Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/yazeedobaid/openai-fsharp
OpenAI - F# - A library that allows you to interact with OpenAI API in an easy, fluent, and typed way!
https://github.com/yazeedobaid/openai-fsharp
api fsharp openai openapi
Last synced: 6 days ago
JSON representation
OpenAI - F# - A library that allows you to interact with OpenAI API in an easy, fluent, and typed way!
- Host: GitHub
- URL: https://github.com/yazeedobaid/openai-fsharp
- Owner: yazeedobaid
- License: mit
- Created: 2023-02-02T12:51:24.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-03-13T19:38:37.000Z (over 1 year ago)
- Last Synced: 2024-11-04T23:07:04.301Z (9 days ago)
- Topics: api, fsharp, openai, openapi
- Language: F#
- Homepage:
- Size: 1.9 MB
- Stars: 59
- Watchers: 6
- Forks: 5
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
------
**OpenAI F#** is a library that allows you to interact with [Open AI API](https://beta.openai.com/docs/api-reference/introduction) in an easy,
fluent, and typed way!
## Get Started
Add the library to your project using DotNet CLI:
```bash
dotnet add package OpenAI.Client
```
Or using Paket:
```bash
paket add OpenAI.Client
```
The library provide two styles to consume the APIs, either a methods calls through pipe operator as shown below:
```fsharp
open OpenAI
open OpenAI.Client
open OpenAI.Models
let client =
Config(
{ Endpoint = "https://api.openai.com/v1"
ApiKey = "your-api-key" },
HttpRequester()
)
let result = client |> models |> list
```
Or using a computation expression builder object as shown below:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
models
list
}
```
You can check OpenAI API reference at [API reference](https://platform.openai.com/docs/api-reference).
## Usage
### `Models` Resource
List and describe the various models available in the API. You can refer to the Models documentation to understand
what models are available and the differences between them.
#### `list`
Lists the currently available models, and provides basic information about each one such as the owner and availability.
```fsharp
let result = client |> models |> list
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
models
list
}
```
#### `retrieve`
Retrieves a model instance, providing basic information about the model such as the owner and permissioning.
```fsharp
let result = client |> models |> retrieve "text-davinci-003"
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
models
retrieve "text-davinci-003"
}
```
#### `delete`
Delete a fine-tuned model.
```fsharp
let result = client |> models |> delete "curie:ft-acmeco-2021-03-03-21-44-20"
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
models
delete "curie:ft-acmeco-2021-03-03-21-44-20"
}
```
### `Completions` Resource
Given a prompt, the model will return one or more predicted completions, and can also return the probabilities
of alternative tokens at each position.
#### `create`
Creates a completion for the provided prompt and parameters.
```fsharp
let result =
client
|> completions
|> Completions.create
{ Model = "text-davinci-003"
Prompt = "What is the meaning of living?"
Temperature = 0.5
Stop = "." }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
completions
create
{ Model = "text-davinci-003"
Prompt = "What is the meaning of living?"
Temperature = 0.5
Stop = "." }
}
```
### `Chat` Resource
Given a chat conversation, the model will return a chat completion response.
#### `create`
Creates a completion for the chat message.
```fsharp
let result =
client
|> chat
|> create
{ Model = "text-davinci-003"
Messages = [| {Role = "user"; Content = "Hello!"} |] }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint (url "")
apiKey "apiKey"
chat
create
{ Model = "text-davinci-003"
Messages = [| {Role = "user"; Content = "Hello!"} |] }
}
```
### `Edits` Resource
Given a prompt and an instruction, the model will return an edited version of the prompt.
#### `create`
Creates a new edit for the provided input, instruction, and parameters.
```fsharp
let result =
client
|> edits
|> Edits.create
{ Model = "text-davinci-edit-001"
Input = "What day of the wek is it?"
Instruction = "Fix the spelling mistakes" }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
edits
create
{ Model = "text-davinci-edit-001"
Input = "What day of the wek is it?"
Instruction = "Fix the spelling mistakes" }
}
```
### `Images` Resource
Given a prompt and/or an input image, the model will generate a new image.
#### `create`
Creates an image given a prompt.
```fsharp
let result =
client
|> images
|> create
{ Prompt = "A cute baby sea otter"
N = 2
Size = "1024x1024"
responseFormat = "url" }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
images
create
{ Prompt = "A cute baby sea otter"
N = 2
Size = "1024x1024"
responseFormat = "url" }
}
```
#### `edit`
Creates an edited or extended image given an original image and a prompt.
```fsharp
let result =
client
|> images
|> edit
{ Image = "sample.png"
Mask = "sample.png"
Prompt = "A cute baby sea otter wearing a beret"
N = 2
Size = "1024x1024"
responseFormat = "url" }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
images
edit
{ Image = "sample.png"
Mask = "sample.png"
Prompt = "A cute baby sea otter wearing a beret"
N = 2
Size = "1024x1024"
responseFormat = "url" }
}
```
#### `variation`
Creates a variation of a given image.
