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

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

Expected output

We are on track

Model output

Reasoning: 1. The task is to assess the current state and determine if we are on track to fulfill the user's request for flight information from London to Paris for tomorrow (2025-05-29).
2. The context indicates that the calendar tool has already been used successfully to determine tomorrow's date as '2025-05-29'.
3. The next step, as outlined in the trajectory, is to use the 'flights' tool to retrieve available flights for the specified date.
4. The progress is currently at step 2 of 4, and the remaining goals include using the 'flights' tool and presenting the results to the user.
5. Since the current step aligns with the plan and no errors or deviations have been identified, we are on track.
6. The next action should be to execute the 'flights' tool with the parameters: from_city='London', to_city='Paris', and date='2025-05-29'.

Response: We are on track. The next action is to use the 'flights' tool to retrieve available flights from London to Paris for 2025-05-29.