The Scenario
Modern LLMs can "call functions" by outputting a JSON object that your backend uses to query an API. You are building a bot for a farming co-op. When a user asks "Will it rain in Stellenbosch tomorrow?", the LLM must realize it needs real-time data and trigger the `get_weather` function.
The Brief
Define the `get_weather` tool schema (the instructions given to the LLM on how and when to use the tool) and the system prompt guiding the bot.
Deliverables
- The JSON Schema for the `get_weather` function (defining parameters like `location` and `date`)
- The description property of the function (crucial, as this tells the LLM *when* to use it)
- The System Prompt instructing the bot to rely on the tool for farming queries rather than guessing
Submission Guidance
Function calling relies entirely on the `description` fields. If you don't explain what `location` means, the AI might pass "my farm" instead of "Stellenbosch". Be explicit with types and examples.
Submit Your Work
Your submission is graded against the rubric on the right. If you pass, you get a public Badge URL you can share on LinkedIn. There is no draft save, so work offline first and paste your finished response here.