Data
DSPy is a machine learning framework, so working in it involves training sets, development sets, and test sets. For each example in your data, we distinguish typically between three types of values: the inputs, the intermediate labels, and the final label. You can use DSPy effectively without any intermediate or final labels, but you will need at least a few example inputs.
DSPy Example objects
The core data type for data in DSPy is Example. You will use Examples to represent items in your training set and test set.
DSPy Examples are similar to Python dicts but have a few useful utilities. Your DSPy modules will return values of the type Prediction, which is a special sub-class of Example.
When you use DSPy, you will do a lot of evaluation and optimization runs. Your individual datapoints will be of type Example:
qa_pair = dspy.Example(question="This is a question?", answer="This is an answer.")
print(qa_pair)
print(qa_pair.question)
print(qa_pair.answer)
Example({'question': 'This is a question?', 'answer': 'This is an answer.'}) (input_keys=None)
This is a question?
This is an answer.
Examples can have any field keys and any value types, though usually values are strings.
You can now express your training set for example as:
Specifying Input Keys
In traditional ML, there are separated "inputs" and "labels".
In DSPy, the Example objects have a with_inputs() method, which can mark specific fields as inputs. (The rest are just metadata or labels.)
# Single Input.
print(qa_pair.with_inputs("question"))
# Multiple Inputs; be careful about marking your labels as inputs unless you mean it.
print(qa_pair.with_inputs("question", "answer"))
Values can be accessed using the .(dot) operator. You can access the value of key name in defined object Example(name="John Doe", job="sleep") through object.name.
To access or exclude certain keys, use inputs() and labels() methods to return new Example objects containing only input or non-input keys, respectively.
article_summary = dspy.Example(article= "This is an article.", summary= "This is a summary.").with_inputs("article")
input_key_only = article_summary.inputs()
non_input_key_only = article_summary.labels()
print("Example object with Input fields only:", input_key_only)
print("Example object with Non-Input fields only:", non_input_key_only)
Output