sectionorder:
- Connect
- Collect
category: Cloud Services
provider: Google
commonfields:
  id: GoogleGemini
  version: -1
configuration:
- additionalinfo: Choose whether to authenticate with a Google AI Studio API Key or a Google Cloud Vertex AI Service Account.
  defaultvalue: AI Studio API Key
  display: Authentication Type
  name: auth_type
  options:
  - AI Studio API Key
  - Vertex AI Service Account
  required: true
  section: Connect
  type: 15
- defaultvalue: https://generativelanguage.googleapis.com
  additionalinfo: "For AI Studio: https://generativelanguage.googleapis.com. For Vertex AI: https://aiplatform.googleapis.com (auto-detected if unchanged)."
  display: Server URL
  name: url
  required: true
  section: Connect
  type: 0
- name: api_key
  displaypassword: API Key
  required: false
  type: 9
  section: Connect
  hiddenusername: true
  additionalinfo: "API Key for Google AI Studio authentication. Required when using AI Studio."
- name: service_account_key
  displaypassword: Service Account Key (JSON)
  required: false
  type: 9
  section: Connect
  hiddenusername: true
  additionalinfo: "Service Account Key JSON for Vertex AI authentication. Required when using Vertex AI."
- additionalinfo: "Google Cloud Project ID. Required when using Vertex AI."
  display: Project ID
  name: project_id
  required: false
  section: Connect
  type: 0
- additionalinfo: "Google Cloud location for Vertex AI (e.g., 'global', 'us-central1'). Defaults to 'global'."
  defaultvalue: global
  display: Location
  name: location
  required: false
  section: Connect
  type: 0
- defaultvalue: gemini-2.5-flash
  additionalinfo: Please choose only one model, or select another from the list https://ai.google.dev/models.
  display: Default Model
  name: model
  options:
  # Stable models
  - gemini-2.5-pro
  - gemini-2.5-flash
  # Deprecated (Legacy Only) - operational until June 1, 2026
  - gemini-2.0-flash
  - gemini-2.0-flash-lite
  # Preview models
  - gemini-3.1-pro-preview
  - gemini-3.1-flash-preview
  - gemini-3.1-flash-lite
  required: true
  section: Collect
  type: 16
- additionalinfo: The maximum number of tokens that can be generated for the response (1-10000). Defaults to 1024.
  defaultvalue: '1024'
  display: Max tokens
  name: max_tokens
  required: true
  section: Collect
  type: 0
- additionalinfo: Controls the degree of randomness in token selection. Lower values (closer to 0) produce more deterministic outputs, while higher values (up to 2.0) increase randomness and creativity.
  advanced: true
  display: Temperature
  name: temperature
  required: false
  section: Collect
  type: 0
- additionalinfo: Changes how the model selects tokens for output. Tokens are selected from most to least probable until their cumulative probability equals the topP value (0.0-1.0). Lower values for less random responses, higher values for more random responses.
  advanced: true
  display: Top P
  name: top_p
  required: false
  section: Collect
  type: 0
- additionalinfo: Consider only the top K most probable tokens when generating text. Affects the diversity of the generated content.
  advanced: true
  display: Top K
  name: top_k
  required: false
  section: Collect
  type: 0
- display: Trust any certificate (not secure)
  name: insecure
  required: false
  section: Connect
  type: 8
- display: Use system proxy settings
  name: proxy
  required: false
  section: Connect
  type: 8
description: |-
  Google Gemini LLM Integration for AI-powered analysis and chat capabilities.

  This integration provides access to Google Gemini's large language models for:
  - AI-powered chat conversations
  - Text analysis and generation
  - Natural language processing tasks

  Supports both Google AI Studio (API key) and Google Cloud Vertex AI (service account) authentication.
  Supported models include Gemini 2.0 Flash, Gemini 1.5 Pro, and various preview models.
display: Google Gemini
name: GoogleGemini
script:
  commands:
  - arguments:
    - description: The prompt or question to send to the AI model.
      name: prompt
      required: true
    - description: The Gemini model to use for this request. If not specified, uses the default model from configuration.
      name: model
      required: false
    - description: |-
        Optional conversation history in JSON format. Array of message objects with 'role' (user/model) and 'parts' containing text.
        Example: [{"role": "user", "parts": [{"text": "Hello"}]}, {"role": "model", "parts": [{"text": "Hi there!"}]}].
      name: history
      required: false
    - defaultValue: false
      description: If true, saves the complete conversation (including the current exchange) to context under GoogleGemini.Chat.History for reuse in subsequent calls.
      name: save_conversation
      required: false
      auto: PREDEFINED
      predefined:
      - 'true'
      - 'false'
    description: Send a chat message to the Gemini AI model.
    name: google-gemini-send-message
    outputs:
    - contextPath: GoogleGemini.Chat.Prompt
      description: The original prompt sent to the model.
      type: String
    - contextPath: GoogleGemini.Chat.Response
      description: The AI model's response.
      type: String
    - contextPath: GoogleGemini.Chat.Model
      description: The model used for generation.
      type: String
    - contextPath: GoogleGemini.Chat.Temperature
      description: The temperature setting used.
      type: Number
    - contextPath: GoogleGemini.Chat.History
      description: Complete conversation history in Gemini format, updated when save_conversation=true. Can be used as input for the history argument in subsequent calls.
      type: Unknown
    - contextPath: GoogleGemini.Chat.ConversationId
      description: A unique identifier, used to identify the chat session.
      type: String
  dockerimage: demisto/google-api-py3:1.0.0.10182333
  runonce: false
  script: ''
  subtype: python3
  type: python
tests:
- No tests (auto formatted)
fromversion: 6.10.0