chore(langchain): remove openai cost span metric

ddtrace/contrib/internal/langchain/constants.py

@@ -80,7 +80,3 @@
 }
 
 API_KEY = "langchain.request.api_key"
-MODEL = "langchain.request.model"
-COMPLETION_TOKENS = "langchain.tokens.completion_tokens"
-PROMPT_TOKENS = "langchain.tokens.prompt_tokens"
-TOTAL_COST = "langchain.tokens.total_cost"

ddtrace/contrib/internal/langchain/patch.py

@@ -41,10 +41,6 @@
 
 from ddtrace import config
 from ddtrace.contrib.internal.langchain.constants import API_KEY
-from ddtrace.contrib.internal.langchain.constants import COMPLETION_TOKENS
-from ddtrace.contrib.internal.langchain.constants import MODEL
-from ddtrace.contrib.internal.langchain.constants import PROMPT_TOKENS
-from ddtrace.contrib.internal.langchain.constants import TOTAL_COST
 from ddtrace.contrib.internal.langchain.constants import agent_output_parser_classes
 from ddtrace.contrib.internal.langchain.constants import text_embedding_models
 from ddtrace.contrib.internal.langchain.constants import vectorstore_classes
@@ -114,9 +110,7 @@ def _extract_api_key(instance: Any) -> str:
     return ""
 
 
-def _tag_openai_token_usage(
-    span: Span, llm_output: Dict[str, Any], propagated_cost: int = 0, propagate: bool = False
-) -> None:
+def _tag_openai_token_usage(span: Span, llm_output: Dict[str, Any]) -> None:
     """
     Extract token usage from llm_output, tag on span.
     Calculate the total cost for each LLM/chat_model, then propagate those values up the trace so that
@@ -126,23 +120,6 @@ def _tag_openai_token_usage(
         current_metric_value = span.get_metric("langchain.tokens.%s_tokens" % token_type) or 0
         metric_value = llm_output["token_usage"].get("%s_tokens" % token_type, 0)
         span.set_metric("langchain.tokens.%s_tokens" % token_type, current_metric_value + metric_value)
-    total_cost = span.get_metric(TOTAL_COST) or 0
-    if not propagate and get_openai_token_cost_for_model:
-        try:
-            completion_cost = get_openai_token_cost_for_model(
-                span.get_tag(MODEL),
-                span.get_metric(COMPLETION_TOKENS),
-                is_completion=True,
-            )
-            prompt_cost = get_openai_token_cost_for_model(span.get_tag(MODEL), span.get_metric(PROMPT_TOKENS))
-            total_cost = completion_cost + prompt_cost
-        except ValueError:
-            # If not in langchain's openai model catalog, the above helpers will raise a ValueError.
-            log.debug("Cannot calculate token/cost as the model is not in LangChain's OpenAI model catalog.")
-    if get_openai_token_cost_for_model:
-        span.set_metric(TOTAL_COST, propagated_cost + total_cost)
-    if span._parent is not None:
-        _tag_openai_token_usage(span._parent, llm_output, propagated_cost=propagated_cost + total_cost, propagate=True)
 
 
 def _is_openai_llm_instance(instance):

releasenotes/notes/deprecate-langchain-openai-cost-042f3a04cda9d23b.yaml

@@ -0,0 +1,5 @@
+---
+upgrade:
+  - |
+    langchain: Removes the `langchain.tokens.total_cost` span metric for OpenAI calls. 
+     For continued cost estimation of OpenAI calls, enable `LLM Observability <https://docs.datadoghq.com/llm_observability/>`_.

tests/contrib/langchain/test_langchain.py

@@ -23,7 +23,6 @@
     "meta.langchain.request.openai.parameters.logprobs",
     "meta.langchain.request.openai.parameters.seed",  # langchain-openai llm call now includes seed as param
     "meta.langchain.request.openai.parameters.logprobs",  # langchain-openai llm call now includes seed as param
-    "metrics.langchain.tokens.total_cost",  # total_cost depends on if tiktoken is installed
     # these are sometimes named differently
     "meta.langchain.request.openai.parameters.max_tokens",
     "meta.langchain.request.openai.parameters.max_completion_tokens",

tests/snapshots/tests.contrib.langchain.test_langchain.test_lcel_chain_batch.json

@@ -61,7 +61,6 @@
          "_dd.measured": 1,
          "langchain.tokens.completion_tokens": 16,
          "langchain.tokens.prompt_tokens": 14,
-         "langchain.tokens.total_cost": 5.3e-05,
          "langchain.tokens.total_tokens": 30
        },
        "duration": 6742000,
@@ -95,7 +94,6 @@
          "_dd.measured": 1,
          "langchain.tokens.completion_tokens": 15,
          "langchain.tokens.prompt_tokens": 14,
-         "langchain.tokens.total_cost": 5.1000000000000006e-05,
          "langchain.tokens.total_tokens": 29
        },
        "duration": 3314000,

tests/snapshots/tests.contrib.langchain.test_langchain.test_lcel_chain_complicated.json

@@ -25,7 +25,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 19,
       "langchain.tokens.prompt_tokens": 53,
-      "langchain.tokens.total_cost": 0.0001175,
       "langchain.tokens.total_tokens": 72,
       "process_id": 82010
     },
@@ -60,7 +59,6 @@
          "_dd.measured": 1,
          "langchain.tokens.completion_tokens": 19,
          "langchain.tokens.prompt_tokens": 53,
-         "langchain.tokens.total_cost": 0.0001175,
          "langchain.tokens.total_tokens": 72
        },
        "duration": 3680000,

tests/snapshots/tests.contrib.langchain.test_langchain.test_lcel_chain_nested.json

