Function Indexing

The library supports function indexing (with some limitations). This means that you can index your functions and then query them using the func-ai library. This is useful if you want to query your functions using natural language and especially when you have a lot of functions which cannot fit in LLM context.

The Function Indexer (FI) relies on chromadb vector store to store function descriptions and then perform semantic search on those descriptions to find the most relevant functions.

Limitations:

• partials while supported for indexing and function wrapping using OpenAIFunctionWrapper cannot be rehydrated in the index once it is reloaded (e.g. app restart). The suggested workaround is at app/script startup to reindex the partials which will not re-add them in the index but will only rehydrate them in the index map.

Usage

import chromadb
from chromadb import Settings
from dotenv import load_dotenv

from func_ai.function_indexer import FunctionIndexer


def function_to_index(a: int, b: int) -> int:
    """
    This is a function that adds two numbers

    :param a: First number
    :param b: Second number
    :return: Sum of a and b
    """
    return a + b


def another_function_to_index() -> str:
    """
    This is a function returns hello world

    :return: Hello World
    """

    return "Hello World"


def test_function_indexer_init_no_args_find_function_enhanced_summary():
    load_dotenv()
    _indexer = FunctionIndexer(chroma_client=chromadb.PersistentClient(settings=Settings(allow_reset=True)))
    _indexer.reset_function_index()
    _indexer.index_functions([function_to_index, another_function_to_index], enhanced_summary=True)
    _results = _indexer.find_functions("Add two numbers", max_results=10, similarity_threshold=0.2)
    assert len(_results) == 1
    assert _results[0].function(1, 2) == 3


if __name__ == "__main__":
    test_function_indexer_init_no_args_find_function_enhanced_summary()

The above code shows how to use the two main functions of the Function Indexer:

• index_functions which indexes a list of functions
• find_functions which finds functions based on a query string

API Docs

FunctionIndexer

Init args:

• chroma_client: A chromadb client to use for storing the function index. If not provided a new client will be created using the default settings (e.g. chromadb.PersistentClient(settings=Settings(allow_reset=True))).
• llm_interface: An LLM interface to use for function wrapping. If not provided a new LLM interface will be created using the default settings (e.g. OpenAIInterface()).
• embedding_function: A function that takes a string and returns an embedding. If not provided the default embedding function will be used (e.g. embedding_functions.OpenAIEmbeddingFunction()).
• collection_name: The name of the collection to use for storing the function index. If not provided the defaults to function_index.

Note: You should always initialize your FunctionIndexer with the same embedding function

index_functions

Args:

• functions: A list of functions to index
• enhanced_summary: If True the function summary will be enhanced with the function docstring. Defaults to False.
• llm_interface: An LLM interface to use for function wrapping. If not provided the one used in Indexer init will be used

find_functions

Args:

• query: The query string to use for finding functions
• max_results: The maximum number of results to return. Defaults to 2.
• similarity_threshold: The similarity threshold to use for filtering results. Defaults to 1.0.

Returns a named tuple SearchResult with the following fields:

• function: The function actual function that can be directly called
• name: The function name
• wrapper: The OpenAIFunctionWrapper function wrapper
• distance: The distance of the function from the query string

Note: The returned list is sorted by distance in ascending order (e.i. the first result is the closest to the query)

functions_summary

Returns: A dictionary containing function names and their descriptions.

index_wrapper_functions

This identical to index_functions but the list of functions is a list of OpenAIFunctionWrapper objects.