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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")
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()
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