Uses of Class
dev.langchain4j.model.google.genai.GoogleGenAiChatModel.Builder

Uses of GoogleGenAiChatModel.Builder in dev.langchain4j.model.google.genai

Methods in dev.langchain4j.model.google.genai that return GoogleGenAiChatModel.Builder

Modifier and Type	Method	Description
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.allowedFunctionNames(List<String> allowedFunctionNames)	Restricts function calling to only the specified function names.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.apiEndpoint(String apiEndpoint)	Overrides the default API endpoint.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.apiKey(String apiKey)	Sets the Google AI Gemini API key used to authenticate requests.
static GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.builder()
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.cachedContent(String cachedContent)	Sets the name of a previously created cached content resource to use with this model.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.client(com.google.genai.Client client)	Sets a pre-configured Google GenAI Client.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.customHeaders(Map<String,String> customHeaders)	Sets extra HTTP headers to include in every request to the Google GenAI API.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.defaultRequestParameters(dev.langchain4j.model.chat.request.ChatRequestParameters defaultRequestParameters)	Sets default ChatRequestParameters that are merged into every request.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.enableGoogleMaps(boolean googleMaps)	Enables the Google Maps grounding tool, allowing the model to retrieve location-based information.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.enableGoogleSearch(boolean googleSearch)	Enables the Google Search grounding tool, allowing the model to retrieve real-time information from the web.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.enableUrlContext(boolean urlContext)	Enables the URL context tool, allowing the model to read and reason about content at provided URLs.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.frequencyPenalty(Double frequencyPenalty)	Sets the frequency penalty, which reduces the likelihood of repeating tokens proportionally to how often they have appeared in the response so far.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.googleCredentials(com.google.auth.oauth2.GoogleCredentials credentials)	Sets the Google OAuth2 credentials used to authenticate requests via Vertex AI.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.labels(Map<String,String> labels)	Sets labels (key-value metadata) attached to the request.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.listeners(List<dev.langchain4j.model.chat.listener.ChatModelListener> listeners)	Sets the list of ChatModelListeners to be notified on each request and response.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.location(String location)	Sets the Google Cloud region/location for Vertex AI access (e.g.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.logRequests(Boolean logRequests)	Enables debug logging of request details sent to the Google GenAI API.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.logRequestsAndResponses(Boolean logRequestsAndResponses)	Enables debug logging of both request and response details.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.logResponses(Boolean logResponses)	Enables debug logging of response details received from the Google GenAI API.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.maxOutputTokens(Integer maxOutputTokens)	Sets the maximum number of tokens to generate in the response.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.maxRetries(Integer maxRetries)	Sets the number of times to retry a request on transient errors (e.g. rate limits, server errors).
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.modelName(String modelName)	Sets the model to use for chat completions.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.presencePenalty(Double presencePenalty)	Sets the presence penalty, which reduces the likelihood of repeating any token that has already appeared in the response, regardless of frequency.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.projectId(String projectId)	Sets the Google Cloud project ID for Vertex AI access.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.responseFormat(dev.langchain4j.model.chat.request.ResponseFormat responseFormat)	Sets the response format, enabling structured output such as JSON mode or JSON Schema.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.safetySettings(List<com.google.genai.types.SafetySetting> safetySettings)	Sets safety content filter settings to block harmful content.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.seed(Integer seed)	Sets the random seed for deterministic output.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.stopSequences(List<String> stopSequences)	Sets sequences that, when generated, will cause the model to stop generating further tokens.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.temperature(Double temperature)	Sets the sampling temperature in the range [0.0, 2.0].
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.thinkingBudget(Integer thinkingBudget)	The thinking budget to use.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.thinkingLevel(String thinkingLevel)	The thinking level to use.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.timeout(Duration timeout)	Sets the HTTP request timeout for calls to the Google GenAI API.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.topK(Integer topK)	Sets the top-K sampling value.
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.topP(Double topP)	Sets the nucleus sampling probability (top-p).
GoogleGenAiChatModel.Builder	GoogleGenAiChatModel.Builder.vertexSearchDatastore(String vertexSearchDatastore)	Sets the Vertex AI Search datastore to use for grounding the model's responses with enterprise data.