LocalAI/api/openai/embeddings.go
Dave 255748bcba
MQTT Startup Refactoring Part 1: core/ packages part 1 (#1728)
This PR specifically introduces a `core` folder and moves the following packages over, without any other changes:

- `api/backend`
- `api/config`
- `api/options`
- `api/schema`

Once this is merged and we confirm there's no regressions, I can migrate over the remaining changes piece by piece to split up application startup, backend services, http, and mqtt as was the goal of the earlier PRs!
2024-02-21 01:21:19 +00:00

79 lines
2.1 KiB
Go

package openai
import (
"encoding/json"
"fmt"
"time"
"github.com/go-skynet/LocalAI/core/backend"
config "github.com/go-skynet/LocalAI/core/config"
"github.com/go-skynet/LocalAI/core/schema"
"github.com/google/uuid"
"github.com/go-skynet/LocalAI/core/options"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
// https://platform.openai.com/docs/api-reference/embeddings
func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readRequest(c, o, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := mergeRequestWithConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
items := []schema.Item{}
for i, s := range config.InputToken {
// get the model function to call for the result
embedFn, err := backend.ModelEmbedding("", s, o.Loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
for i, s := range config.InputStrings {
// get the model function to call for the result
embedFn, err := backend.ModelEmbedding(s, []int{}, o.Loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
id := uuid.New().String()
created := int(time.Now().Unix())
resp := &schema.OpenAIResponse{
ID: id,
Created: created,
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Data: items,
Object: "list",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}