"""Proposal System - PDF Extract Lambda.

Parses vendor proposal PDFs and extracts structured line item data.
Falls back to Claude multimodal for scanned/image-based PDFs.
"""

import base64
import json
import logging
import os
import re
import tempfile
import time

import boto3
from botocore.auth import SigV4Auth
from botocore.awsrequest import AWSRequest
import httpx
import pdfplumber

logger = logging.getLogger(__name__)
logger.setLevel(os.environ.get("LOG_LEVEL", "INFO"))

# Fix: LAM-M8 — pattern for allowed S3 key characters (alphanumeric, hyphens,
# underscores, forward slashes, dots, and spaces)
_SAFE_S3_KEY_RE = re.compile(r"^[a-zA-Z0-9\-_./\s]+$")

UPLOADS_BUCKET = os.environ.get("UPLOADS_BUCKET", "")
API_BASE_URL = os.environ.get("API_BASE_URL", "")
MODEL_ID = os.environ.get("MODEL_ID", "us.anthropic.claude-sonnet-4-5-20250929-v1:0")
INTERNAL_API_KEY_SECRET_ARN = os.environ.get("INTERNAL_API_KEY_SECRET_ARN", "")

s3 = boto3.client("s3")
bedrock_runtime = boto3.client("bedrock-runtime")
secrets_client = boto3.client("secretsmanager")

_cached_api_key: str | None = None
_cached_api_key_ts: float = 0.0
_API_KEY_TTL_SECONDS = 300  # Fix: LAM-M9 — re-fetch every 5 minutes

# Fix: LAM-M3 — maximum PDF file size (50 MB)
_MAX_PDF_SIZE_BYTES = 50 * 1024 * 1024


def _get_api_key() -> str:
    """Fetch internal API key from Secrets Manager with a 5-minute TTL cache.

    Fix: LAM-M9 — the key was previously cached indefinitely. Now the cached
    value expires after _API_KEY_TTL_SECONDS so rotated secrets take effect.
    """
    global _cached_api_key, _cached_api_key_ts
    now = time.monotonic()
    if (
        _cached_api_key is not None
        and (now - _cached_api_key_ts) < _API_KEY_TTL_SECONDS
    ):
        return _cached_api_key
    if INTERNAL_API_KEY_SECRET_ARN:
        resp = secrets_client.get_secret_value(SecretId=INTERNAL_API_KEY_SECRET_ARN)
        _cached_api_key = resp["SecretString"]
    else:
        _cached_api_key = ""
    _cached_api_key_ts = now
    return _cached_api_key


def _validate_s3_key(key: str) -> str:
    """Fix: LAM-M8 — sanitize and validate S3 keys from user-provided data."""
    # Strip path traversal sequences
    sanitized = key.replace("../", "").replace("..\\", "")
    # Collapse any double slashes left behind
    while "//" in sanitized:
        sanitized = sanitized.replace("//", "/")
    sanitized = sanitized.strip("/").strip()

    if not sanitized:
        raise ValueError("S3 key is empty after sanitization")
    if not _SAFE_S3_KEY_RE.match(sanitized):
        raise ValueError(f"S3 key contains disallowed characters: {sanitized!r}")
    return sanitized


def handler(event, context):
    batch_item_failures = []

    # Fix: LAM-M1 — validate event structure before processing
    records = event.get("Records")
    if not isinstance(records, list) or not records:
        logger.warning("Event has no Records or Records is not a list, returning early")
        return {"batchItemFailures": []}

    for record in records:
        if "body" not in record:
            logger.warning(
                "Record missing 'body' key, skipping: %s",
                record.get("messageId", "unknown"),
            )
            continue

        try:
            body = json.loads(record["body"])
        except (json.JSONDecodeError, TypeError) as e:
            # Fix: LAM-M1 — malformed JSON cannot be retried, add to failures
            logger.error("Malformed JSON in record %s: %s", record.get("messageId"), e)
            batch_item_failures.append({"itemIdentifier": record["messageId"]})
            continue

        try:
            payload = body.get("payload", body)
            proposal_id = payload["proposalId"]
            s3_key = payload.get("s3Key", "")
            vendor_proposal_id = payload.get("vendorProposalId", "")

            if not s3_key:
                logger.warning("No s3Key in payload for proposal %s", proposal_id)
                continue

