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feat(client): helpers for discriminated union variants with one required prop (#182)
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lines changed

‎README.md‎

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@@ -93,13 +93,10 @@ To create a new chat completion, first use the `ChatCompletionCreateParams` buil
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```java
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import com.openai.models.ChatCompletion;
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import com.openai.models.ChatCompletionCreateParams;
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import com.openai.models.ChatCompletionUserMessageParam;
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import com.openai.models.ChatModel;
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ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
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.addMessage(ChatCompletionUserMessageParam.builder()
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.content("Say this is a test")
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.build())
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.addUserMessage("Say this is a test")
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.model(ChatModel.O1)
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.build();
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ChatCompletion chatCompletion = client.chat().completions().create(params);

‎openai-java-core/src/main/kotlin/com/openai/models/Assistant.kt‎

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@@ -423,6 +423,13 @@ private constructor(
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*/
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fun addTool(function: FunctionTool) = addTool(AssistantTool.ofFunction(function))
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/**
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* A list of tool enabled on the assistant. There can be a maximum of 128 tools per
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* assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.
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*/
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fun addFunctionTool(function: FunctionDefinition) =
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addTool(FunctionTool.builder().function(function).build())
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/**
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* Specifies the format that the model must output. Compatible with
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* [GPT-4o](https://platform.openai.com/docs/models#gpt-4o), [GPT-4

‎openai-java-core/src/main/kotlin/com/openai/models/BetaAssistantCreateParams.kt‎

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@@ -786,6 +786,13 @@ private constructor(
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*/
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fun addTool(function: FunctionTool) = addTool(AssistantTool.ofFunction(function))
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/**
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* A list of tool enabled on the assistant. There can be a maximum of 128 tools per
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* assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.
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*/
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fun addFunctionTool(function: FunctionDefinition) =
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addTool(FunctionTool.builder().function(function).build())
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/**
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* An alternative to sampling with temperature, called nucleus sampling, where the model
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* considers the results of the tokens with top_p probability mass. So 0.1 means only
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*/
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fun addTool(function: FunctionTool) = apply { body.addTool(function) }
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/**
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* A list of tool enabled on the assistant. There can be a maximum of 128 tools per
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* assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.
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*/
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fun addFunctionTool(function: FunctionDefinition) = apply { body.addFunctionTool(function) }
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/**
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* An alternative to sampling with temperature, called nucleus sampling, where the model
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* considers the results of the tokens with top_p probability mass. So 0.1 means only the
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fun chunkingStrategy(static_: StaticFileChunkingStrategyObjectParam) =
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chunkingStrategy(FileChunkingStrategyParam.ofStatic(static_))
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the
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* `auto` strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) =
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chunkingStrategy(
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StaticFileChunkingStrategyObjectParam.builder().static_(static_).build()
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)
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/**
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* A list of [file](https://platform.openai.com/docs/api-reference/files) IDs to
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* add to the vector store. There can be a maximum of 10000 files in a vector

‎openai-java-core/src/main/kotlin/com/openai/models/BetaAssistantUpdateParams.kt‎

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@@ -788,6 +788,13 @@ private constructor(
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*/
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fun addTool(function: FunctionTool) = addTool(AssistantTool.ofFunction(function))
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/**
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* A list of tool enabled on the assistant. There can be a maximum of 128 tools per
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* assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.
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*/
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fun addFunctionTool(function: FunctionDefinition) =
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addTool(FunctionTool.builder().function(function).build())
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/**
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* An alternative to sampling with temperature, called nucleus sampling, where the model
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* considers the results of the tokens with top_p probability mass. So 0.1 means only
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*/
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fun addTool(function: FunctionTool) = apply { body.addTool(function) }
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/**
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* A list of tool enabled on the assistant. There can be a maximum of 128 tools per
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* assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.
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*/
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fun addFunctionTool(function: FunctionDefinition) = apply { body.addFunctionTool(function) }
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/**
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* An alternative to sampling with temperature, called nucleus sampling, where the model
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* considers the results of the tokens with top_p probability mass. So 0.1 means only the

‎openai-java-core/src/main/kotlin/com/openai/models/BetaThreadCreateAndRunParams.kt‎

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fun chunkingStrategy(static_: StaticFileChunkingStrategyObjectParam) =
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chunkingStrategy(FileChunkingStrategyParam.ofStatic(static_))
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the
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* `auto` strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) =
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chunkingStrategy(
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StaticFileChunkingStrategyObjectParam.builder()
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.static_(static_)
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.build()
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)
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/**
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* A list of [file](https://platform.openai.com/docs/api-reference/files)
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* IDs to add to the vector store. There can be a maximum of 10000 files in

