Major API enhancements (#44)

Signed-off-by: mudler <mudler@c3os.io>

.env

@@ -1,3 +1,4 @@
 THREADS=14
 CONTEXT_SIZE=512
 MODELS_PATH=/models
+# DEBUG=true

.github/workflows/image.yml

@@ -19,7 +19,7 @@ jobs:
       - name: Prepare
         id: prep
         run: |
-          DOCKER_IMAGE=quay.io/go-skynet/llama-cli
+          DOCKER_IMAGE=quay.io/go-skynet/local-ai
           VERSION=master
           SHORTREF=${GITHUB_SHA::8}
 

.gitignore

@@ -2,8 +2,9 @@
 go-llama
 go-gpt4all-j
 
-# llama-cli build binary
-llama-cli
+# LocalAI build binary
+LocalAI
+local-ai
 
 # Ignore models
 models/*.bin

.goreleaser.yaml

@@ -1,5 +1,5 @@
 # Make sure to check the documentation at http://goreleaser.com
-project_name: llama-cli
+project_name: local-ai
 builds:
   - ldflags:
       - -w -s

Dockerfile

@@ -8,5 +8,5 @@ ARG BUILD_TYPE=
 RUN make build${BUILD_TYPE}
 
 FROM debian:$DEBIAN_VERSION
-COPY --from=builder /build/llama-cli /usr/bin/llama-cli
-ENTRYPOINT [ "/usr/bin/llama-cli" ]
+COPY --from=builder /build/local-ai /usr/bin/local-ai
+ENTRYPOINT [ "/usr/bin/local-ai" ]

Earthfile

@@ -2,4 +2,4 @@ VERSION 0.7
 
 build:
     FROM DOCKERFILE -f Dockerfile .
-    SAVE ARTIFACT /usr/bin/llama-cli AS LOCAL llama-cli
+    SAVE ARTIFACT /usr/bin/local-ai AS LOCAL local-ai

Makefile

@@ -1,7 +1,7 @@
 GOCMD=go
 GOTEST=$(GOCMD) test
 GOVET=$(GOCMD) vet
-BINARY_NAME=llama-cli
+BINARY_NAME=local-ai
 GOLLAMA_VERSION?=llama.cpp-5ecff35
 
 GREEN  := $(shell tput -Txterm setaf 2)

README.md

@@ -1,7 +1,13 @@
-## :camel: llama-cli
+<h1 align="center">
+  <br>
+  <img height="300" src="https://user-images.githubusercontent.com/2420543/233147843-88697415-6dbf-4368-a862-ab217f9f7342.jpeg"> <br>
+    LocalAI
+<br>
+</h1>
 
+> :warning: This project has been renamed from `llama-cli` to `LocalAI` to reflect the fact that we are focusing on a fast drop-in OpenAI API rather on the CLI interface. We think that there are already many projects that can be used as a CLI interface already, for instance  [llama.cpp](https://github.com/ggerganov/llama.cpp) and [gpt4all](https://github.com/nomic-ai/gpt4all). If you are were using `llama-cli` for CLI interactions and want to keep using it, use older versions or please open up an issue - contributions are welcome!
 
-llama-cli is a straightforward, drop-in replacement API compatible with OpenAI for local CPU inferencing, based on [llama.cpp](https://github.com/ggerganov/llama.cpp), [gpt4all](https://github.com/nomic-ai/gpt4all) and [ggml](https://github.com/ggerganov/ggml), including support GPT4ALL-J which is Apache 2.0 Licensed and can be used for commercial purposes.
+LocalAI is a straightforward, drop-in replacement API compatible with OpenAI for local CPU inferencing, based on [llama.cpp](https://github.com/ggerganov/llama.cpp), [gpt4all](https://github.com/nomic-ai/gpt4all) and [ggml](https://github.com/ggerganov/ggml), including support GPT4ALL-J which is Apache 2.0 Licensed and can be used for commercial purposes.
 
