jiggybase 0.0.19

Client for Jiggy AI JiggyBase, including ChatGPT Retriever Plugins

JiggyBase

JiggyBase is a Python library for interacting with the JiggyBase service at https://jiggy.ai.

Use it to manage your JiggyBase organization and collections, including uploading documents into a collection.

Requirements

• Python 3.6 or above

Installation

pip install jiggybase

Client Usage

To start using JiggyBase in your Python code, you first need to import it:

import jiggybase

After importing, you need to create a JiggyBase client object:

jb = jiggybase.JiggyBase()

Client methods

Here are the available JiggyBase client methods:

• orgs() - Returns a list of Org objects the user is a member of.
• get_org(name_or_id: str) - Returns the Org object matching the given name or ID.
• api_keys() - Returns a list of the user's ApiKey objects.
• authenticated_user() - Returns the authenticated user's User object.
• collections() - Returns a list of all Collection objects in all organizations the user is a member of.
• collection(name: str) - Returns the Collection object matching the given name.

Organization methods

For an Org object (e.g., my_org = jb.get_org("<org_name>")), you have access to the following methods:

• collections() - Returns a list of Collection objects within the organization.

• collection(name: str) - Returns the Collection object matching the given name.

• update([name: Optional[str] = None, description: Optional[str] = None]) - Updates the organization's name or description.

Collection methods

For a Collection object (e.g., my_collection = jb.collection("<collection_name>")), you have access to the following methods:

(adapt the usage code for each method accordingly)

• set_description(self, description: str) - Updates the description of the collection.
• set_oauth_verification_token(self, openai_verification_token: str) - Sets the OpenAI verification token for the collection's plugin.
• plugin_oauth_config() - Retrieves the OAuth configuration for the collection's plugin.
• delete() - Deletes the collection permanently.
• get_chat_config() - Retrieves the chat configuration for the collection.
• update_chat_config(model: str, prompt_task_id: int) - Updates the chat configuration for the collection.
• upsert_file(file_path: str[, mimetype: str = None]) - Uploads a file to the collection.
• upsert(documents: List[Document]) - Adds a list of Document objects to the collection.
• query(queries: Union[str, List[str], Query][, top_k : int = 10]) - Queries the collection and returns a QueryResponse object.
• get_doc(id: str) - Retrieves a document by its ID.
• get_chunks([start: int = 0, limit: int = 10, reverse: bool = True]) - Iterates through the chunks in a collection.
• delete_docs([ids: Optional[List[str]] = None, document_metadata_filter: Optional[DocumentMetadataFilter] = None, delete_all: Optional[bool] = False]) - Deletes items in the collection by document IDs, metadata filter, or deletes all documents.

Organization User Management

• members() - Returns a list of OrgMember objects within the organization.
• add_member(email: str, role: OrgRole) - Adds a new member to the organization with the given email and role.
• delete_member(email: str) - Deletes a member from the organization using the given email.

Organization Prompt Management

• prompt_tasks([name=None, version=None]) - Returns a list of PromptTask objects, optionally filtering by name and version.
• create_prompt_task(name: str, version: int, prompts: List[PromptMessage][, type: Optional[PromptTaskType] = None, description: Optional[str] = None]) - Creates a new PromptTask object with the specified parameters.
• update_prompt_task(name: str, prompts: List[PromptMessage]) - Updates the specified prompt task's prompts.
• get_prompt_task(prompt_task_id: int) - Retrieves a PromptTask object using the given prompt_task_id.
• delete_prompt_task(prompt_task_id: int) - Deletes a PromptTask object using the given prompt_task_id.