FlaskAI/api/openai.go

package api

import (
	"bufio"
	"encoding/json"
	"fmt"
	"os"
	"path/filepath"
	"regexp"
	"strings"
	"sync"

	model "github.com/go-skynet/LocalAI/pkg/model"
	"github.com/gofiber/fiber/v2"
	"github.com/rs/zerolog/log"
	"github.com/valyala/fasthttp"
)

// APIError provides error information returned by the OpenAI API.
type APIError struct {
	Code    any     `json:"code,omitempty"`
	Message string  `json:"message"`
	Param   *string `json:"param,omitempty"`
	Type    string  `json:"type"`
}

type ErrorResponse struct {
	Error *APIError `json:"error,omitempty"`
}

type OpenAIResponse struct {
	Created int      `json:"created,omitempty"`
	Object  string   `json:"object,omitempty"`
	ID      string   `json:"id,omitempty"`
	Model   string   `json:"model,omitempty"`
	Choices []Choice `json:"choices,omitempty"`
}

type Choice struct {
	Index        int      `json:"index,omitempty"`
	FinishReason string   `json:"finish_reason,omitempty"`
	Message      *Message `json:"message,omitempty"`
	Delta        *Message `json:"delta,omitempty"`
	Text         string   `json:"text,omitempty"`
}

type Message struct {
	Role    string `json:"role,omitempty" yaml:"role"`
	Content string `json:"content,omitempty" yaml:"content"`
}

type OpenAIModel struct {
	ID     string `json:"id"`
	Object string `json:"object"`
}

type OpenAIRequest struct {
	Model string `json:"model" yaml:"model"`

	// Prompt is read only by completion API calls
	Prompt string `json:"prompt" yaml:"prompt"`

	Stop string `json:"stop" yaml:"stop"`

	// Messages is read only by chat/completion API calls
	Messages []Message `json:"messages" yaml:"messages"`

	Stream bool `json:"stream"`
	Echo   bool `json:"echo"`
	// Common options between all the API calls
	TopP        float64 `json:"top_p" yaml:"top_p"`
	TopK        int     `json:"top_k" yaml:"top_k"`
	Temperature float64 `json:"temperature" yaml:"temperature"`
	Maxtokens   int     `json:"max_tokens" yaml:"max_tokens"`

	N int `json:"n"`

	// Custom parameters - not present in the OpenAI API
	Batch         int     `json:"batch" yaml:"batch"`
	F16           bool    `json:"f16" yaml:"f16"`
	IgnoreEOS     bool    `json:"ignore_eos" yaml:"ignore_eos"`
	RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
	Keep          int     `json:"n_keep" yaml:"n_keep"`

	Seed int `json:"seed" yaml:"seed"`
}

func defaultRequest(modelFile string) OpenAIRequest {
	return OpenAIRequest{
		TopP:        0.7,
		TopK:        80,
		Maxtokens:   512,
		Temperature: 0.9,
		Model:       modelFile,
	}
}

func updateConfig(config *Config, input *OpenAIRequest) {
	if input.Echo {
		config.Echo = input.Echo
	}
	if input.TopK != 0 {
		config.TopK = input.TopK
	}
	if input.TopP != 0 {
		config.TopP = input.TopP
	}

	if input.Temperature != 0 {
		config.Temperature = input.Temperature
	}

	if input.Maxtokens != 0 {
		config.Maxtokens = input.Maxtokens
	}

	if input.Stop != "" {
		config.StopWords = append(config.StopWords, input.Stop)
	}

	if input.RepeatPenalty != 0 {
		config.RepeatPenalty = input.RepeatPenalty
	}

	if input.Keep != 0 {
		config.Keep = input.Keep
	}

	if input.Batch != 0 {
		config.Batch = input.Batch
	}

	if input.F16 {
		config.F16 = input.F16
	}

	if input.IgnoreEOS {
		config.IgnoreEOS = input.IgnoreEOS
	}

	if input.Seed != 0 {
		config.Seed = input.Seed
	}
}

var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
var mu sync.Mutex = sync.Mutex{}

// https://platform.openai.com/docs/api-reference/completions
func openAIEndpoint(cm ConfigMerger, chat, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
	return func(c *fiber.Ctx) error {

		input := new(OpenAIRequest)
		// Get input data from the request body
		if err := c.BodyParser(input); err != nil {
			return err
		}

		if input.Stream {
			log.Debug().Msgf("Stream request received")
			//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
			c.Set("Content-Type", "text/event-stream; charset=utf-8")
			c.Set("Cache-Control", "no-cache")
			c.Set("Connection", "keep-alive")
			c.Set("Transfer-Encoding", "chunked")
		}

		modelFile := input.Model
		received, _ := json.Marshal(input)

		log.Debug().Msgf("Request received: %s", string(received))

		// Set model from bearer token, if available
		bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
		bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)

		// If no model was specified, take the first available
		if modelFile == "" && !bearerExists {
			models, _ := loader.ListModels()
			if len(models) > 0 {
				modelFile = models[0]
				log.Debug().Msgf("No model specified, using: %s", modelFile)
			} else {
				log.Debug().Msgf("No model specified, returning error")
				return fmt.Errorf("no model specified")
			}
		}

