[Solved] Given the code snippet below, what will be the effect of passing the tracer to the LLM? from langchain.... Given the code snippet below, what will be the effect of passing the tracer to the LLM? | LangChain

LangChain - LangSmith Observability

Given the code snippet below, what will be the effect of passing the tracer to the LLM?

from langchain.chat_models import ChatOpenAI
from langchain.callbacks import LangChainTracer

tracer = LangChainTracer()
llm = ChatOpenAI(callbacks=[tracer])
response = llm.chat([{'role': 'user', 'content': 'Hello!'}])

AThe LLM will log its steps to LangSmith for tracing

BThe LLM will run without any tracing or logging

CThe code will raise a syntax error due to wrong callback usage

DThe LLM will ignore the tracer and produce no output

Step-by-Step Solution

Solution:

Step 1: Understand passing tracer as callback
Passing LangChainTracer in callbacks enables tracing of LLM steps.
Step 2: Analyze code behavior
The LLM will send its internal steps to LangSmith via the tracer, enabling monitoring.
Final Answer:
The LLM will log its steps to LangSmith for tracing -> Option A
Quick Check:
Callbacks with tracer = tracing enabled [OK]

Quick Trick: Callbacks=[tracer] enables LangSmith tracing [OK]

Common Mistakes:

MISTAKES

Assuming no tracing happens without explicit start call
Thinking callbacks cause syntax errors here
Believing tracer disables output

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Given the code snippet below, what will be the effect of passing the tracer to the LLM?

Step 1: Understand passing tracer as callback

Step 2: Analyze code behavior

Final Answer:

Quick Check:

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