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fix!: Use client provided logger and remove optional parameter #81

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Merged
jsonbailey merged 3 commits into from
Jan 2, 2026
Merged

fix!: Use client provided logger and remove optional parameter #81

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10d81f9
fix!: Use client provided logger and remove optional parameter
jsonbailey Jan 2, 2026
260c2b5
Merge branch 'main' into jb/sdk-1720/use-client-logging
jsonbailey Jan 2, 2026
f90d2f5
update to supported ai client version and fix tests
jsonbailey Jan 2, 2026
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35 changes: 14 additions & 21 deletions packages/ai-providers/server-ai-langchain/src/ldai_langchain/langchain_provider.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@

from langchain_core.language_models.chat_models import BaseChatModel
from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
from ldai import LDMessage
from ldai import LDMessage, log
from ldai.models import AIConfigKind
from ldai.providers import AIProvider
from ldai.providers.types import ChatResponse, LDAIMetrics, StructuredResponse
Expand All @@ -18,27 +18,24 @@ class LangChainProvider(AIProvider):
This provider integrates LangChain models with LaunchDarkly's tracking capabilities.
"""

def __init__(self, llm: BaseChatModel, logger: Optional[Any] = None):
def __init__(self, llm: BaseChatModel):
"""
Initialize the LangChain provider.

:param llm: A LangChain BaseChatModel instance
:param logger: Optional logger for logging provider operations
"""
super().__init__(logger)
self._llm = llm

@staticmethod
async def create(ai_config: AIConfigKind, logger: Optional[Any] = None) -> 'LangChainProvider':
async def create(ai_config: AIConfigKind) -> 'LangChainProvider':
"""
Static factory method to create a LangChain AIProvider from an AI configuration.

:param ai_config: The LaunchDarkly AI configuration
:param logger: Optional logger for the provider
:return: Configured LangChainProvider instance
"""
llm = LangChainProvider.create_langchain_model(ai_config)
return LangChainProvider(llm, logger)
return LangChainProvider(llm)

async def invoke_model(self, messages: List[LDMessage]) -> ChatResponse:
"""
Expand All @@ -56,20 +53,18 @@ async def invoke_model(self, messages: List[LDMessage]) -> ChatResponse:
if isinstance(response.content, str):
content = response.content
else:
if self.logger:
self.logger.warn(
f'Multimodal response not supported, expecting a string. '
f'Content type: {type(response.content)}, Content: {response.content}'
)
log.warn(
f'Multimodal response not supported, expecting a string. '
f'Content type: {type(response.content)}, Content: {response.content}'
)
metrics = LDAIMetrics(success=False, usage=metrics.usage)

return ChatResponse(
message=LDMessage(role='assistant', content=content),
metrics=metrics,
)
except Exception as error:
if self.logger:
self.logger.warn(f'LangChain model invocation failed: {error}')
log.warn(f'LangChain model invocation failed: {error}')

return ChatResponse(
message=LDMessage(role='assistant', content=''),
Expand All @@ -94,11 +89,10 @@ async def invoke_structured_model(
response = await structured_llm.ainvoke(langchain_messages)

if not isinstance(response, dict):
if self.logger:
self.logger.warn(
f'Structured output did not return a dict. '
f'Got: {type(response)}'
)
log.warn(
f'Structured output did not return a dict. '
f'Got: {type(response)}'
)
return StructuredResponse(
data={},
raw_response='',
Expand All @@ -117,8 +111,7 @@ async def invoke_structured_model(
),
)
except Exception as error:
if self.logger:
self.logger.warn(f'LangChain structured model invocation failed: {error}')
log.warn(f'LangChain structured model invocation failed: {error}')

return StructuredResponse(
data={},
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