mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
985496f4be
Big docs refactor! Motivation is to make it easier for people to find resources they are looking for. To accomplish this, there are now three main sections: - Getting Started: steps for getting started, walking through most core functionality - Modules: these are different modules of functionality that langchain provides. Each part here has a "getting started", "how to", "key concepts" and "reference" section (except in a few select cases where it didnt easily fit). - Use Cases: this is to separate use cases (like summarization, question answering, evaluation, etc) from the modules, and provide a different entry point to the code base. There is also a full reference section, as well as extra resources (glossary, gallery, etc) Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>
2.0 KiB
2.0 KiB
Create a custom example selector
In this tutorial, we'll create a custom example selector that selects examples every alternate example given a list of examples.
An ExampleSelector must implement two methods:
- An
add_examplemethod which takes in an example and adds it into the ExampleSelector - A
select_examplesmethod which takes in input variables (which are meant to be user input) and returns a list of examples to use in the few shot prompt.
Let's implement a custom ExampleSelector that just selects two examples at random.
:::{note} Take a look at the current set of example selector implementations supported in LangChain here. :::
Implement custom example selector
from langchain.prompts.example_selector.base import BaseExampleSelector
from typing import Dict, List
import numpy as np
class CustomExampleSelector(BaseExampleSelector):
def __init__(self, examples: List[Dict[str, str]]):
self.examples = examples
def add_example(self, example: Dict[str, str]) -> None:
"""Add new example to store for a key."""
self.examples.append(example)
def select_examples(self, input_variables: Dict[str, str]) -> List[dict]:
"""Select which examples to use based on the inputs."""
return np.random.choice(self.examples, size=2, replace=False)
Use custom example selector
examples = [
{"foo": "1"},
{"foo": "2"},
{"foo": "3"}
]
# Initialize example selector.
example_selector = CustomExampleSelector(examples)
# Select examples
example_selector.select_examples({"foo": "foo"})
# -> array([{'foo': '2'}, {'foo': '3'}], dtype=object)
# Add new example to the set of examples
example_selector.add_example({"foo": "4"})
example_selector.examples
# -> [{'foo': '1'}, {'foo': '2'}, {'foo': '3'}, {'foo': '4'}]
# Select examples
example_selector.select_examples({"foo": "foo"})
# -> array([{'foo': '1'}, {'foo': '4'}], dtype=object)