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| import gradio as gr | |
| import requests | |
| from PyPDF2 import PdfReader | |
| import os | |
| # Function to validate PDF file | |
| def is_valid_pdf(file_path): | |
| try: | |
| # If file_path is a string (Gradio provides a temporary file path) | |
| if isinstance(file_path, str) and os.path.exists(file_path): | |
| with open(file_path, "rb") as f: | |
| pdf = PdfReader(f) | |
| if len(pdf.pages) > 0: | |
| return True, f"Valid PDF with {len(pdf.pages)} pages" | |
| return False, "Invalid PDF: No pages found" | |
| else: | |
| return False, "Invalid PDF: File path is not valid" | |
| except Exception as e: | |
| return False, f"Invalid PDF: {str(e)}" | |
| # Function to send the POST request to the API | |
| def extract_text_from_pdf(pdf_file, page_number, src_lang, tgt_lang, prompt): | |
| if not pdf_file: | |
| return "Error: No file uploaded. Please upload a PDF file." | |
| # Validate the PDF | |
| valid, message = is_valid_pdf(pdf_file) | |
| if not valid: | |
| return f"Error: {message}. Please upload a valid PDF file or repair the current one." | |
| # API endpoint | |
| url = "http://209.20.158.215:7861/extract-text-eng/" | |
| # Prepare the payload | |
| with open(pdf_file, "rb") as f: | |
| files = { | |
| "file": ("uploaded.pdf", f, "application/pdf") | |
| } | |
| data = { | |
| "page_number": str(page_number), | |
| "src_lang": src_lang, | |
| "tgt_lang": tgt_lang, | |
| "prompt": prompt | |
| } | |
| # Headers | |
| headers = { | |
| "accept": "application/json" | |
| } | |
| try: | |
| # Send the POST request | |
| response = requests.post(url, files=files, data=data, headers=headers) | |
| # Check if the request was successful | |
| if response.status_code == 200: | |
| result = response.json() | |
| page_content = result.get("page_content", "No description returned from API") | |
| return page_content | |
| else: | |
| return f"Error: {response.status_code} - {response.text}" | |
| except Exception as e: | |
| return f"Error: Failed to connect to the API - {str(e)}" | |
| # Gradio interface | |
| with gr.Blocks(title="PDF Content Description") as demo: | |
| gr.Markdown("# PDF Content Description Extractor") | |
| gr.Markdown( | |
| """ | |
| Upload a PDF file (e.g., Dhwani-AI-Pitch-Europe.pdf) and specify parameters to extract a description of its content. | |
| The API will analyze the page and return a textual description based on the provided prompt and languages. | |
| """ | |
| ) | |
| # Input components | |
| pdf_input = gr.File(label="Upload PDF File", file_types=[".pdf"], type="filepath") | |
| page_number_input = gr.Number(label="Page Number", value=1, precision=0, minimum=1) | |
| src_lang_input = gr.Textbox( | |
| label="Source Language", | |
| value="eng_Latn", | |
| placeholder="Enter source language (e.g., eng_Latn)" | |
| ) | |
| tgt_lang_input = gr.Textbox( | |
| label="Target Language", | |
| value="eng_Latn", | |
| placeholder="Enter target language (e.g., eng_Latn)" | |
| ) | |
| prompt_input = gr.Textbox( | |
| label="Prompt", | |
| value="describe the image", | |
| placeholder="Enter prompt (e.g., describe the image)" | |
| ) | |
| # Submit button | |
| submit_button = gr.Button("Extract Description") | |
| # Output component | |
| output_text = gr.Textbox( | |
| label="Content Description", | |
| lines=10, | |
| placeholder="The API response will appear here, describing the content of the specified PDF page." | |
| ) | |
| # Connect the button to the function | |
| submit_button.click( | |
| fn=extract_text_from_pdf, | |
| inputs=[pdf_input, page_number_input, src_lang_input, tgt_lang_input, prompt_input], | |
| outputs=output_text | |
| ) | |
| # Launch the Gradio app | |
| demo.launch() |