gcp_vertex_ai_chat

Generates responses to messages in a chat conversation, using the Vertex API AI.

Introduced in version 4.34.0.

  • Common

  • Advanced

# Common configuration fields, showing default values
label: ""
gcp_vertex_ai_chat:
  project: "" # No default (required)
  credentials_json: "" # No default (optional)
  location: us-central1 # No default (optional)
  model: gemini-1.5-pro-001 # No default (required)
  prompt: "" # No default (optional)
  temperature: 0 # No default (optional)
  max_tokens: 0 # No default (optional)
  response_format: text
# All configuration fields, showing default values
label: ""
gcp_vertex_ai_chat:
  project: "" # No default (required)
  credentials_json: "" # No default (optional)
  location: us-central1 # No default (optional)
  model: gemini-1.5-pro-001 # No default (required)
  prompt: "" # No default (optional)
  system_prompt: "" # No default (optional)
  temperature: 0 # No default (optional)
  max_tokens: 0 # No default (optional)
  response_format: text
  top_p: 0 # No default (optional)
  top_k: 0 # No default (optional)
  stop: [] # No default (optional)
  presence_penalty: 0 # No default (optional)
  frequency_penalty: 0 # No default (optional)

This processor sends prompts to your chosen large language model (LLM) and generates text from the responses, using the Vertex AI API.

For more information, see the Vertex AI documentation.

Fields

project

The GCP project ID to use.

Type: string

credentials_json

An optional field to set a Google Service Account Credentials JSON.

This field contains sensitive information that usually shouldn’t be added to a config directly, read our secrets page for more info.

Type: string

location

Specify the location of a fine tuned model. For base models, you can omit this field.

Type: string

# Examples

location: us-central1

model

The name of the LLM to use. For a full list of models, see the Vertex AI Model Garden.

Type: string

# Examples

model: gemini-1.5-pro-001

model: gemini-1.5-flash-001

prompt

The prompt you want to generate a response for. By default, the processor submits the entire payload as a string. This field supports interpolation functions.

Type: string

system_prompt

The system prompt to submit to the Vertex AI LLM. This field supports interpolation functions.

Type: string

temperature

Controls the randomness of predictions.

Type: float

max_tokens

The maximum number of output tokens to generate per message.

Type: int

response_format

The format of the generated response. You must also prompt the model to output the appropriate response type.

Type: string

Default: "text"

Options: text , json .

top_p

Enables nucleus sampling (optional).

Type: float

top_k

Enables top-k sampling (optional).

Type: int

stop

Sets the stop sequences to use. When this pattern is encountered the LLM stops generating text and returns the final response.

Type: array

presence_penalty

Positive values penalize new tokens if they appear in the text already, increasing the model’s likelihood to include new topics.

Type: float

frequency_penalty

Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim.

Type: float