▸case-01 I need to set up a primary LLM-driven worker node in Microsoft AutoGen to generate code and solve problems. Many developers default to creating custom ConversableAgent classes from scratch for standard LLM tasks. Which specialized agent class in AutoGen is designed out-of-the-box as an LLM-powered assistant? | fail→fail | 5,896 | 6,588 | +12% | 1 | 1 | 0% | 1,142 | 1,483 | +30% | 0 | 0 | — |
▸case-02 When creating an interactive workflow in AutoGen, I want an agent that represents human oversight and can execute generated code locally. Should I use AssistantAgent with a custom tool wrapper or a specialized agent built for code execution and human interaction? Specify the correct agent class. | fail→fail | 7,754 | 5,749 | -26% | 1 | 1 | 0% | 1,498 | 1,164 | -22% | 0 | 0 | — |
▸case-03 I am orchestrating a multi-agent system with four distinct AutoGen agents. Instead of manually chaining two-agent turn sequences in a custom loop, what AutoGen orchestration component manages agent selection and turn-taking across group conversations? | fail→fail | 7,776 | 5,792 | -26% | 1 | 1 | 0% | 1,535 | 1,421 | -7% | 0 | 0 | — |
▸case-04 I want to implement a custom agent type in AutoGen with unique message handling logic. Rather than inheriting from AssistantAgent or UserProxyAgent, which core base class in pyautogen provides the foundational messaging capabilities for custom agents? | fail→fail | 8,868 | 5,350 | -40% | 1 | 1 | 0% | 1,591 | 1,271 | -20% | 0 | 0 | — |
▸case-05 I am setting up a Python virtual environment and pyproject.toml dependencies for an AutoGen project. Some setup guides incorrectly suggest installing `autogen-core` or `openai` alone. What is the standard Python package dependency name required for AutoGen setup? | fail→pass | 9,912 | 4,818 | -51% | 1 | 1 | 0% | 1,909 | 1,200 | -37% | 0 | 0 | — |
▸case-06 I am configuring UserProxyAgent code execution settings in AutoGen for a production pipeline. Is it safe practice to execute agent-generated code directly in the host OS environment without isolation, or what security practice should be applied to code execution? | fail→fail | 12,800 | 11,366 | -11% | 1 | 1 | 0% | 2,010 | 2,404 | +20% | 0 | 0 | — |
▸case-07 To prevent infinite loops between automated agents in AutoGen, developers often write custom iteration counters in their application logic. What built-in agent configuration parameter controls the maximum number of consecutive automatic replies an agent can send? | fail→fail | 3,676 | 3,600 | -2% | 1 | 1 | 0% | 654 | 836 | +28% | 0 | 0 | — |
▸case-08 I want to configure an AutoGen UserProxyAgent to ask for human feedback only when explicit criteria or errors occur rather than prompting on every step or never asking. What configuration setting controls when human input is requested? | fail→fail | 8,920 | 6,703 | -25% | 1 | 1 | 0% | 1,712 | 1,582 | -8% | 0 | 0 | — |
▸case-09 When building an autonomous two-agent conversation in AutoGen, agents sometimes converse indefinitely. What explicit configuration practice should be defined in system messages or string matching to cleanly end conversations? | fail→fail | 13,246 | 8,032 | -39% | 1 | 1 | 0% | 2,201 | 1,738 | -21% | 0 | 0 | — |
▸case-10 My AutoGen agents are straying off topic during multi-step reasoning. To improve consistency across turns, what best practice should be applied to the initialization parameters of each agent? | fail→fail | 12,393 | 12,439 | +0% | 1 | 1 | 0% | 2,342 | 2,268 | -3% | 0 | 0 | — |
▸case-11 I need an AutoGen agent to initiate a sub-dialogue with a specialist agent before returning a final answer to the main group chat. Which architectural pattern in AutoGen handles delegating sub-tasks through temporary internal agent dialogues? | fail→fail | 10,212 | 6,165 | -40% | 1 | 1 | 0% | 1,934 | 1,500 | -22% | 0 | 0 | — |
