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https://github.com/mudler/LocalAI.git
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Small refinements and refactors
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mudler
parent
eb4257f946
commit
5556aa46dd
3 changed files with 48 additions and 473 deletions
172
api/api.go
172
api/api.go
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@ -1,4 +1,4 @@
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package main
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package api
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import (
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"embed"
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@ -42,20 +42,31 @@ type OpenAIModel struct {
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Object string `json:"object"`
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}
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type OpenAIRequest struct {
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Model string `json:"model"`
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// Prompt is read only by completion API calls
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Prompt string `json:"prompt"`
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// Messages is readh only by chat/completion API calls
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Messages []Message `json:"messages"`
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// Common options between all the API calls
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TopP float64 `json:"top_p"`
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TopK int `json:"top_k"`
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Temperature float64 `json:"temperature"`
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Maxtokens int `json:"max_tokens"`
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}
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//go:embed index.html
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var indexHTML embed.FS
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func completionEndpoint(defaultModel *llama.LLama, loader *model.ModelLoader, threads int, defaultMutex *sync.Mutex, mutexMap *sync.Mutex, mutexes map[string]*sync.Mutex) func(c *fiber.Ctx) error {
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func openAIEndpoint(chat bool, defaultModel *llama.LLama, loader *model.ModelLoader, threads int, defaultMutex *sync.Mutex, mutexMap *sync.Mutex, mutexes map[string]*sync.Mutex) func(c *fiber.Ctx) error {
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return func(c *fiber.Ctx) error {
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var err error
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var model *llama.LLama
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input := new(OpenAIRequest)
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// Get input data from the request body
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input := new(struct {
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Model string `json:"model"`
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Prompt string `json:"prompt"`
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})
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if err := c.BodyParser(input); err != nil {
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return err
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}
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@ -90,132 +101,35 @@ func completionEndpoint(defaultModel *llama.LLama, loader *model.ModelLoader, th
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}
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// Set the parameters for the language model prediction
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topP, err := strconv.ParseFloat(c.Query("topP", "0.9"), 64) // Default value of topP is 0.9
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if err != nil {
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return err
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topP := input.TopP
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if topP == 0 {
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topP = 0.7
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}
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topK := input.TopK
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if topK == 0 {
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topK = 80
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}
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topK, err := strconv.Atoi(c.Query("topK", "40")) // Default value of topK is 40
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if err != nil {
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return err
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temperature := input.Temperature
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if temperature == 0 {
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temperature = 0.9
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}
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temperature, err := strconv.ParseFloat(c.Query("temperature", "0.5"), 64) // Default value of temperature is 0.5
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if err != nil {
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return err
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}
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tokens, err := strconv.Atoi(c.Query("tokens", "128")) // Default value of tokens is 128
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if err != nil {
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return err
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tokens := input.Maxtokens
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if tokens == 0 {
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tokens = 512
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}
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predInput := input.Prompt
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// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
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templatedInput, err := loader.TemplatePrefix(input.Model, struct {
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Input string
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}{Input: input.Prompt})
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if err == nil {
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predInput = templatedInput
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}
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// Generate the prediction using the language model
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prediction, err := model.Predict(
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predInput,
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llama.SetTemperature(temperature),
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llama.SetTopP(topP),
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llama.SetTopK(topK),
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llama.SetTokens(tokens),
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llama.SetThreads(threads),
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)
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if err != nil {
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return err
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}
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// Return the prediction in the response body
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return c.JSON(OpenAIResponse{
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Model: input.Model,
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Choices: []Choice{{Text: prediction}},
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})
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}
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}
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func chatEndpoint(defaultModel *llama.LLama, loader *model.ModelLoader, threads int, defaultMutex *sync.Mutex, mutexMap *sync.Mutex, mutexes map[string]*sync.Mutex) func(c *fiber.Ctx) error {
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return func(c *fiber.Ctx) error {
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var err error
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var model *llama.LLama
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// Get input data from the request body
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input := new(struct {
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Messages []Message `json:"messages"`
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Model string `json:"model"`
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})
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if err := c.BodyParser(input); err != nil {
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return err
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}
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// TODO: drop me!
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if input.Model == "gpt-3.5-turbo" {
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input.Model = "ggml-koala-7b-model-q4_0-r2"
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}
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if input.Model == "" {
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if defaultModel == nil {
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return fmt.Errorf("no default model loaded, and no model specified")
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if chat {
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mess := []string{}
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for _, i := range input.Messages {
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mess = append(mess, i.Content)
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}
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model = defaultModel
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} else {
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model, err = loader.LoadModel(input.Model)
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if err != nil {
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return err
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}
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}
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// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
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if input.Model != "" {
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mutexMap.Lock()
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l, ok := mutexes[input.Model]
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if !ok {
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m := &sync.Mutex{}
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mutexes[input.Model] = m
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l = m
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}
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mutexMap.Unlock()
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l.Lock()
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defer l.Unlock()
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} else {
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defaultMutex.Lock()
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defer defaultMutex.Unlock()
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predInput = strings.Join(mess, "\n")
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}
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// Set the parameters for the language model prediction
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topP, err := strconv.ParseFloat(c.Query("topP", "0.9"), 64) // Default value of topP is 0.9
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if err != nil {
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return err
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}
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topK, err := strconv.Atoi(c.Query("topK", "40")) // Default value of topK is 40
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if err != nil {
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return err
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}
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temperature, err := strconv.ParseFloat(c.Query("temperature", "0.5"), 64) // Default value of temperature is 0.5
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if err != nil {
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return err
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}
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tokens, err := strconv.Atoi(c.Query("tokens", "128")) // Default value of tokens is 128
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if err != nil {
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return err
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}
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mess := []string{}
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for _, i := range input.Messages {
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mess = append(mess, i.Content)
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}
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predInput := strings.Join(mess, "\n")
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// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
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templatedInput, err := loader.TemplatePrefix(input.Model, struct {
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Input string
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@ -237,10 +151,18 @@ func chatEndpoint(defaultModel *llama.LLama, loader *model.ModelLoader, threads
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return err
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}
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if chat {
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// Return the chat prediction in the response body
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return c.JSON(OpenAIResponse{
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Model: input.Model,
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Choices: []Choice{{Message: Message{Role: "assistant", Content: prediction}}},
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})
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}
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// Return the prediction in the response body
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return c.JSON(OpenAIResponse{
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Model: input.Model,
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Choices: []Choice{{Message: Message{Role: "assistant", Content: prediction}}},
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Choices: []Choice{{Text: prediction}},
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})
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}
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}
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@ -258,8 +180,8 @@ func Start(defaultModel *llama.LLama, loader *model.ModelLoader, listenAddr stri
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var mumutex = &sync.Mutex{}
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// openAI compatible API endpoint
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app.Post("/v1/chat/completions", chatEndpoint(defaultModel, loader, threads, mutex, mumutex, mu))
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app.Post("/v1/completions", completionEndpoint(defaultModel, loader, threads, mutex, mumutex, mu))
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app.Post("/v1/chat/completions", openAIEndpoint(true, defaultModel, loader, threads, mutex, mumutex, mu))
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app.Post("/v1/completions", openAIEndpoint(false, defaultModel, loader, threads, mutex, mumutex, mu))
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app.Get("/v1/models", func(c *fiber.Ctx) error {
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models, err := loader.ListModels()
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if err != nil {
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