Make it compatible with openAI api, support multiple models

Signed-off-by: mudler <mudler@c3os.io>

api.go

@@ -2,24 +2,128 @@ package main
 
 import (
 	"embed"
+	"fmt"
 	"net/http"
 	"strconv"
+	"strings"
 	"sync"
 
 	llama "github.com/go-skynet/go-llama.cpp"
 	"github.com/gofiber/fiber/v2"
+	"github.com/gofiber/fiber/v2/middleware/cors"
 	"github.com/gofiber/fiber/v2/middleware/filesystem"
+	"github.com/gofiber/fiber/v2/middleware/recover"
 )
 
+type OpenAIResponse struct {
+	Created int      `json:"created"`
+	Object  string   `json:"chat.completion"`
+	ID      string   `json:"id"`
+	Model   string   `json:"model"`
+	Choices []Choice `json:"choices"`
+}
+
+type Choice struct {
+	Index        int     `json:"index"`
+	FinishReason string  `json:"finish_reason"`
+	Message      Message `json:"message"`
+}
+
+type Message struct {
+	Role    string `json:"role"`
+	Content string `json:"content"`
+}
+
 //go:embed index.html
 var indexHTML embed.FS
 
-func api(l *llama.LLama, listenAddr string, threads int) error {
+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",
 	}))
+
+	var mutex = &sync.Mutex{}
+
+	// openAI compatible API endpoint
+	app.Post("/v1/chat/completions", func(c *fiber.Ctx) error {
+		var err error
+		var model *llama.LLama
+
+		// Get input data from the request body
+		input := new(struct {
+			Messages []Message `json:"messages"`
+			Model    string    `json:"model"`
+		})
+		if err := c.BodyParser(input); err != nil {
+			return err
+		}
+
+		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
+			}
+		}
+
+		// 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
+		}
+
+		mess := []string{}
+		for _, i := range input.Messages {
+			mess = append(mess, i.Content)
+		}
+
+		fmt.Println("Received", input, input.Model)
+		// Generate the prediction using the language model
+		prediction, err := model.Predict(
+			strings.Join(mess, "\n"),
+			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{{Message: Message{Role: "assistant", Content: prediction}}},
+		})
+	})
+
 	/*
 		curl --location --request POST 'http://localhost:8080/predict' --header 'Content-Type: application/json' --data-raw '{
 		    "text": "What is an alpaca?",
@@ -29,8 +133,6 @@ func api(l *llama.LLama, listenAddr string, threads int) error {
 		    "tokens": 100
 		}'
 	*/
-	var mutex = &sync.Mutex{}
-
 	// Endpoint to generate the prediction
 	app.Post("/predict", func(c *fiber.Ctx) error {
 		mutex.Lock()
@@ -65,7 +167,7 @@ func api(l *llama.LLama, listenAddr string, threads int) error {
 		}
 
 		// Generate the prediction using the language model
-		prediction, err := l.Predict(
+		prediction, err := defaultModel.Predict(
 			input.Text,
 			llama.SetTemperature(temperature),
 			llama.SetTopP(topP),
@@ -86,6 +188,6 @@ func api(l *llama.LLama, listenAddr string, threads int) error {
 	})
 
 	// Start the server
-	app.Listen(":8080")
+	app.Listen(listenAddr)
 	return nil
 }

main.go

@@ -146,8 +146,12 @@ echo "An Alpaca (Vicugna pacos) is a domesticated species of South American came
 						Value:   runtime.NumCPU(),
 					},
 					&cli.StringFlag{
-						Name:    "model",
-						EnvVars: []string{"MODEL_PATH"},
+						Name:    "models-path",
+						EnvVars: []string{"MODELS_PATH"},
+					},
+					&cli.StringFlag{
+						Name:    "default-model",
+						EnvVars: []string{"default-model"},
 					},
 					&cli.StringFlag{
 						Name:    "address",
@@ -161,13 +165,19 @@ echo "An Alpaca (Vicugna pacos) is a domesticated species of South American came
 					},
 				},
 				Action: func(ctx *cli.Context) error {
-					l, err := llamaFromOptions(ctx)
+
+					var defaultModel *llama.LLama
+					defModel := ctx.String("default-model")
+					if defModel != "" {
+						opts := []llama.ModelOption{llama.SetContext(ctx.Int("context-size"))}
+						var err error
+						defaultModel, err = llama.New(ctx.String("default-model"), opts...)
 						if err != nil {
-						fmt.Println("Loading the model failed:", err.Error())
-						os.Exit(1)
+							return err
+						}
 					}
 
-					return api(l, ctx.String("address"), ctx.Int("threads"))
+					return api(defaultModel, NewModelLoader(ctx.String("models-path")), ctx.String("address"), ctx.Int("threads"))
 				},
 			},
 		},

model_loader.go

@@ -0,0 +1,52 @@
+package main
+
+import (
+	"fmt"
+	"os"
+	"path/filepath"
+	"sync"
+
+	llama "github.com/go-skynet/go-llama.cpp"
+)
+
+type ModelLoader struct {
+	modelPath string
+	mu        sync.Mutex
+	models    map[string]*llama.LLama
+}
+
+func NewModelLoader(modelPath string) *ModelLoader {
+	return &ModelLoader{modelPath: modelPath, models: make(map[string]*llama.LLama)}
+}
+
+func (ml *ModelLoader) LoadModel(s string, opts ...llama.ModelOption) (*llama.LLama, error) {
+	ml.mu.Lock()
+	defer ml.mu.Unlock()
+
+	// Check if we already have a loaded model
+	modelFile := filepath.Join(ml.modelPath, s)
+
+	if m, ok := ml.models[modelFile]; ok {
+		return m, nil
+	}
+
+	// Check if the model path exists
+	if _, err := os.Stat(modelFile); os.IsNotExist(err) {
+		// try to find a s.bin
+		modelBin := fmt.Sprintf("%s.bin", modelFile)
+		if _, err := os.Stat(modelBin); os.IsNotExist(err) {
+			return nil, err
+		} else {
+			modelFile = modelBin
+		}
+	}
+
+	// Load the model and keep it in memory for later use
+	model, err := llama.New(modelFile, opts...)
+	if err != nil {
+		return nil, err
+	}
+
+	ml.models[modelFile] = model
+	return model, err
+}