JSONL metadata, tool calls, tool outputs, or thinking
    blocks — so common topic words like "session" do not false-match against
    the sessionId field.
    """
    text_lower = _extract_user_assistant_text(filepath).lower()
    return {kw: text_lower.count(kw.lower()) for kw in keywords}


def process_file(filepath):
    """Extract metadata only. Keyword scanning is done separately so callers
    can apply cheap filters (e.g. --cwd-filter) before paying the full-file
    content scan cost."""
    try:
        size = os.path.getsize(filepath)
        # Session transcripts are UTF-8 JSONL but historical/corrupted files
        # can contain one bad byte. Metadata extraction is a best-effort probe:
        # preserve the batch and surface parse degradation rather than letting
        # locale-dependent decoding abort every remaining session.
        with open(filepath, "r", encoding="utf-8", errors="replace") as f:
            lines = []
            for i, line in enumerate(f):
                if i >= MAX_LINES:
                    break
                lines.append(line)
        result = extract_from_lines(lines)
        if result:
            result["file"] = filepath
            result["size"] = size
            if result["platform"] == "cursor":
                # Cursor transcripts have no timestamps in JSONL.
                # Use file modification time as the best available signal.
                # Derive session ID from the parent directory name (UUID).
                mtime = os.path.getmtime(filepath)
                from datetime import datetime, timezone

                result["ts"] = datetime.fromtimestamp(mtime, tz=timezone.utc).isoformat()
                result["session"] = os.path.basename(os.path.dirname(filepath))
            else:
                last_ts = get_last_timestamp(filepath, size)
                if last_ts:
                    result["last_ts"] = last_ts
            return result, None
        else:
            return None, filepath
    except (OSError, IOError) as e:
        return None, filepath


def cwd_matches_filter(session_cwd, cwd_filter):
    if not session_cwd or not cwd_filter:
        return True
    if os.path.isabs(cwd_filter):
        return os.path.normpath(session_cwd) == os.path.normpath(cwd_filter)
    return cwd_filter in session_cwd


# Parse arguments: files and optional --cwd-filter / --keyword
files = []
cwd_filter = None
keywords = None
args = sys.argv[1:]
i = 0
while i < len(args):
    if args[i] == "--cwd-filter" and i + 1 < len(args):
        cwd_filter = args[i + 1]
        i += 2
    elif args[i] == "--keyword" and i + 1 < len(args):
        keywords = [k for k in args[i + 1].split(",") if k]
        i += 2
    elif not args[i].startswith("-"):
        files.append(args[i])
        i += 1
    else:
        i += 1

if files:
    # Batch mode: process all files
    processed = 0
    parse_errors = 0
    filtered = 0
    matched = 0
    for filepath in files:
        if not filepath.endswith(".jsonl"):
            continue
        result, error = process_file(filepath)
        processed += 1
        if result:
            # Apply CWD filter first: cheap metadata-only check. Skip Codex
            # sessions from other repos before paying the full-file keyword
            # scan cost — Codex discovery returns sessions across all repos,
            # so without this ordering --keyword would scan files that are
            # immediately discarded.
            if cwd_filter and result.get("cwd") and not cwd_matches_filter(result["cwd"], cwd_filter):
                filtered += 1
                continue
            # Apply keyword scan only after cheap filters pass.
            if keywords:
                matches = count_keyword_matches(filepath, keywords)
                result["keyword_matches"] = matches
                result["match_count"] = sum(matches.values())
                if result["match_count"] == 0:
                    continue
                matched += 1
            print(json.dumps(result))
        elif error:
            parse_errors += 1

    meta = {"_meta": True, "files_processed": processed, "parse_errors": parse_errors}
    if filtered:
        meta["filtered_by_cwd"] = filtered
    if keywords:
        meta["files_matched"] = matched
    print(json.dumps(meta))
else:
    # No file arguments: either single-file stdin mode or empty xargs invocation.
    # When xargs runs us with no input (e.g., discover found no files), stdin is
    # empty or a TTY — emit a clean zero-file result instead of a false parse error.
    if sys.stdin.isatty():
        lines = []
    else:
        lines = list(sys.stdin)

    if not lines:
        # No input at all — zero-file result (clean exit for empty pipelines).
        # When --keyword was supplied, emit files_matched: 0 so callers relying
        # on its presence to terminate quickly in zero-match scans see a
        # consistent shape with the batch-mode no-match case.
        meta = {"_meta": True, "files_processed": 0, "parse_errors": 0}
        if keywords:
            meta["files_matched"] = 0
        print(json.dumps(meta))
    else:
        # Genuine single-file stdin mode (backward compatible)
        result = extract_from_lines(lines)
        if result:
            print(json.dumps(result))
        print(json.dumps({"_meta": True, "files_processed": 1, "parse_errors": 0 if result else 1}))