urchade commited on
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d4fe7c0
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1 Parent(s): e17c9d4

Update app.py

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Files changed (1) hide show
  1. app.py +6 -3
app.py CHANGED
@@ -8,6 +8,7 @@ import os
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  hf_token = os.getenv("HF_TOKEN")
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  login(hf_token)
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  model = GLiNER2.from_pretrained("fastino/gliner2-base-0207")
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  def run_ner(text, types_csv, descs):
@@ -82,6 +83,8 @@ header.brand .subtitle {
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  border-radius: 0.75rem;
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  box-shadow: 0 4px 10px rgba(0,0,0,0.05);
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  margin-bottom: 1.5rem;
 
 
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  }
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  .gr-button.primary {
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  background: var(--primary) !important;
@@ -105,7 +108,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple", secondary_hue="blue"),
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  with gr.Tabs():
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  # NER Tab
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  with gr.TabItem("πŸ” Named Entity Recognition"):
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- with gr.Row(elem_classes="card", gap="small"):
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  with gr.Column(scale=2):
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  txt1 = gr.Textbox(label="Input Text", lines=5, placeholder="Enter text to extract entities...")
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  types1 = gr.Textbox(label="Entity Types (CSV)", value="person, organization, location, date, title, topic")
@@ -118,7 +121,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple", secondary_hue="blue"),
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  # Classification Tab
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  with gr.TabItem("πŸ“ Text Classification"):
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- with gr.Row(elem_classes="card", gap="small"):
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  with gr.Column(scale=2):
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  txt2 = gr.Textbox(label="Input Text", lines=5, placeholder="Enter text to classify...")
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  task2 = gr.Textbox(label="Task Name", value="sentiment_analysis")
@@ -133,7 +136,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple", secondary_hue="blue"),
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  # Structure Extraction Tab
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  with gr.TabItem("πŸ“ Structure Extraction"):
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- with gr.Row(elem_classes="card", gap="small"):
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  with gr.Column(scale=2):
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  txt3 = gr.Textbox(label="Input Text", lines=5, placeholder="Enter text for structure extraction...")
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  struct3 = gr.Code(language="json", label="Schema (JSON)", lines=8, value=json.dumps({
 
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  hf_token = os.getenv("HF_TOKEN")
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  login(hf_token)
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+ # Load model once
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  model = GLiNER2.from_pretrained("fastino/gliner2-base-0207")
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  def run_ner(text, types_csv, descs):
 
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  border-radius: 0.75rem;
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  box-shadow: 0 4px 10px rgba(0,0,0,0.05);
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  margin-bottom: 1.5rem;
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+ display: grid;
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+ grid-gap: 1rem;
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  }
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  .gr-button.primary {
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  background: var(--primary) !important;
 
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  with gr.Tabs():
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  # NER Tab
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  with gr.TabItem("πŸ” Named Entity Recognition"):
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+ with gr.Row(elem_classes="card"):
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  with gr.Column(scale=2):
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  txt1 = gr.Textbox(label="Input Text", lines=5, placeholder="Enter text to extract entities...")
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  types1 = gr.Textbox(label="Entity Types (CSV)", value="person, organization, location, date, title, topic")
 
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  # Classification Tab
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  with gr.TabItem("πŸ“ Text Classification"):
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+ with gr.Row(elem_classes="card"):
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  with gr.Column(scale=2):
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  txt2 = gr.Textbox(label="Input Text", lines=5, placeholder="Enter text to classify...")
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  task2 = gr.Textbox(label="Task Name", value="sentiment_analysis")
 
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  # Structure Extraction Tab
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  with gr.TabItem("πŸ“ Structure Extraction"):
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+ with gr.Row(elem_classes="card"):
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  with gr.Column(scale=2):
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  txt3 = gr.Textbox(label="Input Text", lines=5, placeholder="Enter text for structure extraction...")
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  struct3 = gr.Code(language="json", label="Schema (JSON)", lines=8, value=json.dumps({