Fixed long names in leaderboards

ui/utils.py

@@ -0,0 +1,141 @@
+"""
+UI utilities for the Game Reasoning Arena Gradio app.
+
+This module contains utility functions for the Gradio interface,
+including model name cleaning and display formatting.
+"""
+
+
+def clean_model_name(model_name: str) -> str:
+    """
+    Clean up long model names to display only the essential model name.
+
+    This function handles various model naming patterns from different providers:
+    - LiteLLM models with provider prefixes
+    - vLLM models with prefixes
+    - Models with slash-separated paths
+    - GPT model variants
+
+    Args:
+        model_name: Full model name from database
+                   (e.g., "litellm_together_ai_meta_llama_Meta_Llama_3.1...")
+
+    Returns:
+        Cleaned model name (e.g., "Meta-Llama-3.1-8B-Instruct-Turbo")
+
+    Examples:
+        >>> clean_model_name("litellm_together_ai/meta-llama/Meta-Llama-3.1-8B")
+        "Meta-Llama-3.1-8B"
+        >>> clean_model_name("litellm_fireworks_ai/accounts/fireworks/models/glm-4p5-air")
+        "glm-4p5-air"
+        >>> clean_model_name("vllm_Qwen2-7B-Instruct")
+        "Qwen2-7B-Instruct"
+        >>> clean_model_name("litellm_gpt-4-turbo")
+        "GPT-4-turbo"
+    """
+    if not model_name or model_name == "Unknown":
+        return model_name
+
+    # Handle special cases first
+    if model_name == "None" or model_name.lower() == "random":
+        return "Random Bot"
+
+    # Handle random_None specifically
+    if model_name == "random_None":
+        return "Random Bot"
+
+    # GPT models - keep the GPT part
+    if "gpt" in model_name.lower():
+        # Extract GPT model variants
+        if "gpt_3.5" in model_name.lower() or "gpt-3.5" in model_name.lower():
+            return "GPT-3.5-turbo"
+        elif "gpt_4" in model_name.lower() or "gpt-4" in model_name.lower():
+            if "turbo" in model_name.lower():
+                return "GPT-4-turbo"
+            elif "mini" in model_name.lower():
+                return "GPT-4-mini"
+            else:
+                return "GPT-4"
+        elif "gpt_5" in model_name.lower() or "gpt-5" in model_name.lower():
+            if "mini" in model_name.lower():
+                return "GPT-5-mini"
+            else:
+                return "GPT-5"
+        elif "gpt2" in model_name.lower() or "gpt-2" in model_name.lower():
+            return "GPT-2"
+        elif "distilgpt2" in model_name.lower():
+            return "DistilGPT-2"
+        elif "gpt-neo" in model_name.lower():
+            return "GPT-Neo-125M"
+
+    # For litellm models, extract everything after the last slash
+    if "litellm_" in model_name and "/" in model_name:
+        # Split by "/" and take the last part
+        model_part = model_name.split("/")[-1]
+        # Clean up underscores and make it more readable
+        cleaned = model_part.replace("_", "-")
+        return cleaned
+
+    # For vllm models, extract the model name part
+    if model_name.startswith("vllm_"):
+        # Remove vllm_ prefix
+        model_part = model_name[5:]
+        # Clean up underscores
+        cleaned = model_part.replace("_", "-")
+        return cleaned
+
+    # For litellm models without slashes (from database storage)
+    # These correspond to the slash-separated patterns in the YAML
+    if model_name.startswith("litellm_"):
+        parts = model_name.split("_")
+
+        # Handle Fireworks AI pattern: litellm_fireworks_ai_accounts_fireworks_models_*
+        if "fireworks" in model_name and "accounts" in model_name and "models" in model_name:
+            try:
+                models_idx = parts.index("models")
+                model_parts = parts[models_idx + 1:]
+                return "-".join(model_parts)
+            except ValueError:
+                pass
+
+        # Handle Together AI pattern: litellm_together_ai_meta_llama_*
+        # Original: litellm_together_ai/meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo
+        # Becomes: litellm_together_ai_meta_llama_Meta_Llama_3.1_8B_Instruct_Turbo
+        # We want: Meta-Llama-3.1-8B-Instruct-Turbo
+        if "together" in model_name and "meta" in model_name and "llama" in model_name:
+            try:
+                # Find "meta" and "llama" - the model name starts after "meta_llama_"
+                for i, part in enumerate(parts):
+                    if part == "meta" and i + 1 < len(parts) and parts[i + 1] == "llama":
+                        # Model name starts after "meta_llama_"
+                        model_parts = parts[i + 2:]
+                        return "-".join(model_parts)
+            except Exception:
+                pass
+
+        # Handle Groq pattern: litellm_groq_*
+        # These are simpler patterns
+        if parts[1] == "groq" and len(parts) >= 3:
+            model_parts = parts[2:]  # Everything after "litellm_groq_"
+            cleaned = "-".join(model_parts)
+            # Special handling for common models
+            if "llama3" in cleaned.lower():
+                cleaned = cleaned.replace("llama3", "Llama-3")
+            elif "qwen" in cleaned.lower():
+                cleaned = cleaned.replace("qwen", "Qwen")
+            elif "gemma" in cleaned.lower():
+                cleaned = cleaned.replace("gemma", "Gemma")
+            return cleaned
+
+        # For other patterns, skip first two parts (litellm_provider_)
+        if len(parts) >= 3:
+            model_parts = parts[2:]  # Everything after provider
+            cleaned = "-".join(model_parts)
+            return cleaned
+
+    # For models with slashes but not litellm (like direct model paths)
+    if "/" in model_name:
+        return model_name.split("/")[-1].replace("_", "-")
+
+    # Default: just replace underscores with dashes
+    return model_name.replace("_", "-")