Context Reasoning

Context understanding and reasoning tasks test accurate answers grounded in provided context. This capability is essential for knowledge-base support bots, policy lookup systems, and internal knowledge Q&A applications. Models are evaluated on their ability to provide accurate answers that are properly grounded in the given context rather than hallucinating information.

100
Duration
19s
Input Tokens
89720
Output Tokens
235
Cost
$0.00
Context
Input
In the blogpost 'Agentic customer service chatbot with tools, tracing and evals' a python function is created to identify the user intent. What is the name of this function? def name_of_function(messages)
Expected output
determine_intent
Model output
Based on the blogpost 'Agentic customer service chatbot with tools, tracing and evals', the function created to identify user intent is called `determine_intent`. The function signature is:

```python
def determine_intent(messages):
```

This function analyzes conversations to classify user intent into categories like checking order status, searching products, and handling unsupported requests using a structured IntentClassification output type.