Source code for langchain_community.tools.nuclia.tool

"""Tool for the Nuclia Understanding API.

Installation:

```bash
    pip install --upgrade protobuf
    pip install nucliadb-protos
```
"""

import asyncio
import base64
import logging
import mimetypes
import os
from typing import Any, Dict, Optional, Type, Union

import requests
from langchain_core.callbacks import (
    AsyncCallbackManagerForToolRun,
    CallbackManagerForToolRun,
)
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.tools import BaseTool

logger = logging.getLogger(__name__)


[docs]class NUASchema(BaseModel): """Input for Nuclia Understanding API. Attributes: action: Action to perform. Either `push` or `pull`. id: ID of the file to push or pull. path: Path to the file to push (needed only for `push` action). text: Text content to process (needed only for `push` action). """ action: str = Field( ..., description="Action to perform. Either `push` or `pull`.", ) id: str = Field( ..., description="ID of the file to push or pull.", ) path: Optional[str] = Field( ..., description="Path to the file to push (needed only for `push` action).", ) text: Optional[str] = Field( ..., description="Text content to process (needed only for `push` action).", )
[docs]class NucliaUnderstandingAPI(BaseTool): """Tool to process files with the Nuclia Understanding API.""" name: str = "nuclia_understanding_api" description: str = ( "A wrapper around Nuclia Understanding API endpoints. " "Useful for when you need to extract text from any kind of files. " ) args_schema: Type[BaseModel] = NUASchema _results: Dict[str, Any] = {} _config: Dict[str, Any] = {} def __init__(self, enable_ml: bool = False) -> None: zone = os.environ.get("NUCLIA_ZONE", "europe-1") self._config["BACKEND"] = f"https://{zone}.nuclia.cloud/api/v1" key = os.environ.get("NUCLIA_NUA_KEY") if not key: raise ValueError("NUCLIA_NUA_KEY environment variable not set") else: self._config["NUA_KEY"] = key self._config["enable_ml"] = enable_ml super().__init__() # type: ignore[call-arg] def _run( self, action: str, id: str, path: Optional[str], text: Optional[str], run_manager: Optional[CallbackManagerForToolRun] = None, ) -> str: """Use the tool.""" if action == "push": self._check_params(path, text) if path: return self._pushFile(id, path) if text: return self._pushText(id, text) elif action == "pull": return self._pull(id) return "" async def _arun( self, action: str, id: str, path: Optional[str] = None, text: Optional[str] = None, run_manager: Optional[AsyncCallbackManagerForToolRun] = None, ) -> str: """Use the tool asynchronously.""" self._check_params(path, text) if path: self._pushFile(id, path) if text: self._pushText(id, text) data = None while True: data = self._pull(id) if data: break await asyncio.sleep(15) return data def _pushText(self, id: str, text: str) -> str: field = { "textfield": {"text": {"body": text, "format": 0}}, "processing_options": {"ml_text": self._config["enable_ml"]}, } return self._pushField(id, field) def _pushFile(self, id: str, content_path: str) -> str: with open(content_path, "rb") as source_file: response = requests.post( self._config["BACKEND"] + "/processing/upload", headers={ "content-type": mimetypes.guess_type(content_path)[0] or "application/octet-stream", "x-stf-nuakey": "Bearer " + self._config["NUA_KEY"], }, data=source_file.read(), ) if response.status_code != 200: logger.info( f"Error uploading {content_path}: " f"{response.status_code} {response.text}" ) return "" else: field = { "filefield": {"file": f"{response.text}"}, "processing_options": {"ml_text": self._config["enable_ml"]}, } return self._pushField(id, field) def _pushField(self, id: str, field: Any) -> str: logger.info(f"Pushing {id} in queue") response = requests.post( self._config["BACKEND"] + "/processing/push", headers={ "content-type": "application/json", "x-stf-nuakey": "Bearer " + self._config["NUA_KEY"], }, json=field, ) if response.status_code != 200: logger.info( f"Error pushing field {id}:" f"{response.status_code} {response.text}" ) raise ValueError("Error pushing field") else: uuid = response.json()["uuid"] logger.info(f"Field {id} pushed in queue, uuid: {uuid}") self._results[id] = {"uuid": uuid, "status": "pending"} return uuid def _pull(self, id: str) -> str: self._pull_queue() result = self._results.get(id, None) if not result: logger.info(f"{id} not in queue") return "" elif result["status"] == "pending": logger.info(f'Waiting for {result["uuid"]} to be processed') return "" else: return result["data"] def _pull_queue(self) -> None: try: from nucliadb_protos.writer_pb2 import BrokerMessage except ImportError as e: raise ImportError( "nucliadb-protos is not installed. " "Run `pip install nucliadb-protos` to install." ) from e try: from google.protobuf.json_format import MessageToJson except ImportError as e: raise ImportError( "Unable to import google.protobuf, please install with " "`pip install protobuf`." ) from e res = requests.get( self._config["BACKEND"] + "/processing/pull", headers={ "x-stf-nuakey": "Bearer " + self._config["NUA_KEY"], }, ).json() if res["status"] == "empty": logger.info("Queue empty") elif res["status"] == "ok": payload = res["payload"] pb = BrokerMessage() pb.ParseFromString(base64.b64decode(payload)) uuid = pb.uuid logger.info(f"Pulled {uuid} from queue") matching_id = self._find_matching_id(uuid) if not matching_id: logger.info(f"No matching id for {uuid}") else: self._results[matching_id]["status"] = "done" data = MessageToJson( pb, preserving_proto_field_name=True, including_default_value_fields=True, ) self._results[matching_id]["data"] = data def _find_matching_id(self, uuid: str) -> Union[str, None]: for id, result in self._results.items(): if result["uuid"] == uuid: return id return None def _check_params(self, path: Optional[str], text: Optional[str]) -> None: if not path and not text: raise ValueError("File path or text is required") if path and text: raise ValueError("Cannot process both file and text on a single run")