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| import gradio as gr | |
| import PyPDF2 | |
| import pytesseract | |
| from PIL import Image | |
| # Ensure Tesseract is installed and accessible | |
| # On Windows, you may need to specify the Tesseract path: | |
| # pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe' | |
| def process_file(file): | |
| if file is None: | |
| return "No file uploaded." | |
| content = "" | |
| if file.name.endswith(".txt"): | |
| # Read text files | |
| with open(file.name, "r") as f: | |
| content = f.read() | |
| elif file.name.endswith(".pdf"): | |
| # Extract text from PDFs | |
| reader = PyPDF2.PdfReader(file.name) | |
| for page in reader.pages: | |
| content += page.extract_text() | |
| elif file.name.endswith((".png", ".jpg", ".jpeg")): | |
| # Extract text from images using OCR | |
| image = Image.open(file.name) | |
| content = pytesseract.image_to_string(image) | |
| else: | |
| return f"Unsupported file type: {file.name}" | |
| # Simulate passing the content to the phi-4 model | |
| model_response = f"Processed file content:\n{content}" | |
| return model_response | |
| with gr.Blocks(fill_height=True) as demo: | |
| with gr.Sidebar(): | |
| gr.Markdown("# Inference Provider") | |
| gr.Markdown("This Space showcases the microsoft/phi-4 model, served by the nebius API. Sign in with your Hugging Face account to use this API.") | |
| button = gr.LoginButton("Sign in") | |
| with gr.Column(): | |
| # Load the phi-4 model | |
| model = gr.load("models/microsoft/phi-4", accept_token=button, provider="nebius") | |
| # File upload component | |
| file_input = gr.File(label="Upload a file (TXT, PDF, or Image)") | |
| # Output component to display model response | |
| file_output = gr.Textbox(label="Model Response", lines=10) | |
| # Connect the file upload to the processing function | |
| file_input.change(process_file, inputs=file_input, outputs=file_output) | |
| demo.launch() |