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https://github.com/mudler/LocalAI.git
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Minor fixes (#285)
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parent
7e4616646f
commit
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5
.github/workflows/bump_deps.yaml
vendored
5
.github/workflows/bump_deps.yaml
vendored
@ -9,9 +9,6 @@ jobs:
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fail-fast: false
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matrix:
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include:
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- repository: "go-skynet/go-gpt4all-j.cpp"
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variable: "GOGPT4ALLJ_VERSION"
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branch: "master"
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- repository: "go-skynet/go-llama.cpp"
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variable: "GOLLAMA_VERSION"
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branch: "master"
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@ -30,7 +27,7 @@ jobs:
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- repository: "go-skynet/bloomz.cpp"
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variable: "BLOOMZ_VERSION"
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branch: "main"
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- repository: "go-skynet/gpt4all"
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- repository: "nomic-ai/gpt4all"
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variable: "GPT4ALL_VERSION"
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branch: "main"
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runs-on: ubuntu-latest
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@ -696,6 +696,8 @@ curl http://localhost:8080/v1/models
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### Embeddings
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OpenAI docs: https://platform.openai.com/docs/api-reference/embeddings
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<details>
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The embedding endpoint is experimental and enabled only if the model is configured with `embeddings: true` in its `yaml` file, for example:
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@ -742,6 +744,8 @@ curl http://localhost:8080/v1/audio/transcriptions -H "Content-Type: multipart/f
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### Image generation
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OpenAI docs: https://platform.openai.com/docs/api-reference/images/create
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LocalAI supports generating images with Stable diffusion, running on CPU.
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| mode=0 | mode=1 (winograd/sgemm) |
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@ -773,6 +777,8 @@ curl http://localhost:8080/v1/images/generations -H "Content-Type: application/j
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}'
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```
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Note: image generator supports images up to 512x512. You can use other tools however to upscale the image, for instance: https://github.com/upscayl/upscayl.
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#### Setup
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Note: In order to use the `images/generation` endpoint, you need to build LocalAI with `GO_TAGS=stablediffusion`.
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@ -847,7 +853,7 @@ Yes! If the client uses OpenAI and supports setting a different base URL to send
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<details>
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Not currently, as ggml doesn't support GPUs yet: https://github.com/ggerganov/llama.cpp/discussions/915.
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There is partial GPU support, see build instructions above.
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</details>
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116
api/openai.go
116
api/openai.go
@ -289,12 +289,14 @@ func chatEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, thread
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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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r = 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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content := fmt.Sprint(r, " ", i.Content)
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mess = append(mess, content)
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}
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@ -491,66 +493,72 @@ func imageEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, image
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var result []Item
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for _, i := range config.PromptStrings {
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prompts := strings.Split(i, "|")
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positive_prompt := prompts[0]
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negative_prompt := ""
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if len(prompts) > 1 {
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negative_prompt = prompts[1]
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n := input.N
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if input.N == 0 {
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n = 1
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}
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for j := 0; j < n; j++ {
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prompts := strings.Split(i, "|")
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positive_prompt := prompts[0]
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negative_prompt := ""
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if len(prompts) > 1 {
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negative_prompt = prompts[1]
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}
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mode := 0
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step := 15
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mode := 0
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step := 15
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if input.Mode != 0 {
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mode = input.Mode
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}
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if input.Mode != 0 {
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mode = input.Mode
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}
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if input.Step != 0 {
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step = input.Step
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}
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if input.Step != 0 {
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step = input.Step
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}
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tempDir := ""
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if !b64JSON {
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tempDir = imageDir
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}
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// Create a temporary file
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outputFile, err := ioutil.TempFile(tempDir, "b64")
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if err != nil {
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return err
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}
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outputFile.Close()
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output := outputFile.Name() + ".png"
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// Rename the temporary file
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err = os.Rename(outputFile.Name(), output)
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if err != nil {
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return err
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}
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baseURL := c.BaseURL()
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fn, err := ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, loader, *config)
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if err != nil {
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return err
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}
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if err := fn(); err != nil {
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return err
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}
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item := &Item{}
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if b64JSON {
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defer os.RemoveAll(output)
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data, err := os.ReadFile(output)
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tempDir := ""
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if !b64JSON {
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tempDir = imageDir
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}
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// Create a temporary file
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outputFile, err := ioutil.TempFile(tempDir, "b64")
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if err != nil {
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return err
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}
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outputFile.Close()
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output := outputFile.Name() + ".png"
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// Rename the temporary file
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err = os.Rename(outputFile.Name(), output)
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if err != nil {
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return err
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}
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item.B64JSON = base64.StdEncoding.EncodeToString(data)
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} else {
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base := filepath.Base(output)
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item.URL = baseURL + "/generated-images/" + base
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}
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result = append(result, *item)
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baseURL := c.BaseURL()
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fn, err := ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, loader, *config)
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if err != nil {
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return err
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}
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if err := fn(); err != nil {
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return err
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}
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item := &Item{}
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if b64JSON {
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defer os.RemoveAll(output)
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data, err := os.ReadFile(output)
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if err != nil {
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return err
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}
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item.B64JSON = base64.StdEncoding.EncodeToString(data)
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} else {
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base := filepath.Base(output)
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item.URL = baseURL + "/generated-images/" + base
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}
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result = append(result, *item)
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}
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}
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resp := &OpenAIResponse{
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