com.simiacryptus.jopenai.models.ChatModels.kt Maven / Gradle / Ivy
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A Java client for OpenAI's API
package com.simiacryptus.jopenai.models
import com.fasterxml.jackson.core.JsonGenerator
import com.fasterxml.jackson.core.JsonParser
import com.fasterxml.jackson.databind.DeserializationContext
import com.fasterxml.jackson.databind.JsonDeserializer
import com.fasterxml.jackson.databind.SerializerProvider
import com.fasterxml.jackson.databind.annotation.JsonDeserialize
import com.fasterxml.jackson.databind.annotation.JsonSerialize
import com.fasterxml.jackson.databind.ser.std.StdSerializer
import com.simiacryptus.jopenai.ApiModel.Usage
import com.simiacryptus.jopenai.models.ChatModels.Companion.values
@JsonDeserialize(using = ChatModelsDeserializer::class)
@JsonSerialize(using = ChatModelsSerializer::class)
open class ChatModels(
val name: String,
modelName: String,
maxTotalTokens: Int,
maxOutTokens: Int = maxTotalTokens,
override val provider: APIProvider,
val inputTokenPricePerK: Double,
val outputTokenPricePerK: Double,
) : OpenAITextModel(
modelName = modelName,
maxTotalTokens = maxTotalTokens,
maxOutTokens = maxOutTokens
) {
override fun toString() = modelName
override fun pricing(usage: Usage) =
(usage.prompt_tokens * inputTokenPricePerK + usage.completion_tokens * outputTokenPricePerK) / 1000.0
companion object {
val GPT35Turbo = ChatModels(
name = "GPT35Turbo",
modelName = "gpt-3.5-turbo",
maxTotalTokens = 16384,
provider = APIProvider.OpenAI,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val GPT4Turbo = ChatModels(
name = "GPT4Turbo",
modelName = "gpt-4-turbo",
maxTotalTokens = 128000,
provider = APIProvider.OpenAI,
inputTokenPricePerK = 0.01,
outputTokenPricePerK = 0.03
)
val GPT4o = ChatModels(
name = "GPT4o",
modelName = "gpt-4o",
maxTotalTokens = 128000,
provider = APIProvider.OpenAI,
inputTokenPricePerK = 0.005,
outputTokenPricePerK = 0.015
)
val GPT4oMini = ChatModels(
name = "GPT4oMini",
modelName = "gpt-4o-mini",
maxTotalTokens = 128000,
provider = APIProvider.OpenAI,
inputTokenPricePerK = 0.005,
outputTokenPricePerK = 0.015
)
val SonarSmallChat128k = ChatModels(
name = "SonarSmallChat128k",
modelName = "llama-3.1-sonar-small-128k-chat",
maxTotalTokens = 128 * 1024,
provider = APIProvider.Perplexity,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val SonarSmallOnline128k = ChatModels(
name = "SonarSmallOnline128k",
modelName = "llama-3.1-sonar-small-128k-online",
maxTotalTokens = 128 * 1024,
provider = APIProvider.Perplexity,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val SonarLargeChat128k = ChatModels(
name = "SonarLargeChat128k",
modelName = "llama-3.1-sonar-large-128k-chat",
maxTotalTokens = 128 * 1024,
provider = APIProvider.Perplexity,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val SonarLargeOnline128k = ChatModels(
name = "SonarLargeOnline128k",
modelName = "llama-3.1-sonar-large-128k-online",
maxTotalTokens = 128 * 1024,
provider = APIProvider.Perplexity,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Mistral7B = ChatModels(
name = "Mistral7B",
modelName = "open-mistral-7b",
maxTotalTokens = 32768,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val Mixtral8x7B = ChatModels(
name = "Mixtral8x7B",
modelName = "open-mixtral-8x7b",
maxTotalTokens = 32768,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val Mixtral8x22B = ChatModels(
name = "Mixtral8x22B",
modelName = "open-mixtral-8x22b",
maxTotalTokens = 65536,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val MistralSmall = ChatModels(
name = "MistralSmall",
modelName = "mistral-small-latest",
maxTotalTokens = 32768,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val MistralMedium = ChatModels(
name = "MistralMedium",
modelName = "mistral-medium-latest",
