ChatGPTRetrievalPluginClient#

class llama_index.vector_stores.ChatGPTRetrievalPluginClient(endpoint_url: str, bearer_token: Optional[str] = None, retries: Optional[Retry] = None, batch_size: int = 100, **kwargs: Any)#

Bases: VectorStore

ChatGPT Retrieval Plugin Client.

In this client, we make use of the endpoints defined by ChatGPT.

Parameters
  • endpoint_url (str) – URL of the ChatGPT Retrieval Plugin.

  • bearer_token (Optional[str]) – Bearer token for the ChatGPT Retrieval Plugin.

  • retries (Optional[Retry]) – Retry object for the ChatGPT Retrieval Plugin.

  • batch_size (int) – Batch size for the ChatGPT Retrieval Plugin.

Attributes Summary

Methods Summary

add(nodes, **add_kwargs)

Add nodes to index.

delete(ref_doc_id, **delete_kwargs)

Delete nodes using with ref_doc_id.

query(query, **kwargs)

Get nodes for response.

Attributes Documentation

client#

Get client.

is_embedding_query: bool = False#
stores_text: bool = True#

Methods Documentation

add(nodes: List[BaseNode], **add_kwargs: Any) List[str]#

Add nodes to index.

delete(ref_doc_id: str, **delete_kwargs: Any) None#

Delete nodes using with ref_doc_id.

Parameters

ref_doc_id (str) – The doc_id of the document to delete.

query(query: VectorStoreQuery, **kwargs: Any) VectorStoreQueryResult#

Get nodes for response.