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750 lines
20 KiB
750 lines
20 KiB
package api
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import (
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"bufio"
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"bytes"
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"encoding/base64"
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"errors"
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"encoding/json"
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"fmt"
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"io"
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"io/ioutil"
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"net/http"
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"os"
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"path"
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"path/filepath"
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"strconv"
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"strings"
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"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
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model "github.com/go-skynet/LocalAI/pkg/model"
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whisperutil "github.com/go-skynet/LocalAI/pkg/whisper"
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llama "github.com/go-skynet/go-llama.cpp"
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"github.com/gofiber/fiber/v2"
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"github.com/rs/zerolog/log"
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"github.com/valyala/fasthttp"
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)
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// APIError provides error information returned by the OpenAI API.
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type APIError struct {
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Code any `json:"code,omitempty"`
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Message string `json:"message"`
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Param *string `json:"param,omitempty"`
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Type string `json:"type"`
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}
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type ErrorResponse struct {
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Error *APIError `json:"error,omitempty"`
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}
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type OpenAIUsage struct {
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PromptTokens int `json:"prompt_tokens"`
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CompletionTokens int `json:"completion_tokens"`
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TotalTokens int `json:"total_tokens"`
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}
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type Item struct {
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Embedding []float32 `json:"embedding"`
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Index int `json:"index"`
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Object string `json:"object,omitempty"`
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// Images
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URL string `json:"url,omitempty"`
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B64JSON string `json:"b64_json,omitempty"`
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}
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type OpenAIResponse struct {
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Created int `json:"created,omitempty"`
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Object string `json:"object,omitempty"`
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ID string `json:"id,omitempty"`
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Model string `json:"model,omitempty"`
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Choices []Choice `json:"choices,omitempty"`
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Data []Item `json:"data,omitempty"`
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Usage OpenAIUsage `json:"usage"`
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}
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type Choice struct {
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Index int `json:"index,omitempty"`
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FinishReason string `json:"finish_reason,omitempty"`
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Message *Message `json:"message,omitempty"`
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Delta *Message `json:"delta,omitempty"`
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Text string `json:"text,omitempty"`
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}
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type Message struct {
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Role string `json:"role,omitempty" yaml:"role"`
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Content string `json:"content,omitempty" yaml:"content"`
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}
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type OpenAIModel struct {
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ID string `json:"id"`
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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" yaml:"model"`
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// whisper
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File string `json:"file" validate:"required"`
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Language string `json:"language"`
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//whisper/image
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ResponseFormat string `json:"response_format"`
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// image
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Size string `json:"size"`
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// Prompt is read only by completion/image API calls
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Prompt interface{} `json:"prompt" yaml:"prompt"`
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// Edit endpoint
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Instruction string `json:"instruction" yaml:"instruction"`
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Input interface{} `json:"input" yaml:"input"`
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Stop interface{} `json:"stop" yaml:"stop"`
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// Messages is read only by chat/completion API calls
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Messages []Message `json:"messages" yaml:"messages"`
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Stream bool `json:"stream"`
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Echo bool `json:"echo"`
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// Common options between all the API calls
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TopP float64 `json:"top_p" yaml:"top_p"`
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TopK int `json:"top_k" yaml:"top_k"`
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Temperature float64 `json:"temperature" yaml:"temperature"`
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Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
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N int `json:"n"`
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// Custom parameters - not present in the OpenAI API
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Batch int `json:"batch" yaml:"batch"`
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F16 bool `json:"f16" yaml:"f16"`
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IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
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RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
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Keep int `json:"n_keep" yaml:"n_keep"`
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MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
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MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
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Mirostat int `json:"mirostat" yaml:"mirostat"`
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Seed int `json:"seed" yaml:"seed"`
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// Image (not supported by OpenAI)
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Mode int `json:"mode"`
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Step int `json:"step"`
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}
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func defaultRequest(modelFile string) OpenAIRequest {
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return OpenAIRequest{
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TopP: 0.7,
