maestro.ai.openai.Client.kt Maven / Gradle / Ivy
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Maestro is a server-driven platform-agnostic library that allows to drive tests for both iOS and Android using the same implementation through an intuitive API.
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package maestro.ai.openai
import io.ktor.client.HttpClient
import io.ktor.client.request.post
import io.ktor.client.request.setBody
import io.ktor.client.statement.bodyAsText
import io.ktor.http.ContentType
import io.ktor.http.contentType
import io.ktor.http.isSuccess
import io.ktor.util.encodeBase64
import kotlinx.serialization.SerializationException
import kotlinx.serialization.encodeToString
import kotlinx.serialization.json.Json
import kotlinx.serialization.json.JsonObject
import maestro.ai.AI
import maestro.ai.CompletionData
import maestro.ai.common.Base64Image
import org.slf4j.LoggerFactory
private const val API_URL = "https://api.openai.com/v1/chat/completions"
private val logger = LoggerFactory.getLogger(OpenAI::class.java)
class OpenAI(
defaultModel: String = "gpt-4o-2024-08-06",
httpClient: HttpClient = defaultHttpClient,
private val apiKey: String,
private val defaultTemperature: Float = 0.2f,
private val defaultMaxTokens: Int = 1024,
private val defaultImageDetail: String = "high",
) : AI(defaultModel = defaultModel, httpClient = httpClient) {
private val json = Json { ignoreUnknownKeys = true }
override suspend fun chatCompletion(
prompt: String,
images: List,
temperature: Float?,
model: String?,
maxTokens: Int?,
imageDetail: String?,
identifier: String?,
jsonSchema: JsonObject?,
): CompletionData {
val imagesBase64 = images.map { it.encodeBase64() }
// Fallback to OpenAI defaults
val actualTemperature = temperature ?: defaultTemperature
val actualModel = model ?: defaultModel
val actualMaxTokens = maxTokens ?: defaultMaxTokens
val actualImageDetail = imageDetail ?: defaultImageDetail
val imagesContent = imagesBase64.map { image ->
ContentDetail(
type = "image_url",
imageUrl = Base64Image(url = "data:image/png;base64,$image", detail = actualImageDetail),
)
}
val textContent = ContentDetail(type = "text", text = prompt)
val messages = listOf(
MessageContent(
role = "user",
content = imagesContent + textContent,
)
)
val chatCompletionRequest = ChatCompletionRequest(
model = actualModel,
temperature = actualTemperature,
messages = messages,
maxTokens = actualMaxTokens,
seed = 1566,
responseFormat = if (jsonSchema == null) null else ResponseFormat(
type = "json_schema",
jsonSchema = jsonSchema,
),
)
val chatCompletionResponse = try {
val httpResponse = httpClient.post(API_URL) {
contentType(ContentType.Application.Json)
headers["Authorization"] = "Bearer $apiKey"
setBody(json.encodeToString(chatCompletionRequest))
}
val body = httpResponse.bodyAsText()
if (!httpResponse.status.isSuccess()) {
logger.error("Failed to complete request to OpenAI: ${httpResponse.status}, $body")
throw Exception("Failed to complete request to OpenAI: ${httpResponse.status}, $body")
}
json.decodeFromString(body)
} catch (e: SerializationException) {
logger.error("Failed to parse response from OpenAI", e)
throw e
} catch (e: Exception) {
logger.error("Failed to complete request to OpenAI", e)
throw e
}
return CompletionData(
prompt = prompt,
temperature = actualTemperature,
maxTokens = actualMaxTokens,
images = imagesBase64,
model = actualModel,
response = chatCompletionResponse.choices.first().message.content,
)
}
override fun close() = httpClient.close()
}