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-tiny-eu Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Context

Input

Asses the current state and decide if we are on track or not

Expected output

We are on track

Model output

Reasoning: As a LLM agent, I first read and understood the user's request which was to find available flights from London to Paris for tomorrow. I interpreted the 'tomorrow' to mean the current date plus one day. To determine the current date, I used the 'calendar' tool, which returned '2025-05-29'. I then decided that the 'flights' tool would be the most appropriate to use next to find available flights for the specified date. I will use the 'flights' tool with the parameters 'from_city': 'London', 'to_city': 'Paris', and 'date': '2025-05-29'. Once I have the results from the 'flights' tool, I will compile and present them to the user.

Response: Available flights from London to Paris for 2025-05-29.