import asyncio
import base64
import json
from typing import Any

import httpx
from pydantic import ValidationError

from payslip_ingest.schema import ExtractedPayslip

AGENT_PATH = ".claude/agents/payslip-extractor"

EXTRACTION_PROMPT = (
    "You are extracting fields from a UK payslip PDF. Return ONLY a single JSON object "
    "matching this exact schema — no prose, no markdown fences.\n"
    "\n"
    "Schema:\n"
    "{\n"
    '  "pay_date": "YYYY-MM-DD",\n'
    '  "pay_period_start": "YYYY-MM-DD or null",\n'
    '  "pay_period_end": "YYYY-MM-DD or null",\n'
    '  "employer": "string or null",\n'
    '  "currency": "GBP",\n'
    '  "gross_pay": number,\n'
    '  "income_tax": number,\n'
    '  "national_insurance": number,\n'
    '  "pension_employee": number,\n'
    '  "pension_employer": number,\n'
    '  "student_loan": number,\n'
    '  "other_deductions": {"label": number, ...},\n'
    '  "net_pay": number\n'
    "}\n"
    "\n"
    "Rules:\n"
    "- Report numbers as the payslip shows them; do not compute sums.\n"
    "- Unknown numeric fields → 0, not null.\n"
    "- `other_deductions` covers cycle-to-work, share-save, benefits-in-kind, court orders, "
    "anything not in the main fields.\n"
    "- All money in GBP unless the payslip is denominated otherwise.\n"
    '- If a field\'s value is ambiguous, pick the value from the "this period" column, not YTD.')

POLL_INTERVAL_SECONDS = 2
MAX_POLL_SECONDS = 120
BUSY_RETRY_DELAY_SECONDS = 5
MAX_BUSY_RETRIES = 10
DEFAULT_MAX_BUDGET_USD = 1.0
DEFAULT_TIMEOUT_SECONDS = 300

TERMINAL_STATUSES = {"completed", "failed", "timeout", "error"}


class ExtractorError(RuntimeError):
    pass


class ClaudeExtractor:
    """Calls claude-agent-service to extract structured fields from a payslip PDF.

    The agent service serializes execution (one job at a time, 409 when busy);
    we back off and retry so the caller-side queue doesn't have to know.
    """

    def __init__(
        self,
        base_url: str,
        bearer_token: str,
        client: httpx.AsyncClient | None = None,
    ):
        self._base_url = base_url.rstrip("/")
        self._headers = {"Authorization": f"Bearer {bearer_token}"}
        self._client = client or httpx.AsyncClient(timeout=60.0)
        self._owns_client = client is None

    async def aclose(self) -> None:
        if self._owns_client:
            await self._client.aclose()

    async def __aenter__(self) -> "ClaudeExtractor":
        return self

    async def __aexit__(self, *exc: object) -> None:
        await self.aclose()

    async def extract(self, pdf_bytes: bytes, doc_metadata: dict[str, Any]) -> ExtractedPayslip:
        job_id = await self._submit_job(pdf_bytes, doc_metadata)
        output_lines = await self._poll_until_done(job_id)
        payload = _parse_output(output_lines)
        try:
            return ExtractedPayslip.model_validate(payload)
        except ValidationError as exc:
            raise ExtractorError(f"Extracted payload failed schema validation: {exc}") from exc

