LocalAI/core/http/endpoints/openai/request.go

package openai

import (
	"context"
	"encoding/base64"
	"encoding/json"
	"fmt"
	"io"
	"net/http"
	"strings"

	"github.com/go-skynet/LocalAI/core/config"
	fiberContext "github.com/go-skynet/LocalAI/core/http/ctx"
	"github.com/go-skynet/LocalAI/core/schema"
	"github.com/go-skynet/LocalAI/pkg/grammar"
	model "github.com/go-skynet/LocalAI/pkg/model"
	"github.com/gofiber/fiber/v2"
	"github.com/rs/zerolog/log"
)

func readRequest(c *fiber.Ctx, ml *model.ModelLoader, o *config.ApplicationConfig, firstModel bool) (string, *schema.OpenAIRequest, error) {
	input := new(schema.OpenAIRequest)

	// Get input data from the request body
	if err := c.BodyParser(input); err != nil {
		return "", nil, fmt.Errorf("failed parsing request body: %w", err)
	}

	received, _ := json.Marshal(input)

	ctx, cancel := context.WithCancel(o.Context)
	input.Context = ctx
	input.Cancel = cancel

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

	modelFile, err := fiberContext.ModelFromContext(c, ml, input.Model, firstModel)

	return modelFile, input, err
}

// this function check if the string is an URL, if it's an URL downloads the image in memory
// encodes it in base64 and returns the base64 string
func getBase64Image(s string) (string, error) {
	if strings.HasPrefix(s, "http") {
		// download the image
		resp, err := http.Get(s)
		if err != nil {
			return "", err
		}
		defer resp.Body.Close()

		// read the image data into memory
		data, err := io.ReadAll(resp.Body)
		if err != nil {
			return "", err
		}

		// encode the image data in base64
		encoded := base64.StdEncoding.EncodeToString(data)

		// return the base64 string
		return encoded, nil
	}

	// if the string instead is prefixed with "data:image/jpeg;base64,", drop it
	if strings.HasPrefix(s, "data:image/jpeg;base64,") {
		return strings.ReplaceAll(s, "data:image/jpeg;base64,", ""), nil
	}
	return "", fmt.Errorf("not valid string")
}

func updateRequestConfig(config *config.BackendConfig, input *schema.OpenAIRequest) {
	if input.Echo {
		config.Echo = input.Echo
	}
	if input.TopK != nil {
		config.TopK = input.TopK
	}
	if input.TopP != nil {
		config.TopP = input.TopP
	}

	if input.Backend != "" {
		config.Backend = input.Backend
	}

	if input.ClipSkip != 0 {
		config.Diffusers.ClipSkip = input.ClipSkip
	}

	if input.ModelBaseName != "" {
		config.AutoGPTQ.ModelBaseName = input.ModelBaseName
	}

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

	if input.UseFastTokenizer {
		config.UseFastTokenizer = input.UseFastTokenizer
	}

	if input.NegativePrompt != "" {
		config.NegativePrompt = input.NegativePrompt
	}

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

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

	if input.Grammar != "" {
		config.Grammar = input.Grammar
	}

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

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

	switch stop := input.Stop.(type) {
	case string:
		if stop != "" {
			config.StopWords = append(config.StopWords, stop)
		}
	case []interface{}:
		for _, pp := range stop {
			if s, ok := pp.(string); ok {
				config.StopWords = append(config.StopWords, s)
			}
		}
	}

	if len(input.Tools) > 0 {
		for _, tool := range input.Tools {
			input.Functions = append(input.Functions, tool.Function)
		}
	}

	if input.ToolsChoice != nil {
		var toolChoice grammar.Tool

		switch content := input.ToolsChoice.(type) {
		case string:
			_ = json.Unmarshal([]byte(content), &toolChoice)
		case map[string]interface{}:
			dat, _ := json.Marshal(content)
			_ = json.Unmarshal(dat, &toolChoice)
		}
		input.FunctionCall = map[string]interface{}{
			"name": toolChoice.Function.Name,
		}
	}

	// Decode each request's message content
	index := 0
	for i, m := range input.Messages {
		switch content := m.Content.(type) {
		case string:
			input.Messages[i].StringContent = content
		case []interface{}:
			dat, _ := json.Marshal(content)
			c := []schema.Content{}
			json.Unmarshal(dat, &c)
			for _, pp := range c {
				if pp.Type == "text" {
					input.Messages[i].StringContent = pp.Text
				} else if pp.Type == "image_url" {
					// Detect if pp.ImageURL is an URL, if it is download the image and encode it in base64:
					base64, err := getBase64Image(pp.ImageURL.URL)
					if err == nil {
						input.Messages[i].StringImages = append(input.Messages[i].StringImages, base64) // TODO: make sure that we only return base64 stuff
						// set a placeholder for each image
						input.Messages[i].StringContent = fmt.Sprintf("[img-%d]", index) + input.Messages[i].StringContent
						index++
					} else {
						fmt.Print("Failed encoding image", err)
					}
				}
			}
		}
	}

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

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

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

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

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

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

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

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

	switch inputs := input.Input.(type) {
	case string:
		if inputs != "" {
			config.InputStrings = append(config.InputStrings, inputs)
		}
	case []interface{}:
		for _, pp := range inputs {
			switch i := pp.(type) {
			case string:
				config.InputStrings = append(config.InputStrings, i)
			case []interface{}:
				tokens := []int{}
				for _, ii := range i {
					tokens = append(tokens, int(ii.(float64)))
				}
				config.InputToken = append(config.InputToken, tokens)
			}
		}
	}

	// Can be either a string or an object
	switch fnc := input.FunctionCall.(type) {
	case string:
		if fnc != "" {
			config.SetFunctionCallString(fnc)
		}
	case map[string]interface{}:
		var name string
		n, exists := fnc["name"]
		if exists {
			nn, e := n.(string)
			if e {
				name = nn
			}
		}
		config.SetFunctionCallNameString(name)
	}

	switch p := input.Prompt.(type) {
	case string:
		config.PromptStrings = append(config.PromptStrings, p)
	case []interface{}:
		for _, pp := range p {
			if s, ok := pp.(string); ok {
				config.PromptStrings = append(config.PromptStrings, s)
			}
		}
	}
}

func mergeRequestWithConfig(modelFile string, input *schema.OpenAIRequest, cm *config.BackendConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.BackendConfig, *schema.OpenAIRequest, error) {
	cfg, err := cm.LoadBackendConfigFileByName(modelFile, loader.ModelPath,
		config.LoadOptionDebug(debug),
		config.LoadOptionThreads(threads),
		config.LoadOptionContextSize(ctx),
		config.LoadOptionF16(f16),
	)

	// Set the parameters for the language model prediction
	updateRequestConfig(cfg, input)

	return cfg, input, err
}