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Commit ce39294

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TheoKanningTheoKanning
authored
Add JsonProperty snake case names to each variable (TheoKanning#172)
This is a better solution that asking everyone to use snake case in their converter
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+319
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‎.github/workflows/gradle-wrapper-validation.yml

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name: "Validate Gradle Wrapper"
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on: [push, pull_request]
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on:
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push:
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branches: [ main ]
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pull_request:
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branches: [ main ]
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jobs:
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validation:

‎api/build.gradle

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implementation 'com.fasterxml.jackson.core:jackson-annotations:2.9.0'
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compileOnly 'org.projectlombok:lombok:1.18.24'
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annotationProcessor 'org.projectlombok:lombok:1.18.24'
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testImplementation 'com.fasterxml.jackson.core:jackson-databind:2.14.2'
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testImplementation(platform('org.junit:junit-bom:5.8.2'))
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testImplementation('org.junit.jupiter:junit-jupiter')
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}
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compileJava {
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sourceCompatibility = '1.8'
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targetCompatibility = '1.8'
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}
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test {
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useJUnitPlatform()
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}

‎api/src/main/java/com/theokanning/openai/OpenAiHttpException.java

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public OpenAiHttpException(OpenAiError error, Exception parent, int statusCode) {
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super(error.error.message, parent);
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// todo error.error looks dumb
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this.statusCode = statusCode;
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this.code = error.error.code;
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this.param = error.error.param;

‎api/src/main/java/com/theokanning/openai/Usage.java

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package com.theokanning.openai;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import lombok.Data;
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/**
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/**
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* The number of prompt tokens used.
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*/
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@JsonProperty("prompt_tokens")
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long promptTokens;
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/**
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* The number of completion tokens used.
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*/
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@JsonProperty("completion_tokens")
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long completionTokens;
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/**
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* The number of total tokens used
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*/
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@JsonProperty("total_tokens")
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long totalTokens;
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}

‎api/src/main/java/com/theokanning/openai/completion/CompletionRequest.java

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/**
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* The name of the model to use.
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* Required if specifying a fine tuned model or if using the new v1/completions endpoint.
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* Required if specifying a fine-tuned model or if using the new v1/completions endpoint.
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*/
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String model;
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‎api/src/main/java/com/theokanning/openai/completion/CompletionResult.java

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*/
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String id;
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/**
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/**https://beta.openai.com/docs/api-reference/create-completion
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* The type of object returned, should be "text_completion"
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*/
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String object;

‎api/src/main/java/com/theokanning/openai/completion/LogProbResult.java

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package com.theokanning.openai.completion;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import lombok.Data;
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import java.util.List;
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/**
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* The log probability of each token in {@link tokens}
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*/
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@JsonProperty("token_logprobs")
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List<Double> tokenLogprobs;
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/**
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* A map for each index in the completion result.
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* The map contains the top {@link CompletionRequest#logprobs} tokens and their probabilities
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*/
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@JsonProperty("top_logprobs")
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List<Map<String, Double>> topLogprobs;
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/**

‎api/src/main/java/com/theokanning/openai/completion/chat/ChatCompletionChoice.java

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package com.theokanning.openai.completion.chat;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import lombok.Data;
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/**
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/**
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* The reason why GPT-3 stopped generating, for example "length".
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*/
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@JsonProperty("finish_reason")
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String finishReason;
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}

‎api/src/main/java/com/theokanning/openai/completion/chat/ChatCompletionRequest.java

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package com.theokanning.openai.completion.chat;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import lombok.AllArgsConstructor;
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import lombok.Builder;
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import lombok.Data;
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* with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.<br>
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* We generally recommend altering this or temperature but not both.
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*/
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@JsonProperty("top_p")
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Double topP;
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/**
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* The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will
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* be (4096 - prompt tokens).
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*/
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@JsonProperty("max_tokens")
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Integer maxTokens;
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/**
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* Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far,
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* increasing the model's likelihood to talk about new topics.
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*/
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@JsonProperty("presence_penalty")
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Double presencePenalty;
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/**
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* Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far,
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* decreasing the model's likelihood to repeat the same line verbatim.
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@JsonProperty("frequency_penalty")
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Double frequencyPenalty;
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/**
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* vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100
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* should result in a ban or exclusive selection of the relevant token.
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*/
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@JsonProperty("logit_bias")
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Map<String, Integer> logitBias;
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‎api/src/main/java/com/theokanning/openai/embedding/EmbeddingRequest.java