@@ -25,7 +25,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 53,
       "langchain.tokens.prompt_tokens": 50,
-      "langchain.tokens.total_cost": 0.000181,
       "langchain.tokens.total_tokens": 103,
       "process_id": 82010
     },
@@ -51,7 +50,6 @@
          "_dd.measured": 1,
          "langchain.tokens.completion_tokens": 16,
          "langchain.tokens.prompt_tokens": 18,
-         "langchain.tokens.total_cost": 5.9e-05,
          "langchain.tokens.total_tokens": 34
        },
        "duration": 63808000,
@@ -85,7 +83,6 @@
             "_dd.measured": 1,
             "langchain.tokens.completion_tokens": 16,
             "langchain.tokens.prompt_tokens": 18,
-            "langchain.tokens.total_cost": 5.9e-05,
             "langchain.tokens.total_tokens": 34
           },
           "duration": 61552000,
@@ -119,7 +116,6 @@
          "_dd.measured": 1,
          "langchain.tokens.completion_tokens": 37,
          "langchain.tokens.prompt_tokens": 32,
-         "langchain.tokens.total_cost": 0.000122,
          "langchain.tokens.total_tokens": 69
        },
        "duration": 3288000,

tests/snapshots/tests.contrib.langchain.test_langchain.test_lcel_chain_simple.json

@@ -24,7 +24,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 101,
       "langchain.tokens.prompt_tokens": 20,
-      "langchain.tokens.total_cost": 0.000232,
       "langchain.tokens.total_tokens": 121,
       "process_id": 82010
     },
@@ -61,7 +60,6 @@
          "_dd.measured": 1,
          "langchain.tokens.completion_tokens": 101,
          "langchain.tokens.prompt_tokens": 20,
-         "langchain.tokens.total_cost": 0.000232,
          "langchain.tokens.total_tokens": 121
        },
        "duration": 6142000,

tests/snapshots/tests.contrib.langchain.test_langchain.test_lcel_chain_simple_async.json

@@ -24,7 +24,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 78,
       "langchain.tokens.prompt_tokens": 20,
-      "langchain.tokens.total_cost": 0.000186,
       "langchain.tokens.total_tokens": 98,
       "process_id": 82010
     },
@@ -61,7 +60,6 @@
          "_dd.measured": 1,
          "langchain.tokens.completion_tokens": 78,
          "langchain.tokens.prompt_tokens": 20,
-         "langchain.tokens.total_cost": 0.000186,
          "langchain.tokens.total_tokens": 98
        },
        "duration": 3399000,

tests/snapshots/tests.contrib.langchain.test_langchain.test_lcel_with_tools_openai.json

@@ -37,7 +37,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 32,
       "langchain.tokens.prompt_tokens": 85,
-      "langchain.tokens.total_cost": 9.05e-05,
       "langchain.tokens.total_tokens": 117,
       "process_id": 82010
     },

tests/snapshots/tests.contrib.langchain.test_langchain.test_openai_chat_model_async_generate.json

@@ -43,7 +43,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 150,
       "langchain.tokens.prompt_tokens": 60,
-      "langchain.tokens.total_cost": 0.00038999999999999994,
       "langchain.tokens.total_tokens": 210,
       "process_id": 82010
     },

tests/snapshots/tests.contrib.langchain.test_langchain.test_openai_chat_model_sync_call_langchain_openai.json

@@ -35,7 +35,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 83,
       "langchain.tokens.prompt_tokens": 20,
-      "langchain.tokens.total_cost": 0.00019600000000000002,
       "langchain.tokens.total_tokens": 103,
       "process_id": 82010
     },

tests/snapshots/tests.contrib.langchain.test_langchain.test_openai_chat_model_sync_generate.json

@@ -43,7 +43,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 110,
       "langchain.tokens.prompt_tokens": 60,
-      "langchain.tokens.total_cost": 0.00031,
       "langchain.tokens.total_tokens": 170,
       "process_id": 82010
     },

tests/snapshots/tests.contrib.langchain.test_langchain.test_openai_chat_model_vision_generate.json

@@ -35,7 +35,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 56,
       "langchain.tokens.prompt_tokens": 1151,
-      "langchain.tokens.total_cost": 0,
       "langchain.tokens.total_tokens": 1207,
       "process_id": 34354
     },

tests/snapshots/tests.contrib.langchain.test_langchain.test_openai_llm_async.json

@@ -36,7 +36,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 12,
       "langchain.tokens.prompt_tokens": 10,
-      "langchain.tokens.total_cost": 3.9e-05,
       "langchain.tokens.total_tokens": 22,
       "process_id": 82010
     },

tests/snapshots/tests.contrib.langchain.test_langchain.test_openai_llm_sync.json

@@ -36,7 +36,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 256,
       "langchain.tokens.prompt_tokens": 17,
-      "langchain.tokens.total_cost": 0.0005375,
       "langchain.tokens.total_tokens": 273,
       "process_id": 82010
     },

tests/snapshots/tests.contrib.langchain.test_langchain.test_openai_llm_sync_multiple_prompts.json

@@ -40,7 +40,6 @@
       "_sampling_priority_v1": 1,
       "langchain.tokens.completion_tokens": 271,
       "langchain.tokens.prompt_tokens": 23,
-      "langchain.tokens.total_cost": 0.0005765000000000001,
       "langchain.tokens.total_tokens": 294,
       "process_id": 82010
     },