Updated the API client to support RapidAPI, small tweaks and fixes
Browse files- app.py +23 -8
- docs/API.md +2 -2
- try_on_diffusion_client.py +18 -7
app.py
CHANGED
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@@ -16,6 +16,8 @@ EXAMPLE_PATH = os.path.join(os.path.dirname(__file__), "examples")
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API_URL = os.getenv("TRY_ON_DIFFUSION_DEMO_API_URL", "http://localhost:8000")
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API_KEY = os.getenv("TRY_ON_DIFFUSION_DEMO_API_KEY", "")
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CONCURRENCY_LIMIT = int(os.getenv("TRY_ON_DIFFUSION_DEMO_CONCURRENCY_LIMIT", "2"))
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logging.basicConfig(level=LOG_LEVEL, format=LOG_FORMAT, datefmt=LOG_DATE_FORMAT)
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@@ -68,7 +70,7 @@ def try_on(
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)
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if result.status_code == 200:
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return cv2.cvtColor(result.image, cv2.
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else:
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error_message = f"<h3>Error {result.status_code}</h3>"
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@@ -78,7 +80,7 @@ def try_on(
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return None, error_message
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with gr.Blocks(theme=gr.themes.Soft()) as app:
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gr.HTML(
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f"""
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<div style="width: 100%; background-color: #001537; border-radius: 10px; padding-left: 10px">
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@@ -93,13 +95,26 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
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custom diffusion-based pipeline for fast and flexible multi-modal virtual try-on.
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Clothing, avatar and background can be specified by reference images or text prompts allowing for clothing
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transfer, avatar replacement, fashion image generation and other virtual try-on related tasks.
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Feel free to <a href="https://texelmoda.com/contact/" target="_blank">contact us</a> if you are interested
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in commercial API usage or partnership.
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</p>
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<br/>
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"""
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)
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with gr.Row():
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with gr.Column():
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gr.HTML(
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@@ -247,9 +262,9 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
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info="Seed used for generation, specify -1 for random seed for each generation.",
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)
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generate_button = gr.Button(value="Generate",
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result_image = gr.Image(label="Result", show_share_button=False)
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result_details = gr.HTML(label="Details")
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generate_button.click(
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API_URL = os.getenv("TRY_ON_DIFFUSION_DEMO_API_URL", "http://localhost:8000")
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API_KEY = os.getenv("TRY_ON_DIFFUSION_DEMO_API_KEY", "")
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SHOW_RAPIDAPI_LINK = os.getenv("TRY_ON_DIFFUSION_DEMO_SHOW_RAPIDAPI_LINK", "1") == "1"
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CONCURRENCY_LIMIT = int(os.getenv("TRY_ON_DIFFUSION_DEMO_CONCURRENCY_LIMIT", "2"))
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logging.basicConfig(level=LOG_LEVEL, format=LOG_FORMAT, datefmt=LOG_DATE_FORMAT)
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)
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if result.status_code == 200:
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return cv2.cvtColor(result.image, cv2.COLOR_BGR2RGB), f"<h3>Success</h3><p>Seed: {result.seed}</p>"
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else:
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error_message = f"<h3>Error {result.status_code}</h3>"
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return None, error_message
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with gr.Blocks(theme=gr.themes.Soft(), delete_cache=(3600, 3600)) as app:
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gr.HTML(
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f"""
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<div style="width: 100%; background-color: #001537; border-radius: 10px; padding-left: 10px">
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custom diffusion-based pipeline for fast and flexible multi-modal virtual try-on.
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Clothing, avatar and background can be specified by reference images or text prompts allowing for clothing
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transfer, avatar replacement, fashion image generation and other virtual try-on related tasks.
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"""
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)
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if SHOW_RAPIDAPI_LINK:
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gr.Button(
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value="Check out the API @ RapidAPI.com",
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link="https://rapidapi.com/texelmoda-texelmoda-apis/api/try-on-diffusion",
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icon="https://files.readme.io/9336831-small-rapid-logo-favicon.png",
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)
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gr.HTML(
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"""
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<center>
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<a href="https://huggingface.co/spaces/texelmoda/try-on-diffusion/blob/main/docs/API.md">API Documentation</a>
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</center>
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"""
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)
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gr.HTML("</p>")
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with gr.Row():
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with gr.Column():
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gr.HTML(
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info="Seed used for generation, specify -1 for random seed for each generation.",
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)
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generate_button = gr.Button(value="Generate", variant="primary")
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result_image = gr.Image(label="Result", show_share_button=False, format="jpeg")
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result_details = gr.HTML(label="Details")
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generate_button.click(
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docs/API.md
CHANGED
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@@ -33,7 +33,7 @@
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Virtual Try-On Diffusion [VTON-D] by [Texel.Moda](https://texelmoda.com) is a custom diffusion-based pipeline for fast
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and flexible multi-modal virtual try-on. Clothing, avatar and background can be specified by reference images or text
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prompts allowing for clothing transfer, avatar replacement, fashion image generation and other virtual try-on related
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-
tasks. Check out the [demo on
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a user-friendly way.
