OpenAI API support
✋ Only tested with the gpt-4o-mini model, and text-embedding-3-large for the embeddings model.
Since the release 0.2.7 I unified the completion methods
Chat completion
Use: completion.Chat(openAIURL, query, provider.OpenAI, <OPENAI-API-KEY>)
| openAIURL := "https://api.openai.com/v1"
model := "gpt-4o-mini"
systemContent := `You are an expert in Star Trek.`
userContent := `Who is Jean-Luc Picard?`
query := llm.Query{
Model: model,
Messages: []llm.Message{
{Role: "system", Content: systemContent},
{Role: "user", Content: userContent},
},
}
answer, err := completion.Chat(openAIURL, query, provider.OpenAI, os.Getenv("OPENAI_API_KEY"))
if err != nil {
log.Fatal("😡:", err)
}
fmt.Println(answer.Message.Content)
|
Chat completion with stream
Use: completion.ChatStream(openAIURL, query, function, provider.OpenAI, <OPENAI-API-KEY>)
| openAIURL := "https://api.openai.com/v1"
model := "gpt-4o-mini"
systemContent := `You are an expert in Star Trek.`
userContent := `Who is Jean-Luc Picard?`
query := llm.Query{
Model: model,
Messages: []llm.Message{
{Role: "system", Content: systemContent},
{Role: "user", Content: userContent},
},
}
_, err = completion.ChatStream(openAIURL, query,
func(answer llm.Answer) error {
fmt.Print(answer.Message.Content)
return nil
}, provider.OpenAI, os.Getenv("OPENAI_API_KEY"))
if err != nil {
log.Fatal("😡:", err)
}
|
Note
You can find examples in
Use: completion.Chat(openAIURL, query, provider.OpenAI, <OPENAI-API-KEY>) and set query.Tools.
| openAIURL := "https://api.openai.com/v1"
model := "gpt-4o-mini"
openAIKey := os.Getenv("OPENAI_API_KEY")
toolsList := []llm.Tool{
{
Type: "function",
Function: llm.Function{
Name: "addNumbers",
Description: "Make an addition of the two given numbers",
Parameters: llm.Parameters{
Type: "object",
Properties: map[string]llm.Property{
"a": {
Type: "number",
Description: "first operand",
},
"b": {
Type: "number",
Description: "second operand",
},
},
Required: []string{"a", "b"},
},
},
},
}
options := llm.SetOptions(map[string]interface{}{
option.Temperature: 0.0,
})
messages := []llm.Message{
{Role: "user", Content: `add 2 and 40`},
}
query := llm.Query{
Model: model,
Messages: messages,
Tools: toolsList,
Options: options,
}
answer, err := completion.Chat(openAIURL, query, provider.OpenAI, openAIKey)
if err != nil {
log.Fatal("😡:", err)
}
// Search tool to call in the answer
tool, err := answer.Message.ToolCalls.Find("addNumbers")
if err != nil {
log.Fatal("😡:", err)
}
result, _ := tool.Function.ToJSONString()
fmt.Println(result)
|
Create embeddings
| // Create an embedding from a content
embedding, err := embeddings.CreateEmbedding(
openAIURL,
llm.Query4Embedding{
Model: "text-embedding-3-large",
Prompt: "thi is the content of the document",
},
"unique identifier",
provider.OpenAI,
os.Getenv("OPENAI_API_KEY"),
)
|