cleanup

app_dialogue.py

@@ -66,7 +66,6 @@ BAN_TOKENS = (  # For documentation puporse. We are not using this list, it is h
 EOS_STRINGS = ["<end_of_utterance>", "\nUser:"]
 STOP_SUSPECT_LIST = []
 
-GRADIO_LINK = "https://huggingfacem4-ai-meme-generator.hf.space"
 API_TOKEN = os.getenv("HF_AUTH_TOKEN")
 IDEFICS_LOGO = "https://huggingface.co/spaces/HuggingFaceM4/idefics_playground/resolve/main/IDEFICS_logo.png"
 
@@ -151,25 +150,6 @@ def choose_gallery(gallery_type: str):
     return image_gallery_list
 
 
-# This is a hack to make pre-computing the default examples work.
-# During normal inference, we pass images as url to a local file using the method `gradio_link`
-# which allows the tgi server to fetch the local image from the frontend server.
-# however, we are building the space (and pre-computing is part of building the space), the frontend is not available
-# and won't answer. So tgi server will try to fetch an image that is not available yet, which will result in a timeout error
-# because tgi will never be able to return the generation.
-# To bypass that, we pass instead the images URLs from the spaces repo.
-DEFAULT_IMAGES_TMP_PATH_TO_URL = {}
-for image_dir in os.listdir("example_images"):
-    for im_path in os.listdir(f"example_images/{image_dir}"):
-        H = gr.Image(
-            f"example_images/{image_dir}/{im_path}", visible=False, type="filepath"
-        )
-        tmp_filename = H.preprocess(H.value)
-        DEFAULT_IMAGES_TMP_PATH_TO_URL[
-            tmp_filename
-        ] = f"https://huggingface.co/spaces/HuggingFaceM4/AI_Meme_Generator/resolve/main/example_images/{image_dir}/{im_path}"
-
-
 # Utils to handle the image markdown display logic
 def split_str_on_im_markdown(string: str) -> List[str]:
     """
@@ -286,12 +266,7 @@ def handle_manual_images_in_user_prompt(user_prompt: str) -> List[str]:
         return [user_prompt]
 
 
-def gradio_link(img_path: str) -> str:
-    url = f"{GRADIO_LINK}/file={img_path}"
-    return url
-
-
-def prompt_list_to_markdown(prompt_list: List[str], size: int = None) -> str:
+def prompt_list_to_markdown(prompt_list: List[str]) -> str:
     """
     Convert a user prompt in the list format (i.e. elements are either a PIL image or a string) into
     the markdown format that is used for the chatbot history and rendering.
@@ -300,15 +275,9 @@ def prompt_list_to_markdown(prompt_list: List[str], size: int = None) -> str:
     for elem in prompt_list:
         if is_image(elem):
             if is_url(elem):
-                if size is not None:
-                    resulting_string += f"<img src={elem} width={size} height={size}>"
-                else:
-                    resulting_string += f"![]({elem})"
+                resulting_string += f"![]({elem})"
             else:
-                if size is not None:
-                    resulting_string += f"<img src='/file={str(elem)}' width='{size}' height={str(size)}>"
-                else:
-                    resulting_string += f"![](/file={elem})"
+                resulting_string += f"![](/file={elem})"
         else:
             resulting_string += elem
     return resulting_string
@@ -346,9 +315,6 @@ def remove_spaces_around_token(text: str) -> str:
 
 
 # Chatbot utils
-Radio_options_to_font = {}
-
-
 def insert_backslash(string, max_length=50):
     # Check if the string length is less than or equal to the max_length
     if len(string) <= max_length: