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June 11, 2024 06:33
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| [ | |
| { | |
| "name": "openai_chat_completion", | |
| "title": "Create Chat Completion Schema", | |
| "description": "Schema to validate requests for OpenAI's createChatCompletion endpoint", | |
| "type": "object", | |
| "properties": { | |
| "frequency_penalty": { | |
| "type": ["number", "null"], | |
| "title": "frequency_penalty", | |
| "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.", | |
| "minimum": -2, | |
| "maximum": 2, | |
| "default": 0, | |
| "required": false | |
| }, | |
| "logit_bias": { | |
| "type": ["object", "null"], | |
| "title": "logit_bias", | |
| "description": "Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.", | |
| "required": false | |
| }, | |
| "logprobs": { | |
| "type": ["boolean", "null"], | |
| "title": "logprobs", | |
| "description": "Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`.", | |
| "required": false | |
| }, | |
| "max_tokens": { | |
| "type": ["integer", "null"], | |
| "title": "max_tokens", | |
| "description": "The maximum number of tokens that can be generated in the chat completion, including both input and output tokens.", | |
| "default": 2500, | |
| "required": false | |
| }, | |
| "model": { | |
| "type": "string", | |
| "title": "model", | |
| "description": "ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.", | |
| "required": true, | |
| "oneOf": [ | |
| { "const": "gpt-3.5-turbo", "x-max-tokens": 16000 }, | |
| { "const": "gpt-3.5-turbo-instruct", "x-max-tokens": 4000 }, | |
| { "const": "gpt-4o", "x-max-tokens": 128000 }, | |
| { "const": "gpt-4-turbo", "x-max-tokens": 128000 } | |
| ] | |
| }, | |
| "messages": { | |
| "type": "array", | |
| "title": "Messages", | |
| "description": "A list of messages comprising the conversation so far.", | |
| "items": { | |
| "type": "object", | |
| "properties": { | |
| "role": { | |
| "type": "string", | |
| "title": "Role", | |
| "description": "The role of the message's author.", | |
| "enum": ["system", "user", "assistant", "tool"] | |
| }, | |
| "content": { | |
| "type": ["string", "null", "array"], | |
| "title": "Content", | |
| "description": "The contents of the message. `content` is required for all messages, and may be null or an array for specific message types." | |
| }, | |
| "name": { | |
| "type": "string", | |
| "title": "Name", | |
| "description": "An optional name for the participant. Provides the model information to differentiate between participants of the same role.", | |
| "maxLength": 64, | |
| "required": false | |
| }, | |
| "tool_calls": { | |
| "type": "array", | |
| "title": "Tool Calls", | |
| "description": "The tool calls generated by the model, such as function calls.", | |
| "required": false | |
| }, | |
| "tool_call_id": { | |
| "type": "string", | |
| "title": "Tool Call ID", | |
| "description": "Tool call that this message is responding to.", | |
| "required": false | |
| } | |
| }, | |
| "required": ["role", "content"], | |
| "allOf": [ | |
| { | |
| "if": { "properties": { "role": { "const": "system" } } }, | |
| "then": { | |
| "properties": { | |
| "role": { "enum": ["system"] }, | |
| "name": { "type": "string", "required": false }, | |
| "content": { "type": "string", "required": true } | |
| }, | |
| "required": ["role", "content"] | |
| } | |
| }, | |
| { | |
| "if": { "properties": { "role": { "const": "user" } } }, | |
| "then": { | |
| "properties": { | |
| "role": { "enum": ["user"] }, | |
| "name": { "type": "string", "required": false }, | |
| "content": { | |
| "type": ["string", "array"], | |
| "items": { | |
| "oneOf": [ | |
| { | |
| "type": "object", | |
| "properties": { | |
| "type": { "type": "string", "enum": ["text"], "required": true }, | |
| "text": { "type": "string", "required": true } | |
| }, | |
| "required": ["type", "text"] | |
| }, | |
| { | |
| "type": "object", | |
| "properties": { | |
| "type": { "type": "string", "enum": ["image_url"], "required": true }, | |
| "image_url": { | |
| "type": "object", | |
| "properties": { | |
| "url": { "type": "string", "required": true }, | |
| "detail": { "type": "string", "required": false } | |
| }, | |
| "required": ["url"] | |
| } | |
| }, | |
| "required": ["type", "image_url"] | |
| } | |
| ] | |
| }, | |
| "required": true | |
| } | |
| }, | |
| "required": ["role", "content"] | |
| } | |
| }, | |
| { | |
| "if": { "properties": { "role": { "const": "assistant" } } }, | |
| "then": { | |
| "properties": { | |
| "role": { "enum": ["assistant"] }, | |
| "name": { "type": "string", "required": false }, | |
| "content": { "type": ["string", "null"], "required": false }, | |
| "tool_calls": { "type": "array", "required": false } | |
| }, | |
| "required": ["role"] | |
| } | |
| }, | |
| { | |
| "if": { "properties": { "role": { "const": "tool" } } }, | |
| "then": { | |
| "properties": { | |
| "role": { "enum": ["tool"] }, | |
| "name": { "type": "string", "required": false }, | |
| "content": { "type": "string", "required": true }, | |
| "tool_call_id": { "type": "string", "required": true } | |
| }, | |
| "required": ["role", "content", "tool_call_id"] | |
| } | |
| } | |
| ] | |
| }, | |
| "required": true | |
| }, | |
| "n": { | |
| "type": ["integer", "null"], | |
| "title": "n", | |
| "description": "How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to minimize costs.", | |
| "default": 1, | |
| "required": false | |
| }, | |
| "parallel_tool_calls": { | |
| "type": "boolean", | |
| "description": "Enable parallel tool calling. Defaults to true.", | |
| "default": true | |
| }, | |
| "presence_penalty": { | |
| "type": ["number", "null"], | |
| "title": "presence_penalty", | |
| "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.", | |
| "minimum": -2, | |
| "maximum": 2, | |
| "default": 0, | |
| "required": false | |
| }, | |
| "response_format": { | |
| "type": "string", | |
| "title": "response_format", | |
| "description": "The format of the response. If `json`, the response will be a JSON object with a `choices` field containing the completions. If `text`, the response will be a JSON object with a `text` field containing the completions.", | |
| "enum": ["json", "text"], | |
| "default": "json", | |
| "required": false | |
| }, | |
| "stop": { | |
| "type": ["string", "array"], | |
| "description": "Up to 4 sequences where the API will stop generating further tokens.", | |
| "default": null | |
| }, | |
| "stream": { "type": "boolean", "description": "If set, partial message deltas will be sent.", "default": false }, | |
| "temperature": { | |
| "type": ["number", "null"], | |
| "title": "temperature", | |
| "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.", | |
| "minimum": 0, | |
| "maximum": 2, | |
| "default": 1, | |
| "required": false | |
| }, | |
| "tool_choice": { | |
| "oneOf": [ | |
| { | |
| "type": "string", | |
| "description": "Controls whether the model should choose to call a tool, and if so, which one.", | |
| "enum": ["required", "none", "auto"], | |
| "default": "required" | |
| }, | |
| { | |
| "type": "object", | |
| "description": "Controls whether the model should choose to call a tool, and if so, which one.", | |
| "properties": { | |
| "type": { "type": "string", "const": "function" }, | |
| "function": { "type": "string", "description": "The name of the function to call." } | |
| }, | |
| "required": ["type", "function"] | |
| } | |
| ] | |
| }, | |
| "tools": { | |
| "type": "array", | |
| "description": "A list of tools representing functions that the model may generate arguments for.", | |
| "items": { | |
| "type": "object", | |
| "properties": { | |
| "type": { | |
| "type": "string", | |
| "const": "function", | |
| "description": "Currently, the only supported tool type is `function`." | |
| }, | |
| "function": { | |
| "type": "object", | |
| "properties": { | |
| "name": { "type": "string", "description": "The name of the function to be called.", "maxLength": 64 }, | |
| "description": { | |
| "type": "string", | |
| "description": "A description of what the function does, which is used by the model to choose when and how to call the function." | |
| }, | |
| "parameters": { | |
| "type": "object", | |
| "description": "A JSON object containing the parameters that the function accepts. Omitting parameters defines a function with an empty parameter list.", | |
| "additionalProperties": { "type": ["string", "number", "boolean", "object", "array", "null"] } | |
| } | |
| }, | |
| "required": ["name"] | |
| } | |
| }, | |
| "required": ["type", "function"] | |
| } | |
| }, | |
| "top_logprobs": { | |
| "type": ["integer", "null"], | |
| "title": "top_logprobs", | |
| "description": "An integer between `0` and `20` specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to true if this parameter is used.", | |
| "required": false, | |
| "minimum": 0, | |
| "maximum": 20 | |
| }, | |
| "top_p": { | |
| "title": "top_p", | |
| "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.", | |
