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import gradio as gr |
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from pdf_processor import PDFProcessor |
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from utils import AI_MODELS, TRANSLATIONS |
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class PDFProcessorUI: |
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def __init__(self): |
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self.processor = PDFProcessor() |
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self.current_language = "English" |
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self.current_ai_model = "Huggingface / IBM granite granite 3.1 8b Instruct" |
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self.current_type_model = "Api Key" |
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def change_language(self, language): |
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self.current_language = language |
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self.processor.set_language(language) |
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return [ |
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TRANSLATIONS[language]["title"], |
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gr.update(label=TRANSLATIONS[language]["upload_pdf"]), |
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gr.update(label=TRANSLATIONS[language]["chunk_size"]), |
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gr.update(label=TRANSLATIONS[language]["chunk_overlap"]), |
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gr.update(value=TRANSLATIONS[language]["process_btn"]), |
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gr.update(label=TRANSLATIONS[language]["processing_status"]), |
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gr.update(label=TRANSLATIONS[language]["qa_tab"]), |
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gr.update(label=TRANSLATIONS[language]["summary_tab"]), |
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gr.update(label=TRANSLATIONS[language]["specialist_tab"]), |
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gr.update(label=TRANSLATIONS[language]["mini_summary_title"]), |
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gr.update(label=TRANSLATIONS[language]["mini_analysis_title"]), |
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gr.update(placeholder=TRANSLATIONS[language]["chat_placeholder"]), |
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TRANSLATIONS[language]["chat_title"], |
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gr.update(value=TRANSLATIONS[language]["chat_btn"]), |
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gr.update(value=TRANSLATIONS[language]["generate_summary"]), |
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gr.update(label=TRANSLATIONS[language]["summary_label"]), |
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gr.update(label=TRANSLATIONS[language]["ai_model"]), |
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TRANSLATIONS[language]["specialist_title"], |
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gr.update(label=TRANSLATIONS[language]["specialist_label"]), |
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gr.update(label=TRANSLATIONS[language]["specialist_output"]), |
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gr.update(value=TRANSLATIONS[language]["specialist_btn"]) |
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] |
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def change_ai_model(self, ai_model): |
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self.current_ai_model = ai_model |
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if ai_model == "IBM Granite3.1 dense / Ollama local": |
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return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False, maximum=2048), gr.update(visible=False, maximum=200) |
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elif ai_model == "Open AI / GPT-4o-mini": |
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return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False, maximum=2048), gr.update(visible=False, maximum=200) |
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else: |
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return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False, maximum=500), gr.update(visible=False, maximum=100) |
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def change_type_model(self, type_model): |
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self.current_type_model = type_model |
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if type_model == "Api Key": |
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if self.current_ai_model == "IBM Granite3.1 dense / Ollama local": |
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return gr.update(visible=False), gr.update(visible=False) |
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else: |
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return gr.update(visible=True), gr.update(visible=False) |
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else: |
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return gr.update(visible=False), gr.update(visible=False) |
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def process_pdf(self, pdf_file, chunk_size, chunk_overlap, ai_model, type_model, api_key, project_id_watsonx): |
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return self.processor.process_pdf(pdf_file, chunk_size, chunk_overlap, ai_model, type_model, api_key, project_id_watsonx) |
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def qa_interface(self, message, history, ai_model, type_model, api_key, project_id_watsonx): |
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return self.processor.get_qa_response(message, history, ai_model, type_model, api_key, project_id_watsonx) |
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def summarize_interface(self, ai_model, type_model, api_key, project_id_watsonx): |
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return self.processor.get_summary(ai_model, type_model, api_key, project_id_watsonx) |
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def specialist_opinion(self, ai_model, type_model, api_key, project_id_watsonx, specialist_prompt): |
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return self.processor.get_specialist_opinion(ai_model, type_model, api_key, project_id_watsonx, specialist_prompt) |
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def upload_file(files): |
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file_paths = [file.name for file in files] |
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return file_paths[0] |
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def create_ui(self): |
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with gr.Blocks() as demo: |
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title = gr.Markdown(TRANSLATIONS[self.current_language]["title"]) |
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with gr.Row(): |
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language_dropdown = gr.Dropdown( |
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choices=list(TRANSLATIONS.keys()), |
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value=self.current_language, |
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label="Language/Idioma/Sprache/Langue/Língua", |
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key="language_dropdown" |
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) |
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ai_model_dropdown = gr.Dropdown( |
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choices=list(AI_MODELS.keys()), |
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value=self.current_ai_model, |
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label= TRANSLATIONS[self.current_language]["ai_model"], |
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key="ai_model_dropdown" |
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) |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Row(): |
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pdf_file = gr.File( |
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label=TRANSLATIONS[self.current_language]["upload_pdf"], |
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file_types=[".pdf"] |
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) |
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with gr.Column(): |
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type_model=gr.Radio(choices=["Local", "Api Key"], label=TRANSLATIONS[self.current_language]["model_type"], visible=False, value="Api Key") |
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api_key_input = gr.Textbox(label="Api Key", placeholder=TRANSLATIONS[self.current_language]["api_key_placeholder"], visible=False) |
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project_id_watsonx = gr.Textbox(label="Project ID", placeholder=TRANSLATIONS[self.current_language]["project_id_placeholder"], visible=False) |
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chunk_size = gr.Slider( |
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value=250, |
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label=TRANSLATIONS[self.current_language]["chunk_size"], |
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minimum=100, |
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maximum=500, |
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step=10, |
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visible=False |
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) |
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chunk_overlap = gr.Slider( |
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value=25, |
