Docling/docling/models/picture_description_api_model.py
Michele Dolfi 6eaae3cba0
feat: add factory for ocr engines via plugins (#1010)
* add factory for ocr engines

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* apply pre-commit after rebase

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add picture description factory

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* fix enable option

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* switch to create methods

Signed-off-by: Panos Vagenas <pva@zurich.ibm.com>

* make `options` an explicit kwarg

Signed-off-by: Panos Vagenas <pva@zurich.ibm.com>

* keep old lock of docling-core

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* fix lock

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add allow_external_plugins option

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add factory return and ignore options type

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

---------

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Signed-off-by: Panos Vagenas <pva@zurich.ibm.com>
Co-authored-by: Panos Vagenas <pva@zurich.ibm.com>
2025-03-18 13:58:05 +01:00

126 lines
3.6 KiB
Python

import base64
import io
import logging
from pathlib import Path
from typing import Iterable, List, Optional, Type, Union
import requests
from PIL import Image
from pydantic import BaseModel, ConfigDict
from docling.datamodel.pipeline_options import (
AcceleratorOptions,
PictureDescriptionApiOptions,
PictureDescriptionBaseOptions,
)
from docling.exceptions import OperationNotAllowed
from docling.models.picture_description_base_model import PictureDescriptionBaseModel
_log = logging.getLogger(__name__)
class ChatMessage(BaseModel):
role: str
content: str
class ResponseChoice(BaseModel):
index: int
message: ChatMessage
finish_reason: str
class ResponseUsage(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
class ApiResponse(BaseModel):
model_config = ConfigDict(
protected_namespaces=(),
)
id: str
model: Optional[str] = None # returned by openai
choices: List[ResponseChoice]
created: int
usage: ResponseUsage
class PictureDescriptionApiModel(PictureDescriptionBaseModel):
# elements_batch_size = 4
@classmethod
def get_options_type(cls) -> Type[PictureDescriptionBaseOptions]:
return PictureDescriptionApiOptions
def __init__(
self,
enabled: bool,
enable_remote_services: bool,
artifacts_path: Optional[Union[Path, str]],
options: PictureDescriptionApiOptions,
accelerator_options: AcceleratorOptions,
):
super().__init__(
enabled=enabled,
enable_remote_services=enable_remote_services,
artifacts_path=artifacts_path,
options=options,
accelerator_options=accelerator_options,
)
self.options: PictureDescriptionApiOptions
if self.enabled:
if not enable_remote_services:
raise OperationNotAllowed(
"Connections to remote services is only allowed when set explicitly. "
"pipeline_options.enable_remote_services=True."
)
def _annotate_images(self, images: Iterable[Image.Image]) -> Iterable[str]:
# Note: technically we could make a batch request here,
# but not all APIs will allow for it. For example, vllm won't allow more than 1.
for image in images:
img_io = io.BytesIO()
image.save(img_io, "PNG")
image_base64 = base64.b64encode(img_io.getvalue()).decode("utf-8")
messages = [
{
"role": "user",
"content": [
{
"type": "text",
"text": self.options.prompt,
},
{
"type": "image_url",
"image_url": {
"url": f"data:image/png;base64,{image_base64}"
},
},
],
}
]
payload = {
"messages": messages,
**self.options.params,
}
r = requests.post(
str(self.options.url),
headers=self.options.headers,
json=payload,
timeout=self.options.timeout,
)
if not r.ok:
_log.error(f"Error calling the API. Reponse was {r.text}")
r.raise_for_status()
api_resp = ApiResponse.model_validate_json(r.text)
generated_text = api_resp.choices[0].message.content.strip()
yield generated_text