maxTotalTokens = 32768,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val MistralLarge = ChatModels(
name = "MistralLarge",
modelName = "mistral-large-latest",
maxTotalTokens = 32768,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val MistralNemo = ChatModels(
name = "MistralNemo",
modelName = "open-mistral-nemo",
maxTotalTokens = 128*1024-1,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val Codestral = ChatModels(
name = "Codestral",
modelName = "codestral-latest",
maxTotalTokens = 32768,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val CodestralMamba = ChatModels(
name = "CodestralMamba",
modelName = "open-codestral-mamba",
maxTotalTokens = 128*1024-1,
provider = APIProvider.Mistral,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val Llama_31_405B = ChatModels(
name = "Llama_31_405B",
modelName = "llama-3.1-405b-reasoning",
maxTotalTokens = 1288 * 1024 - 1,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Llama_31_70B = ChatModels(
name = "Llama_31_70B",
modelName = "llama-3.1-70b-versatile",
maxTotalTokens = 1288 * 1024 - 1,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Llama_31_8B = ChatModels(
name = "Llama_31_8B",
modelName = "llama-3.1-8b-instant",
maxTotalTokens = 1288 * 1024 - 1,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val LLaMA270bChat = ChatModels(
name = "LLaMA270bChat",
modelName = "llama2-70b-4096",
maxTotalTokens = 4096,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val LLaMA38b = ChatModels(
name = "LLaMA38b",
modelName = "llama3-8b-8192",
maxTotalTokens = 8192,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val Mixtral8x7bInstructV01 = ChatModels(
name = "Mixtral8x7bInstructV01",
modelName = "mixtral-8x7b-32768",
maxTotalTokens = 32768,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Gemma7bIt = ChatModels(
name = "Gemma7bIt",
modelName = "gemma-7b-it",
maxTotalTokens = 8192,
maxOutTokens = 8192,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Gemma2_9bIt = ChatModels(
name = "Gemma2_9bIt",
modelName = "gemma2-9b-it",
maxTotalTokens = 8192,
maxOutTokens = 8192,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Zephyr7bBeta = ChatModels(
name = "Zephyr7bBeta",
modelName = "zephyr-7b-beta",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val DialoGPTLarge = ChatModels(
name = "DialoGPTLarge",
modelName = "DialoGPT-large",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val YarnMistral7b128k = ChatModels(
name = "YarnMistral7b128k",
modelName = "Yarn-Mistral-7b-128k",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Pygmalion13b = ChatModels(
name = "Pygmalion13b",
modelName = "pygmalion-1.3b",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Opt67b = ChatModels(
name = "Opt67b",
modelName = "opt-6.7b",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val MistralLite = ChatModels(
name = "MistralLite",
modelName = "MistralLite",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Openchat35 = ChatModels(
name = "Openchat35",
modelName = "openchat_3.5",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val NeuralChat7bV3 = ChatModels(
name = "NeuralChat7bV3",
modelName = "neural-chat-7b-v3",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val OpenHermes25Mistral7B = ChatModels(
name = "OpenHermes25Mistral7B",
modelName = "OpenHermes-2.5-Mistral-7B",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Dolphin221Mistral7b = ChatModels(
name = "Dolphin221Mistral7b",
modelName = "dolphin-2.2.1-mistral-7b",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Mistral7BOpenOrca = ChatModels(
name = "Mistral7BOpenOrca",
modelName = "Mistral-7B-OpenOrca",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val DeepseekCoder67bInstruct = ChatModels(
name = "DeepseekCoder67bInstruct",
modelName = "deepseek-coder-6.7b-instruct",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Phi15 = ChatModels(