| "type": ["number", "null"], | |
| "maximum": 1, | |
| "default": 1, | |
| "required": false | |
| }, | |
| "user": { | |
| "type": "string", | |
| "title": "user", | |
| "description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.", | |
| "required": false | |
| } | |
| }, | |
| "required": ["model", "messages"] | |
| }, | |
| { | |
| "name": "openai_completion_usage", | |
| "title": "OpenAI/Completion Usage Schema", | |
| "type": "object", | |
| "description": "Usage statistics for an OpenAI completion request", | |
| "properties": { | |
| "completion_tokens": { | |
| "type": "integer", | |
| "title": "Completion Tokens", | |
| "description": "Number of tokens in the generated completion.", | |
| "minimum": 0 | |
| }, | |
| "prompt_tokens": { | |
| "type": "integer", | |
| "title": "Prompt Tokens", | |
| "description": "Number of tokens in the prompt.", | |
| "minimum": 0 | |
| }, | |
| "total_tokens": { | |
| "type": "integer", | |
| "title": "Total Tokens", | |
| "description": "Total number of tokens used in the request (prompt + completion).", | |
| "minimum": 0 | |
| } | |
| }, | |
| "required": ["completion_tokens", "prompt_tokens", "total_tokens"] | |
| }, | |
| { | |
| "name": "openai_fine_tuning_hyperparameters", | |
| "title": "OpenAI/Fine Tuning Hyperparameters Schema", | |
| "description": "Schema for configuring Hyperparameters for Fine-Tuning.", | |
| "type": "object", | |
| "properties": { | |
| "batch_size": { | |
| "title": "Batch Size", | |
| "description": "Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.", | |
| "oneOf": [ | |
| { "type": "string", "enum": ["auto"] }, | |
| { "type": "integer", "minimum": 1 } | |
| ], | |
| "default": "auto" | |
| }, | |
| "learning_rate_multiplier": { | |
| "title": "Learning Rate Multiplier", | |
| "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.", | |
| "oneOf": [ | |
| { "type": "string", "enum": ["auto"] }, | |
| { "type": "number", "minimum": 0 } | |
| ], | |
| "default": "auto" | |
| }, | |
| "n_epochs": { | |
| "title": "Number of Epochs", | |
| "description": "The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.", | |
| "oneOf": [ | |
| { "type": "string", "enum": ["auto"] }, | |
| { "type": "integer", "minimum": 1 } | |
| ], | |
| "default": "auto" | |
| } | |
| }, | |
| "additionalProperties": false | |
| }, | |
| { | |
| "name": "openai_fine_tuning_job_result", | |
| "title": "OpenAI/Fine Tuning Job Schema", | |
| "description": "Schema for the fine-tuning.job object, which is returned by OpenAI after a fine-tuning job is completed.", | |
| "type": "object", | |
| "properties": { | |
| "created_at": { | |
| "type": "integer", | |
| "title": "Created At", | |
| "description": "Unix timestamp for when the job was created" | |
| }, | |
| "status": { | |
| "type": "string", | |
| "title": "Status", | |
| "description": "Current status of the job", | |
| "enum": ["validating_files", "queued", "running", "succeeded", "failed", "cancelled"], | |
| "default": "queued" | |
| }, | |
| "error": { | |
| "type": ["object", "null"], | |
| "title": "Error", | |
| "description": "JSON object for job failure details, if any", | |
| "properties": { | |
| "code": { "type": "string", "title": "Code", "description": "A machine-readable error code." }, | |
| "message": { "type": "string", "title": "Message", "description": "A human-readable error message." }, | |
| "param": { | |
| "type": ["string", "null"], | |
| "title": "Param", | |
| "description": "The parameter that was invalid, usually \"training_file\" or \"validation_file\". This field will be null if the failure was not parameter-specific." | |
| } | |
| } | |
| }, | |
| "fine_tuned_model": { | |
| "type": ["string", "null"], | |
| "title": "Fine Tuned Model", | |
| "description": "Name of the fine-tuned model, if applicable" | |
| }, | |
| "finished_at": { | |
| "type": ["integer", "null"], | |
| "title": "Finished At", | |
| "description": "Unix timestamp for when the job was finished, if applicable" | |
| }, | |
| "hyperparameters": { | |
| "type": "object", | |
| "title": "Hyperparameters", | |
| "description": "JSON object for hyperparameters", | |
| "properties": { | |
| "n_epochs": { | |
| "type": ["integer", "null"], | |
| "title": "Number of Epochs", | |
| "description": "The number of epochs to train the model for" | |
| } | |
| } | |
| }, | |
| "model": { "type": "string", "title": "Model", "description": "Base model that is being fine-tuned" }, | |
| "object": { | |
| "type": "string", | |
| "title": "Object Type", | |
