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# Copyright (c) 2026 Xavier Callens / Socrate AI Lab. All Rights Reserved.
# SPDX-License-Identifier: LicenseRef-RunuX-Commercial
#
# WARS-Quantum-LTN: Programmatic Hugging Face Uploader
# ====================================================
import os
import ssl
import urllib3
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
# Force global unverified HTTPS context
ssl._create_default_https_context = ssl._create_unverified_context
# Intercept and disable verification globally for all default SSLContext creations
original_create_default_context = ssl.create_default_context
def unverified_create_default_context(*args, **kwargs):
context = original_create_default_context(*args, **kwargs)
context.check_hostname = False
context.verify_mode = ssl.CERT_NONE
return context
ssl.create_default_context = unverified_create_default_context
# Monkeypatch requests to disable SSL verification globally
import requests
original_request = requests.Session.request
def unverified_request(self, *args, **kwargs):
kwargs['verify'] = False
return original_request(self, *args, **kwargs)
requests.Session.request = unverified_request
requests.sessions.Session.request = unverified_request
from huggingface_hub import HfApi, create_repo
def run_upload():
print("=========================================================================")
print("WARS-Quantum-LTN: Hugging Face Programmatic Delivery Publisher")
print("=========================================================================")
token = os.environ.get("HF_TOKEN")
if not token:
print("[ERROR] HF_TOKEN environment variable not set. Cannot authenticate.")
return
api = HfApi(token=token)
model_repo_id = "callensxavier/runux-wars-quantum-ltn-512q"
dataset_repo_id = "callensxavier/runux-quantum-dynamics-ea-512q"
# 1. Create Model Repository
print(f"\n[1/4] Ensuring model repository exists: {model_repo_id}...")
try:
create_repo(repo_id=model_repo_id, token=token, repo_type="model", exist_ok=True)
print(" ✅ Model repository is ready.")
except Exception as e:
print(f" [WARNING] Could not create/verify model repository: {e}")
# 2. Create Dataset Repository
print(f"\n[2/4] Ensuring dataset repository exists: {dataset_repo_id}...")
try:
create_repo(repo_id=dataset_repo_id, token=token, repo_type="dataset", exist_ok=True)
print(" ✅ Dataset repository is ready.")
except Exception as e:
print(f" [WARNING] Could not create/verify dataset repository: {e}")
# 3. Upload Model Card and Code Assets
print(f"\n[3/4] Uploading Model Card and reproducible quantum simulator source files to {model_repo_id}...")
try:
# Upload README.md (Model Card)
api.upload_file(
path_or_fileobj="HF_MODEL_README.md",
path_in_repo="README.md",
repo_id=model_repo_id,
repo_type="model"
)
print(" - Uploaded: README.md (Model Card)")
# Upload academic paper draft
api.upload_file(
path_or_fileobj="PAPER_DRAFT.md",
path_in_repo="PAPER_DRAFT.md",
repo_id=model_repo_id,
repo_type="model"
)
print(" - Uploaded: PAPER_DRAFT.md (Preprint)")
# Upload codebase assets
source_files = [
("simulator.py", "simulator.py"),
("ltn_constraints.py", "ltn_constraints.py"),
("polarquant.py", "polarquant.py"),
("scheduler.py", "scheduler.py"),
("bench_ea_spin_glass.py", "bench_ea_spin_glass.py"),
("neuro_symbolic_verifier.py", "neuro_symbolic_verifier.py"),
("upload.py", "upload.py"),
("/Volumes/MacCleanerStorage/xdev/xavux/rust-linux-mini-kernel/paper/quantum_ltn_paper.tex", "quantum_ltn_paper.tex"),
("../tpu_llm_bench.py", "tpu_llm_bench.py"),
("../autoresearch_rust_compiler.py", "autoresearch_rust_compiler.py"),
("../CONTRIBUTION_PROPOSAL.md", "CONTRIBUTION_PROPOSAL.md"),
("../../docs/COMPARATIVE_ANALYSIS.md", "COMPARATIVE_ANALYSIS.md"),
("../../marketing/FRENCH_STYLE_AI_INNOVATION.md", "FRENCH_STYLE_AI_INNOVATION.md")
]
for local_path, repo_path in source_files:
if os.path.exists(local_path):
api.upload_file(
path_or_fileobj=local_path,
path_in_repo=repo_path,
repo_id=model_repo_id,
repo_type="model"
)
print(f" - Uploaded: {repo_path} (Source asset)")
print(" ✅ All model repository uploads finished successfully.")
except Exception as e:
print(f" ❌ Model uploads failed: {e}")
# 4. Upload Dataset Card
print(f"\n[4/4] Uploading Dataset Card to {dataset_repo_id}...")
try:
api.upload_file(
path_or_fileobj="HF_DATASET_README.md",
path_in_repo="README.md",
repo_id=dataset_repo_id,
repo_type="dataset"
)
print(" - Uploaded: README.md (Dataset Card)")
print(" ✅ All dataset repository uploads finished successfully.")
except Exception as e:
print(f" ❌ Dataset uploads failed: {e}")
print("\n=========================================================================")
print("DELIVERY COMPLETED: WARS-Quantum-LTN is successfully live on Hugging Face!")
print("=========================================================================")
if __name__ == "__main__":
run_upload()