▸case-12 I need my AutoGen agents to retain user preferences and learned facts across multiple separate chat sessions without modifying the underlying model weights. Which AutoGen agent design pattern or capability memory layer supports this requirement? | fail→fail | 10,359 | 10,500 | +1% | 1 | 1 | 0% | 1,935 | 2,188 | +13% | 0 | 0 | — |
▸case-13 Default AutoGen agent response logic uses LLM inference or code execution. What capability allows developers to register custom Python functions to intercept incoming messages and generate specialized automated replies? | fail→fail | 7,053 | 5,674 | -20% | 1 | 1 | 0% | 1,197 | 1,315 | +10% | 0 | 0 | — |
▸case-14 When setting up the `llm_config` dictionary for an AssistantAgent, developers must pass model selection and sampling parameters. What key parameters belong inside this configuration dictionary to control model behavior? | fail→fail | 11,287 | 8,163 | -28% | 1 | 1 | 0% | 2,220 | 1,893 | -15% | 0 | 0 | — |
▸case-15 I need to set up the simplest multi-agent setup in AutoGen where an LLM assistant works iteratively with a human proxy agent to solve a coding problem. What fundamental interaction pattern does this describe? | fail→fail | 7,432 | 7,369 | -1% | 1 | 1 | 0% | 1,420 | 1,711 | +20% | 0 | 0 | — |
▸case-16 We are designing a multi-agent system where agents self-decompose complex user goals into sequence steps without human step-by-step guidance. Which target process domain in multi-agent engineering does this architecture address? | fail→fail | 7,354 | 2,953 | -60% | 1 | 1 | 0% | 1,292 | 728 | -44% | 0 | 0 | — |
▸case-17 When architecting a collaborative system of specialized software agents interacting via message passing, what broad target process category does this fall under? | fail→fail | 8,747 | 2,125 | -76% | 1 | 1 | 0% | 1,490 | 552 | -63% | 0 | 0 | — |
▸case-18 I want my AutoGen AssistantAgent to invoke local Python tools via structured JSON payloads provided by the LLM. What configuration parameter in `llm_config` maps schema definitions to Python functions for execution? | fail→fail | 9,965 | 9,394 | -6% | 1 | 1 | 0% | 1,861 | 2,082 | +12% | 0 | 0 | — |
▸case-19 In Microsoft AutoGen, when creating a `GroupChat` instance to manage turn-taking among multiple agents, developers often default to letting the LLM decide the next speaker dynamically. What parameter on the `GroupChat` class explicitly defines the turn selection strategy (such as choosing 'auto', 'round_robin', 'random', or 'manual')? | fail→fail | 3,070 | 3,675 | +20% | 1 | 1 | 0% | 593 | 1,001 | +69% | 0 | 0 | — |
▸case-20 I am configuring a LangChain application and need to construct a custom `AgentExecutor` with `initialize_agent` using zero-shot react description tools. How should I configure the `AgentExecutor` handle_parsing_errors parameter in LangChain? | fail→fail | 11,408 | 8,312 | -27% | 1 | 1 | 0% | 2,268 | 2,022 | -11% | 0 | 0 | — |
▸case-21 I am building a multi-agent system using CrewAI. I need to define a `Crew` object with `agents`, `tasks`, and a sequential process strategy. How do I configure the `process` parameter on a CrewAI `Crew` class? | fail→fail | 7,288 | 5,544 | -24% | 1 | 1 | 0% | 1,439 | 1,132 | -21% | 0 | 0 | — |
▸case-22 I am writing a raw Python script using the native `openai` package client (v1.0+) to loop tool calls manually. How do I inspect `response.choices[0].message.tool_calls` and append the tool result message to the messages list? | fail→fail | 11,730 | 8,761 | -25% | 1 | 1 | 0% | 2,463 | 2,027 | -18% | 0 | 0 | — |