Update cost-tracking for OAI chatcompletions and response API

src/agentlab/llm/tracking.py

@@ -163,6 +163,10 @@ def __call__(self, *args, **kwargs):
         response = self._call_api(*args, **kwargs)
 
         usage = dict(getattr(response, "usage", {}))
+        if "prompt_tokens_details" in usage:
+            usage["cached_tokens"] = usage["prompt_token_details"].cached_tokens
+        if "input_tokens_details" in usage:
+            usage["cached_tokens"] = usage["input_tokens_details"].cached_tokens
         usage = {f"usage_{k}": v for k, v in usage.items() if isinstance(v, (int, float))}
         usage |= {"n_api_calls": 1}
         usage |= {"effective_cost": self.get_effective_cost(response)}
@@ -298,21 +302,29 @@ def get_effective_cost_from_openai_api(self, response) -> float:
         Returns:
             float: The effective cost calculated from the response.
         """
-        usage = getattr(response, "usage", {})
-        prompt_token_details = getattr(response, "prompt_tokens_details", {})
-
-        total_input_tokens = getattr(
-            prompt_token_details, "prompt_tokens", 0
-        )  # Cache read tokens + new input tokens
-        output_tokens = getattr(usage, "completion_tokens", 0)
-        cache_read_tokens = getattr(prompt_token_details, "cached_tokens", 0)
+        usage = getattr(response, "usage", None)
+        if usage is None:
+            logging.warning("No usage information found in the response. Defaulting cost to 0.0.")
+            return 0.0
+        api_type = "chatcompletion" if hasattr(usage, "prompt_tokens_details") else "response"
+        if api_type == "chatcompletion":
+            total_input_tokens = usage.prompt_tokens
+            output_tokens = usage.completion_tokens
+            cached_input_tokens = usage.prompt_tokens_details.cached_tokens
+            non_cached_input_tokens = total_input_tokens - cached_input_tokens
+        elif api_type == "response":
+            total_input_tokens = usage.input_tokens
+            output_tokens = usage.output_tokens
+            cached_input_tokens = usage.input_tokens_details.cached_tokens
+            non_cached_input_tokens = total_input_tokens - cached_input_tokens
+        else:
+            logging.warning(f"Unsupported API type: {api_type}. Defaulting cost to 0.0.")
+            return 0.0
 
-        non_cached_input_tokens = total_input_tokens - cache_read_tokens
         cache_read_cost = self.input_cost * OPENAI_CACHE_PRICING_FACTOR["cache_read_tokens"]
-
         effective_cost = (
             self.input_cost * non_cached_input_tokens
-            + cache_read_tokens * cache_read_cost
+            + cached_input_tokens * cache_read_cost
             + self.output_cost * output_tokens
         )
         return effective_cost