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