Add both API endpoints (completion, chat)

add/first-example
mudler 2 years ago
parent c17dcc5e9d
commit f43aeeb4a1
  1. 182
      api.go

182
api.go

@ -16,46 +16,125 @@ import (
)
type OpenAIResponse struct {
Created int `json:"created"`
Object string `json:"chat.completion"`
ID string `json:"id"`
Model string `json:"model"`
Choices []Choice `json:"choices"`
Created int `json:"created,omitempty"`
Object string `json:"chat.completion,omitempty"`
ID string `json:"id,omitempty"`
Model string `json:"model,omitempty"`
Choices []Choice `json:"choices,omitempty"`
}
type Choice struct {
Index int `json:"index"`
FinishReason string `json:"finish_reason"`
Message Message `json:"message"`
Index int `json:"index,omitempty"`
FinishReason string `json:"finish_reason,omitempty"`
Message Message `json:"message,omitempty"`
Text string `json:"text,omitempty"`
}
type Message struct {
Role string `json:"role"`
Content string `json:"content"`
Role string `json:"role,omitempty"`
Content string `json:"content,omitempty"`
}
//go:embed index.html
var indexHTML embed.FS
func api(defaultModel *llama.LLama, loader *ModelLoader, listenAddr string, threads int) error {
app := fiber.New()
func completionEndpoint(defaultModel *llama.LLama, loader *ModelLoader, threads int, defaultMutex *sync.Mutex, mutexMap *sync.Mutex, mutexes map[string]*sync.Mutex) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
// Default middleware config
app.Use(recover.New())
app.Use(cors.New())
var err error
var model *llama.LLama
app.Use("/", filesystem.New(filesystem.Config{
Root: http.FS(indexHTML),
NotFoundFile: "index.html",
}))
// Get input data from the request body
input := new(struct {
Model string `json:"model"`
Prompt string `json:"prompt"`
})
if err := c.BodyParser(input); err != nil {
return err
}
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
var mutex = &sync.Mutex{}
mu := map[string]*sync.Mutex{}
var mumutex = &sync.Mutex{}
if input.Model == "" {
if defaultModel == nil {
return fmt.Errorf("no default model loaded, and no model specified")
}
model = defaultModel
} else {
model, err = loader.LoadModel(input.Model)
if err != nil {
return err
}
}
// openAI compatible API endpoint
app.Post("/v1/chat/completions", func(c *fiber.Ctx) error {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
if input.Model != "" {
mutexMap.Lock()
l, ok := mutexes[input.Model]
if !ok {
m := &sync.Mutex{}
mutexes[input.Model] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
} else {
defaultMutex.Lock()
defer defaultMutex.Unlock()
}
// Set the parameters for the language model prediction
topP, err := strconv.ParseFloat(c.Query("topP", "0.9"), 64) // Default value of topP is 0.9
if err != nil {
return err
}
topK, err := strconv.Atoi(c.Query("topK", "40")) // Default value of topK is 40
if err != nil {
return err
}
temperature, err := strconv.ParseFloat(c.Query("temperature", "0.5"), 64) // Default value of temperature is 0.5
if err != nil {
return err
}
tokens, err := strconv.Atoi(c.Query("tokens", "128")) // Default value of tokens is 128
if err != nil {
return err
}
predInput := input.Prompt
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(input.Model, struct {
Input string
}{Input: input.Prompt})
if err == nil {
predInput = templatedInput
}
// Generate the prediction using the language model
prediction, err := model.Predict(
predInput,
llama.SetTemperature(temperature),
llama.SetTopP(topP),
llama.SetTopK(topK),
llama.SetTokens(tokens),
llama.SetThreads(threads),
)
if err != nil {
return err
}
// Return the prediction in the response body
return c.JSON(OpenAIResponse{
Model: input.Model,
Choices: []Choice{{Text: prediction}},
})
}
}
func chatEndpoint(defaultModel *llama.LLama, loader *ModelLoader, threads int, defaultMutex *sync.Mutex, mutexMap *sync.Mutex, mutexes map[string]*sync.Mutex) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
var err error
var model *llama.LLama
@ -64,7 +143,6 @@ func api(defaultModel *llama.LLama, loader *ModelLoader, listenAddr string, thre
input := new(struct {
Messages []Message `json:"messages"`
Model string `json:"model"`
Prompt string `json:"prompt"`
})
if err := c.BodyParser(input); err != nil {
return err
@ -84,19 +162,19 @@ func api(defaultModel *llama.LLama, loader *ModelLoader, listenAddr string, thre
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
if input.Model != "" {
mumutex.Lock()
l, ok := mu[input.Model]
mutexMap.Lock()
l, ok := mutexes[input.Model]
if !ok {
m := &sync.Mutex{}
mu[input.Model] = m
mutexes[input.Model] = m
l = m
}
mumutex.Unlock()
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
} else {
mutex.Lock()
defer mutex.Unlock()
defaultMutex.Lock()
defer defaultMutex.Unlock()
}
// Set the parameters for the language model prediction
@ -127,16 +205,12 @@ func api(defaultModel *llama.LLama, loader *ModelLoader, listenAddr string, thre
predInput := strings.Join(mess, "\n")
if input.Prompt == "" {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(input.Model, struct {
Input string
}{Input: predInput})
if err == nil {
predInput = templatedInput
}
} else {
predInput = input.Prompt + predInput
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(input.Model, struct {
Input string
}{Input: predInput})
if err == nil {
predInput = templatedInput
}
// Generate the prediction using the language model
@ -157,7 +231,29 @@ func api(defaultModel *llama.LLama, loader *ModelLoader, listenAddr string, thre
Model: input.Model,
Choices: []Choice{{Message: Message{Role: "assistant", Content: prediction}}},
})
})
}
}
func api(defaultModel *llama.LLama, loader *ModelLoader, listenAddr string, threads int) error {
app := fiber.New()
// Default middleware config
app.Use(recover.New())
app.Use(cors.New())
app.Use("/", filesystem.New(filesystem.Config{
Root: http.FS(indexHTML),
NotFoundFile: "index.html",
}))
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
var mutex = &sync.Mutex{}
mu := map[string]*sync.Mutex{}
var mumutex = &sync.Mutex{}
// openAI compatible API endpoint
app.Post("/v1/chat/completions", chatEndpoint(defaultModel, loader, threads, mutex, mumutex, mu))
app.Post("/v1/completions", completionEndpoint(defaultModel, loader, threads, mutex, mumutex, mu))
/*
curl --location --request POST 'http://localhost:8080/predict' --header 'Content-Type: application/json' --data-raw '{

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