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import os
import requests
import tempfile
import streamlit as st
from huggingface_hub import (
HfApi,
login,
create_repo,
delete_repo,
upload_file,
HfFolder,
)
from huggingface_hub.utils import RepositoryNotFoundError, RevisionNotFoundError
class HuggingFaceClient:
def __init__(self, token=None):
self.token = token
self.api = HfApi(token=token)
def authenticate(self, token):
"""Authenticate with Hugging Face API using token"""
self.token = token
self.api = HfApi(token=token)
try:
login(token=token)
whoami = self.api.whoami()
return True, whoami
except Exception as e:
return False, str(e)
def get_user_models(self):
"""Get all models created by the logged-in user"""
try:
# First try to get username from whoami API call
whoami = self.api.whoami()
username = whoami.get("name")
# Fallback to the HF_USERNAME secret if available
if not username and os.environ.get("HF_USERNAME"):
username = os.environ.get("HF_USERNAME")
# Get all models for this user using the list_models API
user_models = list(self.api.list_models(author=username))
return user_models
except Exception as e:
st.error(f"Error fetching models: {str(e)}")
return []
def get_model_info(self, repo_id):
"""Get detailed information about a specific model"""
try:
model_info = self.api.model_info(repo_id)
return model_info
except RepositoryNotFoundError:
st.error(f"Repository {repo_id} not found")
return None
except Exception as e:
st.error(f"Error fetching model info: {str(e)}")
return None
def create_model_repository(
self, repo_name, is_private=False, exist_ok=False, repo_type="model"
):
"""Create a new model repository on Hugging Face"""
try:
response = create_repo(
repo_id=repo_name,
token=self.token,
private=is_private,
exist_ok=exist_ok,
repo_type=repo_type,
)
return True, response
except Exception as e:
return False, str(e)
def delete_model_repository(self, repo_id):
"""Delete a model repository from Hugging Face"""
try:
response = delete_repo(repo_id=repo_id, token=self.token)
return True, "Repository deleted successfully"
except Exception as e:
return False, str(e)
def upload_model_files(self, repo_id, files, commit_message="Upload model files"):
"""Upload model files to a repository"""
try:
uploaded_files = []
for file_path, file_content in files.items():
with tempfile.NamedTemporaryFile(delete=False) as temp_file:
temp_file.write(file_content)
temp_file_path = temp_file.name
upload_response = upload_file(
path_or_fileobj=temp_file_path,
path_in_repo=file_path,
repo_id=repo_id,
token=self.token,
commit_message=commit_message,
)
uploaded_files.append(upload_response)
# Clean up temporary file
os.unlink(temp_file_path)
return True, uploaded_files
except Exception as e:
return False, str(e)
def update_model_card(self, repo_id, model_card_content):
"""Update the README.md (model card) of a repository"""
try:
with tempfile.NamedTemporaryFile(delete=False, mode="w") as temp_file:
temp_file.write(model_card_content)
temp_file_path = temp_file.name
upload_response = upload_file(
path_or_fileobj=temp_file_path,
path_in_repo="README.md",
repo_id=repo_id,
token=self.token,
commit_message="Update model card",
)
# Clean up temporary file
os.unlink(temp_file_path)
return True, upload_response
except Exception as e:
return False, str(e)
def get_model_tags(self):
"""Get available model tags from Hugging Face Hub"""
try:
# This is a simplified version; in a real app, you'd fetch actual tags from the HF API
tags = [
"text-classification",
"token-classification",
"question-answering",
"translation",
"summarization",
"text-generation",
"fill-mask",
"conversational",
"image-classification",
"object-detection",
"audio-classification",
"automatic-speech-recognition",
]
return tags
except Exception as e:
st.error(f"Error fetching tags: {str(e)}")
return []
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