2024-01-05 17:04:46 +00:00
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package openai
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import (
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"bufio"
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"bytes"
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"encoding/json"
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2024-04-17 21:33:49 +00:00
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"errors"
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2024-01-05 17:04:46 +00:00
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"fmt"
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2024-04-17 21:33:49 +00:00
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"time"
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2024-01-05 17:04:46 +00:00
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2024-06-23 08:24:36 +00:00
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"github.com/mudler/LocalAI/core/backend"
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"github.com/mudler/LocalAI/core/config"
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2024-03-01 15:19:53 +00:00
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2024-01-05 17:04:46 +00:00
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"github.com/gofiber/fiber/v2"
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"github.com/google/uuid"
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2024-06-23 08:24:36 +00:00
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"github.com/mudler/LocalAI/core/schema"
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"github.com/mudler/LocalAI/pkg/functions"
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model "github.com/mudler/LocalAI/pkg/model"
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"github.com/mudler/LocalAI/pkg/templates"
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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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2024-03-29 21:29:33 +00:00
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// CompletionEndpoint is the OpenAI Completion API endpoint https://platform.openai.com/docs/api-reference/completions
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// @Summary Generate completions for a given prompt and model.
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// @Param request body schema.OpenAIRequest true "query params"
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// @Success 200 {object} schema.OpenAIResponse "Response"
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// @Router /v1/completions [post]
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func CompletionEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, evaluator *templates.Evaluator, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
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id := uuid.New().String()
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created := int(time.Now().Unix())
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process := func(s string, req *schema.OpenAIRequest, config *config.BackendConfig, loader *model.ModelLoader, responses chan schema.OpenAIResponse) {
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ComputeChoices(req, s, config, appConfig, loader, func(s string, c *[]schema.Choice) {}, func(s string, usage backend.TokenUsage) bool {
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resp := schema.OpenAIResponse{
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ID: id,
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Created: created,
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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: []schema.Choice{
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{
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Index: 0,
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Text: s,
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},
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},
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Object: "text_completion",
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Usage: schema.OpenAIUsage{
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PromptTokens: usage.Prompt,
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CompletionTokens: usage.Completion,
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TotalTokens: usage.Prompt + usage.Completion,
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},
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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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2024-09-28 15:23:56 +00:00
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// Add Correlation
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c.Set("X-Correlation-ID", id)
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2024-07-10 13:28:39 +00:00
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modelFile, input, err := readRequest(c, cl, ml, appConfig, 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 := mergeRequestWithConfig(modelFile, input, cl, ml, appConfig.Debug, appConfig.Threads, appConfig.ContextSize, appConfig.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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2024-05-29 12:40:54 +00:00
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if config.ResponseFormatMap != nil {
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d := schema.ChatCompletionResponseFormat{}
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dat, _ := json.Marshal(config.ResponseFormatMap)
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_ = json.Unmarshal(dat, &d)
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if d.Type == "json_object" {
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input.Grammar = functions.JSONBNF
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}
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}
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config.Grammar = input.Grammar
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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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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 Streaming")
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}
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predInput := config.PromptStrings[0]
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templatedInput, err := evaluator.EvaluateTemplateForPrompt(templates.CompletionPromptTemplate, *config, templates.PromptTemplateData{
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Input: predInput,
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SystemPrompt: config.SystemPrompt,
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})
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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 schema.OpenAIResponse)
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go process(predInput, input, config, ml, 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 := &schema.OpenAIResponse{
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ID: id,
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Created: created,
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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: []schema.Choice{
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{
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Index: 0,
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FinishReason: "stop",
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},
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},
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Object: "text_completion",
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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 []schema.Choice
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totalTokenUsage := backend.TokenUsage{}
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for k, i := range config.PromptStrings {
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templatedInput, err := evaluator.EvaluateTemplateForPrompt(templates.CompletionPromptTemplate, *config, templates.PromptTemplateData{
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SystemPrompt: config.SystemPrompt,
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Input: i,
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})
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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, tokenUsage, err := ComputeChoices(
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input, i, config, appConfig, ml, func(s string, c *[]schema.Choice) {
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*c = append(*c, schema.Choice{Text: s, FinishReason: "stop", Index: k})
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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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totalTokenUsage.Prompt += tokenUsage.Prompt
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totalTokenUsage.Completion += tokenUsage.Completion
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result = append(result, r...)
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}
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resp := &schema.OpenAIResponse{
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ID: id,
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Created: created,
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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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Usage: schema.OpenAIUsage{
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PromptTokens: totalTokenUsage.Prompt,
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CompletionTokens: totalTokenUsage.Completion,
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TotalTokens: totalTokenUsage.Prompt + totalTokenUsage.Completion,
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},
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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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