Update app.py

app.py

@@ -3,7 +3,7 @@ import base64
 import torch
 import os
 from flask import Flask, request, jsonify
-from diffusers import StableDiffusionPipeline  # Placeholder; adjust based on SF3D docs
+from diffusers import StableDiffusionPipeline  # Placeholder; adjust based on InstantMesh docs
 from PIL import Image
 import logging
 
@@ -12,17 +12,14 @@ logger = logging.getLogger(__name__)
 
 app = Flask(__name__)
 
-# Load the model once at startup (on CPU) with token from environment
+# Load the model once at startup (on CPU) without token (test only)
 try:
-    logger.info("Loading Stable Fast 3D pipeline...")
-    token = os.getenv("HF_TOKEN")  # Retrieve token from environment variable
-    if not token:
-        raise ValueError("HF_TOKEN environment variable not set")
+    logger.info("Loading TencentARC InstantMesh pipeline...")
     pipe = StableDiffusionPipeline.from_pretrained(
-        "stabilityai/stable-fast-3d",
+        "TencentARC/InstantMesh",
         torch_dtype=torch.float32,
         cache_dir="/tmp/hf_home",
-        token=token,  # Use the environment variable token
+        # token=token,  # Comment out or remove for test
     )
     pipe.to("cpu")
     logger.info("=== Application Startup at CPU mode =====")
@@ -37,7 +34,7 @@ def pil_to_base64(image):
 
 @app.route("/")
 def home():
-    return "Stable Fast 3D CPU API is running!"
+    return "TencentARC InstantMesh CPU API is running!"
 
 @app.route("/generate", methods=["POST"])
 def generate():
@@ -57,8 +54,8 @@ def generate():
         image = Image.open(io.BytesIO(base64.b64decode(image_data))).convert("RGB")
 
         logger.info("Processing image with pipeline...")
-        result = pipe(image)  # Adjust based on SF3D documentation
-        output_mesh = result.mesh  # Hypothetical; check SF3D output format
+        result = pipe(image)  # Adjust based on InstantMesh documentation
+        output_mesh = result.mesh  # Hypothetical; check InstantMesh output format
 
         output_path = "/tmp/output.glb"
         output_mesh.save(output_path)