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* To get embeddings for multiple inputs in a single request, pass an array of strings or array of token arrays.
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* Each input must not exceed 2048 tokens in length.
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* <p>
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* Unless your are embedding code, we suggest replacing newlines (\n) in your input with a single space,
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* Unless you are embedding code, we suggest replacing newlines (\n) in your input with a single space,
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* as we have observed inferior results when newlines are present.
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*/
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@NonNull

‎api/src/main/java/com/theokanning/openai/file/File.java

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package com.theokanning.openai.file;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import lombok.Data;
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/**
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/**
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* The creation time in epoch seconds.
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*/
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@JsonProperty("created_at")
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Long createdAt;
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/**

‎api/src/main/java/com/theokanning/openai/finetune/FineTuneEvent.java

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package com.theokanning.openai.finetune;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import lombok.Data;
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/**
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/**
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* The creation time in epoch seconds.
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*/
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@JsonProperty("created_at")
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Long createdAt;
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/**

‎api/src/main/java/com/theokanning/openai/finetune/FineTuneRequest.java

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* The ID of an uploaded file that contains training data.
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*/
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@NonNull
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@JsonProperty("training_file")
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String trainingFile;
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/**
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*/
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@JsonProperty("validation_file")
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String validationFile;
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/**
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* By default, the batch size will be dynamically configured to be ~0.2% of the number of examples in the training
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* set, capped at 256 - in general, we've found that larger batch sizes tend to work better for larger datasets.
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*/
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@JsonProperty("batch_size")
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Integer batchSize;
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/**
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* (larger learning rates tend to perform better with larger batch sizes).
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* We recommend experimenting with values in the range 0.02 to 0.2 to see what produces the best results.
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*/
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@JsonProperty("learning_rate_multiplier")
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Double learningRateMultiplier;
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/**
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* If prompts are extremely long (relative to completions), it may make sense to reduce this weight so as to
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*/
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@JsonProperty("prompt_loss_weight")
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Double promptLossWeight;
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/**
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* Additionally, you must specify {@link FineTuneRequest#classificationNClasses} for multiclass
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* classification or {@link FineTuneRequest#classificationPositiveClass} for binary classification.
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@JsonProperty("compute_classification_metrics")
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Boolean computeClassificationMetrics;
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*
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* This parameter is needed to generate precision, recall, and F1 metrics when doing binary classification.
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@JsonProperty("classification_positive_class")
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String classificationPositiveClass;
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* A larger beta score puts more weight on recall and less on precision.
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@JsonProperty("classification_betas")
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List<Double> classificationBetas;
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‎api/src/main/java/com/theokanning/openai/finetune/FineTuneResult.java

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package com.theokanning.openai.finetune;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import com.theokanning.openai.file.File;
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/**
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@JsonProperty("created_at")
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* The ID of the fine-tuned model, null if tuning job is not finished.
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* This is the id used to call the model.
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@JsonProperty("fine_tuned_model")
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/**
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@JsonProperty("organization_id")
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/**
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@JsonProperty("result_files")
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/**
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@JsonProperty("training_files")
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List<File> trainingFiles;
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@JsonProperty("updated_at")
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Long updatedAt;
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/**
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* Validation files for this fine-tune job.
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@JsonProperty("validation_files")
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List<File> validationFiles;
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}

‎api/src/main/java/com/theokanning/openai/finetune/HyperParameters.java

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package com.theokanning.openai.finetune;
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import com.fasterxml.jackson.annotation.JsonProperty;
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/**
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/**
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*/
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String batchSize;
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Integer batchSize;
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@JsonProperty("learning_rate_multiplier")
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Double learningRateMultiplier;
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/**
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* The number of epochs to train the model for.
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*/
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@JsonProperty("n_epochs")
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Integer nEpochs;
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/**
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* The weight to use for loss on the prompt tokens.
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*/
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@JsonProperty("prompt_loss_weight")
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Double promptLossWeight;
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}

‎api/src/main/java/com/theokanning/openai/image/CreateImageEditRequest.java

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package com.theokanning.openai.image;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import lombok.*;
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/**
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/**
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* The format in which the generated images are returned. Must be one of url or b64_json. Defaults to url.
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@JsonProperty("response_format")
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String responseFormat;
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/**

‎api/src/main/java/com/theokanning/openai/image/CreateImageVariationRequest.java

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package com.theokanning.openai.image;
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import com.fasterxml.jackson.annotation.JsonProperty;
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/**
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@JsonProperty("response_format")
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/**

‎api/src/main/java/com/theokanning/openai/image/ImageResult.java

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package com.theokanning.openai.image;
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import com.fasterxml.jackson.annotation.JsonProperty;
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import java.util.List;
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/**
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* The creation time in epoch seconds.
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Long createdAt;
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Long created;
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/**
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* List of image results.

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