chore: update langchain examples to use top-level get_ai_metrics_from_response

Replace LangChainProvider.get_ai_metrics_from_response with the
top-level get_ai_metrics_from_response function from ldai_langchain,
which is the new API in launchdarkly-server-sdk-ai-langchain 0.4.0.

Co-Authored-By: rlamb@launchdarkly.com <4955475+kinyoklion@users.noreply.github.com>

Author: devin-ai-integration[bot]

examples/langchain_example.py

@@ -4,7 +4,7 @@
 from ldclient import Context
 from ldclient.config import Config
 from ldai.client import LDAIClient
-from ldai_langchain import LangChainProvider
+from ldai_langchain import get_ai_metrics_from_response
 from langchain.chat_models import init_chat_model
 
 # Set sdk_key to your LaunchDarkly SDK key.
@@ -89,7 +89,7 @@ async def async_main():
         # Track the LangChain completion with LaunchDarkly metrics using the LD LangChain provider's extractor
         completion = await tracker.track_metrics_of(
             lambda: llm.ainvoke(messages),
-            LangChainProvider.get_ai_metrics_from_response,
+            get_ai_metrics_from_response,
         )
         ai_response = completion.content
 

examples/langgraph_agent_example.py

@@ -5,7 +5,7 @@
 from ldclient.config import Config
 from ldai.client import LDAIClient
 from ldai.tracker import TokenUsage
-from ldai_langchain import LangChainProvider
+from ldai_langchain import get_ai_metrics_from_response
 from langchain.chat_models import init_chat_model
 from langgraph.prebuilt import create_react_agent
 
@@ -36,7 +36,7 @@ def track_langgraph_metrics(tracker, func):
         total_tokens = 0
         if "messages" in result:
             for message in result["messages"]:
-                metrics = LangChainProvider.get_ai_metrics_from_response(message)
+                metrics = get_ai_metrics_from_response(message)
                 if metrics.usage:
                     total_input_tokens += metrics.usage.input
                     total_output_tokens += metrics.usage.output

examples/langgraph_multi_agent_example.py

@@ -4,7 +4,7 @@
 from ldclient.config import Config
 from ldai.client import LDAIClient
 from ldai.tracker import TokenUsage
-from ldai_langchain import LangChainProvider
+from ldai_langchain import get_ai_metrics_from_response
 from langchain.chat_models import init_chat_model
 from langgraph.prebuilt import create_react_agent
 from langgraph.graph import StateGraph, END
@@ -47,7 +47,7 @@ def track_langgraph_metrics(tracker, func, prev_message_count=0):
         if "messages" in result:
             new_messages = result["messages"][prev_message_count:]
             for message in new_messages:
-                metrics = LangChainProvider.get_ai_metrics_from_response(message)
+                metrics = get_ai_metrics_from_response(message)
                 if metrics.usage:
                     total_input_tokens += metrics.usage.input
                     total_output_tokens += metrics.usage.output