tri.ai.openai.OpenAiCompletionChat.kt Maven / Gradle / Ivy
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LLM and prompt engineering.
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/*-
* #%L
* tri.promptfx:promptkt
* %%
* Copyright (C) 2023 - 2024 Johns Hopkins University Applied Physics Laboratory
* %%
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* #L%
*/
package tri.ai.openai
import com.aallam.openai.api.chat.ChatCompletionRequest
import com.aallam.openai.api.chat.ChatMessage
import com.aallam.openai.api.chat.ChatResponseFormat
import com.aallam.openai.api.chat.ChatRole
import com.aallam.openai.api.model.ModelId
import tri.ai.core.TextCompletion
import tri.ai.openai.OpenAiModelIndex.GPT35_TURBO
import tri.ai.prompt.trace.AiPromptTrace
/** Text completion with OpenAI chat models. */
class OpenAiCompletionChat(override val modelId: String = GPT35_TURBO, val client: OpenAiClient = OpenAiClient.INSTANCE) :
TextCompletion {
override fun toString() = modelId
override suspend fun complete(text: String, tokens: Int?, temperature: Double?, stop: String?, numResponses: Int?) =
complete(text, tokens, temperature, stop, null, numResponses)
suspend fun complete(text: String, tokens: Int?, temperature: Double?, stop: String?, requestJson: Boolean?, numResponses: Int?): AiPromptTrace =
client.chatCompletion(ChatCompletionRequest(
ModelId(modelId),
listOf(ChatMessage(ChatRole.User, text)),
temperature = temperature,
maxTokens = tokens,
stop = stop?.let { listOf(it) },
responseFormat = if (requestJson == true) ChatResponseFormat.JsonObject else null,
n = numResponses
))
}