add sambanova coder

app.py

@@ -29,6 +29,7 @@ from app_qwen import demo as demo_qwen
 from app_qwen_coder import demo as demo_qwen_coder
 from app_nvidia_coder import demo as demo_nvidia_coder
 from app_openai import demo as demo_openai
+from app_sambanova_coder import demo as demo_sambanova_coder
 from utils import get_app
 import gradio as gr
 
@@ -60,6 +61,7 @@ gr.load(
 # Create mapping of providers to their demos
 PROVIDERS = {
     "OpenAI Coder": demo_openai_coder,
+    "Sambanova Coder": demo_sambanova_coder,
     "Gemini Coder": demo_gemini_coder,
     "OpenAI": demo_openai,
     "NVIDIA Coder": demo_nvidia_coder,

app_sambanova.py

@@ -1,28 +1,19 @@
-import os
+import ai_gradio
 
-import sambanova_gradio
+from utils_ai_gradio import get_app
 
-from utils import get_app
+# Get the hyperbolic models but keep their full names for loading
+SAMBANOVA_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("sambanova:")]
+
+# Create display names without the prefix
+SAMBANOVA_MODELS_DISPLAY = [k.replace("sambanova:", "") for k in SAMBANOVA_MODELS_FULL]
 
-demo = get_app(
-    models=[
-        "Meta-Llama-3.2-1B-Instruct",
-        "Meta-Llama-3.2-3B-Instruct",
-        "Llama-3.2-11B-Vision-Instruct",
-        "Llama-3.2-90B-Vision-Instruct",
-        "Meta-Llama-3.1-8B-Instruct",
-        "Meta-Llama-3.1-70B-Instruct",
-        "Meta-Llama-3.1-405B-Instruct",
-        "Qwen2.5-72B-Instruct",
-        "Qwen2.5-Coder-32B-Instruct",
-        "Meta-Llama-3.3-70B-Instruct",
-        "QwQ-32B-Preview",
-    ],
-    default_model="QwQ-32B-Preview",
-    src=sambanova_gradio.registry,
-    accept_token=not os.getenv("SAMBANOVA_API_KEY"),
-    multimodal=True,
-)
 
-if __name__ == "__main__":
-    demo.launch()
+# Create and launch the interface using get_app utility
+demo = get_app(
+    models=SAMBANOVA_MODELS_FULL,  # Use the full names with prefix
+    default_model=SAMBANOVA_MODELS_FULL[-1],
+    dropdown_label="Select Sambanova Model",
+    choices=SAMBANOVA_MODELS_DISPLAY,  # Display names without prefix
+    fill_height=True,
+)

app_sambanova_coder.py

@@ -0,0 +1,20 @@
+import ai_gradio
+
+from utils_ai_gradio import get_app
+
+# Get the hyperbolic models but keep their full names for loading
+SAMBANOVA_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("sambanova:")]
+
+# Create display names without the prefix
+SAMBANOVA_MODELS_DISPLAY = [k.replace("sambanova:", "") for k in SAMBANOVA_MODELS_FULL]
+
+
+# Create and launch the interface using get_app utility
+demo = get_app(
+    models=SAMBANOVA_MODELS_FULL,  # Use the full names with prefix
+    default_model=SAMBANOVA_MODELS_FULL[-1],
+    dropdown_label="Select Sambanova Model",
+    choices=SAMBANOVA_MODELS_DISPLAY,  # Display names without prefix
+    fill_height=True,
+    coder=True,
+)

pyproject.toml

@@ -38,7 +38,7 @@ dependencies = [
     "langchain>=0.3.14",
     "chromadb>=0.5.23",
     "openai>=1.55.0",
-    "ai-gradio[crewai,deepseek,gemini,groq,hyperbolic,openai,smolagents,transformers, langchain, mistral,minimax,nvidia, qwen]>=0.2.41",
+    "ai-gradio[crewai,deepseek,gemini,groq,hyperbolic,openai,smolagents,transformers, langchain, mistral,minimax,nvidia, qwen]>=0.2.42",
 ]
 
 [tool.uv.sources]

requirements.txt

@@ -2,7 +2,7 @@
 #    uv pip compile pyproject.toml -o requirements.txt
 accelerate==1.2.1
     # via ai-gradio
-ai-gradio==0.2.41
+ai-gradio==0.2.42
     # via anychat (pyproject.toml)
 aiofiles==23.2.1
     # via gradio