Agents – mistral/mistral-small-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

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: As AgentX, I approach tasks systematically. The user wants to know which tools I'll need to find the cheapest flights from London to Paris for tomorrow.

1. **Analyze**: I read the context and understand the task.
2. **Plan**: I'll need to use the 'flights' tool to search, filter, and retrieve flight info. To get the date for 'tomorrow', I'll use the 'calendar' tool. I'll store and retrieve relevant information using the 'memory' tool.
3. **Act**: I'll start by using the 'calendar' tool to find tomorrow's date. I'll then use the 'flights' tool with the appropriate parameters.
4. **Reflect**: After each action, I'll reflect on the results and decide on the next action.
5. **Decide next action**: After getting the flight options, I'll filter the top 3 cheapest, sort them, and store them in memory.

Following the rules, I'll first get the available methods and parameters of each tool.

Response: I will use the 'calendar', 'flights', and 'memory' tools to complete this task.