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68 lines
2.1 KiB
Python
68 lines
2.1 KiB
Python
import base64
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import io
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import uuid
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from pathlib import Path
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from typing import List, Literal, Optional
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from autogen_core.code_executor import ImportFromModule
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from autogen_core.tools import FunctionTool
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from openai import OpenAI
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from PIL import Image
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async def generate_image(
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query: str, output_dir: Optional[Path] = None, image_size: Literal["1024x1024", "512x512", "256x256"] = "1024x1024"
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) -> List[str]:
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"""
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Generate images using OpenAI's DALL-E model based on a text description.
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Args:
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query: Natural language description of the desired image
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output_dir: Directory to save generated images (default: current directory)
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image_size: Size of generated image (1024x1024, 512x512, or 256x256)
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Returns:
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List[str]: Paths to the generated image files
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"""
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# Initialize the OpenAI client
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client = OpenAI()
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# Generate images using DALL-E 3
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response = client.images.generate(model="dall-e-3", prompt=query, n=1, response_format="b64_json", size=image_size)
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saved_files = []
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# Process the response
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if response.data:
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for image_data in response.data:
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# Generate a unique filename
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file_name: str = f"{uuid.uuid4()}.png"
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# Use output_dir if provided, otherwise use current directory
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file_path = Path(output_dir) / file_name if output_dir else Path(file_name)
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base64_str = image_data.b64_json
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if base64_str:
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img = Image.open(io.BytesIO(base64.decodebytes(bytes(base64_str, "utf-8"))))
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# Save the image to a file
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img.save(file_path)
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saved_files.append(str(file_path))
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return saved_files
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# Create the image generation tool
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generate_image_tool = FunctionTool(
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func=generate_image,
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description="Generate images using DALL-E based on text descriptions.",
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global_imports=[
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"io",
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"uuid",
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"base64",
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ImportFromModule("typing", ("List", "Optional", "Literal")),
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ImportFromModule("pathlib", ("Path",)),
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ImportFromModule("openai", ("OpenAI",)),
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ImportFromModule("PIL", ("Image",)),
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],
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)
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