Warning
This release is currently in alpha. Minor breaking changes may occur.
The OpenAI Go library provides convenient access to the OpenAI REST API from applications written in Go. The full API of this library can be found in api.md.
import (
"github.com/openai/openai-go" // imported as openai
)
Or to pin the version:
go get -u 'github.com/openai/openai-go@v0.1.0-alpha.33'
This library requires Go 1.18+.
The full API of this library can be found in api.md.
See the examples directory for complete and runnable examples.
package main
import (
"context"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
)
chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Messages: openai.F([]openai.ChatCompletionMessageParamUnion{
openai.UserMessage("Say this is a test"),
}),
Model: openai.F(openai.ChatModelGPT4o),
})
if err != nil {
panic(err.Error())
}
println(chatCompletion.Choices[0].Message.Content)
}
Conversations
param := openai.ChatCompletionNewParams{
Messages: openai.F([]openai.ChatCompletionMessageParamUnion{
openai.UserMessage("What kind of houseplant is easy to take care of?"),
}),
Seed: openai.Int(1),
Model: openai.F(openai.ChatModelGPT4o),
}
completion, err := client.Chat.Completions.New(ctx, params)
param.Messages.Value = append(param.Messages.Value, completion.Choices[0].Message)
param.Messages.Value = append(param.Messages.Value, openai.UserMessage("How big are those?"))
// continue the conversation
completion, err = client.Chat.Completions.New(ctx, param)
Streaming responses
question := "Write an epic"
stream := client.Chat.Completions.NewStreaming(ctx, openai.ChatCompletionNewParams{
Messages: openai.F([]openai.ChatCompletionMessageParamUnion{
openai.UserMessage(question),
}),
Seed: openai.Int(0),
Model: openai.F(openai.ChatModelGPT4o),
})
// optionally, an accumulator helper can be used
acc := openai.ChatCompletionAccumulator{}
for stream.Next() {
chunk := stream.Current()
acc.AddChunk(chunk)
if content, ok := acc.JustFinishedContent(); ok {
println("Content stream finished:", content)
}
// if using tool calls
if tool, ok := acc.JustFinishedToolCall(); ok {
println("Tool call stream finished:", tool.Index, tool.Name, tool.Arguments)
}
if refusal, ok := acc.JustFinishedRefusal(); ok {
println("Refusal stream finished:", refusal)
}
// it's best to use chunks after handling JustFinished events
if len(chunk.Choices) > 0 {
println(chunk.Choices[0].Delta.Content)
}
}
if err := stream.Err(); err != nil {
panic(err)
}
// After the stream is finished, acc can be used like a ChatCompletion
_ = acc.Choices[0].Message.Content
Tool calling
import (
"encoding/json"
// ...
)
// ...
question := "What is the weather in New York City?"
params := openai.ChatCompletionNewParams{
Messages: openai.F([]openai.ChatCompletionMessageParamUnion{
openai.UserMessage(question),
}),
Tools: openai.F([]openai.ChatCompletionToolParam{
{
Type: openai.F(openai.ChatCompletionToolTypeFunction),
Function: openai.F(openai.FunctionDefinitionParam{
Name: openai.String("get_weather"),
Description: openai.String("Get weather at the given location"),
Parameters: openai.F(openai.FunctionParameters{
"type": "object",
"properties": map[string]interface{}{
"location": map[string]string{
"type": "string",
},
},
"required": []string{"location"},
}),
}),
},
}),
Model: openai.F(openai.ChatModelGPT4o),
}
// chat completion request with tool calls
completion, _ := client.Chat.Completions.New(ctx, params)
for _, toolCall := range completion.Choices[0].Message.ToolCalls {
if toolCall.Function.Name == "get_weather" {
// extract the location from the function call arguments
var args map[string]interface{}
_ := json.Unmarshal([]byte(toolCall.Function.Arguments), &args)
// call a weather API with the arguments requested by the model
weatherData := getWeather(args["location"].(string))
params.Messages.Value = append(params.Messages.Value, openai.ToolMessage(toolCall.ID, weatherData))
}
}
// ... continue the conversation with the information provided by the tool
See the full tool calling example
Structured outputs
import (
"encoding/json"
"github.com/invopop/jsonschema"
// ...
