643 matches
25 actions
OpenAI
25 actions
- Answers the specified question using the provided documents and examples. The endpoint first [searches](/docs/api-reference/searches) over provided documents or files to find relevant context. The relevant context is combined with the provided examples and question to create the prompt for [completion](/docs/api-reference/completions). POSTv1.0.0
- Classifies if text violates OpenAI's Content PolicyPOSTv1.0.0
- Creates a completion for the chat messagePOSTv1.0.0
- Creates a completion for the provided prompt and parametersPOSTv1.0.0
- Creates a job that fine-tunes a specified model from a given dataset. Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete. [Learn more about Fine-tuning](/docs/guides/fine-tuning) POSTv1.0.0
- Creates a new edit for the provided input, instruction, and parameters.POSTv1.0.0
- Creates a variation of a given image.POSTv1.0.0
- Creates an edited or extended image given an original image and a prompt.POSTv1.0.0
- Creates an embedding vector representing the input text.POSTv1.0.0
- Creates an image given a prompt.POSTv1.0.0
- Delete a file.DELETEv1.0.0
- Delete a fine-tuned model. You must have the Owner role in your organization.DELETEv1.0.0
- Get fine-grained status updates for a fine-tune job. GETv1.0.0
- Gets info about the fine-tune job. [Learn more about Fine-tuning](/docs/guides/fine-tuning) GETv1.0.0
- Immediately cancel a fine-tune job. POSTv1.0.0
- List your organization's fine-tuning jobs GETv1.0.0
- Lists the currently available (non-finetuned) models, and provides basic information about each one such as the owner and availability.GETv1.0.0
- Lists the currently available models, and provides basic information about each one such as the owner and availability.GETv1.0.0
- Retrieves a model instance, providing basic information about it such as the owner and availability.GETv1.0.0
- Retrieves a model instance, providing basic information about the model such as the owner and permissioning.GETv1.0.0
- Returns a list of files that belong to the user's organization.GETv1.0.0
- Returns information about a specific file.GETv1.0.0
- The search endpoint computes similarity scores between provided query and documents. Documents can be passed directly to the API if there are no more than 200 of them. To go beyond the 200 document limit, documents can be processed offline and then used for efficient retrieval at query time. When `file` is set, the search endpoint searches over all the documents in the given file and returns up to the `max_rerank` number of documents. These documents will be returned along with their search scores. The similarity score is a positive score that usually ranges from 0 to 300 (but can sometimes go higher), where a score above 200 usually means the document is semantically similar to the query. POSTv1.0.0
- Transcribes audio into the input language.POSTv1.0.0
- Translates audio into into English.POSTv1.0.0
AI & ML/OpenAI
Creates a new edit for the provided input, instruction, and parameters.
v1.0.0Input
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{
"type": "object",
"required": [
"instruction",
"model"
],
"properties": {
"input": {
"type": "string",
"description": "The input text to use as a starting point for the edit."
},
"instruction": {
"type": "string",
"description": "The instruction that tells the model how to edit the prompt."
},
"model": {
"type": "string",
"description": "ID of the model to use. You can use the `text-davinci-edit-001` or `code-davinci-edit-001` model with this endpoint."
},
"n": {
"type": "integer",
"description": "How many edits to generate for the input and instruction."
},
"temperature": {
"type": "number",
"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.\n\nWe generally recommend altering this or `top_p` but not both.\n"
},
"top_p": {
"type": "number",
"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.\n\nWe generally recommend altering this or `temperature` but not both.\n"
}
}
}Output
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{
"type": "object",
"required": [
"choices",
"created",
"object",
"usage"
],
"properties": {
"choices": {
"type": "array",
"items": {
"type": "object",
"properties": {
"finish_reason": {
"type": "string"
},
"index": {
"type": "integer"
},
"logprobs": {
"type": "object",
"properties": {
"text_offset": {
"type": "array",
"items": {
"type": "integer"
}
},
"token_logprobs": {
"type": "array",
"items": {
"type": "number"
}
},
"tokens": {
"type": "array",
"items": {
"type": "string"
}
},
"top_logprobs": {
"type": "array",
"items": {
"type": "object"
}
}
}
},
"text": {
"type": "string"
}
}
}
},
"created": {
"type": "integer"
},
"object": {
"type": "string"
},
"usage": {
"type": "object",
"required": [
"completion_tokens",
"prompt_tokens",
"total_tokens"
],
"properties": {
"completion_tokens": {
"type": "integer"
},
"prompt_tokens": {
"type": "integer"
},
"total_tokens": {
"type": "integer"
}
}
}
}
}