Quiz: LangChain vs LangGraph vs LangSmith

Test your understanding of the specific differences between LangChain and LangGraph frameworks, and their applications in building LLM-powered applications.

Technology mixed 5 Questions Video Quiz

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Q1 Beginner 1 pts

According to the video, what specific problem does RAG (Retrieval Augmented Generation) solve for LLM chatbots? Video Reference:
"to solve this problem you build a rag chatbot which is retrieval augmented generation where you prov..."

It allows LLMs to access private organizational data and documents It improves general internet data training It reduces the size of the language model It eliminates the need for vector databases

Q2 Intermediate 2 pts

The video describes two main categories of LLM-powered applications according to Anthropic's guide. What are they? Video Reference:
"If you categorize LLM powered application into two groups then those two groups uh as per anthropics..."

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Workflows Agents Databases Networks

Q3 Advanced 3 pts

According to the video, what is the key difference between LangChain and LangGraph in terms of their primary use cases? Video Reference:
"So just remember if you are writing a simple linear workflows you use lang chain but if you want to ..."

LangChain is for simple linear workflows, LangGraph is for complex agents LangChain is for databases, LangGraph is for APIs LangChain is for coding, LangGraph is for documentation LangChain is for training, LangGraph is for deployment

Q4 Intermediate 2 pts

In the video's example of a complex t-shirt exchange chatbot, what are the specific steps mentioned that the agent needs to perform? Video Reference:
"to summarize the steps you have to check first the refund policy for the item that they are returnin..."

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Check refund policy Check order details in database Check availability of new item Print shipping label

Q5 Advanced 3 pts

According to the video, what is a key characteristic of graph-based stateful workflow in agentic applications? Video Reference:
"LLM will decide what to do as a next step. So let's say there is some conditional logic and LLM migh..."

LLM autonomously decides the next step with conditional logic It only follows a linear predetermined path It requires manual intervention at each step It cannot make multiple LLM calls

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Quiz: LangChain vs LangGraph vs LangSmith

According to the video, what specific problem does RAG (Retrieval Augmented Generation) solve for LLM chatbots? Video Reference: "to solve this problem you build a rag chatbot which is retrieval augmented generation where you prov..."

The video describes two main categories of LLM-powered applications according to Anthropic's guide. What are they? Video Reference: "If you categorize LLM powered application into two groups then those two groups uh as per anthropics..."

According to the video, what is the key difference between LangChain and LangGraph in terms of their primary use cases? Video Reference: "So just remember if you are writing a simple linear workflows you use lang chain but if you want to ..."

In the video's example of a complex t-shirt exchange chatbot, what are the specific steps mentioned that the agent needs to perform? Video Reference: "to summarize the steps you have to check first the refund policy for the item that they are returnin..."

According to the video, what is a key characteristic of graph-based stateful workflow in agentic applications? Video Reference: "LLM will decide what to do as a next step. So let's say there is some conditional logic and LLM migh..."