    async def _submit_job(self, pdf_bytes: bytes, doc_metadata: dict[str, Any]) -> str:
        encoded = base64.b64encode(pdf_bytes).decode("ascii")
        prompt = f"{EXTRACTION_PROMPT}\n\nPDF_BASE64:\n{encoded}\n"
        body = {
            "prompt": prompt,
            "agent": AGENT_PATH,
            "max_budget_usd": DEFAULT_MAX_BUDGET_USD,
            "timeout_seconds": DEFAULT_TIMEOUT_SECONDS,
            "metadata": {
                "paperless_doc_id": doc_metadata.get("id")
            },
        }
        for _ in range(MAX_BUSY_RETRIES):
            resp = await self._client.post(f"{self._base_url}/execute",
                                           headers=self._headers,
                                           json=body)
            if resp.status_code == 409:
                await asyncio.sleep(BUSY_RETRY_DELAY_SECONDS)
                continue
            resp.raise_for_status()
            job_id = resp.json().get("job_id")
            if not isinstance(job_id, str):
                raise ExtractorError(f"Missing job_id in response: {resp.json()}")
            return job_id
        raise ExtractorError(f"Agent service remained busy after {MAX_BUSY_RETRIES} retries")

    async def _poll_until_done(self, job_id: str) -> list[str]:
        max_iterations = max(1, MAX_POLL_SECONDS // max(1, POLL_INTERVAL_SECONDS))
        for _ in range(max_iterations):
            resp = await self._client.get(f"{self._base_url}/jobs/{job_id}", headers=self._headers)
            resp.raise_for_status()
            job = resp.json()
            status = job.get("status")
            if status in TERMINAL_STATUSES:
                if status != "completed":
                    raise ExtractorError(f"Job {job_id} terminated with status={status}: {job}")
                output = job.get("output", [])
                if not isinstance(output, list):
                    raise ExtractorError(f"Job {job_id} output is not a list: {output!r}")
                return [str(line) for line in output]
            await asyncio.sleep(POLL_INTERVAL_SECONDS)
        raise TimeoutError(f"Job {job_id} did not complete within {MAX_POLL_SECONDS}s")


def _parse_output(output_lines: list[str]) -> dict[str, Any]:
    """Extract the JSON payload from claude CLI --output-format json stream.

    The CLI emits one JSON object per line; the final 'result' message holds the
    assistant's final text. We walk from the end, parse each line, and return
    the first embedded JSON object we can recover from the assistant response.
    """
    non_empty = [line.strip() for line in output_lines if line.strip()]
    if not non_empty:
        raise ExtractorError("Agent produced no output")

    for line in reversed(non_empty):
        try:
            parsed = json.loads(line)
        except json.JSONDecodeError:
            continue
        text = _extract_assistant_text(parsed)
        if text is None:
            continue
        payload = _first_json_object(text)
        if payload is not None:
            return payload

    # Fallback: the last line itself might be the JSON object.
    try:
        candidate = json.loads(non_empty[-1])
    except json.JSONDecodeError as exc:
        raise ExtractorError(f"Could not parse JSON from agent output: {exc}") from exc
    if isinstance(candidate, dict):
        return candidate
    raise ExtractorError(f"Last agent line is not a JSON object: {candidate!r}")


def _extract_assistant_text(parsed: Any) -> str | None:
    if not isinstance(parsed, dict):
        return None
    result = parsed.get("result")
    if parsed.get("type") == "result" and isinstance(result, str):
        return result
    message = parsed.get("message")
    if isinstance(message, dict):
        content = message.get("content")
        if isinstance(content, list):
            texts = [
                block.get("text", "") for block in content
                if isinstance(block, dict) and block.get("type") == "text"
            ]
            combined = "".join(str(t) for t in texts)
            if combined:
                return combined
        if isinstance(content, str):
            return content
    text = parsed.get("text")
    if isinstance(text, str):
        return text
    return None


def _first_json_object(text: str) -> dict[str, Any] | None:
    start = text.find("{")
    while start != -1:
        depth = 0
        for i in range(start, len(text)):
            ch = text[i]
            if ch == "{":
                depth += 1
            elif ch == "}":
                depth -= 1
                if depth == 0:
                    candidate = text[start:i + 1]
                    try:
                        obj = json.loads(candidate)
                    except json.JSONDecodeError:
                        break
                    if isinstance(obj, dict):
                        return obj
                    break
        start = text.find("{", start + 1)
    return None