 - OpenAI compatible API
 - Supports multiple-models
@@ -18,12 +24,15 @@ Note: You might need to convert older models to the new format, see [here](https
 
 ## Usage
 
-The easiest way to run llama-cli is by using `docker-compose`:
+> `LocalAI` comes by default as a container image. You can check out all the available images with corresponding tags [here](https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest).
+
+The easiest way to run LocalAI is by using `docker-compose`:
 
 ```bash
 
-git clone https://github.com/go-skynet/llama-cli
-cd llama-cli
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI
 
 # copy your models to models/
 cp your-model.bin models/
@@ -45,8 +54,11 @@ curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d
    }'
 ```
 
-Note: The API doesn't inject a default prompt for talking to the model, while the CLI does. You have to use a prompt similar to what's described in the standford-alpaca docs: https://github.com/tatsu-lab/stanford_alpaca#data-release.
+## Prompt templates 
 
+The API doesn't inject a default prompt for talking to the model. You have to use a prompt similar to what's described in the standford-alpaca docs: https://github.com/tatsu-lab/stanford_alpaca#data-release.
+
+<details>
 You can use a default template for every model present in your model path, by creating a corresponding file with the `.tmpl` suffix next to your model. For instance, if the model is called `foo.bin`, you can create a sibiling file, `foo.bin.tmpl` which will be used as a default prompt, for instance this can be used with alpaca:
 
 ```
@@ -58,70 +70,19 @@ Below is an instruction that describes a task. Write a response that appropriate
 ### Response:
 ```
 
-See the [prompt-templates](https://github.com/go-skynet/llama-cli/tree/master/prompt-templates) directory in this repository for templates for most popular models.
+See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prompt-templates) directory in this repository for templates for most popular models.
 
-## Container images
-
-`llama-cli` comes by default as a container image. You can check out all the available images with corresponding tags [here](https://quay.io/repository/go-skynet/llama-cli?tab=tags&tag=latest)
-
-To begin, run:
-
-```
-docker run -ti --rm quay.io/go-skynet/llama-cli:latest  --instruction "What's an alpaca?" --topk 10000 --model ...
-```
-
-Where `--model` is the path of the model you want to use. 
-
-Note: you need to mount a volume to the docker container in order to load a model, for instance:
-
-```
-# assuming your model is in /path/to/your/models/foo.bin
-docker run -v /path/to/your/models:/models -ti --rm quay.io/go-skynet/llama-cli:latest  --instruction "What's an alpaca?" --topk 10000 --model /models/foo.bin
-```
-
-You will receive a response like the following:
-
-```
-An alpaca is a member of the South American Camelid family, which includes the llama, guanaco and vicuña. It is a domesticated species that originates from the Andes mountain range in South America. Alpacas are used in the textile industry for their fleece, which is much softer than wool. Alpacas are also used for meat, milk, and fiber.
-```
-
-## Basic usage
-
-To use llama-cli, specify a pre-trained GPT-based model, an input text, and an instruction for text generation. llama-cli takes the following arguments when running from the CLI:
-
-```
-llama-cli --model <model_path> --instruction <instruction> [--input <input>] [--template <template_path>] [--tokens <num_tokens>] [--threads <num_threads>] [--temperature <temperature>] [--topp <top_p>] [--topk <top_k>]
-```
-
-| Parameter    | Environment Variable | Default Value | Description                            |
-| ------------ | -------------------- | ------------- | -------------------------------------- |
-| template     | TEMPLATE             |               | A file containing a template for output formatting (optional).  |
-| instruction  | INSTRUCTION          |               | Input prompt text or instruction. "-" for STDIN.   |
-| input        | INPUT                | -             | Path to text or "-" for STDIN.                    |
-| model        | MODEL           |               | The path to the pre-trained GPT-based model.      |
-| tokens       | TOKENS               | 128           | The maximum number of tokens to generate. |
-| threads      | THREADS              | NumCPU()      | The number of threads to use for text generation. |
-| temperature  | TEMPERATURE          | 0.95          | Sampling temperature for model output. ( values between `0.1` and `1.0` )  |
-| top_p        | TOP_P                | 0.85          | The cumulative probability for top-p sampling. |
-| top_k        | TOP_K                | 20            | The number of top-k tokens to consider for text generation.  |
-| context-size | CONTEXT_SIZE         | 512           | Default token context size. |
-
-Here's an example of using `llama-cli`:
-
-```
-llama-cli --model ~/ggml-alpaca-7b-q4.bin --instruction "What's an alpaca?"
-```
-
-This will generate text based on the given model and instruction.
+</details>
 
 ## API
 
-`llama-cli` also provides an API for running text generation as a service. The models once loaded the first time will be kept in memory.
+`LocalAI` provides an API for running text generation as a service, that follows the OpenAI reference and can be used as a drop-in. The models once loaded the first time will be kept in memory.
 
