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/mistral-small-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: As AgentX, I understand the user's request is to determine the next action in the current cycle. The user is in cycle 3, and the past trajectory includes determining the date for the flight search.

My next action is to use the 'flights' tool to find available flights from London to Paris on the previously determined date, '2025-05-29'. I will follow the instructions for using the 'flights' tool, including setting the 'from_city' parameter to 'London', the 'to_city' parameter to 'Paris', and the 'date' parameter to '2025-05-29'.

Once I have the results from the 'flights' tool, I will be ready to provide the final answer to the user.


Response: The next action is to use the 'flights' tool to find available flights from London to Paris on the date 2025-05-29.