Viewing trace details and latency in LangChain - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to enable tracing in LangChain.

LangChain

from langchain import [1]

tracer = [1]()

Drag options to blanks, or click blank then click option'

ATracing

Btrace

CTracer

DTrace

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase 'trace' instead of the class name.

Confusing 'Tracing' with 'Tracer'.

The Tracer class is used to enable tracing in LangChain.

2fill in blank

medium

Complete the code to attach the tracer to the LangChain client.

LangChain

from langchain import LangChainClient

client = LangChainClient()
client.[1] = tracer

Drag options to blanks, or click blank then click option'

Atracer

Btracing

Ctrace

Dtracer_enabled

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'trace' instead of 'tracer' as the attribute name.

Trying to enable tracing with a boolean attribute.

The client uses the tracer attribute to attach the tracer instance.

3fill in blank

hard

Fix the error in printing the latency from the trace details.

LangChain

trace_details = tracer.get_trace()
print(f"Latency: {trace_details.[1] ms")

Drag options to blanks, or click blank then click option'

Alatency

Bduration

Ctime

Ddelay

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'latency' which is not the attribute name.

Using 'time' or 'delay' which do not exist on trace details.

The correct attribute to get latency is duration in milliseconds.

4fill in blank

hard

Fill both blanks to filter trace spans by operation name and minimum latency.

LangChain

filtered_spans = [span for span in tracer.get_trace().spans if span.[1] == '[2]' and span.duration > 100]

Drag options to blanks, or click blank then click option'

Aoperation_name

Bname

Coperation

Dop

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'operation' or 'op' which are not the correct attribute names.

Confusing the attribute name with the value to compare.

The span attribute for the operation is operation_name, and the value to filter by is name.

5fill in blank

hard

Fill all three blanks to create a dictionary of span names and their latencies for spans longer than 200 ms.

LangChain

latency_dict = {span.[1]: span.[2] for span in tracer.get_trace().spans if span.[3] > 200}

Drag options to blanks, or click blank then click option'

Aoperation_name

Bduration

Cduration_ms

Dlatency

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'duration_ms' which is not the attribute name.

Using 'latency' which does not exist as an attribute.

Use operation_name for the key, and duration for the latency attribute and comparison.

Practice

1. What is the main purpose of viewing trace details in a LangChain application?

easy

A. To change the output format of the application

B. To understand the internal steps and flow of the application

C. To increase the speed of the application automatically

D. To add new features without coding

Solution

1. Step 1: Understand what trace details represent

   Trace details show the internal steps and flow of the LangChain app during execution.

2. Step 2: Identify the purpose of viewing these details

   Viewing trace details helps developers see what happens inside, making debugging and optimization easier.

3. Final Answer:

   To understand the internal steps and flow of the application -> Option B

4. Quick Check:

   Trace details = internal flow insight [OK]

Hint: Trace details show what happens inside your app [OK]

Common Mistakes:

• Thinking trace changes output format
• Believing trace speeds up app automatically
• Confusing trace with adding features

2. Which of the following is the correct way to enable LangChainTracer to view trace details?

easy

A. from langchain.callbacks import tracer\ntracer = tracer()

B. import LangChainTracer from langchain.callbacks\ntracer = LangChainTracer()

C. from langchain import LangChainTracer\ntracer = LangChainTracer()

D. from langchain.callbacks import LangChainTracer\ntracer = LangChainTracer()

Solution

1. Step 1: Recall the correct import path for LangChainTracer

   LangChainTracer is imported from langchain.callbacks module.

2. Step 2: Check the correct instantiation syntax

   The correct way is to import LangChainTracer and then create an instance with LangChainTracer().

3. Final Answer:

   from langchain.callbacks import LangChainTracer\ntracer = LangChainTracer() -> Option D

4. Quick Check:

   Correct import and instantiation = from langchain.callbacks import LangChainTracer\ntracer = LangChainTracer() [OK]

Hint: Import from langchain.callbacks and instantiate with () [OK]

Common Mistakes:

• Wrong import path
• Using incorrect import syntax
• Calling a non-existent function

3. Given this code snippet using LangChainTracer, what will be the output regarding latency?

from langchain.callbacks import LangChainTracer
tracer = LangChainTracer()

with tracer:
    result = chain.run("Hello")

print(tracer.get_trace())

medium

A. A detailed trace including each step's latency in milliseconds

B. Only the final output without any timing information

C. An error because get_trace() is not a valid method

D. An empty trace because tracer was not started

Solution

1. Step 1: Understand what LangChainTracer does inside a with block

   LangChainTracer collects detailed trace info including latency for each step during the with block execution.

2. Step 2: Check the output of get_trace()

   get_trace() returns the collected trace data, which includes latency details for each step.

3. Final Answer:

   A detailed trace including each step's latency in milliseconds -> Option A

4. Quick Check:

   Tracer with block + get_trace() = detailed latency trace [OK]

Hint: Tracer inside with block captures latency info [OK]

Common Mistakes:

• Assuming get_trace() does not exist
• Expecting output without timing info
• Forgetting to use with block for tracing

4. You added LangChainTracer but see no trace output after running your chain. What is the most likely cause?

medium

A. The chain.run() method does not support tracing

B. You did not import LangChainTracer correctly

C. You forgot to wrap the chain execution inside the tracer's with block

D. You need to call tracer.start() before running the chain

Solution

1. Step 1: Check how LangChainTracer collects trace data

   LangChainTracer collects trace only when chain execution is inside its with block context.

2. Step 2: Identify the missing step causing no trace output

   If chain.run() is outside the with block, no trace is recorded, so output is empty.

3. Final Answer:

   You forgot to wrap the chain execution inside the tracer's with block -> Option C

4. Quick Check:

   Tracing requires with block wrapping chain run [OK]

Hint: Always run chain inside tracer's with block [OK]

Common Mistakes:

• Assuming import error causes no trace
• Thinking chain.run() disables tracing
• Trying to call non-existent start() method

5. You want to find the slowest step in your LangChain app using LangChainTracer. Which approach correctly identifies it?

hard

A. Extract latency from each trace step and find the maximum value

B. Check the total runtime of the app without step details

C. Use print statements inside the chain to guess slow parts

D. Restart the app multiple times to see when it feels slow

Solution

1. Step 1: Understand what latency data LangChainTracer provides

   LangChainTracer records latency for each individual step in the trace details.

2. Step 2: Identify how to find the slowest step

   By extracting latency values from each step and comparing them, you can find the maximum latency which indicates the slowest step.

3. Final Answer:

   Extract latency from each trace step and find the maximum value -> Option A

4. Quick Check:

   Find max latency in trace steps = slowest step [OK]

Hint: Find max latency value in trace steps to spot slowest [OK]

Common Mistakes:

• Ignoring step-level latency and checking only total time
• Using print statements instead of trace data
• Guessing speed without data