Update app.py

app.py

@@ -1,68 +1,71 @@
 from diffusers import StableDiffusionXLPipeline
-from huggingface_hub import hf_hub_download, HfApi
+from huggingface_hub import hf_hub_download, HfApi, upload_folder
 import torch, os
 
-# ------------------------------
-# SETTINGS
-# ------------------------------
-LORA_REPO = "CoolKrishh/Comic-SDXL-LoRA"  # LoRA repo on HuggingFace
-LORA_FILENAME = "Comic-SDXL.safetensors"  # exact filename in repo
-OUTPUT_REPO = "CoolKrishh/mythic-sdxl"    # final full model repo
+HF_REPO = "CoolKrishh/mythic-sdxl"  # new repo name
+LORA_REPO = "CoolKrishh/Comic-SDXL-LoRA"
+LORA_FILENAME = "Comic-SDXL.safetensors"
 SAVE_DIR = "mythic-sdxl-pipeline"
-# ------------------------------
 
 print("🔑 Fetching HF token from secrets...")
 HF_TOKEN = os.getenv("HF_TOKEN") or os.getenv("HUGGINGFACE_TOKEN")
-
 if HF_TOKEN is None:
-    raise ValueError("❌ HF_TOKEN not found! Add in HF Space → Secrets → New variable → HF_TOKEN")
+    raise ValueError("❌ HF_TOKEN not found! Add it in Space → Settings → Secrets")
+
+api = HfApi()
 
-# ------------------------------
-# DOWNLOAD BASE MODEL
-# ------------------------------
-print("🚀 Downloading SDXL base pipeline...")
+# ----------------------------------------------------
+# ✅ Create repo if not exists
+# ----------------------------------------------------
+try:
+    api.create_repo(
+        repo_id=HF_REPO,
+        private=False,
+        exist_ok=True,
+        token=HF_TOKEN
+    )
+    print(f"✅ Repo exists or created: https://huggingface.co/{HF_REPO}")
+except Exception as e:
+    print("⚠️ Repo creation error:", e)
+
+# ----------------------------------------------------
+# Download base model
+# ----------------------------------------------------
+print("🚀 Downloading SDXL base config...")
 pipe = StableDiffusionXLPipeline.from_pretrained(
     "stabilityai/stable-diffusion-xl-base-1.0",
     torch_dtype=torch.float16
 )
-pipe.to("cpu")
 
-# ------------------------------
-# DOWNLOAD LORA WEIGHTS
-# ------------------------------
-print("⬇️ Downloading LoRA weights from:", LORA_REPO)
+# ----------------------------------------------------
+# Download LoRA File
+# ----------------------------------------------------
+print("⬇️ Downloading LoRA weights...")
 lora_path = hf_hub_download(
     repo_id=LORA_REPO,
-    filename=LORA_FILENAME
+    filename=LORA_FILENAME,
+    token=HF_TOKEN
 )
 
-# ------------------------------
-# MERGE LoRA INTO PIPELINE
-# ------------------------------
-print("🔄 Applying LoRA weights...")
+print("🔄 Applying LoRA to pipeline...")
 pipe.load_lora_weights(lora_path)
-pipe.fuse_lora()  # <---- applies LoRA permanently into UNet/TextEncoder
+pipe.fuse_lora()
 
-print("✅ LoRA successfully merged into the base model!")
-
-# ------------------------------
-# SAVE FULL PIPELINE
-# ------------------------------
-print("💾 Saving full pipeline to:", SAVE_DIR)
+# ----------------------------------------------------
+# Save Pipeline
+# ----------------------------------------------------
+print("💾 Saving with LoRA merged...")
 pipe.save_pretrained(SAVE_DIR)
 
-# ------------------------------
-# UPLOAD MODEL TO HF
-# ------------------------------
-from huggingface_hub import upload_folder
-
-print(f"⬆️ Uploading model to: {OUTPUT_REPO}")
-
+# ----------------------------------------------------
+# Upload to HF
+# ----------------------------------------------------
+print("⬆️ Uploading full pipeline to Hugging Face...")
 upload_folder(
-    repo_id=OUTPUT_REPO,
+    repo_id=HF_REPO,
     folder_path=SAVE_DIR,
     repo_type="model",
     token=HF_TOKEN
 )
 
-print("✅ DONE — Full model uploaded to Hugging Face successfully!")
+print("✅ DONE! Model uploaded successfully.")