TextLLM: Add token usage to response meta

modules/text/module_text_llm/module_text_llm/helpers/models/callbacks.py

@@ -0,0 +1,33 @@
+from langchain.callbacks.base import BaseCallbackHandler
+from langchain_core.outputs import  LLMResult
+from langchain_core.messages.ai import UsageMetadata
+
+from athena import emit_meta, get_meta
+
+
+class UsageHandler(BaseCallbackHandler):
+    def on_llm_end(self, response: LLMResult, **kwargs) -> None:
+        meta = get_meta()
+
+        total_usage = meta.get("total_usage", {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0})
+        llm_calls = meta.get("llm_calls", [])
+
+        for generations in response.generations:
+            for generation in generations:
+                message = generation.dict()["message"]
+                generation_usage: UsageMetadata = message["usage_metadata"]
+                model_name = message["response_metadata"].get("model_name", None)
+
+                total_usage["input_tokens"] += generation_usage["input_tokens"]
+                total_usage["output_tokens"] += generation_usage["output_tokens"]
+                total_usage["total_tokens"] += generation_usage["total_tokens"]
+
+                llm_calls.append({
+                    "model_name": model_name,
+                    "input_tokens": generation_usage["input_tokens"],
+                    "output_tokens": generation_usage["output_tokens"],
+                    "total_tokens": generation_usage["total_tokens"],
+                })
+
+        emit_meta("total_usage", total_usage)
+        emit_meta("llm_calls", llm_calls)

modules/text/module_text_llm/module_text_llm/helpers/models/openai.py

@@ -10,6 +10,8 @@
 
 from athena.logger import logger
 from .model_config import ModelConfig
+from .callbacks import UsageHandler
+
 
 OPENAI_PREFIX = "openai_"
 AZURE_OPENAI_PREFIX = "azure_openai_"
@@ -132,6 +134,7 @@ def get_model(self) -> BaseLanguageModel:
                     # Otherwise, add it to model_kwargs (necessary for chat models)
                     model_kwargs[attr] = value
             kwargs["model_kwargs"] = model_kwargs
+            kwargs["callbacks"] = [UsageHandler()]
 
             # Initialize a copy of the model using the config
             model = model.__class__(**kwargs)