```fsharp
let result =
client
|> images
|> variation
{ Image = "sample.png"
N = 2
Size = "1024x1024"
responseFormat = "url" }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
images
variation
{ Image = "sample.png"
N = 2
Size = "1024x1024"
responseFormat = "url" }
}
```
### `Embeddings` Resource
Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
#### `create`
Creates an embedding vector representing the input text.
```fsharp
let result =
client
|> embeddings
|> create
{ Model = "text-embedding-ada-002"
Input = "The food was delicious and the waiter..." }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
embeddings
create
{ Model = "text-embedding-ada-002"
Input = "The food was delicious and the waiter..." }
}
```
### `Audio` Resource
Turn audio into text.
#### `transcript`
Transcribes audio into the input language.
```fsharp
let result =
client
|> audio
|> transcript
{ TranscriptRequest.Default with
File = "sample-audio.mp3"
Model = "whisper-1" }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint (url "")
apiKey "apiKey"
audio
transcript
{ TranscriptRequest.Default with
File = "sample-audio.mp3"
Model = "whisper-1" }
}
```
#### `translate`
Translates audio into into English.
```fsharp
let result =
client
|> audio
|> translate
{ File = "sample-audio.mp3"
Model = "whisper-1" }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint (url "")
apiKey "apiKey"
audio
translate
{ File = "sample-audio.mp3"
Model = "whisper-1" }
}
```
### `Files` Resource
Files are used to upload documents that can be used with features like Fine-tuning.
#### `list`
Returns a list of files that belong to the user's organization.
```fsharp
let result = client |> files |> list
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
files
list
}
```
#### `upload`
Upload a file that contains document(s) to be used across various endpoints/features.
```fsharp
let result =
client
|> files
|> upload
{ File = @"sample-json.txt"
Purpose = "fine-tune" }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
files
upload
{ File = @"sample-json.txt"
Purpose = "fine-tune" }
}
```
#### `delete`
Delete a file.
```fsharp
let result =
client
|> files
|> delete "file-qtUwySute1Zf2yT6mWIGTCwq"
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
files
delete "file-qtUwySute1Zf2yT6mWIGTCwq"
}
```
#### `retrieve`
Returns information about a specific file.
```fsharp
let result = client |> files |> retrieve "file-Lpe0n5tOHtoG6OVVbk5d4iXA"
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
files
retrieve "file-Lpe0n5tOHtoG6OVVbk5d4iXA"
}
```
#### `download`
Returns the contents of the specified file.
```fsharp
let result = client |> files |> download "file-Lpe0n5tOHtoG6OVVbk5d4iXA"
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
files
download "file-Lpe0n5tOHtoG6OVVbk5d4iXA"
}
```
### `FineTunes` Resource
Manage fine-tuning jobs to tailor a model to your specific training data.
#### `create`
Creates a job that fine-tunes a specified model from a given dataset.
```fsharp
let result =
client
|> fineTunes
|> create { CreateRequest.Default with TrainingFile = "file-Lpe0n5tOHtoG6OVVbk5d4iXA" }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
fineTunes
create { CreateRequest.Default with TrainingFile = "file-Lpe0n5tOHtoG6OVVbk5d4iXA" }
}
```
#### `list`
List your organization's fine-tuning jobs.
```fsharp
let result = client |> fineTunes |> list
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
fineTunes
list
}
```
#### `retrieve`
Gets info about the fine-tune job.
```fsharp
let result = client |> fineTunes |> retrieve "ft-kNJeZjAhlmFLdCuIzcpkrmNI"
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
retrieve
retrieve "ft-kNJeZjAhlmFLdCuIzcpkrmNI"
}
```
#### `cancel`
Immediately cancel a fine-tune job.
```fsharp
let result = client |> fineTunes |> cancel "ft-kNJeZjAhlmFLdCuIzcpkrmNI"
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
fineTunes
cancel "ft-kNJeZjAhlmFLdCuIzcpkrmNI"
}
```
#### `list events`
Get fine-grained status updates for a fine-tune job.
```fsharp
let result = client |> fineTunes |> listEvents "ft-kNJeZjAhlmFLdCuIzcpkrmNI"
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
fineTunes
listEvents "ft-kNJeZjAhlmFLdCuIzcpkrmNI"
}
```
### `Moderations` Resource
Given a input text, outputs if the model classifies it as violating OpenAI's content policy.
#### `create`
Classifies if text violates OpenAI's Content Policy.
```fsharp
let result =
client
|> moderations
|> create
{ Model = "text-moderation-latest"
Input = "I want to kill them." }
```
Or using a computation expression builder:
```fsharp
let result =
openAI {
endPoint "https://api.openai.com/v1"
apiKey "your-api-key"
moderations
create
{ Model = "text-moderation-latest"
Input = "I want to kill them." }
}
```
## Credits
This library was inspired from [openai-php](https://github.com/openai-php/client) and [FsHttp](https://github.com/fsprojects/FsHttp).