ChatGoogleVertexAI

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Node Details

• Name: chatGoogleVertexAI
• Type: ChatGoogleVertexAI
• Version: 4.0
• Category: Chat Models
• Name: chatGoogleVertexAI
• Type: ChatGoogleVertexAI
• Version: 4.0
• Category: Chat Models

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Base Classes

• ChatGoogleVertexAI
• BaseChatModel
• BaseLanguageModel
• Runnable

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Parameters

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Parameters

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Credential

• Type: googleVertexAuth
• Description: Google Vertex AI credential. Not required if using a GCP service like Cloud Run or if default credentials are installed on the local machine.

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Credential

• Type: googleVertexAuth
• Description: Google Vertex AI credential. Not required if using a GCP service like Cloud Run or if default credentials are installed on the local machine.

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Inputs

1. Model Name
   • Type: asyncOptions
   • Default: “chat-bison”
   • Description: The name of the Google Vertex AI model to use

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Inputs

1. Model Name
   • Type: asyncOptions
   • Default: “chat-bison”
   • Description: The name of the Google Vertex AI model to use
2. Cache (optional)
   • Type: BaseCache
   • Description: Caching mechanism for storing and retrieving conversation history
3. Cache (optional)
   • Type: BaseCache
   • Description: Caching mechanism for storing and retrieving conversation history
4. Temperature (optional)
   • Type: number
   • Default: 0.9
   • Step: 0.1
   • Description: Controls the randomness of the model’s output. Higher values make the output more random, while lower values make it more deterministic
5. Temperature (optional)
   • Type: number
   • Default: 0.9
   • Step: 0.1
   • Description: Controls the randomness of the model’s output. Higher values make the output more random, while lower values make it more deterministic
6. Max Output Tokens (optional)
   • Type: number
   • Step: 1
   • Description: The maximum number of tokens to generate in the output
7. Max Output Tokens (optional)
   • Type: number
   • Step: 1
   • Description: The maximum number of tokens to generate in the output
8. Top Probability (Top P) (optional)
   • Type: number
   • Step: 0.1
   • Description: Limits the selection of tokens to a subset that together have a cumulative probability of at most Top P
9. Top Probability (Top P) (optional)
   • Type: number
   • Step: 0.1
   • Description: Limits the selection of tokens to a subset that together have a cumulative probability of at most Top P
10. Top Next Highest Probability Tokens (Top K) (optional)
    • Type: number
    • Step: 1
    • Description: Limits the number of tokens considered for each step of text generation to the K highest probability tokens
11. Top Next Highest Probability Tokens (Top K) (optional)
    • Type: number
    • Step: 1
    • Description: Limits the number of tokens considered for each step of text generation to the K highest probability tokens

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Use Cases

1. Conversational AI: Develop chatbots and virtual assistants that can engage in human-like conversations across various domains.
2. Content Generation: Generate high-quality text content for articles, product descriptions, or creative writing.
3. Language Translation: Utilize the model’s multilingual capabilities for translating text between different languages.
4. Question Answering: Create systems that can understand and respond to user queries with relevant and accurate information.
5. Text Summarization: Automatically generate concise summaries of longer texts or documents.
6. Sentiment Analysis: Analyze the sentiment and emotional tone of text inputs for market research or customer feedback processing.
7. Code Generation and Explanation: Assist developers by generating code snippets or explaining complex code structures.
8. Personalized Recommendations: Generate personalized content or product recommendations based on user preferences and historical data.

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Notes

• This node requires proper authentication with Google Vertex AI services. Ensure that you have the necessary credentials and permissions set up.
• The performance and capabilities of the model may vary depending on the selected model name and parameters.
• Be mindful of token usage and associated costs when using this node in production environments.