name = "Phi15",
modelName = "phi-1_5",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val Zephyr7bAlpha = ChatModels(
name = "Zephyr7bAlpha",
modelName = "zephyr-7b-alpha",
maxTotalTokens = 16384,
provider = APIProvider.ModelsLab,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
val AWSLLaMA31_405bChat = ChatModels(
name = "AWSLLaMA31_405bChat",
modelName = "meta.llama3-1-405b-instruct-v1:0",
maxTotalTokens = 128 * 1024 - 1,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.00195,
outputTokenPricePerK = 0.00256
)
val AWSLLaMA31_70bChat = ChatModels(
name = "AWSLLaMA31_70bChat",
modelName = "meta.llama3-1-70b-instruct-v1:0",
maxTotalTokens = 128 * 1024 - 1,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.00195,
outputTokenPricePerK = 0.00256
)
val AWSLLaMA31_8bChat = ChatModels(
name = "AWSLLaMA31_8bChat",
modelName = "meta.llama3-1-8b-instruct-v1:0",
maxTotalTokens = 128 * 1024 - 1,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.00195,
outputTokenPricePerK = 0.00256
)
val AWSLLaMA270bChat = ChatModels(
name = "AWSLLaMA270bChat",
modelName = "meta.llama2-70b-chat-v1",
maxTotalTokens = 2048,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.00195,
outputTokenPricePerK = 0.00256
)
val AWSLLaMA213bChat = ChatModels(
name = "AWSLLaMA213bChat",
modelName = "meta.llama2-13b-chat-v1",
maxTotalTokens = 2048,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.00075,
outputTokenPricePerK = 0.001
)
val Mistral7bInstructV02 = ChatModels(
name = "Mistral7bInstructV02",
modelName = "mistral.mistral-7b-instruct-v0:2",
maxTotalTokens = 32 * 1024,
maxOutTokens = 2 * 1024,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.00015,
outputTokenPricePerK = 0.0002
)
val Mixtral8x7bInstructV01AWS = ChatModels(
name = "Mixtral8x7bInstructV01AWS",
modelName = "mistral.mixtral-8x7b-instruct-v0:1",
maxTotalTokens = 32 * 1024,
maxOutTokens = 2 * 1024,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.00045,
outputTokenPricePerK = 0.0007
)
val MistralLarge2402 = ChatModels(
name = "MistralLarge2402",
modelName = "mistral.mistral-large-2402-v1:0",
maxTotalTokens = 32 * 1024,
maxOutTokens = 4000,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.008,
outputTokenPricePerK = 0.024
)
val MistralLarge2407 = ChatModels(
name = "MistralLarge2407",
modelName = "mistral.mistral-large-2407-v1:0",
maxTotalTokens = 32 * 1024,
maxOutTokens = 4000,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.008,
outputTokenPricePerK = 0.024
)
val AmazonTitanTextLiteV1 = ChatModels(
name = "AmazonTitanTextLiteV1",
modelName = "amazon.titan-text-lite-v1",
maxTotalTokens = 4096,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.0003,
outputTokenPricePerK = 0.0004
)
val AmazonTitanTextExpressV1 = ChatModels(
name = "AmazonTitanTextExpressV1",
modelName = "amazon.titan-text-express-v1",
maxTotalTokens = 8192,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.0008,
outputTokenPricePerK = 0.0016
)
val Claude3OpusAWS = ChatModels(
name = "Claude3OpusAWS",
modelName = "anthropic.claude-3-opus-20240229-v1:0",
maxTotalTokens = 200000,
maxOutTokens = 4096,
provider = APIProvider.AWS,
inputTokenPricePerK = 15.0 / 1000.0,
outputTokenPricePerK = 75.0 / 1000.0
)
val CohereCommandTextV14 = ChatModels(
name = "CohereCommandTextV14",
modelName = "cohere.command-text-v14",
maxTotalTokens = 4000,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.0015,
outputTokenPricePerK = 0.002
)
val AI21J2UltraV1 = ChatModels(
name = "AI21J2UltraV1",
modelName = "ai21.j2-ultra-v1",
maxTotalTokens = 8191,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.0125,
outputTokenPricePerK = 0.0125
)
val AI21J2MidV1 = ChatModels(
name = "AI21J2MidV1",
modelName = "ai21.j2-mid-v1",
maxTotalTokens = 8191,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.0188,
outputTokenPricePerK = 0.0188
)
val Claude35Sonnet = ChatModels(