)
// A struct that will be converted to a Structured Outputs response schema
type HistoricalComputer struct {
Origin Origin `json:"origin" jsonschema_description:"The origin of the computer"`
Name string `json:"full_name" jsonschema_description:"The name of the device model"`
NotableFacts []string `json:"notable_facts" jsonschema_description:"A few key facts about the computer"`
}
type Origin struct {
YearBuilt int64 `json:"year_of_construction" jsonschema_description:"The year it was made"`
Organization string `json:"organization" jsonschema_description:"The organization that was in charge of its development"`
}
func GenerateSchema[T any]() interface{} {
reflector := jsonschema.Reflector{
AllowAdditionalProperties: false,
DoNotReference: true,
}
var v T
schema := reflector.Reflect(v)
return schema
}
// Generate the JSON schema at initialization time
var HistoricalComputerResponseSchema = GenerateSchema[HistoricalComputer]()
func main() {
// ...
question := "What computer ran the first neural network?"
schemaParam := openai.ResponseFormatJSONSchemaJSONSchemaParam{
Name: openai.F("biography"),
Description: openai.F("Notable information about a person"),
Schema: openai.F(HistoricalComputerResponseSchema),
Strict: openai.Bool(true),
}
chat, _ := client.Chat.Completions.New(ctx, openai.ChatCompletionNewParams{
// ...
ResponseFormat: openai.F[openai.ChatCompletionNewParamsResponseFormatUnion](
openai.ResponseFormatJSONSchemaParam{
Type: openai.F(openai.ResponseFormatJSONSchemaTypeJSONSchema),
JSONSchema: openai.F(schemaParam),
},
),
// only certain models can perform structured outputs
Model: openai.F(openai.ChatModelGPT4o2024_08_06),
})
// extract into a well-typed struct
historicalComputer := HistoricalComputer{}
_ = json.Unmarshal([]byte(chat.Choices[0].Message.Content), &historicalComputer)
historicalComputer.Name
historicalComputer.Origin.YearBuilt
historicalComputer.Origin.Organization
for i, fact := range historicalComputer.NotableFacts {
// ...
}
}
See the full structured outputs example
All request parameters are wrapped in a generic Field
type,
which we use to distinguish zero values from null or omitted fields.
This prevents accidentally sending a zero value if you forget a required parameter,
and enables explicitly sending null
, false
, ''
, or 0
on optional parameters.
Any field not specified is not sent.
To construct fields with values, use the helpers String()
, Int()
, Float()
, or most commonly, the generic F[T]()
.
To send a null, use Null[T]()
, and to send a nonconforming value, use Raw[T](any)
. For example:
params := FooParams{
Name: openai.F("hello"),
// Explicitly send `"description": null`
Description: openai.Null[string](),
Point: openai.F(openai.Point{
X: openai.Int(0),
Y: openai.Int(1),
// In cases where the API specifies a given type,
// but you want to send something else, use `Raw`:
Z: openai.Raw[int64](0.01), // sends a float
}),
}
All fields in response structs are value types (not pointers or wrappers).
If a given field is null
, not present, or invalid, the corresponding field
will simply be its zero value.
All response structs also include a special JSON
field, containing more detailed
information about each property, which you can use like so:
if res.Name == "" {
// true if `"name"` is either not present or explicitly null
res.JSON.Name.IsNull()
// true if the `"name"` key was not present in the repsonse JSON at all
res.JSON.Name.IsMissing()
// When the API returns data that cannot be coerced to the expected type:
if res.JSON.Name.IsInvalid() {
raw := res.JSON.Name.Raw()
legacyName := struct{
First string `json:"first"`
Last string `json:"last"`
}{}
json.Unmarshal([]byte(raw), &legacyName)
name = legacyName.First + " " + legacyName.Last
}
}
These .JSON
structs also include an Extras
map containing
any properties in the json response that were not specified
in the struct. This can be useful for API features not yet
present in the SDK.
body := res.JSON.ExtraFields["my_unexpected_field"].Raw()
This library uses the functional options pattern. Functions defined in the
option
package return a RequestOption
, which is a closure that mutates a
RequestConfig
. These options can be supplied to the client or at individual
requests. For example:
client := openai.NewClient(
// Adds a header to every request made by the client
option.WithHeader("X-Some-Header", "custom_header_info"),
)
client.Chat.Completions.New(context.TODO(), ...,
// Override the header
option.WithHeader("X-Some-Header", "some_other_custom_header_info"),
// Add an undocumented field to the request body, using sjson syntax
option.WithJSONSet("some.json.path", map[string]string{"my": "object"}),
)
See the full list of request options.
