143 lines
6.1 KiB
Plaintext
143 lines
6.1 KiB
Plaintext
# Small Quiz (ungraded) [[quiz1]]
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Let's test your understanding of `smolagents` with a quick quiz! Remember, testing yourself helps reinforce learning and identify areas that may need review.
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This is an optional quiz and it's not graded.
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### Q1: What is one of the primary advantages of choosing `smolagents` over other frameworks?
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Which statement best captures a core strength of the `smolagents` approach?
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<Question
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choices={[
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{
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text: "It uses highly specialized configuration files and a steep learning curve to ensure only expert developers can use it",
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explain: "smolagents is designed for simplicity and minimal code complexity, not steep learning curves.",
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},
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{
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text: "It supports a code-first approach with minimal abstractions, letting agents interact directly via Python function calls",
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explain: "Yes, smolagents emphasizes a straightforward, code-centric design with minimal abstractions.",
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correct: true
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},
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{
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text: "It focuses on JSON-based actions, removing the need for agents to write any code",
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explain: "While smolagents supports JSON-based tool calls (ToolCallingAgents), the library emphasizes code-based approaches with CodeAgents.",
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},
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{
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text: "It deeply integrates with a single LLM provider and specialized hardware",
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explain: "smolagents supports multiple model providers and does not require specialized hardware.",
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}
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]}
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/>
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---
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### Q2: In which scenario would you likely benefit most from using smolagents?
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Which situation aligns well with what smolagents does best?
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<Question
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choices={[
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{
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text: "Prototyping or experimenting quickly with agent logic, particularly when your application is relatively straightforward",
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explain: "Yes. smolagents is designed for simple and nimble agent creation without extensive setup overhead.",
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correct: true
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},
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{
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text: "Building a large-scale enterprise system where you need dozens of microservices and real-time data pipelines",
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explain: "While possible, smolagents is more focused on lightweight, code-centric experimentation rather than heavy enterprise infrastructure.",
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},
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{
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text: "Needing a framework that only supports cloud-based LLMs and forbids local inference",
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explain: "smolagents offers flexible integration with local or hosted models, not exclusively cloud-based LLMs.",
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},
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{
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text: "A scenario that requires advanced orchestration, multi-modal perception, and enterprise-scale features out-of-the-box",
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explain: "While you can integrate advanced capabilities, smolagents itself is lightweight and minimal at its core.",
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}
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]}
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/>
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---
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### Q3: smolagents offers flexibility in model integration. Which statement best reflects its approach?
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Choose the most accurate description of how smolagents interoperates with LLMs.
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<Question
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choices={[
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{
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text: "It only provides a single built-in model and does not allow custom integrations",
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explain: "smolagents supports multiple different backends and user-defined models.",
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},
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{
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text: "It requires you to implement your own model connector for every LLM usage",
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explain: "There are multiple prebuilt connectors that make LLM integration straightforward.",
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},
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{
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text: "It only integrates with open-source LLMs but not commercial APIs",
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explain: "smolagents can integrate with both open-source and commercial model APIs.",
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},
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{
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text: "It can be used with a wide range of LLMs, offering predefined classes like TransformersModel, HfApiModel, and LiteLLMModel",
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explain: "This is correct. smolagents supports flexible model integration through various classes.",
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correct: true
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}
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]}
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/>
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---
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### Q4: How does smolagents handle the debate between code-based actions and JSON-based actions?
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Which statement correctly characterizes smolagents' philosophy about action formats?
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<Question
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choices={[
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{
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text: "It only allows JSON-based actions for all agent tasks, requiring a parser to extract the tool calls",
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explain: "ToolCallingAgent uses JSON-based calls, but smolagents also provides a primary CodeAgent option that writes Python code.",
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},
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{
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text: "It focuses on code-based actions via a CodeAgent but also supports JSON-based tool calls with a ToolCallingAgent",
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explain: "Yes, smolagents primarily recommends code-based actions but includes a JSON-based alternative for users who prefer it or need it.",
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correct: true
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},
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{
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text: "It disallows any external function calls, instead requiring all logic to reside entirely within the LLM",
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explain: "smolagents is specifically designed to grant LLMs the ability to call tools or code externally.",
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},
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{
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text: "It requires users to manually convert every code snippet into a JSON object before running the agent",
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explain: "smolagents can automatically manage code snippet creation within the CodeAgent path, no manual JSON conversion necessary.",
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}
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]}
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/>
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---
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### Q5: How does smolagents integrate with the Hugging Face Hub for added benefits?
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Which statement accurately describes one of the core advantages of Hub integration?
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<Question
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choices={[
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{
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text: "It automatically upgrades all public models to commercial license tiers",
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explain: "Hub integration doesn't change the license tier for models or tools.",
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},
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{
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text: "It disables local inference entirely, forcing remote model usage only",
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explain: "Users can still do local inference if they prefer; pushing to the Hub doesn't override local usage.",
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},
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{
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text: "It allows you to push and share agents or tools, making them easily discoverable and reusable by other developers",
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explain: "Correct. smolagents supports uploading agents and tools to the HF Hub for others to reuse.",
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correct: true
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},
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{
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text: "It permanently stores all your code-based agents, preventing any updates or versioning",
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explain: "Hub repositories support updates and version control, so you can revise your code-based agents any time.",
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}
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]}
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/>
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---
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Congratulations on completing this quiz! 🎉 If you missed any questions, consider reviewing the *Why use smolagents* section for a deeper understanding. If you did well, you're ready to explore more advanced topics in smolagents!
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