mirror of
https://github.com/xtekky/gpt4free.git
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152 lines
4.7 KiB
Python
152 lines
4.7 KiB
Python
"""
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Module to handle image uploading and processing for Bing AI integrations.
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"""
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from __future__ import annotations
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import json
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import math
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from aiohttp import ClientSession, FormData
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from ...typing import ImageType, Tuple
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from ...image import to_image, process_image, to_base64_jpg, ImageRequest, Image
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IMAGE_CONFIG = {
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"maxImagePixels": 360000,
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"imageCompressionRate": 0.7,
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"enableFaceBlurDebug": False,
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}
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async def upload_image(
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session: ClientSession,
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image_data: ImageType,
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tone: str,
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proxy: str = None
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) -> ImageRequest:
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"""
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Uploads an image to Bing's AI service and returns the image response.
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Args:
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session (ClientSession): The active session.
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image_data (bytes): The image data to be uploaded.
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tone (str): The tone of the conversation.
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proxy (str, optional): Proxy if any. Defaults to None.
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Raises:
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RuntimeError: If the image upload fails.
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Returns:
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ImageRequest: The response from the image upload.
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"""
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image = to_image(image_data)
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new_width, new_height = calculate_new_dimensions(image)
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image = process_image(image, new_width, new_height)
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img_binary_data = to_base64_jpg(image, IMAGE_CONFIG['imageCompressionRate'])
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data = build_image_upload_payload(img_binary_data, tone)
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headers = prepare_headers(session)
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async with session.post("https://www.bing.com/images/kblob", data=data, headers=headers, proxy=proxy) as response:
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if response.status != 200:
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raise RuntimeError("Failed to upload image.")
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return parse_image_response(await response.json())
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def calculate_new_dimensions(image: Image) -> Tuple[int, int]:
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"""
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Calculates the new dimensions for the image based on the maximum allowed pixels.
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Args:
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image (Image): The PIL Image object.
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Returns:
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Tuple[int, int]: The new width and height for the image.
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"""
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width, height = image.size
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max_image_pixels = IMAGE_CONFIG['maxImagePixels']
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if max_image_pixels / (width * height) < 1:
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scale_factor = math.sqrt(max_image_pixels / (width * height))
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return int(width * scale_factor), int(height * scale_factor)
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return width, height
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def build_image_upload_payload(image_bin: str, tone: str) -> FormData:
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"""
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Builds the payload for image uploading.
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Args:
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image_bin (str): Base64 encoded image binary data.
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tone (str): The tone of the conversation.
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Returns:
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Tuple[str, str]: The data and boundary for the payload.
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"""
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data = FormData()
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knowledge_request = json.dumps(build_knowledge_request(tone), ensure_ascii=False)
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data.add_field('knowledgeRequest', knowledge_request, content_type="application/json")
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data.add_field('imageBase64', image_bin)
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return data
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def build_knowledge_request(tone: str) -> dict:
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"""
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Builds the knowledge request payload.
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Args:
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tone (str): The tone of the conversation.
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Returns:
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dict: The knowledge request payload.
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"""
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return {
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"imageInfo": {},
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"knowledgeRequest": {
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'invokedSkills': ["ImageById"],
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'subscriptionId': "Bing.Chat.Multimodal",
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'invokedSkillsRequestData': {
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'enableFaceBlur': True
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},
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'convoData': {
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'convoid': "",
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'convotone': tone
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}
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}
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}
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def prepare_headers(session: ClientSession) -> dict:
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"""
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Prepares the headers for the image upload request.
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Args:
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session (ClientSession): The active session.
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boundary (str): The boundary string for the multipart/form-data.
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Returns:
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dict: The headers for the request.
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"""
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headers = session.headers.copy()
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headers["Referer"] = 'https://www.bing.com/search?q=Bing+AI&showconv=1&FORM=hpcodx'
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headers["Origin"] = 'https://www.bing.com'
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return headers
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def parse_image_response(response: dict) -> ImageRequest:
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"""
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Parses the response from the image upload.
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Args:
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response (dict): The response dictionary.
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Raises:
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RuntimeError: If parsing the image info fails.
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Returns:
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ImageRequest: The parsed image response.
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"""
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if not response.get('blobId'):
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raise RuntimeError("Failed to parse image info.")
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result = {'bcid': response.get('blobId', ""), 'blurredBcid': response.get('processedBlobId', "")}
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result["imageUrl"] = f"https://www.bing.com/images/blob?bcid={result['blurredBcid'] or result['bcid']}"
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result['originalImageUrl'] = (
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f"https://www.bing.com/images/blob?bcid={result['blurredBcid']}"
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if IMAGE_CONFIG["enableFaceBlurDebug"] else
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f"https://www.bing.com/images/blob?bcid={result['bcid']}"
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)
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return ImageRequest(result) |