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import gradio as gr |
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from gradio import File |
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from process.ocr import perform_raw_ocr, correct_text_with_ai |
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from process.interpretation import get_interpretation |
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from process.translation import get_translaton |
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from process.gradio_css import CUSTOM_CSS |
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from process.agent import AutomatedAnalysisAgent |
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MISTRAL_API_KEY = "" |
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GEMINI_API_KEY = "" |
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def update_api_keys(mistral_key, gemini_key): |
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""" |
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Updates the global MISTRAL_API_KEY and GEMINI_API_KEY variables. |
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Args: |
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mistral_key: The Mistral API key. |
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gemini_key: The Gemini API key. |
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Returns: |
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A string confirming that the API keys have been saved. |
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""" |
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global MISTRAL_API_KEY, GEMINI_API_KEY |
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MISTRAL_API_KEY = mistral_key |
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GEMINI_API_KEY = gemini_key |
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return "API keys saved" |
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def ocr_workflow_wrapper(file: File, mistral_key: str): |
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""" |
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Manages the OCR workflow, processing an uploaded file to extract text. |
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Args: |
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file: The file object to process (image, PDF, or text). |
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mistral_key: The Mistral API key for OCR processing. |
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Yields: |
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Status messages and the extracted text or error messages. |
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""" |
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if not mistral_key: |
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error_msg = "Error: Mistral API Key not set." |
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yield error_msg, error_msg |
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return |
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if not file or file.name == "": |
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error_msg = "Error: File/Text not found." |
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yield error_msg, error_msg |
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return |
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try: |
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result = perform_raw_ocr(file, mistral_key) |
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yield result, result |
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except Exception as e: |
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error_msg = f"An error occurred during processing: {str(e)}" |
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yield error_msg, error_msg |
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def ai_correct(current_text: str, mistral_key: str): |
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""" |
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Corrects the provided text using an AI model. |
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Args: |
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current_text: The text to be corrected. |
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mistral_key: The Mistral API key for AI correction. |
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Yields: |
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Status messages and the corrected text or error messages. |
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""" |
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if not mistral_key: |
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error_msg = "Error: Mistral API Key not set." |
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yield error_msg, error_msg |
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return |
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if not current_text or current_text.strip() == "": |
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error_msg = "*No text to correct. Upload a file, or paste text into 'Raw Text' box first*" |
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yield error_msg, error_msg |
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return |
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try: |
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result = correct_text_with_ai(current_text, mistral_key) |
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yield result, result |
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except Exception as e: |
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error_msg = f"Error : {e}" |
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yield error_msg, error_msg |
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def interpretation_workflow( |
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text: str, genre: str, learn_language: str, target_language: str, gemini_key: str |
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): |
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""" |
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Generates an interpretation of the text based on genre and language settings. |
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Args: |
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text: The text to interpret. |
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genre: The genre of the text (e.g., "general", "news"). |
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learn_language: The language being learned. |
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target_language: The language for the interpretation output. |
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gemini_key: The Gemini API key for interpretation. |
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Yields: |
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Status messages and the generated interpretation or error messages. |
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""" |
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if not gemini_key: |
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yield "Error: Gemini api key not found." |
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return |
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if not text or text.strip() == "": |
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yield "Error: Text is empty" |
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return |
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if not learn_language or not target_language: |
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yield "Error: Language not selected" |
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return |
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if genre.lower() in ["general", "news", "philosophy"]: |
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result = get_interpretation( |
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genre.lower(), gemini_key, text, learn_language, target_language |
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) |
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yield result |
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else: |
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yield "not implemented yet" |
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def translation_workflow(text: str, target_language: str, gemini_key): |
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""" |
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Translates the provided text to the target language. |
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Args: |
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text: The text to translate. |
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target_language: The language to translate the text into. |
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gemini_key: The Gemini API key for translation. |
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Yields: |
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Status messages and the translated text or error messages. |
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""" |
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if not gemini_key: |
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yield "Error: Gemini api key not found." |
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return |
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if not text or text.strip() == "": |
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yield "Error: Text is empty" |
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return |
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if not target_language: |
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yield "Error: Language not selected" |
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existin_languages = [ |
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"العربية", |
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"Deutsch", |
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"Español", |
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"English", |
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"Français", |
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"Italiano", |
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"日本語", |
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"Русский язык", |
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"中文", |
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] |
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if target_language in existin_languages: |
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result = get_translaton(text, gemini_key, target_language) |
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yield result |
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else: |
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yield "not implemented yet" |
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def agent_workflow(text: str, prof_language: str, mistral_key: str, gemini_key: str): |
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if not mistral_key or not gemini_key: |
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return "Error: Both Mistral and Gemini API keys are required." |
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if not text or not text.strip(): |
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return "Error: Input text is empty." |
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try: |
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agent = AutomatedAnalysisAgent(mistral_key=mistral_key, gemini_key=gemini_key) |
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result = agent.run(text, prof_language=prof_language) |
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return result |
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except Exception as e: |
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return f"An error occurred in the agent workflow: {e}" |
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with gr.Blocks(theme=gr.themes.Monochrome(), css=CUSTOM_CSS) as demo: |
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gr.Markdown( |
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"# 📚 LogosAI - Intensive Reading in Any Language", |
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elem_classes=["section-header"], |
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) |
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with gr.Accordion("API Configuration", open=True): |
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with gr.Row(): |
