io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.jdp Maven / Gradle / Ivy
io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.logRequests=Whether chat model requests should be logged
io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.logResponses=Whether chat model responses should be logged
io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.maxOutputTokens=Maximum number of tokens that can be generated in the response. A token is approximately four characters. 100 tokens\ncorrespond to roughly 60-80 words.\nSpecify a lower value for shorter responses and a higher value for potentially longer responses.
io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.modelId=The id of the model to use
io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.temperature=The temperature is used for sampling during response generation, which occurs when topP and topK are applied.\nTemperature controls the degree of randomness in token selection. Lower temperatures are good for prompts that require a\nless open-ended or creative response, while higher temperatures can lead to more diverse or creative results.\nA temperature of 0 means that the highest probability tokens are always selected. In this case, responses for a given\nprompt are mostly deterministic, but a small amount of variation is still possible.\n\nIf the model returns a response that's too generic, too short, or the model gives a fallback response, try increasing the\ntemperature.\n
\nRange for gemini-1.0-pro-001\n
\nRange for gemini-1.0-pro-002, gemini-1.5-pro\: 0.0 - 2.0\n
\nDefault for gemini-1.5-pro and gemini-1.0-pro-002\: 1.0\n
\nDefault for gemini-1.0-pro-001\: 0.9
io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.timeout=Global timeout for requests to gemini APIs
io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.topK=Top-K changes how the model selects tokens for output. A top-K of 1 means the next selected token is the most probable\namong all tokens in the model's vocabulary (also called greedy decoding),\nwhile a top-K of 3 means that the next token is selected from among the three most probable tokens by using temperature.\n
\nFor each token selection step, the top-K tokens with the highest probabilities are sampled. Then tokens are further\nfiltered based on top-P with the final token selected using temperature sampling.\n
\nSpecify a lower value for less random responses and a higher value for more random responses.\n
\nRange\: 1-40\n
\nDefault for gemini-1.5-pro\: 0.94\n
\nDefault for gemini-1.0-pro\: 1
io.quarkiverse.langchain4j.vertexai.runtime.gemini.config.ChatModelConfig.topP=Top-P changes how the model selects tokens for output. Tokens are selected from the most (see top-K) to least probable\nuntil the sum of their probabilities equals the top-P value.\nFor example, if tokens A, B, and C have a probability of 0.3, 0.2, and 0.1 and the top-P value is 0.5, then the model\nwill select either A or B as the next token by using temperature and excludes C as a candidate.\n
\nSpecify a lower value for less random responses and a higher value for more random responses.\n
\nRange\: 0.0 - 1.0\n
\ngemini-1.0-pro and gemini-1.5-pro don't support topK