LangChain ecosystem (LangSmith, LangGraph, LangServe) - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the LangSmith client correctly.

LangChain

from langchain.[1] import LangSmithClient

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

Alangsmith

Blanggraph

Clangserve

Dcore

Attempts:

3 left

💡 Hint

Common Mistakes

Importing LangSmithClient from langgraph or langserve modules.

Using incorrect module names like 'core'.

The LangSmith client is imported from the langsmith module in LangChain.

2fill in blank

medium

Complete the code to create a LangGraph client instance.

LangChain

client = [1]()

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

ALangServeClient

BLangGraphClient

CLangSmithClient

DLangChainClient

Attempts:

3 left

💡 Hint

Common Mistakes

Using LangSmithClient or LangServeClient instead of LangGraphClient.

Trying to instantiate a non-existent LangChainClient.

The LangGraph client is created by calling LangGraphClient().

3fill in blank

hard

Fix the error in this LangServe server start code by filling the blank.

LangChain

from langchain.[1] import start_server

start_server()

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

Alanggraph

Blangsmith

Clangserve

Dcore

Attempts:

3 left

💡 Hint

Common Mistakes

Importing start_server from langsmith or langgraph modules.

Forgetting to import start_server before calling it.

The start_server function is imported from the langserve module to run the LangServe server.

4fill in blank

hard

Fill both blanks to create a LangSmith client and log a run.

LangChain

client = [1]()
run = client.[2](name="test_run")

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

ALangSmithClient

BLangGraphClient

Cstart_server

Dlog_run

Attempts:

3 left

💡 Hint

Common Mistakes

Using LangGraphClient instead of LangSmithClient.

Calling start_server instead of log_run on the client.

We create a LangSmithClient instance and call its log_run method to log a run.

5fill in blank

hard

Fill all three blanks to import LangGraphClient, create it, and visualize a graph.

LangChain

from langchain.[1] import [2]
client = [2]()
client.[3]()

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

Alanggraph

BLangGraphClient

Cvisualize

Dlangsmith

Attempts:

3 left

💡 Hint

Common Mistakes

Importing from langsmith or using LangSmithClient here.

Calling wrong methods like start_server instead of visualize.

We import LangGraphClient from langgraph, create an instance, and call its visualize method to show the graph.

Practice

1. Which LangChain ecosystem tool is primarily used to track and log your language app runs?

easy

A. LangFlow

B. LangGraph

C. LangServe

D. LangSmith

Solution

1. Step 1: Understand the purpose of LangSmith and differentiate from other tools

   LangSmith is designed to track and log the execution of language applications, capturing run data. LangGraph visualizes app processes, and LangServe helps deploy apps, so they do not focus on logging.

2. Final Answer:

   LangSmith -> Option D

3. Quick Check:

   Tracking runs = LangSmith [OK]

Hint: Remember: Smith = logs and tracks runs [OK]

Common Mistakes:

• Confusing LangGraph with logging tool
• Thinking LangServe handles logging
• Assuming LangFlow is part of LangChain ecosystem

2. Which of the following is the correct way to start LangServe to deploy your app?

easy

A. langsmith deploy my_app.py

B. langserve start --app my_app.py

C. langgraph visualize my_app.py

D. serve langchain --run my_app.py

Solution

1. Step 1: Identify LangServe command syntax and eliminate incorrect commands

   LangServe uses the command langserve start --app <file> to deploy an app. Other options use wrong tool names or commands not related to LangServe.

2. Final Answer:

   langserve start --app my_app.py -> Option B

3. Quick Check:

   Deploy app = langserve start [OK]

Hint: Deploy apps with 'langserve start --app' command [OK]

Common Mistakes:

• Using langsmith or langgraph commands to deploy
• Mixing command order or flags
• Assuming 'serve langchain' is valid

3. Given this code snippet using LangGraph:

from langchain.tools import LangGraph
graph = LangGraph(app=my_app)
graph.show()

What will happen when graph.show() is called?

medium

A. It visually displays the language task flow of the app

B. It logs the app run details to LangSmith dashboard

C. It deploys the app to a server for sharing

D. It raises a syntax error due to missing parameters

Solution

1. Step 1: Understand LangGraph's role and analyze the code behavior

   LangGraph is used to visualize how language tasks flow in an app, showing a graphical representation. Calling graph.show() triggers the visual display of the app's task graph, not logging or deployment.

2. Final Answer:

   It visually displays the language task flow of the app -> Option A

3. Quick Check:

   graph.show() = visual flow display [OK]

Hint: LangGraph = visualize app flow, show() displays it [OK]

Common Mistakes:

• Confusing visualization with logging
• Thinking it deploys the app
• Assuming code has syntax errors

4. You wrote this code to deploy your app with LangServe:

import langserve
langserve.run('my_app.py')

But it raises an error. What is the likely cause?

medium

A. The method 'run' does not exist in LangServe; use 'start' instead

B. You must import LangSmith, not LangServe, to deploy apps

C. The filename must be a module, not a string

D. LangServe requires a config file, missing here

Solution

1. Step 1: Check LangServe API usage and confirm other options

   LangServe does not have a 'run' method; the correct command is 'start' to deploy apps. Importing LangSmith is unrelated to deployment, filename as string is valid, and config file is optional.

2. Final Answer:

   The method 'run' does not exist in LangServe; use 'start' instead -> Option A

3. Quick Check:

   Use 'start' method, not 'run' [OK]

Hint: LangServe uses 'start', not 'run' to deploy [OK]

Common Mistakes:

• Using 'run' instead of 'start'
• Confusing LangSmith with LangServe
• Thinking filename must be a module object

5. You want to build a language app that you can deploy, track, and visualize easily. Which sequence of LangChain ecosystem tools should you use?

hard

A. Use LangGraph to deploy, LangServe to track runs, and LangSmith to visualize flow

B. Use LangSmith to deploy, LangGraph to track runs, and LangServe to visualize flow

C. Use LangServe to deploy, LangSmith to track runs, and LangGraph to visualize flow

D. Use LangServe to track runs, LangGraph to deploy, and LangSmith to visualize flow

Solution

1. Step 1: Match each tool to its function and arrange tools in correct usage order

   LangServe deploys apps, LangSmith tracks and logs runs, LangGraph visualizes the app's task flow. First deploy with LangServe, then track runs with LangSmith, and visualize with LangGraph.

2. Final Answer:

   Use LangServe to deploy, LangSmith to track runs, and LangGraph to visualize flow -> Option C

3. Quick Check:

   Deploy, track, visualize = Serve, Smith, Graph [OK]

Hint: Deploy with Serve, track with Smith, visualize with Graph [OK]

Common Mistakes:

• Mixing up tool roles
• Using LangSmith for deployment
• Assuming LangGraph tracks runs