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with gr.Column(scale=2): |
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mistral_api = gr.Textbox( |
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label="Mistral API Key", |
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type="password", |
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placeholder="Enter your key", |
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info="OCR recognition & text processing", |
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) |
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with gr.Column(scale=2): |
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gemini_api = gr.Textbox( |
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label="Gemini API Key", |
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type="password", |
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placeholder="Enter your key", |
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info="text interpretation", |
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) |
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with gr.Column(scale=1): |
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update_keys_button = gr.Button("Save keys") |
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api_key_status_output = gr.Markdown() |
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update_keys_button.click( |
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fn=update_api_keys, |
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inputs=[mistral_api, gemini_api], |
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outputs=api_key_status_output, |
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) |
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gr.Markdown("---") |
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with gr.Tab("Text"): |
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with gr.Row(): |
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with gr.Column(scale=1): |
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gr.Markdown("### Upload documents") |
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file_input = gr.File( |
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label="Upload Image/PDF/text", file_types=["image", ".pdf", ".txt"] |
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) |
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process_button = gr.Button( |
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"1. File Process (OCR/Read)", variant="primary" |
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) |
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ai_correct_button = gr.Button("2. AI Correct", variant="primary") |
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with gr.Column(scale=2): |
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gr.Markdown("### Processed result") |
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with gr.Tabs(): |
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with gr.Tab("Raw Text"): |
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text_display = gr.Textbox( |
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label="Raw Text(editable)", |
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lines=15, |
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max_lines=20, |
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show_copy_button=True, |
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value="", |
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interactive=True, |
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) |
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with gr.Tab("Formatted Text"): |
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text_markdown = gr.Markdown( |
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value="*Processed text will appear here...*\n\n", |
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label="Formatted Text", |
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) |
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process_button.click( |
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fn=ocr_workflow_wrapper, |
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inputs=[file_input, mistral_api], |
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outputs=[text_display, text_markdown], |
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) |
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ai_correct_button.click( |
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fn=ai_correct, |
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inputs=[text_display, mistral_api], |
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outputs=[text_display, text_markdown], |
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) |
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with gr.Tab("Agent"): |
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gr.Markdown("### Automated Analysis") |
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with gr.Row(): |
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with gr.Column(scale=1): |
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agent_prof_language_selector = gr.Dropdown( |
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["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"], |
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label="Prof's Language", |
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value="EN", |
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) |
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agent_run_button = gr.Button( |
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"Run Automated Analysis", variant="primary" |
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) |
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with gr.Column(scale=2): |
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gr.Markdown("### Agent Result") |
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agent_output = gr.Markdown( |
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value="*Agent analysis will appear here...*\n\n", |
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label="Agent Result", |
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) |
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agent_run_button.click( |
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fn=agent_workflow, |
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inputs=[ |
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text_display, |
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agent_prof_language_selector, |
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mistral_api, |
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gemini_api, |
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], |
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outputs=agent_output, |
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) |
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with gr.Tab("🎓 Interpretation"): |
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gr.Markdown("### Configure Interpretation Settings") |
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with gr.Row(): |
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with gr.Column(scale=1): |
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prof_language_seletor = gr.Dropdown( |
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["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"], |
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label="Prof's Language", |
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value="EN", |
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) |
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learn_language_seletor = gr.Dropdown( |
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["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"], |
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label="Language to Learn", |
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value="EN", |
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) |
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style_seletor = gr.Dropdown( |
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["General", "News", "Philosophy", "Narrative", "Poem", "Paper"], |
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label="Genre", |
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) |
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interpret_button = gr.Button( |
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"Generate Interpretation", variant="primary" |
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) |
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with gr.Column(scale=2): |
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gr.Markdown("### COURSE") |
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interpretation_output = gr.Markdown( |
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value="*Interpretation will appear here after processing...*\n\n", |
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label="Interpretation Result", |
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show_copy_button=True, |
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) |
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interpret_button.click( |
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fn=interpretation_workflow, |
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inputs=[ |
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text_display, |
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style_seletor, |
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learn_language_seletor, |
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prof_language_seletor, |
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gemini_api, |
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], |
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outputs=interpretation_output, |
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) |
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with gr.Tab("Translation"): |
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gr.Markdown("### Configure Translation Settings") |
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with gr.Row(): |
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with gr.Column(scale=1): |
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target_language_selector = gr.Dropdown( |
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[ |
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"العربية", |
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"Deutsch", |
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"Español", |
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"English", |
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"Français", |
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"Italiano", |
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"日本語", |
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"Русский язык", |
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"中文", |
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], |
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value="English", |
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label="Target Language", |
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interactive=True, |
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) |
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translation_button = gr.Button("Translate!", variant="primary") |
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with gr.Column(scale=2): |
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interpretation_output = gr.Markdown( |
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value="*Translation will appear here ...*\n\n", |
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label="Translation Result", |
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show_copy_button=True, |
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) |
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translation_button.click( |
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fn=translation_workflow, |
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inputs=[text_display, target_language_selector, gemini_api], |
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outputs=interpretation_output, |
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) |
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if __name__ == "__main__": |
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demo.launch(mcp_server=True) |
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