		// If a model is found in bearer token takes precedence
		if bearerExists {
			log.Debug().Msgf("Using model from bearer token: %s", bearer)
			modelFile = bearer
		}

		// Load a config file if present after the model name
		modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
		if _, err := os.Stat(modelConfig); err == nil {
			if err := cm.LoadConfig(modelConfig); err != nil {
				return fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
			}
		}

		var config *Config
		cfg, exists := cm[modelFile]
		if !exists {
			config = &Config{
				OpenAIRequest: defaultRequest(modelFile),
			}
		} else {
			config = &cfg
		}

		// Set the parameters for the language model prediction
		updateConfig(config, input)

		if threads != 0 {
			config.Threads = threads
		}
		if ctx != 0 {
			config.ContextSize = ctx
		}
		if f16 {
			config.F16 = true
		}

		if debug {
			config.Debug = true
		}

		log.Debug().Msgf("Parameter Config: %+v", config)

		predInput := input.Prompt
		if chat {
			mess := []string{}
			for _, i := range input.Messages {
				r := config.Roles[i.Role]
				if r == "" {
					r = i.Role
				}

				content := fmt.Sprint(r, " ", i.Content)
				mess = append(mess, content)
			}

			predInput = strings.Join(mess, "\n")
		}

		templateFile := config.Model
		if config.TemplateConfig.Chat != "" && chat {
			templateFile = config.TemplateConfig.Chat
		}

		if config.TemplateConfig.Completion != "" && !chat {
			templateFile = config.TemplateConfig.Completion
		}

		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
		templatedInput, err := loader.TemplatePrefix(templateFile, struct {
			Input string
		}{Input: predInput})
		if err == nil {
			predInput = templatedInput
			log.Debug().Msgf("Template found, input modified to: %s", predInput)
		}

		result := []Choice{}

		n := input.N

		if input.N == 0 {
			n = 1
		}

		// get the model function to call for the result
		predFunc, err := ModelInference(predInput, loader, *config)
		if err != nil {
			return err
		}

		finetunePrediction := func(prediction string) string {
			if config.Echo {
				prediction = predInput + prediction
			}

			for _, c := range config.Cutstrings {
				mu.Lock()
				reg, ok := cutstrings[c]
				if !ok {
					cutstrings[c] = regexp.MustCompile(c)
					reg = cutstrings[c]
				}
				mu.Unlock()
				prediction = reg.ReplaceAllString(prediction, "")
			}

			for _, c := range config.TrimSpace {
				prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
			}
			return prediction
		}

		for i := 0; i < n; i++ {
			prediction, err := predFunc()
			if err != nil {
				return err
			}

			prediction = finetunePrediction(prediction)

			if chat {
				if input.Stream {
					result = append(result, Choice{Delta: &Message{Role: "assistant", Content: prediction}})
				} else {
					result = append(result, Choice{Message: &Message{Role: "assistant", Content: prediction}})
				}
			} else {
				result = append(result, Choice{Text: prediction})
			}
		}

		resp := &OpenAIResponse{
			Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
			Choices: result,
		}
		if input.Stream && chat {
			resp.Object = "chat.completion.chunk"
		} else if chat {
			resp.Object = "chat.completion"
		} else {
			resp.Object = "text_completion"
		}

		jsonResult, _ := json.Marshal(resp)
		log.Debug().Msgf("Response: %s", jsonResult)

		if input.Stream {
			log.Debug().Msgf("Handling stream request")
			c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
				fmt.Fprintf(w, "event: data\n")
				w.Flush()

				fmt.Fprintf(w, "data: %s\n\n", jsonResult)
				w.Flush()

				fmt.Fprintf(w, "event: data\n")
				w.Flush()

				resp := &OpenAIResponse{
					Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
					Choices: []Choice{Choice{FinishReason: "stop"}},
				}
				respData, _ := json.Marshal(resp)

				fmt.Fprintf(w, "data: %s\n\n", respData)
				w.Flush()

				//	fmt.Fprintf(w, "data: [DONE]\n\n")
				//		w.Flush()
			}))
			return nil
		} else {
			// Return the prediction in the response body
			return c.JSON(resp)
		}
	}
}

func listModels(loader *model.ModelLoader, cm ConfigMerger) func(ctx *fiber.Ctx) error {
	return func(c *fiber.Ctx) error {
		models, err := loader.ListModels()
		if err != nil {
			return err
		}
		var mm map[string]interface{} = map[string]interface{}{}

		dataModels := []OpenAIModel{}
		for _, m := range models {
			mm[m] = nil
			dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
		}

		for k := range cm {
			if _, exists := mm[k]; !exists {
				dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
			}
		}

		return c.JSON(struct {
			Object string        `json:"object"`
			Data   []OpenAIModel `json:"data"`
		}{
			Object: "list",
			Data:   dataModels,
		})
	}
}