Update app.py

app.py

@@ -6,6 +6,7 @@ import time
 import asyncio
 import tempfile
 from threading import Thread
+import base64
 
 import gradio as gr
 import spaces
@@ -36,6 +37,16 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
         seed = random.randint(0, MAX_SEED)
     return seed
 
+def glb_to_data_url(glb_path: str) -> str:
+    """
+    Reads a GLB file from disk and returns a data URL with a base64 encoded representation.
+    This data URL can be used as the `src` for an HTML <model-viewer> tag.
+    """
+    with open(glb_path, "rb") as f:
+        data = f.read()
+    b64_data = base64.b64encode(data).decode("utf-8")
+    return f"data:model/gltf-binary;base64,{b64_data}"
+
 class Model:
     def __init__(self):
         self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -117,7 +128,6 @@ MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
-# Load the text-only model and tokenizer (for pure text chat)
 model_id = "prithivMLmods/FastThink-0.5B-Tiny"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(
@@ -236,7 +246,6 @@ def generate_image_fn(
     image_paths = [save_image(img) for img in images]
     return image_paths, seed
 
-
 @spaces.GPU(duration=120, enable_queue=True)
 def generate_3d_fn(
     prompt: str,
@@ -287,7 +296,13 @@ def generate(
             num_steps=64,
             randomize_seed=True,
         )
-        yield gr.File(glb_path, label="3D Model (GLB)")
+        # Convert the GLB file to a base64 data URL and embed it in an HTML <model-viewer> tag.
+        data_url = glb_to_data_url(glb_path)
+        html_output = f'''
+        <model-viewer src="{data_url}" alt="3D Model" auto-rotate camera-controls style="width: 100%; height: 400px;"></model-viewer>
+        <script type="module" src="https://unpkg.com/@google/model-viewer/dist/model-viewer.min.js"></script>
+        '''
+        yield gr.HTML(html_output)
         return
 
     # --- Image Generation branch ---
@@ -415,4 +430,4 @@ demo = gr.ChatInterface(
 
 if __name__ == "__main__":
     # To create a public link, set share=True in launch().
-    demo.queue(max_size=20).launch(share=True)
+    demo.queue(max_size=20).launch(share=True)