fleet-memory/hindsight-api-slim/hindsight_api/engine/parsers/iris.py

"""Iris parser implementation using the Vectorize Iris HTTP API."""

import asyncio
import logging
import mimetypes
import time

import httpx

from .base import FileParser, UnsupportedFileTypeError

logger = logging.getLogger(__name__)

_IRIS_BASE_URL = "https://api.vectorize.io/v1"
_DEFAULT_POLL_INTERVAL = 2.0  # seconds
_DEFAULT_TIMEOUT = 300.0  # seconds


class IrisParser(FileParser):
    """
    Iris file parser using the Vectorize Iris cloud extraction service.

    Uploads files to the Vectorize Iris API, starts an extraction job,
    and polls until the text is ready. The API determines which file types
    are supported — UnsupportedFileTypeError is raised if the file is rejected.

    Authentication:
        Requires HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN and
        HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID environment variables,
        or pass them explicitly via the constructor.
    """

    def __init__(
        self,
        token: str,
        org_id: str,
        poll_interval: float = _DEFAULT_POLL_INTERVAL,
        timeout: float = _DEFAULT_TIMEOUT,
    ):
        """
        Initialize iris parser.

        Args:
            token: Vectorize API token
            org_id: Vectorize organization ID
            poll_interval: Seconds between status poll requests (default: 2)
            timeout: Maximum seconds to wait for extraction (default: 300)
        """
        self._token = token
        self._org_id = org_id
        self._poll_interval = poll_interval
        self._timeout = timeout
        self._auth_headers = {"Authorization": f"Bearer {token}"}

    async def convert(self, file_data: bytes, filename: str) -> str:
        """
        Parse file to text using the Vectorize Iris API.

        Raises:
            UnsupportedFileTypeError: If the Iris API rejects the file type (4xx)
            RuntimeError: If extraction fails for another reason
        """
        content_type = mimetypes.guess_type(filename)[0] or "application/octet-stream"

        async with httpx.AsyncClient(timeout=httpx.Timeout(30.0, read=120.0)) as client:
            # Step 1: Request a presigned upload URL
            init_resp = await client.post(
                f"{_IRIS_BASE_URL}/org/{self._org_id}/files",
                headers=self._auth_headers,
                json={"name": filename, "contentType": content_type},
            )
            _raise_for_status(init_resp, filename, "file upload init")
            init_data = init_resp.json()
            file_id: str = init_data["fileId"]
            upload_url: str = init_data["uploadUrl"]

            # Step 2: Upload the file bytes to the presigned URL (no auth header)
            # Ensure file_data is plain bytes (GCS storage may return obstore.Bytes)
            upload_resp = await client.put(
                upload_url,
                content=bytes(file_data),
                headers={"Content-Type": content_type},
            )
            _raise_for_status(upload_resp, filename, "file upload")

            # Step 3: Start extraction
            extract_resp = await client.post(
                f"{_IRIS_BASE_URL}/org/{self._org_id}/extraction",
                headers=self._auth_headers,
                json={"fileId": file_id},
            )
            _raise_for_status(extract_resp, filename, "start extraction")
            extraction_id: str = extract_resp.json()["extractionId"]

            # Step 4: Poll until ready or timeout
            deadline = time.monotonic() + self._timeout
            while True:
                status_resp = await client.get(
                    f"{_IRIS_BASE_URL}/org/{self._org_id}/extraction/{extraction_id}",
                    headers=self._auth_headers,
                )
                _raise_for_status(status_resp, filename, "poll extraction status")
                status_data = status_resp.json()

                if status_data.get("ready"):
                    data = status_data.get("data", {})
                    if not data.get("success"):
                        error = data.get("error", "unknown error")
                        raise RuntimeError(f"Iris extraction failed for '{filename}': {error}")
                    text = data.get("text")
                    if not text:
                        raise RuntimeError(f"No content extracted from '{filename}'")
                    return text

                if time.monotonic() >= deadline:
                    raise RuntimeError(f"Iris extraction timed out after {self._timeout}s for '{filename}'")

                await asyncio.sleep(self._poll_interval)

    def name(self) -> str:
        """Get parser name."""
        return "iris"


def _raise_for_status(response: httpx.Response, filename: str, step: str) -> None:
    """
    Raise an appropriate error including the response body on HTTP errors.

    Raises UnsupportedFileTypeError for 4xx responses (file rejected by the API),
    RuntimeError for other HTTP errors.
    """
    if not response.is_error:
        return
    body = response.text or "<empty>"
    msg = f"Iris API error during {step} for '{filename}': {response.status_code} {response.reason_phrase} — {body}"
    if response.is_client_error:
        raise UnsupportedFileTypeError(msg)
    raise RuntimeError(msg)