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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Context

Input

Of the available tools. Which ones will you need to use to successfully complete the task?

Expected output

All tools will need to be used: calendar, flights,memory

Model output

Reasoning: To determine the tools needed to complete the task, I analyzed the user's request and the provided context. The task is to find the cheapest flights from London to Paris for tomorrow and return the top 3 options. Here's my step-by-step reasoning:
    1. The task requires retrieving flight information, specifically filtering by price and date. The 'flights' tool is directly relevant for this purpose, as it has methods like 'search_flights', 'filter_by_price', and 'get_cheapest_option'.
    2. The task also involves handling date-specific information (tomorrow's date). The 'calendar' tool can be used to retrieve tomorrow's date, which is necessary for the flight search.
    3. The 'memory' tool will be used to store meaningful results after every tool call, as per the instructions. This ensures that results are saved and can be retrieved later if needed.
    Therefore, the tools needed are 'calendar', 'flights', and 'memory'.

Response: The tools needed to successfully complete the task are: 'calendar', 'flights', and 'memory'.