Iker commited on
Commit
30b1c42
1 Parent(s): 8a22027
Files changed (1) hide show
  1. app.py +36 -1
app.py CHANGED
@@ -4,6 +4,8 @@ import gradio as gr
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  from download_url import download_text_and_title
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  from cache_system import CacheHandler
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  from gradio_client import Client
 
 
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  print(f"CPU cores: {os.cpu_count()}.")
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@@ -13,6 +15,36 @@ auth_token = os.environ.get("TOKEN") or True
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  client = Client(server)
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  def finish_generation(text: str) -> str:
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  return f"{text}\n\n⬇️ Ayuda a mejorar la herramienta marcando si el resumen es correcto o no.⬇️"
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@@ -86,7 +118,10 @@ def generate_text(
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  cache_handler = CacheHandler(max_cache_size=1000)
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- hf_writer = gr.HuggingFaceDatasetSaver(auth_token, "Iker/Clickbait-News")
 
 
 
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  demo = gr.Interface(
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  generate_text,
 
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  from download_url import download_text_and_title
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  from cache_system import CacheHandler
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  from gradio_client import Client
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+ from collections import OrderedDict
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+ from typing import Any
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  print(f"CPU cores: {os.cpu_count()}.")
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  client = Client(server)
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+ class HuggingFaceDatasetSaver_custom(gr.HuggingFaceDatasetSaver):
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+ def _deserialize_components(
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+ self,
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+ data_dir,
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+ flag_data: list[Any],
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+ flag_option: str = "",
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+ username: str = "",
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+ ) -> tuple[dict[Any, Any], list[Any]]:
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+ """Deserialize components and return the corresponding row for the flagged sample.
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+
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+ Images/audio are saved to disk as individual files.
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+ """
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+ # Components that can have a preview on dataset repos
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+ file_preview_types = {gr.Audio: "Audio", gr.Image: "Image"}
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+
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+ # Generate the row corresponding to the flagged sample
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+ features = OrderedDict()
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+ row = []
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+ for component, sample in zip(self.components, flag_data):
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+ label = component.label or ""
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+ features[label] = {"dtype": "string", "_type": "Value"}
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+ row.append(sample)
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+
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+ features["flag"] = {"dtype": "string", "_type": "Value"}
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+ features["username"] = {"dtype": "string", "_type": "Value"}
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+ row.append(flag_option)
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+ row.append(username)
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+ return features, row
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+
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+
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  def finish_generation(text: str) -> str:
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  return f"{text}\n\n⬇️ Ayuda a mejorar la herramienta marcando si el resumen es correcto o no.⬇️"
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  cache_handler = CacheHandler(max_cache_size=1000)
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+ hf_writer = HuggingFaceDatasetSaver_custom(
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+ auth_token, "Iker/Clickbait-News", private=True, separate_dirs=False
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+ )
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+
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  demo = gr.Interface(
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  generate_text,