            # Fix: LAM-M8 — validate S3 key before use
            s3_key = _validate_s3_key(s3_key)

            process_pdf(proposal_id, s3_key, vendor_proposal_id)
        except Exception as e:
            # Fix: LAM-M5 — include stack trace in error logging
            logger.exception(
                "Failed to process record %s: %s", record.get("messageId"), e
            )
            batch_item_failures.append({"itemIdentifier": record["messageId"]})
    return {"batchItemFailures": batch_item_failures}


def process_pdf(proposal_id: str, s3_key: str, vendor_proposal_id: str):
    update_processing_status(vendor_proposal_id, "Processing")

    pdf_path = None
    try:
        pdf_path = download_pdf(s3_key)
        extracted = extract_with_pdfplumber(pdf_path)

        if not extracted["lineItems"] and extracted["rawText"].strip():
            extracted = extract_with_claude_multimodal(pdf_path)

        if not extracted["lineItems"] and not extracted["rawText"].strip():
            extracted = extract_with_claude_multimodal(pdf_path)

        save_extraction(vendor_proposal_id, extracted)

    except Exception as e:
        # Fix: LAM-M5 — include stack trace in error logging
        logger.exception("Error processing PDF: %s", e)
        update_processing_status(vendor_proposal_id, "Failed")
    finally:
        if pdf_path:
            try:
                os.unlink(pdf_path)
            except Exception:
                pass


def download_pdf(s3_key: str) -> str:
    # Fix: LAM-M3 — check file size before downloading to avoid processing
    # excessively large PDFs that could exhaust Lambda memory/tmp storage.
    head = s3.head_object(Bucket=UPLOADS_BUCKET, Key=s3_key)
    file_size = head.get("ContentLength", 0)
    if file_size > _MAX_PDF_SIZE_BYTES:
        logger.warning(
            "Fix: LAM-M3 — PDF too large: key=%s size=%d bytes (max=%d)",
            s3_key,
            file_size,
            _MAX_PDF_SIZE_BYTES,
        )
        raise ValueError(
            f"PDF file size ({file_size} bytes) exceeds maximum "
            f"allowed size ({_MAX_PDF_SIZE_BYTES} bytes) for key: {s3_key}"
        )

    tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
    s3.download_file(UPLOADS_BUCKET, s3_key, tmp.name)
    tmp.close()
    return tmp.name


def extract_with_pdfplumber(pdf_path: str) -> dict:
    result = {
        "vendorName": "",
        "lineItems": [],
        "rawText": "",
        "totalVendorCost": 0.0,
    }

    try:
        with pdfplumber.open(pdf_path) as pdf:
            all_text = ""
            all_tables = []

            for page in pdf.pages:
                text = page.extract_text() or ""
                all_text += text + "\n"

                tables = page.extract_tables()
                for table in tables:
                    all_tables.append(table)

            result["rawText"] = all_text.strip()

            if all_tables:
                result["lineItems"] = parse_tables(all_tables)
                result["totalVendorCost"] = sum(
                    li.get("total", 0) for li in result["lineItems"]
                )

            if not result["vendorName"] and all_text:
                lines = all_text.split("\n")
                for line in lines[:5]:
                    stripped = line.strip()
                    if stripped and len(stripped) > 3 and not stripped[0].isdigit():
                        result["vendorName"] = stripped
                        break

    except Exception as e:
        # Fix: LAM-M5 — include stack trace in error logging
        logger.exception("pdfplumber extraction failed: %s", e)

    return result


def parse_tables(tables: list) -> list[dict]:
    line_items = []

    for table in tables:
        if not table or len(table) < 2:
            continue

