Update app.py
Browse files
app.py
CHANGED
@@ -32,8 +32,9 @@ def process_input(text_input, labels_or_premise, mode):
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results = {label: score for label, score in zip(prediction['labels'], prediction['scores'])}
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return results, ''
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else: # NLI mode
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pred
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results
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return results, ''
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def update_interface(mode):
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@@ -41,17 +42,19 @@ def update_interface(mode):
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return (
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gr.update(
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label="π·οΈ Categories",
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placeholder="Enter comma-separated categories..."
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),
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gr.update()
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)
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else:
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return (
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gr.update(
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label="π Hypothesis",
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placeholder="Enter a hypothesis to compare with the premise..."
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),
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gr.update()
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)
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with gr.Blocks() as demo:
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@@ -75,14 +78,14 @@ with gr.Blocks() as demo:
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label="βοΈ Input Text",
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placeholder="Enter your text...",
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lines=3,
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value=zero_shot_examples[0][0]
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)
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labels_or_premise = gr.Textbox(
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label="π·οΈ Categories",
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placeholder="Enter comma-separated categories...",
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lines=2,
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value=zero_shot_examples[0][1]
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)
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submit_btn = gr.Button("Submit")
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@@ -92,15 +95,11 @@ with gr.Blocks() as demo:
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gr.Markdown(label="π Analysis", visible=False)
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]
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# Create a dummy textbox to trigger updates when examples are selected
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example_trigger = gr.Textbox(visible=False)
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-
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with gr.Column(variant="panel") as zero_shot_examples_panel:
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gr.Examples(
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examples=zero_shot_examples,
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inputs=[text_input, labels_or_premise],
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label="Zero-Shot Classification Examples",
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outputs=example_trigger
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)
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with gr.Column(variant="panel") as nli_examples_panel:
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@@ -108,8 +107,7 @@ with gr.Blocks() as demo:
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examples=nli_examples,
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inputs=[text_input, labels_or_premise],
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label="Natural Language Inference Examples",
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-
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)
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def update_visibility(mode):
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return (
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@@ -117,7 +115,6 @@ with gr.Blocks() as demo:
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gr.update(visible=(mode == "Natural Language Inference"))
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)
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# Update interface on mode change
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mode.change(
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fn=update_interface,
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inputs=[mode],
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@@ -130,13 +127,6 @@ with gr.Blocks() as demo:
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outputs=[zero_shot_examples_panel, nli_examples_panel]
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)
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# Update the label whenever an example is selected
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example_trigger.change(
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fn=update_interface,
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inputs=[mode],
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outputs=[labels_or_premise, text_input]
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)
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-
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submit_btn.click(
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fn=process_input,
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inputs=[text_input, labels_or_premise, mode],
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results = {label: score for label, score in zip(prediction['labels'], prediction['scores'])}
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return results, ''
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else: # NLI mode
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pred= nli_classifier([{"text": text_input, "text_pair": labels_or_premise}],return_all_scores=True)[0]
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results= {pred['label']:pred['score'] for pred in pred}
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+
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return results, ''
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def update_interface(mode):
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return (
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gr.update(
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label="π·οΈ Categories",
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placeholder="Enter comma-separated categories...",
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value=zero_shot_examples[0][1]
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),
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gr.update(value=zero_shot_examples[0][0])
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)
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else:
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return (
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gr.update(
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label="π Hypothesis",
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placeholder="Enter a hypothesis to compare with the premise...",
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value=nli_examples[0][1]
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),
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gr.update(value=nli_examples[0][0])
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)
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with gr.Blocks() as demo:
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label="βοΈ Input Text",
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placeholder="Enter your text...",
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lines=3,
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value=zero_shot_examples[0][0] # Initial value
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)
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labels_or_premise = gr.Textbox(
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label="π·οΈ Categories",
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placeholder="Enter comma-separated categories...",
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lines=2,
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value=zero_shot_examples[0][1] # Initial value
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)
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submit_btn = gr.Button("Submit")
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gr.Markdown(label="π Analysis", visible=False)
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]
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with gr.Column(variant="panel") as zero_shot_examples_panel:
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gr.Examples(
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examples=zero_shot_examples,
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inputs=[text_input, labels_or_premise],
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label="Zero-Shot Classification Examples",
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)
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with gr.Column(variant="panel") as nli_examples_panel:
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examples=nli_examples,
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inputs=[text_input, labels_or_premise],
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label="Natural Language Inference Examples",
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+
)
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def update_visibility(mode):
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return (
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gr.update(visible=(mode == "Natural Language Inference"))
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)
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mode.change(
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fn=update_interface,
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inputs=[mode],
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outputs=[zero_shot_examples_panel, nli_examples_panel]
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)
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submit_btn.click(
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fn=process_input,
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inputs=[text_input, labels_or_premise, mode],
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