This library provides some conveniences for working with paginated list endpoints.
You can use .ListAutoPaging()
methods to iterate through items across all pages:
iter := client.FineTuning.Jobs.ListAutoPaging(context.TODO(), openai.FineTuningJobListParams{
Limit: openai.F(int64(20)),
})
// Automatically fetches more pages as needed.
for iter.Next() {
fineTuningJob := iter.Current()
fmt.Printf("%+v\n", fineTuningJob)
}
if err := iter.Err(); err != nil {
panic(err.Error())
}
Or you can use simple .List()
methods to fetch a single page and receive a standard response object
with additional helper methods like .GetNextPage()
, e.g.:
page, err := client.FineTuning.Jobs.List(context.TODO(), openai.FineTuningJobListParams{
Limit: openai.F(int64(20)),
})
for page != nil {
for _, job := range page.Data {
fmt.Printf("%+v\n", job)
}
page, err = page.GetNextPage()
}
if err != nil {
panic(err.Error())
}
When the API returns a non-success status code, we return an error with type
*openai.Error
. This contains the StatusCode
, *http.Request
, and
*http.Response
values of the request, as well as the JSON of the error body
(much like other response objects in the SDK).
To handle errors, we recommend that you use the errors.As
pattern:
_, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
Model: openai.F(openai.FineTuningJobNewParamsModelBabbage002),
TrainingFile: openai.F("file-abc123"),
})
if err != nil {
var apierr *openai.Error
if errors.As(err, &apierr) {
println(string(apierr.DumpRequest(true))) // Prints the serialized HTTP request
println(string(apierr.DumpResponse(true))) // Prints the serialized HTTP response
}
panic(err.Error()) // GET "/fine_tuning/jobs": 400 Bad Request { ... }
}
When other errors occur, they are returned unwrapped; for example,
if HTTP transport fails, you might receive *url.Error
wrapping *net.OpError
.
Requests do not time out by default; use context to configure a timeout for a request lifecycle.
Note that if a request is retried, the context timeout does not start over.
To set a per-retry timeout, use option.WithRequestTimeout()
.
// This sets the timeout for the request, including all the retries.
ctx, cancel := context.WithTimeout(context.Background(), 5*time.Minute)
defer cancel()
client.Chat.Completions.New(
ctx,
openai.ChatCompletionNewParams{
Messages: openai.F([]openai.ChatCompletionMessageParamUnion{
openai.UserMessage("Say this is a test"),
}),
Model: openai.F(openai.ChatModelGPT4o),
},
// This sets the per-retry timeout
option.WithRequestTimeout(20*time.Second),
)
Request parameters that correspond to file uploads in multipart requests are typed as
param.Field[io.Reader]
. The contents of the io.Reader
will by default be sent as a multipart form
part with the file name of "anonymous_file" and content-type of "application/octet-stream".
The file name and content-type can be customized by implementing Name() string
or ContentType() string
on the run-time type of io.Reader
. Note that os.File
implements Name() string
, so a
file returned by os.Open
will be sent with the file name on disk.
We also provide a helper openai.FileParam(reader io.Reader, filename string, contentType string)
which can be used to wrap any io.Reader
with the appropriate file name and content type.
// A file from the file system
file, err := os.Open("input.jsonl")
openai.FileNewParams{
File: openai.F[io.Reader](file),
Purpose: openai.F(openai.FilePurposeFineTune),
}
// A file from a string
openai.FileNewParams{
File: openai.F[io.Reader](strings.NewReader("my file contents")),
Purpose: openai.F(openai.FilePurposeFineTune),
}
// With a custom filename and contentType
openai.FileNewParams{
File: openai.FileParam(strings.NewReader(`{"hello": "foo"}`), "file.go", "application/json"),
Purpose: openai.F(openai.FilePurposeFineTune),
}
Certain errors will be automatically retried 2 times by default, with a short exponential backoff. We retry by default all connection errors, 408 Request Timeout, 409 Conflict, 429 Rate Limit, and >=500 Internal errors.
