Create app.py

app.py

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+import os
+import gradio as gr
+import copy
+from llama_cpp import Llama
+from huggingface_hub import hf_hub_download
+from trimesh.exchange.gltf import export_glb
+import trimesh
+import numpy as np
+import tempfile
+
+# Initialize Llama model from Hugging Face
+model = Llama(
+    model_path=hf_hub_download(
+        repo_id=os.environ.get("REPO_ID", "Lyte/LLaMA-Mesh-Q4_K_M-GGUF"),
+        filename=os.environ.get("MODEL_FILE", "llama-mesh-q4_k_m.gguf"),
+    )
+)
+
+DESCRIPTION = '''
+<div>
+<h1 style="text-align: center;">LLaMA-Mesh</h1>
+<p>LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models.</p>
+<p>Supports up to 4096 tokens. Run locally for 8k token context.</p>
+<p>To generate another mesh, click "clear" and start a new dialog.</p>
+</div>
+'''
+
+LICENSE = """
+<p/>--- Built with Meta Llama 3.1 8B ---
+"""
+
+PLACEHOLDER = """
+<div style="padding: 30px; text-align: center;">
+   <h1 style="font-size: 28px; opacity: 0.55;">LLaMA-Mesh</h1>
+   <p style="font-size: 18px; opacity: 0.65;">Create 3D meshes by chatting.</p>
+</div>
+"""
+
+css = """
+h1 {
+  text-align: center;
+}
+
+#duplicate-button {
+  margin: auto;
+  color: white;
+  background: #1565c0;
+  border-radius: 100vh;
+}
+"""
+
+def generate_text(message, history, max_tokens=2048, temperature=0.9, top_p=0.95):
+    temp = ""
+    response = model.create_chat_completion(
+        messages=[{"role": "user", "content": message}],
+        temperature=temperature,
+        max_tokens=max_tokens,
+        top_p=top_p,
+        stream=True,
+    )
+    for streamed in response:
+        delta = streamed["choices"][0].get("delta", {})
+        print(delta)
+        text_chunk = delta.get("content", "")
+        
+        temp += text_chunk
+        yield temp
+
+def apply_gradient_color(mesh_text):
+    temp_file = tempfile.NamedTemporaryFile(suffix=".obj", delete=False).name
+    with open(temp_file, "w") as f:
+        f.write(mesh_text)
+    mesh = trimesh.load_mesh(temp_file, file_type='obj')
+
+    vertices = mesh.vertices
+    y_values = vertices[:, 1]
+    y_normalized = (y_values - y_values.min()) / (y_values.max() - y_values.min())
+    colors = np.zeros((len(vertices), 4))
+    colors[:, 0] = y_normalized
+    colors[:, 2] = 1 - y_normalized
+    colors[:, 3] = 1.0
+    mesh.visual.vertex_colors = colors
+
+    glb_path = temp_file.replace(".obj", ".glb")
+    with open(glb_path, "wb") as f:
+        f.write(export_glb(mesh))
+    return glb_path
+
+with gr.Blocks(css=css) as demo:
+    gr.Markdown(DESCRIPTION)
+    chatbot = gr.ChatInterface(
+        generate_text,
+        title="LLaMA-Mesh | GGUF Integration",
+        description="Supports generating 3D meshes with LLaMA-GGUF.",
+        examples=[
+            ['Create a 3D model of a wooden hammer'],
+            ['Create a 3D model of a pyramid in OBJ format'],
+            ['Create a 3D model of a table.'],
+        ],
+        cache_examples=False,
+        additional_inputs=[
+            gr.Slider(minimum=128, maximum=4096, value=1024, step=1, label="Max new tokens"),
+            gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+            gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
+        ],
+    )
+
+    gr.Markdown("### 3D Mesh Visualization")
+    mesh_input = gr.Textbox(
+        label="3D Mesh Input",
+        placeholder="Paste your 3D mesh in OBJ format here...",
+        lines=5,
+    )
+    visualize_button = gr.Button("Visualize 3D Mesh")
+    output_model = gr.Model3D(label="3D Mesh Visualization")
+    visualize_button.click(
+        fn=apply_gradient_color,
+        inputs=[mesh_input],
+        outputs=[output_model]
+    )
+    gr.Markdown(LICENSE)
+
+# Launch the demo
+if __name__ == "__main__":
+    demo.launch()