LocalAI/api/openai.go

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package api
import (
"bufio"
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"bytes"
"encoding/json"
"fmt"
"os"
"path/filepath"
"strings"
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 OpenAIUsage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
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"`
Usage OpenAIUsage `json:"usage"`
}
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 interface{} `json:"prompt" yaml:"prompt"`
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// Edit endpoint
Instruction string `json:"instruction" yaml:"instruction"`
Input string `json:"input" yaml:"input"`
Stop interface{} `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
}
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 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
}
}
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func readConfig(cm ConfigMerger, c *fiber.Ctx, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*Config, *OpenAIRequest, error) {
input := new(OpenAIRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return nil, nil, err
}
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modelFile := input.Model
received, _ := json.Marshal(input)
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log.Debug().Msgf("Request received: %s", string(received))
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// Set model from bearer token, if available
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
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// 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 nil, nil, fmt.Errorf("no model specified")
}
}
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// If a model is found in bearer token takes precedence
if bearerExists {
log.Debug().Msgf("Using model from bearer token: %s", bearer)
modelFile = bearer
}
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// 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 nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
}
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}
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var config *Config
cfg, exists := cm[modelFile]
if !exists {
config = &Config{
OpenAIRequest: defaultRequest(modelFile),
}
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} else {
config = &cfg
}
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// Set the parameters for the language model prediction
updateConfig(config, input)
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if threads != 0 {
config.Threads = threads
}
if ctx != 0 {
config.ContextSize = ctx
}
if f16 {
config.F16 = true
}
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if debug {
config.Debug = true
}
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return config, input, nil
}
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// https://platform.openai.com/docs/api-reference/completions
func completionEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
config, input, err := readConfig(cm, c, loader, debug, threads, ctx, f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
predInput := []string{}
switch p := input.Prompt.(type) {
case string:
predInput = append(predInput, p)
case []interface{}:
for _, pp := range p {
if s, ok := pp.(string); ok {
predInput = append(predInput, s)
}
}
}
templateFile := config.Model
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if config.TemplateConfig.Completion != "" {
templateFile = config.TemplateConfig.Completion
}
var result []Choice
for _, i := range predInput {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(templateFile, struct {
Input string
}{Input: i})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input, config, loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
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}
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resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "text_completion",
}
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jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
func chatEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
ComputeChoices(s, req, config, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Role: "assistant", Content: s}}},
Object: "chat.completion.chunk",
}
log.Debug().Msgf("Sending goroutine: %s", s)
responses <- resp
return true
})
close(responses)
}
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return func(c *fiber.Ctx) error {
config, input, err := readConfig(cm, c, loader, debug, threads, ctx, f16)
if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
}
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log.Debug().Msgf("Parameter Config: %+v", config)
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var predInput string
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mess := []string{}
for _, i := range input.Messages {
r := config.Roles[i.Role]
if r == "" {
r = i.Role
}
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content := fmt.Sprint(r, " ", i.Content)
mess = append(mess, content)
}
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predInput = strings.Join(mess, "\n")
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if input.Stream {
log.Debug().Msgf("Stream request received")
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c.Context().SetContentType("text/event-stream")
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//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
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// c.Set("Content-Type", "text/event-stream")
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c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
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templateFile := config.Model
if config.TemplateConfig.Chat != "" {
templateFile = config.TemplateConfig.Chat
}
// 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)
}
if input.Stream {
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responses := make(chan OpenAIResponse)
go process(predInput, input, config, loader, responses)
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c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
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for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
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fmt.Fprintf(w, "event: data\n\n")
fmt.Fprintf(w, "data: %v\n\n", buf.String())
log.Debug().Msgf("Sending chunk: %s", buf.String())
w.Flush()
}
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w.WriteString("event: data\n\n")
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: []Choice{{FinishReason: "stop"}},
}
respData, _ := json.Marshal(resp)
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w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.Flush()
}))
return nil
}
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result, err := ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: s}})
}, nil)
if err != nil {
return err
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "chat.completion",
}
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respData, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", respData)
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// Return the prediction in the response body
return c.JSON(resp)
}
}
func editEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
config, input, err := readConfig(cm, c, loader, debug, threads, ctx, f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
predInput := input.Input
templateFile := config.Model
if config.TemplateConfig.Edit != "" {
templateFile = config.TemplateConfig.Edit
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(templateFile, struct {
Input string
Instruction string
}{Input: predInput, Instruction: input.Instruction})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
result, err := ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
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}, nil)
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if err != nil {
return err
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "edit",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// 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,
})
}
}