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TopK: 80,
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Maxtokens: 512,
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Temperature: 0.9,
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Model: modelFile,
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}
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}
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// https://platform.openai.com/docs/api-reference/completions
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func completionEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
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process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
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ComputeChoices(s, req, config, loader, func(s string, c *[]Choice) {}, func(s string) bool {
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resp := OpenAIResponse{
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Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: []Choice{{Text: s}},
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Object: "text_completion",
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}
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log.Debug().Msgf("Sending goroutine: %s", s)
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responses <- resp
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return true
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})
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close(responses)
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}
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return func(c *fiber.Ctx) error {
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model, input, err := readInput(c, o.loader, true)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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log.Debug().Msgf("`input`: %+v", input)
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config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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log.Debug().Msgf("Parameter Config: %+v", config)
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if input.Stream {
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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")
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c.Set("Connection", "keep-alive")
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c.Set("Transfer-Encoding", "chunked")
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}
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templateFile := config.Model
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if config.TemplateConfig.Completion != "" {
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templateFile = config.TemplateConfig.Completion
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}
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if input.Stream {
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if (len(config.PromptStrings) > 1) {
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return errors.New("cannot handle more than 1 `PromptStrings` when `Stream`ing")
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}
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predInput := config.PromptStrings[0]
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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 := o.loader.TemplatePrefix(templateFile, struct {
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Input string
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}{Input: predInput})
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if err == nil {
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predInput = templatedInput
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log.Debug().Msgf("Template found, input modified to: %s", predInput)
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}
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responses := make(chan OpenAIResponse)
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go process(predInput, input, config, o.loader, responses)
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c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
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for ev := range responses {
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var buf bytes.Buffer
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enc := json.NewEncoder(&buf)
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enc.Encode(ev)
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log.Debug().Msgf("Sending chunk: %s", buf.String())
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fmt.Fprintf(w, "data: %v\n", buf.String())
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w.Flush()
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}
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resp := &OpenAIResponse{
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Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: []Choice{{FinishReason: "stop"}},
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}
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respData, _ := json.Marshal(resp)
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w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
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w.WriteString("data: [DONE]\n\n")
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w.Flush()
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}))
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return nil
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}
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var result []Choice
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for _, i := range config.PromptStrings {
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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 := o.loader.TemplatePrefix(templateFile, struct {
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Input string
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}{Input: i})
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if err == nil {
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i = templatedInput
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log.Debug().Msgf("Template found, input modified to: %s", i)
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}
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r, err := ComputeChoices(i, input, config, o.loader, func(s string, c *[]Choice) {
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*c = append(*c, Choice{Text: s})
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}, nil)
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if err != nil {
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return err
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}
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result = append(result, r...)
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}
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resp := &OpenAIResponse{
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Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: result,
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Object: "text_completion",
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}
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jsonResult, _ := json.Marshal(resp)
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log.Debug().Msgf("Response: %s", jsonResult)
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// Return the prediction in the response body
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return c.JSON(resp)
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}
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}
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// https://platform.openai.com/docs/api-reference/embeddings
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func embeddingsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
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return func(c *fiber.Ctx) error {
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model, input, err := readInput(c, o.loader, true)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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log.Debug().Msgf("Parameter Config: %+v", config)
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items := []Item{}
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for i, s := range config.InputToken {
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// get the model function to call for the result
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embedFn, err := ModelEmbedding("", s, o.loader, *config)
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if err != nil {
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return err
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}
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embeddings, err := embedFn()
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if err != nil {
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return err
