appmixer.openai.core.createCompletion
1.0.0
Public
| Field | Type | Description |
|---|---|---|
| Model | text | The ID of the model to use for this request |
| Prompt | text | Example: This is a test. |
| Max Tokens | number | The maximum number of tokens to generate in the completion.
The token count of your prompt plus max_tokens cannot exceed the model's context length. Example Python code for counting tokens.
Example: 16 |
| Temperature | number | 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. OpenAI generally recommends altering this or top_p but not both. Example: 1 |
| Top P | number | 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. OpenAI generally recommends altering this or temperature but not both. Example: 1 |
| N | number | How many completions to generate for each prompt.
Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop.
Example: 1 |
| Logprobs | number | Include the log probabilities on the logprobs most likely tokens, as well the chosen tokens. For example, if logprobs is 5, the API will return a list of the 5 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response.
The maximum value for logprobs is 5. |
| Echo | toggle | If true, the API includes the input prompt in the response. |
| Stop | text | One or more sequences where the model should stop generating tokens. |
| Presence Penalty | number | 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. See more information about frequency and presence penalties. |
| Frequency Penalty | number | 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. See more information about frequency and presence penalties. |
| Best Of | number | Generates best_of completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed.
When used with n, best_of controls the number of candidate completions and n specifies how many to return – best_of must be greater than n.
Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop. |
| User | text | A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more. Example: user-1234 |
| Seed | number | If specified, the system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend. |
| Suffix | text | The suffix that comes after a completion of inserted text. This is only supported for Model gpt-3.5-turbo-instruct. |
| Field | Type | Description |
|---|---|---|
| Id | - | |
| Choices | - | |
| Created | - | |
| Model | - | |
| System Fingerprint | - | |
| Object | - | |
| Usage | - | |
| Usage Completion Tokens | - | |
| Usage Prompt Tokens | - | |
| Usage Total Tokens | - |