Source code for autogen_core._image

from __future__ import annotations

import base64
import re
from io import BytesIO
from pathlib import Path
from typing import Any, cast

import aiohttp
from openai.types.chat import ChatCompletionContentPartImageParam
from PIL import Image as PILImage
from pydantic import GetCoreSchemaHandler, ValidationInfo
from pydantic_core import core_schema
from typing_extensions import Literal


[docs] class Image: def __init__(self, image: PILImage.Image): self.image: PILImage.Image = image.convert("RGB")
[docs] @classmethod def from_pil(cls, pil_image: PILImage.Image) -> Image: return cls(pil_image)
[docs] @classmethod def from_uri(cls, uri: str) -> Image: if not re.match(r"data:image/(?:png|jpeg);base64,", uri): raise ValueError("Invalid URI format. It should be a base64 encoded image URI.") # A URI. Remove the prefix and decode the base64 string. base64_data = re.sub(r"data:image/(?:png|jpeg);base64,", "", uri) return cls.from_base64(base64_data)
[docs] @classmethod async def from_url(cls, url: str) -> Image: async with aiohttp.ClientSession() as session: async with session.get(url) as response: content = await response.read() return cls(PILImage.open(content))
[docs] @classmethod def from_base64(cls, base64_str: str) -> Image: return cls(PILImage.open(BytesIO(base64.b64decode(base64_str))))
[docs] def to_base64(self) -> str: buffered = BytesIO() self.image.save(buffered, format="PNG") content = buffered.getvalue() return base64.b64encode(content).decode("utf-8")
[docs] @classmethod def from_file(cls, file_path: Path) -> Image: return cls(PILImage.open(file_path))
def _repr_html_(self) -> str: # Show the image in Jupyter notebook return f'<img src="{self.data_uri}"/>' @property def data_uri(self) -> str: return _convert_base64_to_data_uri(self.to_base64())
[docs] def to_openai_format(self, detail: Literal["auto", "low", "high"] = "auto") -> ChatCompletionContentPartImageParam: return {"type": "image_url", "image_url": {"url": self.data_uri, "detail": detail}}
@classmethod def __get_pydantic_core_schema__(cls, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema: # Custom validation def validate(value: Any, validation_info: ValidationInfo) -> Image: if isinstance(value, dict): base_64 = cast(str | None, value.get("data")) # type: ignore if base_64 is None: raise ValueError("Expected 'data' key in the dictionary") return cls.from_base64(base_64) elif isinstance(value, cls): return value else: raise TypeError(f"Expected dict or {cls.__name__} instance, got {type(value)}") # Custom serialization def serialize(value: Image) -> dict[str, Any]: return {"data": value.to_base64()} return core_schema.with_info_after_validator_function( validate, core_schema.any_schema(), # Accept any type; adjust if needed serialization=core_schema.plain_serializer_function_ser_schema(serialize), )
def _convert_base64_to_data_uri(base64_image: str) -> str: def _get_mime_type_from_data_uri(base64_image: str) -> str: # Decode the base64 string image_data = base64.b64decode(base64_image) # Check the first few bytes for known signatures if image_data.startswith(b"\xff\xd8\xff"): return "image/jpeg" elif image_data.startswith(b"\x89PNG\r\n\x1a\n"): return "image/png" elif image_data.startswith(b"GIF87a") or image_data.startswith(b"GIF89a"): return "image/gif" elif image_data.startswith(b"RIFF") and image_data[8:12] == b"WEBP": return "image/webp" return "image/jpeg" # use jpeg for unknown formats, best guess. mime_type = _get_mime_type_from_data_uri(base64_image) data_uri = f"data:{mime_type};base64,{base64_image}" return data_uri