name = "Claude3Sonnet",
modelName = "anthropic.claude-3-5-sonnet-20240620-v1:0",
maxTotalTokens = 200000,
maxOutTokens = 4096,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.003,
outputTokenPricePerK = 0.015
)
val Claude3Sonnet = ChatModels(
name = "Claude3Sonnet",
modelName = "anthropic.claude-3-sonnet-20240229-v1:0",
maxTotalTokens = 200000,
maxOutTokens = 4096,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.003,
outputTokenPricePerK = 0.015
)
val Claude3Haiku = ChatModels(
name = "Claude3Haiku",
modelName = "anthropic.claude-3-haiku-20240307-v1:0",
maxTotalTokens = 200000,
maxOutTokens = 4096,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.00025,
outputTokenPricePerK = 0.000125
)
val ClaudeV2_1 = ChatModels(
name = "ClaudeV2",
modelName = "anthropic.claude-v2:1",
maxTotalTokens = 100000,
maxOutTokens = 4096,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.008,
outputTokenPricePerK = 0.024
)
val ClaudeV2 = ChatModels(
name = "ClaudeV2",
modelName = "anthropic.claude-v2",
maxTotalTokens = 100000,
maxOutTokens = 4096,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.008,
outputTokenPricePerK = 0.024
)
val ClaudeV2Instant = ChatModels(
name = "ClaudeV2",
modelName = "anthropic.claude-instant-v1",
maxTotalTokens = 100000,
maxOutTokens = 4096,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.0008,
outputTokenPricePerK = 0.0024
)
val LLaMA38bInstructAWS = ChatModels(
name = "LLaMA38bInstructAWS",
modelName = "meta.llama3-8b-instruct-v1:0",
maxTotalTokens = 8192,
maxOutTokens = 2048,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val LLaMA370bInstructAWS = ChatModels(
name = "LLaMA370bInstructAWS",
modelName = "meta.llama3-70b-instruct-v1:0",
maxTotalTokens = 8192,
maxOutTokens = 2048,
provider = APIProvider.AWS,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val LaMA38b = ChatModels(
name = "LaMA38b",
modelName = "llama3-8b-8192",
maxTotalTokens = 8192,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val LLaMA370b = ChatModels(
name = "LLaMA370b",
modelName = "llama3-70b-8192",
maxTotalTokens = 8192,
provider = APIProvider.Groq,
inputTokenPricePerK = 0.0005, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.0015 // Assuming pricing, adjust as necessary
)
val AnthropicClaude3Opus = ChatModels(
name = "Claude3Opus",
modelName = "claude-3-opus-20240229",
maxTotalTokens = 200000,
maxOutTokens = 4096,
provider = APIProvider.Anthropic,
inputTokenPricePerK = 15.0 / 1000.0,
outputTokenPricePerK = 75.0 / 1000.0
)
val AnthropicClaude35Sonnet = ChatModels(
name = "Claude35Sonnet",
modelName = "claude-3-5-sonnet-20240620",
maxTotalTokens = 200000,
maxOutTokens = 4096,
provider = APIProvider.Anthropic,
inputTokenPricePerK = 3.0 / 1000.0,
outputTokenPricePerK = 15.0 / 1000.0
)
val AnthropicClaude3Sonnet = ChatModels(
name = "Claude3Sonnet",
modelName = "claude-3-sonnet-20240229",
maxTotalTokens = 200000,
maxOutTokens = 4096,
provider = APIProvider.Anthropic,
inputTokenPricePerK = 3.0 / 1000.0,
outputTokenPricePerK = 15.0 / 1000.0
)
val AnthropicClaude3Haiku = ChatModels(
name = "Claude3Haiku",
modelName = "claude-3-haiku-20240307",
maxTotalTokens = 200000,
maxOutTokens = 4096,
provider = APIProvider.Anthropic,
inputTokenPricePerK = 0.25 / 1000.0,
outputTokenPricePerK = 1.25 / 1000.0
)
val Gemini15ProPreview = ChatModels(
name = "Gemini15ProPreview",
modelName = "models/gemini-1.5-pro-latest",
maxTotalTokens = 1048576,
maxOutTokens = 8192,
provider = APIProvider.Google,
inputTokenPricePerK = 0.007, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.021
)
val GeminiFlashPreview = ChatModels(
name = "GeminiFlashPreview",
modelName = "gemini-1.5-flash-latest",
maxTotalTokens = 1048576,
maxOutTokens = 8192,
provider = APIProvider.Google,
inputTokenPricePerK = 0.007, // Assuming pricing, adjust as necessary
outputTokenPricePerK = 0.021
