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Update app.py
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app.py
CHANGED
@@ -9,27 +9,25 @@ import gradio as gr
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from huggingface_hub import InferenceClient
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from transformers import pipeline
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from datasets import load_dataset
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import time
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import fitz # PyMuPDF
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def score_argument_from_outcome(outcome, argument):
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if "Prosecutor" in outcome:
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prosecutor_score = outcome.count("Prosecutor") * 2
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if "won" in outcome and "Prosecutor" in outcome:
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def chat_between_bots(system_message1, system_message2, max_tokens, temperature, top_p, history1, history2, shared_history, message):
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response1, history1 = list(respond(message, history1, system_message1, max_tokens, temperature, top_p))[-1]
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response2, history2 = list(respond(message, history2, system_message2, max_tokens, temperature, top_p))[-1]
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return response1, response2, history1, history2, shared_history
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def extract_text_from_pdf(pdf_file):
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text = ""
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@@ -62,8 +60,8 @@ def update_pdf_gallery_and_extract_text(pdf_files):
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return pdf_files, pdf_text
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def add_message(history, message):
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return history, gr.
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def bot(history):
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system_message = "You are a helpful assistant."
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@@ -96,6 +94,13 @@ def reset_conversation():
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def save_conversation(history1, history2, shared_history):
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return history1, history2, shared_history
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with gr.Blocks(css=custom_css) as demo:
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history1 = gr.State([])
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history2 = gr.State([])
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@@ -105,8 +110,18 @@ with gr.Blocks(css=custom_css) as demo:
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with gr.Tab("Argument Evaluation"):
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message = gr.Textbox(label="Case to Argue")
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shared_argument = gr.Textbox(label="Case Outcome", interactive=True)
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submit_btn = gr.Button("Argue")
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clear_btn = gr.Button("Clear and Reset")
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save_btn = gr.Button("Save Conversation")
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@@ -123,10 +138,12 @@ with gr.Blocks(css=custom_css) as demo:
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pdf_answer = gr.Textbox(label="Answer", interactive=False, elem_classes=["scroll-box"])
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pdf_upload_btn = gr.Button("Update PDF Gallery")
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pdf_ask_btn = gr.Button("Ask")
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pdf_upload_btn.click(update_pdf_gallery_and_extract_text, inputs=[pdf_upload], outputs=[pdf_gallery, pdf_text])
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pdf_text.change(fn=lambda x: x, inputs=pdf_text, outputs=pdf_view)
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pdf_ask_btn.click(ask_about_pdf, inputs=[pdf_text, pdf_question], outputs=pdf_answer)
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with gr.Tab("Chatbot"):
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chatbot = gr.Chatbot(
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from huggingface_hub import InferenceClient
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from transformers import pipeline
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from datasets import load_dataset
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import fitz # PyMuPDF
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client = InferenceClient()
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dataset = load_dataset("ibunescu/qa_legal_dataset_train")
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def score_argument_from_outcome(outcome, argument):
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prosecutor_score = 0
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if "Prosecutor" in outcome:
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prosecutor_score = outcome.count("Prosecutor") * 2
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if "won" in outcome and "Prosecutor" in outcome:
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prosecutor_score += 10
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return prosecutor_score
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def chat_between_bots(system_message1, system_message2, max_tokens, temperature, top_p, history1, history2, shared_history, message):
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response1, history1 = list(respond(message, history1, system_message1, max_tokens, temperature, top_p))[-1]
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response2, history2 = list(respond(message, history2, system_message2, max_tokens, temperature, top_p))[-1]
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return response1, response2, history1, history2, shared_history
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def extract_text_from_pdf(pdf_file):
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text = ""
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return pdf_files, pdf_text
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def add_message(history, message):
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history.append(message)
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return history, gr.Textbox(value=None, interactive=False)
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def bot(history):
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system_message = "You are a helpful assistant."
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def save_conversation(history1, history2, shared_history):
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return history1, history2, shared_history
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custom_css = """
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.scroll-box {
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max-height: 400px;
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overflow-y: auto;
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}
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"""
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with gr.Blocks(css=custom_css) as demo:
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history1 = gr.State([])
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history2 = gr.State([])
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with gr.Tab("Argument Evaluation"):
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message = gr.Textbox(label="Case to Argue")
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system_message1 = "System message for bot 1"
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system_message2 = "System message for bot 2"
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max_tokens = 150
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temperature = 0.6
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top_p = 0.95
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prosecutor_response = gr.Textbox(label="Prosecutor Response", interactive=False)
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defense_response = gr.Textbox(label="Defense Response", interactive=False)
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prosecutor_score_color = gr.Textbox(label="Prosecutor Score Color", interactive=False)
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defense_score_color = gr.Textbox(label="Defense Score Color", interactive=False)
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shared_argument = gr.Textbox(label="Case Outcome", interactive=True)
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submit_btn = gr.Button("Argue")
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clear_btn = gr.Button("Clear and Reset")
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save_btn = gr.Button("Save Conversation")
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pdf_answer = gr.Textbox(label="Answer", interactive=False, elem_classes=["scroll-box"])
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pdf_upload_btn = gr.Button("Update PDF Gallery")
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pdf_ask_btn = gr.Button("Ask")
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pdf_upload_btn.click(update_pdf_gallery_and_extract_text, inputs=[pdf_upload], outputs=[pdf_gallery, pdf_text])
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pdf_text.change(fn=lambda x: x, inputs=pdf_text, outputs=pdf_view)
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pdf_ask_btn.click(ask_about_pdf, inputs=[pdf_text, pdf_question], outputs=pdf_answer)
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with gr.Tab("Chatbot"):
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chatbot = gr.Chatbot()
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demo.launch()
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