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af9e5a2d05
* Revert "fix(fncall): fix regression introduced in #1963 (#2048)" This reverts commit6b06d4e0af. * Revert "fix: action-tmate back to upstream, dead code removal (#2038)" This reverts commitfdec8a9d00. * Revert "feat(grpc): return consumed token count and update response accordingly (#2035)" This reverts commite843d7df0e. * Revert "refactor: backend/service split, channel-based llm flow (#1963)" This reverts commiteed5706994. * feat(grpc): return consumed token count and update response accordingly Fixes: #1920 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
86 lines
3.0 KiB
Go
86 lines
3.0 KiB
Go
package startup
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import (
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"errors"
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"os"
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"path/filepath"
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"github.com/go-skynet/LocalAI/embedded"
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"github.com/go-skynet/LocalAI/pkg/downloader"
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"github.com/go-skynet/LocalAI/pkg/utils"
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"github.com/rs/zerolog/log"
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)
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// PreloadModelsConfigurations will preload models from the given list of URLs
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// It will download the model if it is not already present in the model path
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// It will also try to resolve if the model is an embedded model YAML configuration
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func PreloadModelsConfigurations(modelLibraryURL string, modelPath string, models ...string) {
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for _, url := range models {
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// As a best effort, try to resolve the model from the remote library
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// if it's not resolved we try with the other method below
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if modelLibraryURL != "" {
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lib, err := embedded.GetRemoteLibraryShorteners(modelLibraryURL)
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if err == nil {
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if lib[url] != "" {
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log.Debug().Msgf("[startup] model configuration is defined remotely: %s (%s)", url, lib[url])
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url = lib[url]
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}
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}
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}
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url = embedded.ModelShortURL(url)
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switch {
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case embedded.ExistsInModelsLibrary(url):
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modelYAML, err := embedded.ResolveContent(url)
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// If we resolve something, just save it to disk and continue
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if err != nil {
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log.Error().Err(err).Msg("error resolving model content")
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continue
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}
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log.Debug().Msgf("[startup] resolved embedded model: %s", url)
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md5Name := utils.MD5(url)
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modelDefinitionFilePath := filepath.Join(modelPath, md5Name) + ".yaml"
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if err := os.WriteFile(modelDefinitionFilePath, modelYAML, os.ModePerm); err != nil {
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log.Error().Err(err).Str("filepath", modelDefinitionFilePath).Msg("error writing model definition")
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}
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case downloader.LooksLikeURL(url):
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log.Debug().Msgf("[startup] resolved model to download: %s", url)
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// md5 of model name
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md5Name := utils.MD5(url)
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// check if file exists
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if _, err := os.Stat(filepath.Join(modelPath, md5Name)); errors.Is(err, os.ErrNotExist) {
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modelDefinitionFilePath := filepath.Join(modelPath, md5Name) + ".yaml"
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err := downloader.DownloadFile(url, modelDefinitionFilePath, "", func(fileName, current, total string, percent float64) {
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utils.DisplayDownloadFunction(fileName, current, total, percent)
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})
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if err != nil {
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log.Error().Err(err).Str("url", url).Str("filepath", modelDefinitionFilePath).Msg("error downloading model")
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}
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}
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default:
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if _, err := os.Stat(url); err == nil {
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log.Debug().Msgf("[startup] resolved local model: %s", url)
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// copy to modelPath
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md5Name := utils.MD5(url)
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modelYAML, err := os.ReadFile(url)
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if err != nil {
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log.Error().Err(err).Str("filepath", url).Msg("error reading model definition")
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continue
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}
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modelDefinitionFilePath := filepath.Join(modelPath, md5Name) + ".yaml"
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if err := os.WriteFile(modelDefinitionFilePath, modelYAML, os.ModePerm); err != nil {
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log.Error().Err(err).Str("filepath", modelDefinitionFilePath).Msg("error loading model: %s")
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}
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} else {
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log.Warn().Msgf("[startup] failed resolving model '%s'", url)
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}
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}
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}
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}
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