Opper

Agents

AI agent reasoning and tool selection tests planning, tool choice, and self-diagnosis capabilities. These skills are crucial for autonomous ticket triage systems and complex agent workflows where models must decide which tools to use, plan multi-step processes, and diagnose when things go wrong. This represents some of the most challenging tasks as they require open-ended reasoning and decision-making.

Agents – mistral/pixtral-large-latest-eu Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Context

Input

What is your next action?

Expected output

The next action is to call the flight tool with the date 2025-05-29,from_city: London, to_city: Paris

Model output

Reasoning: Based on the task and context, the user's request is to find information about available flights from London to Paris for tomorrow. In the previous cycle, the calendar tool was used to determine tomorrow's date, which is '2025-05-29'. The next logical step is to use the 'flights' tool to search for available flights using the provided date and cities (London to Paris). This aligns with the user's goal and follows the instructions to proceed systematically.

Response: The next action is to call the 'flights' tool with the parameters: {'from_city': 'London', 'to_city': 'Paris', 'date': '2025-05-29'}.