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

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.

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Output Tokens

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Context

Input

The flights.search_flights call has returned 6 available flights from London to Paris for tomorrow. What is the next tool you will call, and why?

Expected output

The next tool is memory, to store the flights tool call result.

Model output

Reasoning: The task is to determine the next tool to call after the flights.search_flights call has returned 6 available flights from London to Paris for tomorrow. The user's ultimate goal is to find the top 3 cheapest flights. According to the context, the next planned step is to filter the flights by price and select the top 3 cheapest options. This aligns with the user's request and the trajectory outlined in the context. Therefore, the next tool to call is flights.filter_by_price.

Response: The next tool to call is flights.filter_by_price to filter the 6 available flights by price and select the top 3 cheapest options.