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## Consuming the API
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@@ -60,7 +60,7 @@ curl --request POST \
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```
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For a simple Python client implementation please see the
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[
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## Try-On Endpoints
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Virtual Try-On Diffusion [VTON-D] by [Texel.Moda](https://texelmoda.com) is a custom diffusion-based pipeline for fast
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and flexible multi-modal virtual try-on. Clothing, avatar and background can be specified by reference images or text
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prompts allowing for clothing transfer, avatar replacement, fashion image generation and other virtual try-on related
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tasks. Check out the [demo on Hugging Face](https://huggingface.co/spaces/texelmoda/try-on-diffusion) to try the API in
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a user-friendly way.
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## Consuming the API
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```
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For a simple Python client implementation please see the
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[Hugging Face demo application source](https://huggingface.co/spaces/texelmoda/try-on-diffusion/blob/main/try_on_diffusion_client.py).
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## Try-On Endpoints
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try_on_diffusion_client.py
CHANGED
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@@ -2,6 +2,7 @@ import cv2
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import numpy as np
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import requests
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from requests_toolbelt.multipart.encoder import MultipartEncoder
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import logging
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import json
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from io import BytesIO
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@@ -26,6 +27,13 @@ class TryOnDiffusionClient:
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if self._base_url[-1] == "/":
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self._base_url = self._base_url[:-1]
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@staticmethod
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def _image_to_upload_file(image: np.ndarray) -> tuple:
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_, jpeg_data = cv2.imencode(".jpg", image, [int(cv2.IMWRITE_JPEG_QUALITY), 99])
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@@ -44,14 +52,12 @@ class TryOnDiffusionClient:
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avatar_sex: str = None,
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background_image: np.ndarray = None,
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background_prompt: str = None,
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negative_prompt: str = None,
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num_images: int = 1,
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seed: int = -1,
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raw_response: bool = False,
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) -> TryOnDiffusionAPIResponse:
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url = self._base_url + "/try-on-file"
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request_data = {"
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if clothing_image is not None:
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request_data["clothing_image"] = self._image_to_upload_file(clothing_image)
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@@ -74,16 +80,21 @@ class TryOnDiffusionClient:
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if background_prompt is not None:
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request_data["background_prompt"] = background_prompt
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if negative_prompt is not None:
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request_data["negative_prompt"] = negative_prompt
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multipart_data = MultipartEncoder(fields=request_data)
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try:
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response = requests.post(
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url,
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data=multipart_data,
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headers=
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)
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except Exception as e:
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self._logger.error(e, exc_info=True)
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import numpy as np
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import requests
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from requests_toolbelt.multipart.encoder import MultipartEncoder
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from urllib.parse import urlparse
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import logging
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import json
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from io import BytesIO
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if self._base_url[-1] == "/":
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self._base_url = self._base_url[:-1]
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parsed_url = urlparse(self._base_url)
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self._rapidapi_host = parsed_url.netloc if parsed_url.netloc.endswith(".rapidapi.com") else None
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if self._rapidapi_host is not None:
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self._logger.info(f"Using RapidAPI proxy: {self._rapidapi_host}")
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@staticmethod
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def _image_to_upload_file(image: np.ndarray) -> tuple:
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_, jpeg_data = cv2.imencode(".jpg", image, [int(cv2.IMWRITE_JPEG_QUALITY), 99])
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avatar_sex: str = None,
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background_image: np.ndarray = None,
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background_prompt: str = None,
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seed: int = -1,
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raw_response: bool = False,
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) -> TryOnDiffusionAPIResponse:
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url = self._base_url + "/try-on-file"
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request_data = {"seed": str(seed)}
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if clothing_image is not None:
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request_data["clothing_image"] = self._image_to_upload_file(clothing_image)
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if background_prompt is not None:
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request_data["background_prompt"] = background_prompt
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multipart_data = MultipartEncoder(fields=request_data)
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headers = {"Content-Type": multipart_data.content_type}
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if self._rapidapi_host is not None:
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headers["X-RapidAPI-Key"] = self._api_key
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headers["X-RapidAPI-Host"] = self._rapidapi_host
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else:
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headers["X-API-Key"] = self._api_key
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try:
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response = requests.post(
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url,
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data=multipart_data,
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headers=headers,
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)
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except Exception as e:
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self._logger.error(e, exc_info=True)
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