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}
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items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
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}
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for i, s := range config.InputStrings {
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// get the model function to call for the result
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embedFn, err := ModelEmbedding(s, []int{}, o.loader, *config)
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if err != nil {
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return err
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}
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embeddings, err := embedFn()
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if err != nil {
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return err
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}
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items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
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}
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resp := &OpenAIResponse{
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Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
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Data: items,
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Object: "list",
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}
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jsonResult, _ := json.Marshal(resp)
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log.Debug().Msgf("Response: %s", jsonResult)
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// Return the prediction in the response body
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return c.JSON(resp)
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}
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}
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func chatEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
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process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
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initialMessage := OpenAIResponse{
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Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: []Choice{{Delta: &Message{Role: "assistant"}}},
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Object: "chat.completion.chunk",
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}
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responses <- initialMessage
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ComputeChoices(s, req, config, loader, func(s string, c *[]Choice) {}, func(s string) bool {
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resp := OpenAIResponse{
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Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: []Choice{{Delta: &Message{Content: s}}},
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Object: "chat.completion.chunk",
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}
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log.Debug().Msgf("Sending goroutine: %s", s)
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responses <- resp
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return true
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})
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close(responses)
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}
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return func(c *fiber.Ctx) error {
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model, input, err := readInput(c, o.loader, true)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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log.Debug().Msgf("Parameter Config: %+v", config)
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var predInput string
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mess := []string{}
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for _, i := range input.Messages {
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var content string
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r := config.Roles[i.Role]
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if r != "" {
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content = fmt.Sprint(r, " ", i.Content)
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} else {
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content = i.Content
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}
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mess = append(mess, content)
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}
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predInput = strings.Join(mess, "\n")
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if input.Stream {
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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")
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c.Set("Connection", "keep-alive")
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c.Set("Transfer-Encoding", "chunked")
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}
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templateFile := config.Model
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if config.TemplateConfig.Chat != "" {
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templateFile = config.TemplateConfig.Chat
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}
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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 := o.loader.TemplatePrefix(templateFile, struct {
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Input string
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}{Input: predInput})
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if err == nil {
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predInput = templatedInput
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log.Debug().Msgf("Template found, input modified to: %s", predInput)
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}
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if input.Stream {
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responses := make(chan OpenAIResponse)
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go process(predInput, input, config, o.loader, responses)
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c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
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for ev := range responses {
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var buf bytes.Buffer
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enc := json.NewEncoder(&buf)
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enc.Encode(ev)
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log.Debug().Msgf("Sending chunk: %s", buf.String())
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fmt.Fprintf(w, "data: %v\n", buf.String())
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w.Flush()
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}
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resp := &OpenAIResponse{
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Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: []Choice{{FinishReason: "stop"}},
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}
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respData, _ := json.Marshal(resp)
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w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
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w.WriteString("data: [DONE]\n\n")
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w.Flush()
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}))
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return nil
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}
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result, err := ComputeChoices(predInput, input, config, o.loader, func(s string, c *[]Choice) {
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*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: s}})
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}, nil)
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if err != nil {
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return err
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}
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resp := &OpenAIResponse{
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Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: result,
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Object: "chat.completion",
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}
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respData, _ := json.Marshal(resp)
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log.Debug().Msgf("Response: %s", respData)
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// Return the prediction in the response body
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return c.JSON(resp)
