Update app.py

app.py

@@ -1,71 +1,62 @@
 from diffusers import StableDiffusionXLPipeline
-from huggingface_hub import hf_hub_download, HfApi, upload_folder
+from huggingface_hub import HfApi, HfFolder, create_repo, hf_hub_download, upload_folder
 import torch, os
 
-HF_REPO = "CoolKrishh/mythic-sdxl"  # new repo name
-LORA_REPO = "CoolKrishh/Comic-SDXL-LoRA"
-LORA_FILENAME = "Comic-SDXL.safetensors"
-SAVE_DIR = "mythic-sdxl-pipeline"
+# ---------------------------------------------------
+# ✅ CONFIGURATION — CHANGE THESE
+# ---------------------------------------------------
+BASE_MODEL = "stabilityai/stable-diffusion-xl-base-1.0"
+LORA_REPO = "CoolKrishh/Comic-SDXL-LoRA"     # where LoRA exists
+LORA_FILENAME = "comic-sdxl.safetensors"     # LoRA file name inside repo
 
-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 it in Space → Settings → Secrets")
+REPO_ID = "CoolKrishh/mythic-sdxl"           # final merged model repo
+# ---------------------------------------------------
 
+token = os.getenv("HF_TOKEN")
+if not token:
+    raise ValueError("❌ Missing HF_TOKEN env var!")
+
+print("🔹 Authenticating…")
+HfFolder.save_token(token)
 api = HfApi()
 
-# ----------------------------------------------------
-# ✅ Create repo if not exists
-# ----------------------------------------------------
+# ✅ create repo (ignore if 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
-)
+    create_repo(REPO_ID, exist_ok=True, private=False)
+except Exception:
+    pass
 
-# ----------------------------------------------------
-# Download LoRA File
-# ----------------------------------------------------
-print("⬇️ Downloading LoRA weights...")
+# ✅ download LoRA file from HF repo
+print("⬇️ Downloading LoRA from Hugging Face...")
 lora_path = hf_hub_download(
     repo_id=LORA_REPO,
     filename=LORA_FILENAME,
-    token=HF_TOKEN
+    token=token
+)
+
+print(f"✅ LoRA downloaded: {lora_path}")
+
+print("🔹 Loading SDXL base pipeline...")
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    BASE_MODEL,
+    torch_dtype=torch.float16
 )
 
-print("🔄 Applying LoRA to pipeline...")
+print("🔹 Applying LoRA weights into pipeline...")
 pipe.load_lora_weights(lora_path)
-pipe.fuse_lora()
+pipe.fuse_lora()   # <-- merges LoRA into UNet + Text Encoder
 
-# ----------------------------------------------------
-# Save Pipeline
-# ----------------------------------------------------
-print("💾 Saving with LoRA merged...")
-pipe.save_pretrained(SAVE_DIR)
+OUTPUT_DIR = "./merged_sdxl"
+print(f"💾 Saving merged pipeline to {OUTPUT_DIR}...")
+pipe.save_pretrained(OUTPUT_DIR, safe_serialization=True)
 
-# ----------------------------------------------------
-# Upload to HF
-# ----------------------------------------------------
-print("⬆️ Uploading full pipeline to Hugging Face...")
+print("☁️ Uploading merged model to Hugging Face...")
 upload_folder(
-    repo_id=HF_REPO,
-    folder_path=SAVE_DIR,
-    repo_type="model",
-    token=HF_TOKEN
+    repo_id=REPO_ID,
+    folder_path=OUTPUT_DIR,
+    commit_message="Merged SDXL + LoRA — full diffusers pipeline",
+    token=token
 )
 
-print("✅ DONE! Model uploaded successfully.")
+print("\n✅ DONE! Your merged SDXL model is uploaded and ready for Inference API.")
+print(f"👉 https://huggingface.co/{REPO_ID}")