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import gradio as gr
import os
import requests
import json
from huggingface_hub import HfApi, create_repo
HF_TOKEN = os.environ.get("HF_TOKEN")
def download_file(digest, image):
url = f"https://registry.ollama.ai/v2/library/{image}/blobs/{digest}"
file_name = f"blobs/{digest}"
# Create the directory if it doesn't exist
os.makedirs(os.path.dirname(file_name), exist_ok=True)
# Download the file
print(f"Downloading {url} to {file_name}")
response = requests.get(url, allow_redirects=True)
if response.status_code == 200:
with open(file_name, 'wb') as f:
f.write(response.content)
else:
print(f"Failed to download {url}")
def fetch_manifest(image, tag):
manifest_url = f"https://registry.ollama.ai/v2/library/{image}/manifests/{tag}"
response = requests.get(manifest_url)
if response.status_code == 200:
return response.json()
else:
return None
def upload_to_huggingface(repo_id, folder_path):
api = HfApi(token=HF_TOKEN)
repo_path = api.create_repo(repo_id, "model", exist_ok=True)
print(f"Repo created {repo_path}")
try:
api.upload_folder(
folder_path=folder_path,
repo_id=repo_id,
repo_type="model",
)
return "Upload successful"
except Exception as e:
return f"Upload failed: {str(e)}"
def process_image_tag(image_tag, repo_id):
# Extract image and tag from the input
try:
image, tag = image_tag.split(':')
# Fetch the manifest JSON
manifest_json = fetch_manifest(image, tag)
if not manifest_json or 'errors' in manifest_json:
return f"Failed to fetch the manifest for {image}:{tag}"
# Save the manifest JSON to the blobs folder
manifest_file_path = "blobs/manifest.json"
os.makedirs(os.path.dirname(manifest_file_path), exist_ok=True)
with open(manifest_file_path, 'w') as f:
json.dump(manifest_json, f)
# Extract the digest values from the JSON
digests = [layer['digest'] for layer in manifest_json.get('layers', [])]
# Download each file
for digest in digests:
download_file(digest, image)
# Download the config file
config_digest = manifest_json.get('config', {}).get('digest')
if config_digest:
download_file(config_digest, image)
# Upload to Hugging Face Hub
upload_result = upload_to_huggingface(repo_id, 'blobs')
# Delete the blobs folder
os.rmtree('blobs')
return f"Successfully fetched and downloaded files for {image}:{tag}\n{upload_result}\nBlobs folder deleted"
except Exception as e:
os.rmtree('blobs', ignore_errors=True)
return f"Error found: {str(e)}"
# Create the Gradio interface using gr.Blocks
with gr.Blocks() as demo:
gr.Markdown("# Ollama <> HF Hub 🤝")
gr.Markdown("Enter the image and tag to download the corresponding files from the Ollama registry and upload them to the Hugging Face Hub.")
with gr.Row():
image_tag_input = gr.Textbox(placeholder="Enter Ollama ID", label="Image and Tag")
repo_id_input = gr.Textbox(placeholder="Enter Hugging Face repo ID", label="Hugging Face Repo ID")
result_output = gr.Textbox(label="Result")
process_button = gr.Button("Process")
process_button.click(fn=process_image_tag, inputs=[image_tag_input, repo_id_input], outputs=result_output)
# Launch the Gradio app
demo.launch() |