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authorHeiner Lohaus <hlohaus@users.noreply.github.com>2024-01-14 07:45:41 +0100
committerHeiner Lohaus <hlohaus@users.noreply.github.com>2024-01-14 07:45:41 +0100
commit5756586cde6ed6da147119113fb5a5fd640d5f83 (patch)
tree64a9612c8c32e3c7eb4cdeb6f4ad63a08e5706b0 /g4f/Provider/bing/upload_image.py
parentFix process_image in Bing (diff)
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Diffstat (limited to 'g4f/Provider/bing/upload_image.py')
-rw-r--r--g4f/Provider/bing/upload_image.py188
1 files changed, 128 insertions, 60 deletions
diff --git a/g4f/Provider/bing/upload_image.py b/g4f/Provider/bing/upload_image.py
index 1af902ef..4d70659f 100644
--- a/g4f/Provider/bing/upload_image.py
+++ b/g4f/Provider/bing/upload_image.py
@@ -1,64 +1,107 @@
-from __future__ import annotations
+"""
+Module to handle image uploading and processing for Bing AI integrations.
+"""
+from __future__ import annotations
import string
import random
import json
import math
-from ...typing import ImageType
from aiohttp import ClientSession
+from PIL import Image
+
+from ...typing import ImageType, Tuple
from ...image import to_image, process_image, to_base64, ImageResponse
-image_config = {
+IMAGE_CONFIG = {
"maxImagePixels": 360000,
"imageCompressionRate": 0.7,
- "enableFaceBlurDebug": 0,
+ "enableFaceBlurDebug": False,
}
async def upload_image(
- session: ClientSession,
- image: ImageType,
- tone: str,
+ session: ClientSession,
+ image_data: ImageType,
+ tone: str,
proxy: str = None
) -> ImageResponse:
- image = to_image(image)
- width, height = image.size
- max_image_pixels = image_config['maxImagePixels']
- if max_image_pixels / (width * height) < 1:
- new_width = int(width * math.sqrt(max_image_pixels / (width * height)))
- new_height = int(height * math.sqrt(max_image_pixels / (width * height)))
- else:
- new_width = width
- new_height = height
- new_img = process_image(image, new_width, new_height)
- new_img_binary_data = to_base64(new_img, image_config['imageCompressionRate'])
- data, boundary = build_image_upload_api_payload(new_img_binary_data, tone)
- headers = session.headers.copy()
- headers["content-type"] = f'multipart/form-data; boundary={boundary}'
- headers["referer"] = 'https://www.bing.com/search?q=Bing+AI&showconv=1&FORM=hpcodx'
- headers["origin"] = 'https://www.bing.com'
+ """
+ Uploads an image to Bing's AI service and returns the image response.
+
+ Args:
+ session (ClientSession): The active session.
+ image_data (bytes): The image data to be uploaded.
+ tone (str): The tone of the conversation.
+ proxy (str, optional): Proxy if any. Defaults to None.
+
+ Raises:
+ RuntimeError: If the image upload fails.
+
+ Returns:
+ ImageResponse: The response from the image upload.
+ """
+ image = to_image(image_data)
+ new_width, new_height = calculate_new_dimensions(image)
+ processed_img = process_image(image, new_width, new_height)
+ img_binary_data = to_base64(processed_img, IMAGE_CONFIG['imageCompressionRate'])
+
+ data, boundary = build_image_upload_payload(img_binary_data, tone)
+ headers = prepare_headers(session, boundary)
+
async with session.post("https://www.bing.com/images/kblob", data=data, headers=headers, proxy=proxy) as response:
if response.status != 200:
raise RuntimeError("Failed to upload image.")
- image_info = await response.json()
- if not image_info.get('blobId'):
- raise RuntimeError("Failed to parse image info.")
- result = {'bcid': image_info.get('blobId', "")}
- result['blurredBcid'] = image_info.get('processedBlobId', "")
- if result['blurredBcid'] != "":
- result["imageUrl"] = "https://www.bing.com/images/blob?bcid=" + result['blurredBcid']
- elif result['bcid'] != "":
- result["imageUrl"] = "https://www.bing.com/images/blob?bcid=" + result['bcid']
- result['originalImageUrl'] = (
- "https://www.bing.com/images/blob?bcid="
- + result['blurredBcid']
- if image_config["enableFaceBlurDebug"]
- else "https://www.bing.com/images/blob?bcid="
- + result['bcid']
- )
- return ImageResponse(result["imageUrl"], "", result)
-
-def build_image_upload_api_payload(image_bin: str, tone: str):
- payload = {
+ return parse_image_response(await response.json())
+
+def calculate_new_dimensions(image: Image.Image) -> Tuple[int, int]:
+ """
+ Calculates the new dimensions for the image based on the maximum allowed pixels.
