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Update app.py
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app.py
CHANGED
@@ -11,7 +11,7 @@ from transformers import pipeline
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from datasets import load_dataset
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import fitz # PyMuPDF
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#
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dataset = load_dataset("ibunescu/qa_legal_dataset_train")
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# Different pipelines for different tasks
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@@ -82,7 +82,7 @@ def determine_winner(outcome):
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else:
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return "No clear winner"
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# Custom CSS for
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custom_css = """
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body {
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background-color: #ffffff;
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@@ -194,8 +194,8 @@ def update_pdf_gallery_and_extract_text(pdf_files):
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return pdf_files, pdf_text
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def get_top_10_cases():
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return
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def add_message(history, message):
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for x in message["files"]:
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@@ -215,7 +215,7 @@ def bot(history):
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response = ""
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for message in client.chat_completion(
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messages,
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max_tokens=
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stream=True,
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temperature=0.6,
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top_p=0.95,
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@@ -250,8 +250,8 @@ with gr.Blocks(css=custom_css) as demo:
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with gr.Tab("Argument Evaluation"):
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with gr.Row():
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with gr.Column(scale=1):
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top_10_btn = gr.Button("Give me
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top_10_output = gr.Textbox(label="
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top_10_btn.click(get_top_10_cases, outputs=top_10_output)
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with gr.Column(scale=2):
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message = gr.Textbox(label="Case to Argue")
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from datasets import load_dataset
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import fitz # PyMuPDF
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# Load dataset
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dataset = load_dataset("ibunescu/qa_legal_dataset_train")
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# Different pipelines for different tasks
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else:
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return "No clear winner"
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# Custom CSS for a clean layout
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custom_css = """
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body {
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background-color: #ffffff;
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return pdf_files, pdf_text
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def get_top_10_cases():
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summary = summarization_pipeline("Show 10 legal cases with names and numbers from any State Court of Appeals in the US.", max_length=150, min_length=50, do_sample=False)
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return summary[0]['summary_text']
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def add_message(history, message):
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for x in message["files"]:
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response = ""
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for message in client.chat_completion(
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messages,
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max_tokens=150,
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stream=True,
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temperature=0.6,
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top_p=0.95,
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with gr.Tab("Argument Evaluation"):
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with gr.Row():
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with gr.Column(scale=1):
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top_10_btn = gr.Button("Give me the top 10 cases")
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top_10_output = gr.Textbox(label="Top 10 Cases", interactive=False, elem_classes=["scroll-box"])
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top_10_btn.click(get_top_10_cases, outputs=top_10_output)
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with gr.Column(scale=2):
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message = gr.Textbox(label="Case to Argue")
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