Node.js Library

GitHub - kinesysai/cortex-tsGitHub

Documents

.getDocument(knowledgeName: string, documentID: string)

The function .getDocument takes in two parameters: knowledgeName and documentID. It retrieves a specific document from a specified knowledge base. The function returns an AxiosPromise with the document object.

Example return json:

{
    "document": {
        "created": integer,
        "document_id": string,
        "timestamp": integer,
        "tags": string[],
        "source_url": string,
        "hash": string,
        "text_size": integer,
        "chunk_count": integer,
        "chunks": [],
        "text": string
    } 
}

.uploadDocument(knowledgeName: string, documentID: string, document: createDocument)

The function .uploadDocument takes in three parameters: knowledgeName, documentID, and document. It uploads a new document to a specified knowledge base. The function returns an AxiosPromise with the newly uploaded document object and the knowledge object that the document was uploaded to.

The Document object has the following interface:

interface createDocument {
  timestamp?: number;
  tags?: string[];
  text?: string | null;
  source_url?: string | null;
};

Example return json:

{
    "document": {
        "created": integer,
        "document_id": string,
        "timestamp": integer,
        "tags": [],
        "source_url": string,
        "hash": string,
        "text_size": integer,
        "chunk_count": integer,
        "chunks": [
            {
                "text": string,
                "hash": string,
                "offset": 0,
                "vector": [],
                "score": null
            }
        ]
    },
    "knowledge": {
        "name": string,
        "description": string,
        "visibility": "private" | "public",
        "config": "{\"provider_id\":\"openai\",\"model_id\":\"text-embedding-ada-002\",\"extras\":null,\"splitter_id\":\"base_v0\",\"max_chunk_size\":365,\"use_cache\":false}",
        "runnerProjectId": string,
        "lastUpdatedAt": string,
        "hub": null
    }
}

.deleteDocument(knowledgeName: string, documentID: string)

The function .deleteDocument takes in two parameters: knowledgeName and documentID. It deletes a specific document from a specified knowledge base. The function returns an AxiosPromise with the deleted document object.

Callable

.runCallable(callableID: string, data: CallableParams): AxiosPromise<{run: RunType}>

This function runs a callable identified by callableID with the given data. The data parameter must be an object of type CallableParams which includes the version, config, inputs, blocking, and block_filter properties. The version property specifies the version of the callable to run. The config property is an object of configuration parameters for the callable. The inputs property is an array of input values for the callable. The blocking property is a boolean that specifies whether the function should wait for the callable to complete before returning. The block_filter property is an array of block status filters for the callable. The function returns a promise that resolves to an object of type AxiosPromise<{run: RunType}> which includes the status of the run.

.runCallableWithStream(callableID: string, data: CallableParams): AxiosPromise

This function runs a callable identified by callableID with the given data and streams the output. The data parameter must be an object of type CallableParams which includes the version, config, inputs, blocking, and block_filter properties. The version property specifies the version of the callable to run. The config property is an object of configuration parameters for the callable. The inputs property is an array of input values for the callable. The blocking property is a boolean that specifies whether the function should wait for the callable to complete before returning. The block_filter property is an array of block status filters for the callable. The function returns a promise that resolves to an object of type AxiosPromise which includes the streamed output of the callable.

.runChatCompletion(version: string, messages: Message[], input: string, projectID:string, knowledgeName: string, copilotID: string)

Name	Description
version	(string) "latest" | version number
messages	(Message[]) array of messages previously sent to the chat callable
input	(string) chat message that wants to be answered
projectID	(string) projectID of user who created the knowledge that is being referenced
knowledgeName	(string) name of knowledge being referenced
copilotID	(string) ID of chat copilot