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| import gradio as gr | |
| import gspread | |
| from oauth2client.service_account import ServiceAccountCredentials | |
| import json | |
| import os | |
| import requests | |
| # Load Google Sheets credentials from secrets | |
| creds_json = os.getenv("GOOGLE_SHEETS_KEY_JSON") | |
| creds_dict = json.loads(creds_json) | |
| # Google Sheets setup | |
| scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"] | |
| creds = ServiceAccountCredentials.from_json_keyfile_dict(creds_dict, scope) | |
| client = gspread.authorize(creds) | |
| sheet = client.open("QF - Quant Request").sheet1 # Use the correct sheet name | |
| def validate_repo(link): | |
| """Check if the repository exists on Hugging Face.""" | |
| # Extract repo_id from the link (format: {username}/{model_name} or {dataset_name}) | |
| repo_id = link.split("https://huggingface.co./")[-1].strip("/") | |
| url = f"https://huggingface.co./api/models/{repo_id}" # Adjust the URL for datasets if needed | |
| response = requests.head(url) | |
| return response.status_code == 200 | |
| def check_quant_exists(link): | |
| """Check if the quantization request already exists in the Google Sheet.""" | |
| extracted_text = link.split("https://huggingface.co./")[-1] | |
| existing_texts = sheet.col_values(1) # Assuming the extracted text is in the first column | |
| return extracted_text in existing_texts | |
| def check_quant_factory_quant_exists(link): | |
| """Check if a GGUF quantized model exists in the QuantFactory repository.""" | |
| # Extract the model name from the original link | |
| model_name = link.split('/')[-1] # Get the last item from the split list, which is the model name | |
| # Create the QuantFactory GGUF quant link | |
| quant_factory_link = f"https://huggingface.co./QuantFactory/{model_name}-GGUF" | |
| # Check if the QuantFactory GGUF repo exists | |
| response = requests.head(quant_factory_link) | |
| if response.status_code == 200: | |
| return True, quant_factory_link | |
| else: | |
| return False, quant_factory_link | |
| def submit_link(link): | |
| # Normalize the input link | |
| if not link.startswith("https://huggingface.co."): | |
| link = f"https://huggingface.co./{link}" | |
| # Validate the repo | |
| if not validate_repo(link): | |
| return "Invalid model or repository link. Please provide a valid Hugging Face link." | |
| # Check if the GGUF quantized model already exists in QuantFactory | |
| quant_exists, quant_link = check_quant_factory_quant_exists(link) | |
| if quant_exists: | |
| model_name = link.split('/')[-1] # Extract the model name | |
| # Return a formatted Markdown string to create a clickable hyperlink | |
| return f"Quant already exists at [QuantFactory/{model_name}-GGUF]({quant_link})." | |
| # Check if the quant request already exists in the Google Sheet | |
| if check_quant_exists(link): | |
| return "Quant requests have already been made for this model." | |
| # Extract text after "huggingface.co/" | |
| extracted_text = link.split("https://huggingface.co./")[-1] | |
| # Append the row with the extracted text and default status "Pending" | |
| row_index = len(sheet.get_all_values()) + 1 | |
| sheet.append_row(["", ""]) # Append an empty row first to ensure correct row index | |
| # Set the hyperlink formula in the first column | |
| sheet.update_cell(row_index, 1, f'=HYPERLINK("{link}", "{extracted_text}")') | |
| # Copy content from cell B2 to the new row in column B | |
| b2_value = sheet.cell(2, 2).value | |
| sheet.update_cell(row_index, 2, b2_value) | |
| return "Request submitted successfully." | |
| # Gradio Interface | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(scale=1): # Left column | |
| gr.Markdown("## QuantFactory - Model Request") | |
| gr.Markdown("*NOTE: Due to limited resources, currently we can only quantize models with upto 20B parameters.*") | |
| link_input = gr.Textbox(label="Hugging Face Link") | |
| submit_button = gr.Button("Submit") | |
| result = gr.Markdown() # Use Markdown to render the output as a clickable hyperlink | |
| submit_button.click(fn=submit_link, inputs=link_input, outputs=result) | |
| with gr.Column(scale=1): # Right column | |
| gr.Image("image.png") # Display the image on the right | |
| demo.launch() | |