        header = [str(cell).lower().strip() if cell else "" for cell in table[0]]

        desc_col = find_column(
            header, ["description", "item", "service", "work", "scope"]
        )
        qty_col = find_column(header, ["qty", "quantity", "count"])
        price_col = find_column(
            header, ["unit price", "rate", "price/unit", "unit cost"]
        )
        total_col = find_column(
            header, ["total", "amount", "ext", "extended", "line total"]
        )

        if desc_col is None:
            continue

        for row in table[1:]:
            if not row or len(row) <= desc_col:
                continue

            description = str(row[desc_col]).strip() if row[desc_col] else ""
            if not description or description.lower() in (
                "",
                "total",
                "subtotal",
                "grand total",
            ):
                continue

            quantity = (
                parse_number(row[qty_col])
                if qty_col is not None and qty_col < len(row)
                else None
            )
            unit_price = (
                parse_number(row[price_col])
                if price_col is not None and price_col < len(row)
                else None
            )
            total = (
                parse_number(row[total_col])
                if total_col is not None and total_col < len(row)
                else None
            )

            if total is None and quantity and unit_price:
                total = quantity * unit_price

            if description and (total or unit_price):
                line_items.append(
                    {
                        "description": description,
                        "quantity": quantity,
                        "unitPrice": unit_price,
                        "total": total,
                    }
                )

    return line_items


def find_column(header: list[str], keywords: list[str]) -> int | None:
    for i, col in enumerate(header):
        for kw in keywords:
            if kw in col:
                return i
    return None


def parse_number(value) -> float | None:
    if value is None:
        return None
    try:
        cleaned = str(value).replace("$", "").replace(",", "").strip()
        if not cleaned or cleaned == "-":
            return None
        return float(cleaned)
    except (ValueError, TypeError):
        return None


def extract_with_claude_multimodal(pdf_path: str) -> dict:
    try:
        with open(pdf_path, "rb") as f:
            pdf_bytes = f.read()

        pdf_b64 = base64.standard_b64encode(pdf_bytes).decode("utf-8")

        response = bedrock_runtime.invoke_model(
            modelId=MODEL_ID,
            contentType="application/json",
            accept="application/json",
            body=json.dumps(
                {
                    "anthropic_version": "bedrock-2023-05-31",
                    "max_tokens": 4096,
                    "messages": [
                        {
                            "role": "user",
                            "content": [
                                {
                                    "type": "document",
                                    "source": {
                                        "type": "base64",
                                        "media_type": "application/pdf",
                                        "data": pdf_b64,
                                    },
                                },
                                {
                                    "type": "text",
                                    "text": """Extract all line items from this vendor proposal PDF.
Return a JSON object with these fields:
- vendorName: the vendor/company name
- lineItems: array of objects with: description, quantity (number or null), unitPrice (number or null), total (number or null)
- totalVendorCost: the grand total amount

Respond ONLY with the JSON object, no additional text.""",
                                },
                            ],
                        }
                    ],
                    "temperature": 0.1,
                }
            ),
        )

        response_body = json.loads(response["body"].read())
        content = response_body["content"][0]["text"]

        content = content.strip()
        if content.startswith("```"):
            content = content.split("\n", 1)[1]
            content = content.rsplit("```", 1)[0]

        parsed = json.loads(content)
        return {
            "vendorName": parsed.get("vendorName", ""),
            "lineItems": parsed.get("lineItems", []),
            "rawText": "",
            "totalVendorCost": float(parsed.get("totalVendorCost", 0)),
        }

    except Exception as e:
        # Fix: LAM-M5 — include stack trace in error logging
        logger.exception("Claude multimodal extraction failed: %s", e)
        return {
            "vendorName": "",
            "lineItems": [],
            "rawText": "",
            "totalVendorCost": 0.0,
        }


def save_extraction(vendor_proposal_id: str, extracted: dict):
    extracted_data = {
        "lineItems": extracted["lineItems"],
        "vendorName": extracted["vendorName"],
    }