‎openai-java-core/src/main/kotlin/com/openai/models/BetaThreadCreateParams.kt‎

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fun chunkingStrategy(static_: StaticFileChunkingStrategyObjectParam) =
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chunkingStrategy(FileChunkingStrategyParam.ofStatic(static_))
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the
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* `auto` strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) =
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chunkingStrategy(
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StaticFileChunkingStrategyObjectParam.builder().static_(static_).build()
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)
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/**
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* A list of [file](https://platform.openai.com/docs/api-reference/files) IDs to
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* add to the vector store. There can be a maximum of 10000 files in a vector

‎openai-java-core/src/main/kotlin/com/openai/models/BetaThreadRunCreateParams.kt‎

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*/
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fun addTool(function: FunctionTool) = addTool(AssistantTool.ofFunction(function))
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/**
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* Override the tools the assistant can use for this run. This is useful for modifying
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* the behavior on a per-run basis.
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*/
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fun addFunctionTool(function: FunctionDefinition) =
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addTool(FunctionTool.builder().function(function).build())
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/**
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* An alternative to sampling with temperature, called nucleus sampling, where the model
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* considers the results of the tokens with top_p probability mass. So 0.1 means only
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*/
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fun addTool(function: FunctionTool) = apply { body.addTool(function) }
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/**
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* Override the tools the assistant can use for this run. This is useful for modifying the
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* behavior on a per-run basis.
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*/
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fun addFunctionTool(function: FunctionDefinition) = apply { body.addFunctionTool(function) }
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/**
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* An alternative to sampling with temperature, called nucleus sampling, where the model
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* considers the results of the tokens with top_p probability mass. So 0.1 means only the

‎openai-java-core/src/main/kotlin/com/openai/models/BetaVectorStoreCreateParams.kt‎

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fun chunkingStrategy(static_: StaticFileChunkingStrategyObjectParam) =
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chunkingStrategy(FileChunkingStrategyParam.ofStatic(static_))
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the `auto`
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* strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) =
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chunkingStrategy(
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StaticFileChunkingStrategyObjectParam.builder().static_(static_).build()
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)
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/** The expiration policy for a vector store. */
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fun expiresAfter(expiresAfter: ExpiresAfter) = expiresAfter(JsonField.of(expiresAfter))
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body.chunkingStrategy(static_)
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}
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the `auto`
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* strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) = apply {
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body.staticChunkingStrategy(static_)
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}
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/** The expiration policy for a vector store. */
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fun expiresAfter(expiresAfter: ExpiresAfter) = apply { body.expiresAfter(expiresAfter) }
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‎openai-java-core/src/main/kotlin/com/openai/models/BetaVectorStoreFileBatchCreateParams.kt‎

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fun chunkingStrategy(static_: StaticFileChunkingStrategyObjectParam) =
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the `auto`
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* strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) =
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chunkingStrategy(
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StaticFileChunkingStrategyObjectParam.builder().static_(static_).build()
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)
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fun additionalProperties(additionalProperties: Map<String, JsonValue>) = apply {
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this.additionalProperties.clear()
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putAllAdditionalProperties(additionalProperties)
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body.chunkingStrategy(static_)
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}
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the `auto`
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* strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) = apply {
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body.staticChunkingStrategy(static_)
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}
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fun additionalBodyProperties(additionalBodyProperties: Map<String, JsonValue>) = apply {
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body.additionalProperties(additionalBodyProperties)
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}

‎openai-java-core/src/main/kotlin/com/openai/models/BetaVectorStoreFileCreateParams.kt‎

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fun chunkingStrategy(static_: StaticFileChunkingStrategyObjectParam) =
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chunkingStrategy(FileChunkingStrategyParam.ofStatic(static_))
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the `auto`
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* strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) =
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chunkingStrategy(
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StaticFileChunkingStrategyObjectParam.builder().static_(static_).build()
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)
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fun additionalProperties(additionalProperties: Map<String, JsonValue>) = apply {
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this.additionalProperties.clear()
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putAllAdditionalProperties(additionalProperties)
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body.chunkingStrategy(static_)
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}
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/**
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* The chunking strategy used to chunk the file(s). If not set, will use the `auto`
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* strategy. Only applicable if `file_ids` is non-empty.
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*/
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fun staticChunkingStrategy(static_: StaticFileChunkingStrategy) = apply {
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body.staticChunkingStrategy(static_)
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}
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fun additionalBodyProperties(additionalBodyProperties: Map<String, JsonValue>) = apply {
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body.additionalProperties(additionalBodyProperties)
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}

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