feat: implement model initialization based on environment API keys

README.md

@@ -30,4 +30,4 @@ A powerful AI coding assistant that can create and preview Gradio applications i
 
 ## Docker Deployment
 
-This Space runs a simplified Docker configuration optimized for Hugging Face Spaces, with the main Gradio application running directly on port 7860.
+This Space runs a simplified Docker configuration optimized for Hugging Face Spaces, with the main Gradio application running directly on port 7860.

app.py

@@ -427,6 +427,68 @@ def get_default_provider():
     return "Anthropic"
 
 
+def initialize_model_from_environment():
+    """Initialize the model configuration based on available API keys in environment."""
+    default_provider = get_default_provider()
+    available_providers = get_available_providers()
+    current_model_id = os.getenv("MODEL_ID", "")
+
+    print(f"🔍 Available providers: {available_providers}")
+    print(f"🔍 Default provider: {default_provider}")
+    print(f"🔍 Current MODEL_ID: {current_model_id if current_model_id else 'NOT_SET'}")
+
+    # If we have available providers, check if current model matches the
+    # default provider
+    if available_providers:
+        expected_model = get_default_model_for_provider(default_provider)
+
+        # If MODEL_ID doesn't match the expected model for available provider,
+        # override it
+        if current_model_id != expected_model:
+            print(
+                f"🔧 MODEL_ID mismatch: expected {expected_model} for "
+                f"{default_provider}, got {current_model_id}"
+            )
+            print("🔧 Configuring based on available providers...")
+
+            # Set the model for the default provider
+            if default_provider != "Hugging Face":
+                env_var_map = {
+                    "Anthropic": "ANTHROPIC_API_KEY",
+                    "OpenAI": "OPENAI_API_KEY",
+                    "SambaNova": "SAMBANOVA_API_KEY",
+                    "Mistral": "MISTRAL_API_KEY",
+                }
+
+                env_var_name = env_var_map.get(default_provider)
+                api_key = os.getenv(env_var_name)
+
+                print(
+                    f"🔧 Checking {default_provider} with key: "
+                    f"{'SET' if api_key else 'NOT_SET'}"
+                )
+
+                if api_key:
+                    os.environ["API_KEY"] = api_key
+                    os.environ["MODEL_ID"] = expected_model
+                    print(
+                        f"🔧 Auto-configured model: {default_provider}"
+                        f"-> {expected_model}"
+                    )
+                    print("🔧 Set API_KEY and MODEL_ID environment variables")
+                    return True
+                else:
+                    print(f"❌ No API key found for {default_provider}")
+            else:
+                print("🔧 Default provider is Hugging Face, keeping current model")
+        else:
+            print(f"✅ MODEL_ID matches expected model for {default_provider}")
+    else:
+        print("ℹ️ No available providers detected, keeping current model")
+
+    return False
+
+
 def save_api_key(provider, api_key):
     """Save API key to environment variable and update model accordingly."""
     if not api_key.strip():
@@ -917,6 +979,10 @@ if __name__ == "__main__":
 
     from kiss_agent import KISSAgent
 
+    # Initialize model configuration based on available API keys
+    print("🔍 Checking for available API keys...")
+    initialize_model_from_environment()
+
     agent = KISSAgent()
 
     # Start the preview app automatically when the main app starts