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}
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}
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func editEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
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return func(c *fiber.Ctx) error {
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model, input, err := readInput(c, o.loader, true)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
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if err != nil {
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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log.Debug().Msgf("Parameter Config: %+v", config)
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templateFile := config.Model
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if config.TemplateConfig.Edit != "" {
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templateFile = config.TemplateConfig.Edit
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}
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var result []Choice
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for _, i := range config.InputStrings {
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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 := o.loader.TemplatePrefix(templateFile, struct {
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Input string
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Instruction string
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}{Input: i})
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if err == nil {
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i = templatedInput
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log.Debug().Msgf("Template found, input modified to: %s", i)
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}
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r, err := ComputeChoices(i, input, config, o.loader, func(s string, c *[]Choice) {
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*c = append(*c, Choice{Text: s})
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}, nil)
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if err != nil {
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return err
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}
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result = append(result, r...)
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}
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resp := &OpenAIResponse{
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Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
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Choices: result,
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Object: "edit",
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}
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jsonResult, _ := json.Marshal(resp)
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log.Debug().Msgf("Response: %s", jsonResult)
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// Return the prediction in the response body
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return c.JSON(resp)
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}
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}
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// https://platform.openai.com/docs/api-reference/images/create
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/*
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*
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curl http://localhost:8080/v1/images/generations \
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-H "Content-Type: application/json" \
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-d '{
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"prompt": "A cute baby sea otter",
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"n": 1,
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"size": "512x512"
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}'
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*
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*/
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func imageEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
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return func(c *fiber.Ctx) error {
|
|
m, input, err := readInput(c, o.loader, false)
|
|
if err != nil {
|
|
return fmt.Errorf("failed reading parameters from request:%w", err)
|
|
}
|
|
|
|
if m == "" {
|
|
m = model.StableDiffusionBackend
|
|
}
|
|
log.Debug().Msgf("Loading model: %+v", m)
|
|
|
|
config, input, err := readConfig(m, input, cm, o.loader, o.debug, 0, 0, false)
|
|
if err != nil {
|
|
return fmt.Errorf("failed reading parameters from request:%w", err)
|
|
}
|
|
|
|
log.Debug().Msgf("Parameter Config: %+v", config)
|
|
|
|
// XXX: Only stablediffusion is supported for now
|
|
if config.Backend == "" {
|
|
config.Backend = model.StableDiffusionBackend
|
|
}
|
|
|
|
sizeParts := strings.Split(input.Size, "x")
|
|
if len(sizeParts) != 2 {
|
|
return fmt.Errorf("Invalid value for 'size'")
|
|
}
|
|
width, err := strconv.Atoi(sizeParts[0])
|
|
if err != nil {
|
|
return fmt.Errorf("Invalid value for 'size'")
|
|
}
|
|
height, err := strconv.Atoi(sizeParts[1])
|
|
if err != nil {
|
|
return fmt.Errorf("Invalid value for 'size'")
|
|
}
|
|
|
|
b64JSON := false
|
|
if input.ResponseFormat == "b64_json" {
|
|
b64JSON = true
|
|
}
|
|
|
|
var result []Item
|
|
for _, i := range config.PromptStrings {
|
|
n := input.N
|
|
if input.N == 0 {
|
|
n = 1
|
|
}
|
|
for j := 0; j < n; j++ {
|
|
prompts := strings.Split(i, "|")
|
|
positive_prompt := prompts[0]
|
|
negative_prompt := ""
|
|
if len(prompts) > 1 {
|
|
negative_prompt = prompts[1]
|
|
}
|
|
|
|
mode := 0
|
|
step := 15
|
|
|
|
if input.Mode != 0 {
|
|
mode = input.Mode
|
|
}
|
|
|
|
if input.Step != 0 {
|
|
step = input.Step
|
|
}
|
|
|
|
tempDir := ""
|
|
if !b64JSON {
|
|
tempDir = o.imageDir
|
|
}
|
|
// Create a temporary file
|
|
outputFile, err := ioutil.TempFile(tempDir, "b64")
|
|
if err != nil {
|
|
return err
|
|
}
|
|
outputFile.Close()
|
|
output := outputFile.Name() + ".png"
|
|
// Rename the temporary file
|
|
err = os.Rename(outputFile.Name(), output)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
|
|
baseURL := c.BaseURL()
|
|
|
|
fn, err := ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.loader, *config)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
if err := fn(); err != nil {
|
|
return err
|
|
}
|
|
|
|
item := &Item{}
|
|
|
|
if b64JSON {
|
|
defer os.RemoveAll(output)
|
|
data, err := os.ReadFile(output)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
item.B64JSON = base64.StdEncoding.EncodeToString(data)
|
|
} else {
|
|
base := filepath.Base(output)
|
|
item.URL = baseURL + "/generated-images/" + base
|
|
}
|
|
|
|
result = append(result, *item)
|
|
}
|
|
}
|
|
|
|
resp := &OpenAIResponse{
|
|
Data: result,
|
|
}
|
|
|
|
jsonResult, _ := json.Marshal(resp)
|
|
log.Debug().Msgf("Response: %s", jsonResult)
|
|
|
|
// Return the prediction in the response body
|
|
return c.JSON(resp)
|
|
}
|
|
}
|
|
|
|
// https://platform.openai.com/docs/api-reference/audio/create
|
|
func transcriptEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
|
return func(c *fiber.Ctx) error {
|
|
m, input, err := readInput(c, o.loader, false)
|
|
if err != nil {
|
|
return fmt.Errorf("failed reading parameters from request:%w", err)
|
|
}
|
|
|
|
config, input, err := readConfig(m, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
|
if err != nil {
|
|
return fmt.Errorf("failed reading parameters from request:%w", err)
|
|
}
|
|
// retrieve the file data from the request
|
|
file, err := c.FormFile("file")
|
|
if err != nil {
|
|
return err
|
|
}
|
|
f, err := file.Open()
|
|
if err != nil {
|
|
return err
|
|
}
|
|
defer f.Close()
|
|
|
|
dir, err := os.MkdirTemp("", "whisper")
|
|
|
|
if err != nil {
|
|
return err
|
|
}
|
|
defer os.RemoveAll(dir)
|
|
|
|
dst := filepath.Join(dir, path.Base(file.Filename))
|
|
dstFile, err := os.Create(dst)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
|
|
if _, err := io.Copy(dstFile, f); err != nil {
|
|
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
|
|
return err
|
|
}
|
|
|
|
log.Debug().Msgf("Audio file copied to: %+v", dst)
|
|
|
|
whisperModel, err := o.loader.BackendLoader(model.WhisperBackend, config.Model, []llama.ModelOption{}, uint32(config.Threads))
|
|
if err != nil {
|
|
return err
|
|
}
|
|
|
|
if whisperModel == nil {
|
|
return fmt.Errorf("could not load whisper model")
|
|
}
|
|
|
|
w, ok := whisperModel.(whisper.Model)
|
|
if !ok {
|
|
return fmt.Errorf("loader returned non-whisper object")
|
|
}
|
|
|
|
tr, err := whisperutil.Transcript(w, dst, input.Language, uint(config.Threads))
|
|
if err != nil {
|
|
return err
|
|
}
|
|
|
|
log.Debug().Msgf("Trascribed: %+v", tr)
|
|
// TODO: handle different outputs here
|
|
return c.Status(http.StatusOK).JSON(fiber.Map{"text": tr})
|
|
}
|
|
}
|
|
|
|
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.ListConfigs() {
|
|
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,
|
|
})
|
|
}
|
|
}
|
|
|