chore: initial public snapshot for github upload

llm-gateway-competitors/litellm-wheel-src/litellm/search/cost_calculator.py

@@ -0,0 +1,53 @@
+"""
+Cost calculation for search providers.
+"""
+from typing import Optional, Tuple
+
+from litellm.utils import get_model_info
+
+
+def search_provider_cost_per_query(
+    model: str,
+    custom_llm_provider: Optional[str] = None,
+    number_of_queries: int = 1,
+    optional_params: Optional[dict] = None,
+) -> Tuple[float, float]:
+    """
+    Calculate cost for search-only providers.
+
+    Returns (input_cost, output_cost) where input_cost = queries * cost_per_query
+    Supports tiered pricing based on max_results parameter.
+
+    Args:
+        model: Model name (e.g., "exa_ai/search", "tavily/search")
+        custom_llm_provider: Provider name (e.g., "exa_ai", "tavily")
+        number_of_queries: Number of search queries performed (default: 1)
+        optional_params: Optional parameters including max_results for tiered pricing
+
+    Returns:
+        Tuple of (input_cost, output_cost) where output_cost is always 0.0
+    """
+    model_info = get_model_info(model=model, custom_llm_provider=custom_llm_provider)
+
+    # Check for tiered pricing (e.g., Exa AI based on max_results)
+    tiered_pricing = model_info.get("tiered_pricing")
+    if tiered_pricing and isinstance(tiered_pricing, list):
+        max_results = (optional_params or {}).get(
+            "max_results", 10
+        )  # default 10 results
+        cost_per_query = 0.0
+
+        for tier in tiered_pricing:
+            range_min, range_max = tier["max_results_range"]
+            if range_min <= max_results <= range_max:
+                cost_per_query = tier["input_cost_per_query"]
+                break
+        else:
+            # Fallback to highest tier if out of range
+            cost_per_query = tiered_pricing[-1]["input_cost_per_query"]
+    else:
+        # Simple flat rate
+        cost_per_query = float(model_info.get("input_cost_per_query") or 0.0)
+
+    total_cost = number_of_queries * cost_per_query
+    return (total_cost, 0.0)  # (input_cost, output_cost)