You can use the WithMaxRetries
option to configure or disable this:
// Configure the default for all requests:
client := openai.NewClient(
option.WithMaxRetries(0), // default is 2
)
// Override per-request:
client.Chat.Completions.New(
context.TODO(),
openai.ChatCompletionNewParams{
Messages: openai.F([]openai.ChatCompletionMessageParamUnion{
openai.UserMessage("Say this is a test"),
}),
Model: openai.F(openai.ChatModelGPT4o),
},
option.WithMaxRetries(5),
)
This library is typed for convenient access to the documented API. If you need to access undocumented endpoints, params, or response properties, the library can still be used.
To make requests to undocumented endpoints, you can use client.Get
, client.Post
, and other HTTP verbs.
RequestOptions
on the client, such as retries, will be respected when making these requests.
var (
// params can be an io.Reader, a []byte, an encoding/json serializable object,
// or a "…Params" struct defined in this library.
params map[string]interface{}
// result can be an []byte, *http.Response, a encoding/json deserializable object,
// or a model defined in this library.
result *http.Response
)
err := client.Post(context.Background(), "/unspecified", params, &result)
if err != nil {
…
}
To make requests using undocumented parameters, you may use either the option.WithQuerySet()
or the option.WithJSONSet()
methods.
params := FooNewParams{
ID: openai.F("id_xxxx"),
Data: openai.F(FooNewParamsData{
FirstName: openai.F("John"),
}),
}
client.Foo.New(context.Background(), params, option.WithJSONSet("data.last_name", "Doe"))
To access undocumented response properties, you may either access the raw JSON of the response as a string
with result.JSON.RawJSON()
, or get the raw JSON of a particular field on the result with
result.JSON.Foo.Raw()
.
Any fields that are not present on the response struct will be saved and can be accessed by result.JSON.ExtraFields()
which returns the extra fields as a map[string]Field
.
We provide option.WithMiddleware
which applies the given
middleware to requests.
func Logger(req *http.Request, next option.MiddlewareNext) (res *http.Response, err error) {
// Before the request
start := time.Now()
LogReq(req)
// Forward the request to the next handler
res, err = next(req)
// Handle stuff after the request
end := time.Now()
LogRes(res, err, start - end)
return res, err
}
client := openai.NewClient(
option.WithMiddleware(Logger),
)
When multiple middlewares are provided as variadic arguments, the middlewares
are applied left to right. If option.WithMiddleware
is given
multiple times, for example first in the client then the method, the
middleware in the client will run first and the middleware given in the method
will run next.
You may also replace the default http.Client
with
option.WithHTTPClient(client)
. Only one http client is
accepted (this overwrites any previous client) and receives requests after any
middleware has been applied.
To use this library with Azure OpenAI, use the option.RequestOption functions in the azure
package.
package main
import (
"github.com/Azure/azure-sdk-for-go/sdk/azidentity"
"github.com/openai/openai-go"
"github.com/openai/openai-go/azure"
)
func main() {
const azureOpenAIEndpoint = "https://<azure-openai-resource>.openai.azure.com"
// The latest API versions, including previews, can be found here:
// https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#rest-api-versioning
const azureOpenAIAPIVersion = "2024-06-01"
tokenCredential, err := azidentity.NewDefaultAzureCredential(nil)
if err != nil {
fmt.Printf("Failed to create the DefaultAzureCredential: %s", err)
os.Exit(1)
}
client := openai.NewClient(
azure.WithEndpoint(azureOpenAIEndpoint, azureOpenAIAPIVersion),
// Choose between authenticating using a TokenCredential or an API Key
azure.WithTokenCredential(tokenCredential),
// or azure.WithAPIKey(azureOpenAIAPIKey),
)
}
This package generally follows SemVer conventions, though certain backwards-incompatible changes may be released as minor versions:
- Changes to library internals which are technically public but not intended or documented for external use. (Please open a GitHub issue to let us know if you are relying on such internals).
- Changes that we do not expect to impact the vast majority of users in practice.
We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.
We are keen for your feedback; please open an issue with questions, bugs, or suggestions.