Select by n-gram overlap

The NGramOverlapExampleSelector selects and orders examples based on which examples are most similar to the input, according to an ngram overlap score. The ngram overlap score is a float between 0.0 and 1.0, inclusive.

The selector allows for a threshold score to be set. Examples with an ngram overlap score less than or equal to the threshold are excluded. The threshold is set to -1.0, by default, so will not exclude any examples, only reorder them. Setting the threshold to 0.0 will exclude examples that have no ngram overlaps with the input.

from langchain.prompts import FewShotPromptTemplate, PromptTemplate
from langchain.prompts.example_selector.ngram_overlap import NGramOverlapExampleSelector

example_prompt = PromptTemplate(
    input_variables=["input", "output"],
    template="Input: {input}\nOutput: {output}",
)

# Examples of a fictional translation task.
examples = [
    {"input": "See Spot run.", "output": "Ver correr a Spot."},
    {"input": "My dog barks.", "output": "Mi perro ladra."},
    {"input": "Spot can run.", "output": "Spot puede correr."},
]

example_selector = NGramOverlapExampleSelector(
    # The examples it has available to choose from.
    examples=examples,
    # The PromptTemplate being used to format the examples.
    example_prompt=example_prompt,
    # The threshold, at which selector stops.
    # It is set to -1.0 by default.
    threshold=-1.0,
    # For negative threshold:
    # Selector sorts examples by ngram overlap score, and excludes none.
    # For threshold greater than 1.0:
    # Selector excludes all examples, and returns an empty list.
    # For threshold equal to 0.0:
    # Selector sorts examples by ngram overlap score,
    # and excludes those with no ngram overlap with input.
)
dynamic_prompt = FewShotPromptTemplate(
    # We provide an ExampleSelector instead of examples.
    example_selector=example_selector,
    example_prompt=example_prompt,
    prefix="Give the Spanish translation of every input",
    suffix="Input: {sentence}\nOutput:",
    input_variables=["sentence"],
)

# An example input with large ngram overlap with "Spot can run."
# and no overlap with "My dog barks."
print(dynamic_prompt.format(sentence="Spot can run fast."))

Give the Spanish translation of every input

Input: Spot can run.
Output: Spot puede correr.

Input: See Spot run.
Output: Ver correr a Spot.

Input: My dog barks.
Output: Mi perro ladra.

Input: Spot can run fast.
Output:

# You can add examples to NGramOverlapExampleSelector as well.
new_example = {"input": "Spot plays fetch.", "output": "Spot juega a buscar."}

example_selector.add_example(new_example)
print(dynamic_prompt.format(sentence="Spot can run fast."))

Give the Spanish translation of every input

Input: Spot can run.
Output: Spot puede correr.

Input: See Spot run.
Output: Ver correr a Spot.

Input: Spot plays fetch.
Output: Spot juega a buscar.

Input: My dog barks.
Output: Mi perro ladra.

Input: Spot can run fast.
Output:

# You can set a threshold at which examples are excluded.
# For example, setting threshold equal to 0.0
# excludes examples with no ngram overlaps with input.
# Since "My dog barks." has no ngram overlaps with "Spot can run fast."
# it is excluded.
example_selector.threshold = 0.0
print(dynamic_prompt.format(sentence="Spot can run fast."))

Give the Spanish translation of every input

Input: Spot can run.
Output: Spot puede correr.

Input: See Spot run.
Output: Ver correr a Spot.

Input: Spot plays fetch.
Output: Spot juega a buscar.

Input: Spot can run fast.
Output:

# Setting small nonzero threshold
example_selector.threshold = 0.09
print(dynamic_prompt.format(sentence="Spot can play fetch."))

Give the Spanish translation of every input

Input: Spot can run.
Output: Spot puede correr.

Input: Spot plays fetch.
Output: Spot juega a buscar.

Input: Spot can play fetch.
Output:

# Setting threshold greater than 1.0
example_selector.threshold = 1.0 + 1e-9
print(dynamic_prompt.format(sentence="Spot can play fetch."))

Give the Spanish translation of every input

Input: Spot can play fetch.
Output: