​

GridSearch Class

The GridSearch class is used for performing grid search on a given chain.

​

Attributes

• experiments: A list of Experiment objects.
• experiment_results: A DataFrame containing the results of the experiments.
• console: A Rich Console object.
• vectorstore_list: A list of vector stores.
• retrievers_list: A list of retrievers.
• chain: A Chain object.

​

Methods

​

__init__(self, chain)

Initializes a GridSearch object.

​

Parameters

• chain (Chain): A Chain object.

grid_search = GridSearch(chain=RetrievalQA)

​

create_experiments(self, param_grid, loader=None, documents=None)

Creates a list of Experiment objects based on the given parameter grid.

​

Parameters

• param_grid (dict): A dictionary containing the parameter grid.
• loader (Loader): A Loader object.
• documents (list): A list of documents.

​

Example

param_grid = {
    "chunk_size": [50, 300, 500],
    "vector_store": [FAISS],
    "embeddings": [OpenAIEmbeddings(), HuggingFaceEmbeddings()],
}

grid_search.create_experiments(param_grid=param_grid, loader=PyPDFLoader("recycling.pdf"))