| "description": "Type of the object", | |
| "default": "fine_tuning.job", | |
| "const": "fine_tuning.job" | |
| }, | |
| "object_type": { | |
| "type": "string", | |
| "title": "Object Type", | |
| "description": "Type of the object", | |
| "default": "fine_tuning.job", | |
| "const": "fine_tuning.job" | |
| }, | |
| "organization_id": { | |
| "type": "string", | |
| "title": "Organization ID", | |
| "description": "Organization that owns the job" | |
| }, | |
| "result_files": { | |
| "type": "array", | |
| "title": "Result Files", | |
| "description": "Array of result file IDs", | |
| "items": { "type": "string" } | |
| }, | |
| "trained_tokens": { | |
| "type": ["integer", "null"], | |
| "title": "Trained Tokens", | |
| "description": "Total number of billable tokens processed, if applicable" | |
| }, | |
| "training_file": { "type": "string", "title": "Training File", "description": "File ID used for training" }, | |
| "validation_file": { | |
| "type": ["string", "null"], | |
| "title": "Validation File", | |
| "description": "File ID used for validation, if applicable" | |
| } | |
| }, | |
| "required": [ | |
| "created_at", | |
| "hyperparameters", | |
| "model", | |
| "object", | |
| "object_type", | |
| "organization_id", | |
| "status", | |
| "result_files", | |
| "training_file" | |
| ] | |
| }, | |
| { | |
| "name": "openai_transcription_request", | |
| "title": "Audio Transcription Request", | |
| "description": "A schema representing the input required to transcribe an audio file", | |
| "type": "object", | |
| "properties": { | |
| "file": { | |
| "description": "The audio file object to be transcribed.", | |
| "type": "string", | |
| "contentMediaType": "application/octet-stream", | |
| "pattern": ".*\\.(flac|mp3|mp4|mpeg|mpga|m4a|ogg|wav|webm)$", | |
| "x-ui": false | |
| }, | |
| "model": { "description": "ID of the transcription model to use.", "type": "string", "enum": ["whisper-1"] }, | |
| "language": { | |
| "description": "ISO-639-1 language code of the input audio, improves accuracy and latency.", | |
| "type": "string", | |
| "default": "en", | |
| "pattern": "^[a-z]{2}$" | |
| }, | |
| "prompt": { | |
| "description": "Optional text to guide the model's style or to continue a previous segment.", | |
| "type": "string" | |
| }, | |
| "response_format": { | |
| "description": "The format of the transcript output.", | |
| "type": "string", | |
| "default": "verbose_json", | |
| "enum": ["json", "text", "srt", "verbose_json", "vtt"], | |
| "x-ui": false | |
| }, | |
| "temperature": { | |
| "description": "Sampling temperature between 0 and 1 to control randomness of the output.", | |
| "type": "number", | |
| "default": 0, | |
| "minimum": 0, | |
| "maximum": 1 | |
| }, | |
| "timestamp_granularities": { | |
| "description": "The timestamp granularities to populate in the transcription.", | |
| "type": "array", | |
| "default": ["segment"], | |
| "items": { "type": "string", "enum": ["word", "segment"] }, | |
| "uniqueItems": true | |
| } | |
| }, | |
| "required": ["file", "model"] | |
| }, | |
| { | |
| "name": "openai_translation_request", | |
| "title": "Create Translation Request", | |
| "description": "A request schema for creating a translation of an audio file into English.", | |
| "type": "object", | |
| "properties": { | |
| "file": { | |
| "description": "The audio file object to translate. Must be in one of the supported formats.", | |
| "type": "string", | |
| "format": "binary", | |
| "contentMediaType": "audio/*", | |
| "contentEncoding": "base64", | |
| "examples": ["flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, webm"], | |
| "pattern": ".*\\.(flac|mp3|mp4|mpeg|mpga|m4a|ogg|wav|webm)$" | |
| }, | |
| "model": { "description": "ID of the model to use for translation.", "type": "string", "enum": ["whisper-1"] }, | |
| "prompt": { | |
| "description": "An optional text to guide the model's style or to continue a previous audio segment.", | |
| "type": "string" | |
| }, | |
| "response_format": { | |
| "description": "Format of the transcript output.", | |
| "type": "string", | |
| "default": "json", | |
| "enum": ["json", "text", "srt", "verbose_json", "vtt"] | |
| }, | |
| "temperature": { | |
| "description": "Sampling temperature to control randomness in the output.", | |
| "type": "number", | |
| "default": 0, | |
| "minimum": 0, | |
| "maximum": 1 | |
| } | |
| }, | |
| "required": ["file", "model"], | |
| "additionalProperties": false | |
| } | |
| ] |
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