The GenerativeModelPreview
class is the base class for the generative models that are in preview. NOTE: Don't instantiate this class directly. Use vertexai.preview.getGenerativeModel()
instead.
Package
@google-cloud/vertexaiConstructors
(constructor)(getGenerativeModelParams)
constructor(getGenerativeModelParams: GetGenerativeModelParams);
Constructs a new instance of the GenerativeModelPreview
class
Parameter | |
---|---|
Name | Description |
getGenerativeModelParams |
GetGenerativeModelParams
|
Methods
countTokens(request)
countTokens(request: CountTokensRequest): Promise<CountTokensResponse>;
Makes an async request to count tokens.
The countTokens
function returns the token count and the number of billable characters for a prompt.
Parameter | |
---|---|
Name | Description |
request |
CountTokensRequest
A CountTokensRequest object with the request contents. |
Returns | |
---|---|
Type | Description |
Promise<CountTokensResponse> |
The CountTokensResponse object with the token count. |
const request = {
contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
};
const resp = await generativeModelPreview.countTokens(request);
console.log('count tokens response: ', resp);
generateContent(request)
generateContent(request: GenerateContentRequest | string): Promise<GenerateContentResult>;
Makes an async call to generate content.
The response will be returned in GenerateContentResult.response.
Parameter | |
---|---|
Name | Description |
request |
GenerateContentRequest | string
A GenerateContentRequest object with the request contents. |
Returns | |
---|---|
Type | Description |
Promise<GenerateContentResult> |
The GenerateContentResponse object with the response candidates. |
const request = {
contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
};
const result = await generativeModelPreview.generateContent(request);
console.log('Response: ', JSON.stringify(result.response));
generateContentStream(request)
generateContentStream(request: GenerateContentRequest | string): Promise<StreamGenerateContentResult>;
Makes an async stream request to generate content.
The response is returned chunk by chunk as it's being generated in StreamGenerateContentResult.stream. After all chunks of the response are returned, the aggregated response is available in StreamGenerateContentResult.response.
Parameter | |
---|---|
Name | Description |
request |
GenerateContentRequest | string
|
Returns | |
---|---|
Type | Description |
Promise<StreamGenerateContentResult> |
Promise of StreamGenerateContentResult |
const request = {
contents: [{role: 'user', parts: [{text: 'How are you doing today?'}]}],
};
const streamingResult = await generativeModelPreview.generateContentStream(request);
for await (const item of streamingResult.stream) {
console.log('stream chunk: ', JSON.stringify(item));
}
const aggregatedResponse = await streamingResult.response;
console.log('aggregated response: ', JSON.stringify(aggregatedResponse));
getCachedContent()
getCachedContent(): CachedContent | undefined;
Returns | |
---|---|
Type | Description |
CachedContent | undefined |
getModelName()
getModelName(): string;
Returns | |
---|---|
Type | Description |
string |
getSystemInstruction()
getSystemInstruction(): Content | undefined;
Returns | |
---|---|
Type | Description |
Content | undefined |
startChat(request)
startChat(request?: StartChatParams): ChatSessionPreview;
Instantiates a ChatSessionPreview.
The ChatSessionPreview class is a stateful class that holds the state of the conversation with the model and provides methods to interact with the model in chat mode. Calling this method doesn't make any calls to a remote endpoint. To make remote call, use ChatSessionPreview.sendMessage() or ChatSessionPreview.sendMessageStream().
Parameter | |
---|---|
Name | Description |
request |
StartChatParams
|
Returns | |
---|---|
Type | Description |
ChatSessionPreview |
const chat = generativeModelPreview.startChat();
const result1 = await chat.sendMessage("How can I learn more about Node.js?");
const response1 = await result1.response;
console.log('Response: ', JSON.stringify(response1));
const result2 = await chat.sendMessageStream("What about python?");
const response2 = await result2.response;
console.log('Response: ', JSON.stringify(await response2));