)
val GeminiPro = ChatModels(
name = "GeminiPro",
modelName = "models/gemini-pro",
maxTotalTokens = 30720,
maxOutTokens = 2048,
provider = APIProvider.Google,
inputTokenPricePerK = 0.0005,
outputTokenPricePerK = 0.0015
)
// val Gemini10ProVision = ChatModels(
// name = "Gemini10ProVision",
// modelName = "models/gemini-pro-vision",
// maxTotalTokens = 12288,
// maxOutTokens = 4096,
// provider = APIProvider.Google,
// inputTokenPricePerK = 0.002, // Assuming pricing, adjust as necessary
// outputTokenPricePerK = 0.004 // Assuming pricing, adjust as necessary
// )
fun values() = mapOf(
"GPT35Turbo" to GPT35Turbo,
"GPT4Turbo" to GPT4Turbo,
"GPT4o" to GPT4o,
"GPT4oMini" to GPT4oMini,
"SonarSmallChat128k" to SonarSmallChat128k,
"SonarSmallOnline128k" to SonarSmallOnline128k,
"SonarLargeChat128k" to SonarLargeChat128k,
"SonarLargeOnline128k" to SonarLargeOnline128k,
"Llama_31_405B" to Llama_31_405B,
"Llama_31_70B" to Llama_31_70B,
"Llama_31_8B" to Llama_31_8B,
"LLaMA270bChat" to LLaMA270bChat,
"Mixtral8x7bInstructV01" to Mixtral8x7bInstructV01,
"Gemma7bIt" to Gemma7bIt,
"Gemma2_9bIt" to Gemma2_9bIt,
"Zephyr7bBeta" to Zephyr7bBeta,
"DialoGPTLarge" to DialoGPTLarge,
"YarnMistral7b128k" to YarnMistral7b128k,
"Pygmalion13b" to Pygmalion13b,
"Opt67b" to Opt67b,
"MistralLite" to MistralLite,
"Openchat35" to Openchat35,
"NeuralChat7bV3" to NeuralChat7bV3,
"OpenHermes25Mistral7B" to OpenHermes25Mistral7B,
"Dolphin221Mistral7b" to Dolphin221Mistral7b,
"Mistral7BOpenOrca" to Mistral7BOpenOrca,
"DeepseekCoder67bInstruct" to DeepseekCoder67bInstruct,
"Phi15" to Phi15,
"Zephyr7bAlpha" to Zephyr7bAlpha,
"MistralLarge2402" to MistralLarge2402,
"MistralLarge2407" to MistralLarge2407,
"AWSLLaMA31_405bChat" to AWSLLaMA31_405bChat,
"AWSLLaMA31_70bChat" to AWSLLaMA31_70bChat,
"AWSLLaMA31_8bChat" to AWSLLaMA31_8bChat,
"AWSLLaMA270bChat" to AWSLLaMA270bChat,
"AWSLLaMA213bChat" to AWSLLaMA213bChat,
"Mistral7bInstructV02" to Mistral7bInstructV02,
"Mixtral8x7bInstructV01AWS" to Mixtral8x7bInstructV01AWS,
"AmazonTitanTextLiteV1" to AmazonTitanTextLiteV1,
"AmazonTitanTextExpressV1" to AmazonTitanTextExpressV1,
"Claude3OpusAWS" to Claude3OpusAWS,
"LLaMA38bInstructAWS" to LLaMA38bInstructAWS,
"LLaMA370bInstructAWS" to LLaMA370bInstructAWS,
"CohereCommandTextV14" to CohereCommandTextV14,
"AI21J2UltraV1" to AI21J2UltraV1,
"AI21J2MidV1" to AI21J2MidV1,
"Claude35Sonnet" to Claude35Sonnet,
"Claude3Sonnet" to Claude3Sonnet,
"Claude3Haiku" to Claude3Haiku,
"ClaudeV2_1" to ClaudeV2_1,
"ClaudeV2" to ClaudeV2,
"ClaudeV2Instant" to ClaudeV2Instant,
"AnthropicClaude3Opus" to AnthropicClaude3Opus,
"AnthropicClaude35Sonnet" to AnthropicClaude35Sonnet,
"AnthropicClaude3Sonnet" to AnthropicClaude3Sonnet,
"LLaMA38b" to LLaMA38b,
"LLaMA370b" to LLaMA370b,
"LaMA38b" to LaMA38b,
"LLaMA370b" to LLaMA370b,
"AnthropicClaude3Haiku" to AnthropicClaude3Haiku,
"Mistral7B" to Mistral7B,
"Mixtral8x7B" to Mixtral8x7B,
"Mixtral8x22B" to Mixtral8x22B,
"MistralSmall" to MistralSmall,
"MistralMedium" to MistralMedium,
"MistralLarge" to MistralLarge,
"MistralNemo" to MistralNemo,
"CodestralMamba" to CodestralMamba,
"Codestral" to Codestral,
"GeminiFlashPreview" to GeminiFlashPreview,
"Gemini15ProPreview" to Gemini15ProPreview,
"GeminiPro" to GeminiPro,
)
}
}
class ChatModelsSerializer : StdSerializer(ChatModels::class.java) {
override fun serialize(value: ChatModels, gen: JsonGenerator, provider: SerializerProvider) {
values().entries.find { it.value == value }?.key?.let { gen.writeString(it) }
}
}
class ChatModelsDeserializer : JsonDeserializer() {
override fun deserialize(p: JsonParser, ctxt: DeserializationContext): ChatModels {
val modelName = p.readValueAs(String::class.java)
return values()[modelName] ?: throw IllegalArgumentException("Unknown model name: $modelName")
}
} © 2015 - 2025 Weber Informatics LLC | Privacy Policy