    try:
        resp = _retry_request(
            "PUT",
            f"{API_BASE_URL}/api/vendor-proposals/{vendor_proposal_id}",
            json={
                "vendorName": extracted["vendorName"],
                "extractedData": json.dumps(extracted_data),
                "totalVendorCost": extracted["totalVendorCost"],
                "processingStatus": "Complete",
            },
            headers=_api_headers(),
        )
        if resp.status_code not in (200, 204):
            logger.error(
                "Failed to save extraction: %s %s", resp.status_code, resp.text
            )
    except Exception as e:
        # Fix: LAM-M5 — include stack trace in error logging
        logger.exception("Error saving extraction: %s", e)


def update_processing_status(vendor_proposal_id: str, status: str):
    if not vendor_proposal_id:
        return
    try:
        _retry_request(
            "PUT",
            f"{API_BASE_URL}/api/vendor-proposals/{vendor_proposal_id}/status",
            json={"processingStatus": status},
            headers=_api_headers(),
        )
    except Exception as e:
        # Fix: LAM-M5 — include stack trace in error logging
        logger.exception("Error updating status: %s", e)


def _api_headers() -> dict:
    headers = {"Content-Type": "application/json"}
    api_key = _get_api_key()
    if api_key:
        headers["X-Internal-Api-Key"] = api_key
    return headers


# Fix (v1 PR1): SigV4-sign internal calls to the .NET API Function URL (authType=AWS_IAM).
# The X-Internal-Api-Key header is preserved for the application-layer check; SigV4
# satisfies the transport-layer IAM auth the Function URL enforces.
_SIGV4_SERVICE = "lambda"
_boto_session = boto3.Session()


def _sign_request_headers(method: str, url: str, body: bytes, headers: dict) -> dict:
    """Return headers with a SigV4 signature for the AWS_IAM Function URL call.

    Falls back to the unsigned headers when no AWS credentials are resolvable, so a
    non-IAM target still works in local development.
    """
    creds = _boto_session.get_credentials()
    if creds is None:
        return headers
    region = os.environ.get("AWS_REGION") or os.environ.get(
        "AWS_DEFAULT_REGION", "us-east-1"
    )
    aws_request = AWSRequest(method=method, url=url, data=body, headers=dict(headers))
    SigV4Auth(creds, _SIGV4_SERVICE, region).add_auth(aws_request)
    return dict(aws_request.headers)


def _retry_request(
    method: str, url: str, *, max_retries: int = 3, **kwargs
) -> httpx.Response:
    kwargs.setdefault("timeout", 10)
    base_headers = dict(kwargs.pop("headers", None) or {})
    # Serialize the body once so the bytes we sign are exactly the bytes we send:
    # SigV4 hashes the payload, so httpx must not re-serialize a json= kwarg.
    if "json" in kwargs:
        body = json.dumps(kwargs.pop("json")).encode("utf-8")
        base_headers.setdefault("Content-Type", "application/json")
    elif "content" in kwargs:
        raw = kwargs.pop("content")
        body = raw if isinstance(raw, bytes) else (raw or "").encode("utf-8")
    else:
        body = b""
    kwargs["content"] = body
    last_resp = None
    for attempt in range(max_retries):
        # Sign per attempt so a slow retry never sends an expired SigV4 timestamp.
        kwargs["headers"] = _sign_request_headers(method, url, body, base_headers)
        try:
            resp = httpx.request(method, url, **kwargs)
            if resp.status_code < 500:
                return resp
            last_resp = resp
        except (httpx.ConnectError, httpx.ReadTimeout, httpx.WriteTimeout) as exc:
            if attempt == max_retries - 1:
                raise
            logger.warning(
                "Retryable error (attempt %d/%d): %s", attempt + 1, max_retries, exc
            )
        time.sleep(min(2**attempt, 4))
    if last_resp is not None:
        return last_resp
    raise RuntimeError(f"All {max_retries} retries failed for {method} {url}")