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label=TRANSLATIONS[self.current_language]["chunk_overlap"], |
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minimum=10, |
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maximum=100, |
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step=5, |
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visible=False |
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) |
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process_btn = gr.Button( |
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TRANSLATIONS[self.current_language]["process_btn"] |
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) |
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process_output = gr.Textbox( |
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label=TRANSLATIONS[self.current_language]["processing_status"] |
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) |
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with gr.Tabs() as tabs: |
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qa_tab = gr.Tab(TRANSLATIONS[self.current_language]["qa_tab"]) |
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summary_tab = gr.Tab(TRANSLATIONS[self.current_language]["summary_tab"]) |
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specialist_tab = gr.Tab(TRANSLATIONS[self.current_language]["specialist_tab"]) |
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with qa_tab: |
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chat_title = gr.Markdown(TRANSLATIONS[self.current_language]["chat_title"]) |
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chat_placeholder = gr.Textbox( |
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placeholder=TRANSLATIONS[self.current_language]["chat_placeholder"], |
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container=False, |
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show_label=False |
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) |
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chat_btn = gr.Button(TRANSLATIONS[self.current_language]["chat_btn"]) |
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chatbot = gr.Markdown(height=400) |
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with summary_tab: |
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with gr.Accordion(TRANSLATIONS[self.current_language]["mini_analysis_title"], open=False, visible=False): |
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minisummaries_output = gr.Textbox( |
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label=TRANSLATIONS[self.current_language]["mini_analysis_title"], |
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lines=10 |
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) |
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summary_output = gr.Textbox( |
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label=TRANSLATIONS[self.current_language]["summary_label"], |
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lines=10 |
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) |
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summarize_btn = gr.Button( |
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TRANSLATIONS[self.current_language]["generate_summary"] |
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) |
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with specialist_tab: |
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specialist_title = gr.Markdown(TRANSLATIONS[self.current_language]["specialist_title"]) |
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specialist_placeholder = gr.Textbox( |
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label=TRANSLATIONS[self.current_language]["specialist_label"], |
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lines=10 |
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) |
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with gr.Accordion(TRANSLATIONS[self.current_language]["mini_analysis_title"], open=False, visible=False): |
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minianalysis_output = gr.Textbox( |
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label=TRANSLATIONS[self.current_language]["mini_analysis_title"], |
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lines=10 |
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) |
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specialist_output = gr.Textbox(label=TRANSLATIONS[self.current_language]["specialist_output"], lines=20) |
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specialist_btn = gr.Button(TRANSLATIONS[self.current_language]["specialist_btn"]) |
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language_dropdown.change( |
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fn=self.change_language, |
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inputs=[language_dropdown], |
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outputs=[ |
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title, |
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pdf_file, |
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chunk_size, |
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chunk_overlap, |
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process_btn, |
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process_output, |
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qa_tab, |
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summary_tab, |
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specialist_tab, |
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minisummaries_output, |
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minianalysis_output, |
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chat_placeholder, |
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chat_title, |
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chat_btn, |
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summarize_btn, |
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summary_output, |
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ai_model_dropdown, |
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specialist_title, |
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specialist_placeholder, |
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specialist_output, |
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specialist_btn |
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] |
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) |
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ai_model_dropdown.change( |
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fn=self.change_ai_model, |
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inputs=[ai_model_dropdown], |
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outputs=[type_model, api_key_input, project_id_watsonx, chunk_size, chunk_overlap] |
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) |
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type_model.change( |
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fn=self.change_type_model, |
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inputs=[type_model], |
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outputs=[api_key_input,project_id_watsonx] |
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) |
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chat_placeholder.submit( |
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fn=self.qa_interface, |
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inputs=[chat_placeholder, chatbot, ai_model_dropdown, type_model, api_key_input, project_id_watsonx], |
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outputs=[chatbot] |
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) |
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process_btn.click( |
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fn=self.process_pdf, |
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inputs=[pdf_file, chunk_size, chunk_overlap, ai_model_dropdown, type_model, api_key_input, project_id_watsonx], |
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outputs=[process_output] |
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) |
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summarize_btn.click( |
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fn=self.summarize_interface, |
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inputs=[ai_model_dropdown, type_model, api_key_input, project_id_watsonx], |
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outputs=[summary_output] |
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) |
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specialist_btn.click( |
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fn=self.specialist_opinion, |
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inputs=[ai_model_dropdown, type_model, api_key_input, project_id_watsonx, specialist_placeholder], |
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outputs=[specialist_output] |
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) |
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chat_btn.click( |
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fn=self.qa_interface, |
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inputs=[chat_placeholder, chatbot, ai_model_dropdown, type_model, api_key_input, project_id_watsonx], |
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outputs=[chatbot] |
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) |
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return demo |
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if __name__ == "__main__": |
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ui = PDFProcessorUI() |
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demo = ui.create_ui() |
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demo.launch() |
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