don't set success

Author: jsonbailey

packages/ai-providers/server-ai-langchain/src/ldai_langchain/langchain_provider.py

@@ -1,5 +1,6 @@
 """LangChain implementation of AIProvider for LaunchDarkly AI SDK."""
 
+from tokenize import Token
 from typing import Any, Dict, List, Optional, Union
 
 from langchain_core.language_models.chat_models import BaseChatModel
@@ -107,11 +108,10 @@ async def invoke_structured_model(
             if raw_response is not None:
                 if hasattr(raw_response, 'content'):
                     structured_response.raw_response = raw_response.content
-                structured_response.metrics = LangChainProvider.get_ai_metrics_from_response(raw_response)
+                structured_response.metrics.usage = LangChainProvider.get_ai_usage_from_response(raw_response)
 
             if response.get('parsing_error'):
                 log.warning(f'LangChain structured model invocation had a parsing error')
-                structured_response.metrics.success = False
                 return structured_response
 
             structured_response.metrics.success = True
@@ -147,24 +147,14 @@ def map_provider(ld_provider_name: str) -> str:
             'bedrock': 'bedrock_converse',
         }
         return mapping.get(lowercased_name, lowercased_name)
-
+    
     @staticmethod
-    def get_ai_metrics_from_response(response: BaseMessage) -> LDAIMetrics:
+    def get_ai_usage_from_response(response: BaseMessage) -> TokenUsage:
         """
-        Get AI metrics from a LangChain provider response.
-
-        This method extracts token usage information and success status from LangChain responses
-        and returns a LaunchDarkly AIMetrics object.
+        Get token usage from a LangChain provider response.
 
         :param response: The response from the LangChain model
-        :return: LDAIMetrics with success status and token usage
-
-        Example:
-            # Use with tracker.track_metrics_of for automatic tracking
-            response = await tracker.track_metrics_of(
-                lambda: llm.ainvoke(messages),
-                LangChainProvider.get_ai_metrics_from_response
-            )
+        :return: TokenUsage with success status and token usage
         """
         # Extract token usage if available
         usage: Optional[TokenUsage] = None
@@ -183,6 +173,29 @@ def get_ai_metrics_from_response(response: BaseMessage) -> LDAIMetrics:
                     output=token_usage.get('completionTokens', 0) or token_usage.get('completion_tokens', 0),
                 )
 
+        return usage
+
+    @staticmethod
+    def get_ai_metrics_from_response(response: BaseMessage) -> LDAIMetrics:
+        """
+        Get AI metrics from a LangChain provider response.
+
+        This method extracts token usage information and success status from LangChain responses
+        and returns a LaunchDarkly AIMetrics object.
+
+        :param response: The response from the LangChain model
+        :return: LDAIMetrics with success status and token usage
+
+        Example:
+            # Use with tracker.track_metrics_of for automatic tracking
+            response = await tracker.track_metrics_of(
+                lambda: llm.ainvoke(messages),
+                LangChainProvider.get_ai_metrics_from_response
+            )
+        """
+        # Extract token usage if available
+        usage = LangChainProvider.get_ai_usage_from_response(response)
+
         return LDAIMetrics(success=True, usage=usage)
 
     @staticmethod
@@ -238,7 +251,7 @@ def create_langchain_model(ai_config: AIConfigKind) -> BaseChatModel:
         # Bedrock requires the foundation provider (e.g. Bedrock:Anthropic) passed in
         # parameters separately from model_provider, which is used for LangChain routing.
         if mapped_provider == 'bedrock_converse' and 'provider' not in parameters:
-            parameters['provider'] = provider
+            parameters['provider'] = provider.removeprefix('bedrock:')
         return init_chat_model(
             model_name,
             model_provider=mapped_provider,