+
+ Args:
+ image (Image): The PIL Image object.
+
+ Returns:
+ Tuple[int, int]: The new width and height for the image.
+ """
+ width, height = image.size
+ max_image_pixels = IMAGE_CONFIG['maxImagePixels']
+ if max_image_pixels / (width * height) < 1:
+ scale_factor = math.sqrt(max_image_pixels / (width * height))
+ return int(width * scale_factor), int(height * scale_factor)
+ return width, height
+
+def build_image_upload_payload(image_bin: str, tone: str) -> Tuple[str, str]:
+ """
+ Builds the payload for image uploading.
+
+ Args:
+ image_bin (str): Base64 encoded image binary data.
+ tone (str): The tone of the conversation.
+
+ Returns:
+ Tuple[str, str]: The data and boundary for the payload.
+ """
+ boundary = "----WebKitFormBoundary" + ''.join(random.choices(string.ascii_letters + string.digits, k=16))
+ data = f"--{boundary}\r\n" \
+ f"Content-Disposition: form-data; name=\"knowledgeRequest\"\r\n\r\n" \
+ f"{json.dumps(build_knowledge_request(tone), ensure_ascii=False)}\r\n" \
+ f"--{boundary}\r\n" \
+ f"Content-Disposition: form-data; name=\"imageBase64\"\r\n\r\n" \
+ f"{image_bin}\r\n" \
+ f"--{boundary}--\r\n"
+ return data, boundary
+
+def build_knowledge_request(tone: str) -> dict:
+ """
+ Builds the knowledge request payload.
+
+ Args:
+ tone (str): The tone of the conversation.
+
+ Returns:
+ dict: The knowledge request payload.
+ """
+ return {
'invokedSkills': ["ImageById"],
'subscriptionId': "Bing.Chat.Multimodal",
'invokedSkillsRequestData': {
@@ -69,21 +112,46 @@ def build_image_upload_api_payload(image_bin: str, tone: str):
'convotone': tone
}
}
- knowledge_request = {
- 'imageInfo': {},
- 'knowledgeRequest': payload
- }
- boundary="----WebKitFormBoundary" + ''.join(random.choices(string.ascii_letters + string.digits, k=16))
- data = (
- f'--{boundary}'
- + '\r\nContent-Disposition: form-data; name="knowledgeRequest"\r\n\r\n'
- + json.dumps(knowledge_request, ensure_ascii=False)
- + "\r\n--"
- + boundary
- + '\r\nContent-Disposition: form-data; name="imageBase64"\r\n\r\n'
- + image_bin
- + "\r\n--"
- + boundary
- + "--\r\n"
+
+def prepare_headers(session: ClientSession, boundary: str) -> dict:
+ """
+ Prepares the headers for the image upload request.
+
+ Args:
+ session (ClientSession): The active session.
+ boundary (str): The boundary string for the multipart/form-data.
+
+ Returns:
+ dict: The headers for the request.
+ """
+ headers = session.headers.copy()
+ headers["Content-Type"] = f'multipart/form-data; boundary={boundary}'
+ headers["Referer"] = 'https://www.bing.com/search?q=Bing+AI&showconv=1&FORM=hpcodx'
+ headers["Origin"] = 'https://www.bing.com'
+ return headers
+
+def parse_image_response(response: dict) -> ImageResponse:
+ """
+ Parses the response from the image upload.
+
+ Args:
+ response (dict): The response dictionary.
+
+ Raises:
+ RuntimeError: If parsing the image info fails.
+
+ Returns:
+ ImageResponse: The parsed image response.
+ """
+ if not response.get('blobId'):
+ raise RuntimeError("Failed to parse image info.")
+
+ result = {'bcid': response.get('blobId', ""), 'blurredBcid': response.get('processedBlobId', "")}
+ result["imageUrl"] = f"https://www.bing.com/images/blob?bcid={result['blurredBcid'] or result['bcid']}"
+
+ result['originalImageUrl'] = (
+ f"https://www.bing.com/images/blob?bcid={result['blurredBcid']}"
+ if IMAGE_CONFIG["enableFaceBlurDebug"] else
+ f"https://www.bing.com/images/blob?bcid={result['bcid']}"
)
- return data, boundary \ No newline at end of file
+ return ImageResponse(result["imageUrl"], "", result) \ No newline at end of file