+<details>
 Example of starting the API with `docker`:
 
 ```bash
-docker run -p 8080:8080 -ti --rm quay.io/go-skynet/llama-cli:latest api --models-path /path/to/models --context-size 700 --threads 4
+docker run -p 8080:8080 -ti --rm quay.io/go-skynet/local-ai:latest --models-path /path/to/models --context-size 700 --threads 4
 ```
 
 And you'll see:
@@ -136,15 +97,15 @@ And you'll see:
 └───────────────────────────────────────────────────┘ 
 ```
 
-Note: Models have to end up with `.bin`.
+Note: Models have to end up with `.bin` so can be listed by the `/models` endpoint.
 
 You can control the API server options with command line arguments:
 
 ```
-llama-cli api --models-path <model_path> [--address <address>] [--threads <num_threads>]
+local-api --models-path <model_path> [--address <address>] [--threads <num_threads>]
 ```
 
-The API takes takes the following:
+The API takes takes the following parameters:
 
 | Parameter    | Environment Variable | Default Value | Description                            |
 | ------------ | -------------------- | ------------- | -------------------------------------- |
@@ -155,6 +116,8 @@ The API takes takes the following:
 
 Once the server is running, you can start making requests to it using HTTP, using the OpenAI API. 
 
+</details>
+
 ### Supported OpenAI API endpoints
 
 You can check out the [OpenAI API reference](https://platform.openai.com/docs/api-reference/chat/create). 
@@ -212,41 +175,34 @@ python 828bddec6162a023114ce19146cb2b82/gistfile1.txt models tokenizer.model
 
 ### Windows compatibility
 
-It should work, however you need to make sure you give enough resources to the container. See https://github.com/go-skynet/llama-cli/issues/2
+It should work, however you need to make sure you give enough resources to the container. See https://github.com/go-skynet/LocalAI/issues/2
 
 ### Kubernetes
 
-You can run the API directly in Kubernetes:
-
-```bash
-kubectl apply -f https://raw.githubusercontent.com/go-skynet/llama-cli/master/kubernetes/deployment.yaml
-```
+You can run the API in Kubernetes, see an example deployment in [kubernetes](https://github.com/go-skynet/LocalAI/tree/master/kubernetes)
 
 ### Build locally
 
 Pre-built images might fit well for most of the modern hardware, however you can and might need to build the images manually.
 
-In order to build the `llama-cli` container image locally you can use `docker`:
+In order to build the `LocalAI` container image locally you can use `docker`:
 
 ```
-# build the image as "alpaca-image"
-docker build -t llama-cli .
-docker run llama-cli --instruction "What's an alpaca?"
+# build the image
+docker build -t LocalAI .
+docker run LocalAI
 ```
 
-Or build the binary with:
+Or build the binary with `make`:
 
 ```
-# build the image as "alpaca-image"
-docker run --privileged -v /var/run/docker.sock:/var/run/docker.sock --rm -t -v "$(pwd)":/workspace -v earthly-tmp:/tmp/earthly:rw earthly/earthly:v0.7.2 +build
-# run the binary
-./llama-cli --instruction "What's an alpaca?"
+make build
 ```
 
 ## Short-term roadmap
 
-- [x] Mimic OpenAI API (https://github.com/go-skynet/llama-cli/issues/10)
-- Binary releases (https://github.com/go-skynet/llama-cli/issues/6)
+- [x] Mimic OpenAI API (https://github.com/go-skynet/LocalAI/issues/10)
+- Binary releases (https://github.com/go-skynet/LocalAI/issues/6)
 - Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351)
 - [x] Multi-model support
 - Have a webUI!

api/api.go

@@ -1,17 +1,19 @@
 package api
 
 import (
+	"encoding/json"
+	"errors"
 	"fmt"
 	"strings"
 	"sync"
 
-	model "github.com/go-skynet/llama-cli/pkg/model"
-
+	model "github.com/go-skynet/LocalAI/pkg/model"
 	gptj "github.com/go-skynet/go-gpt4all-j.cpp"
 	llama "github.com/go-skynet/go-llama.cpp"
 	"github.com/gofiber/fiber/v2"
 	"github.com/gofiber/fiber/v2/middleware/cors"
 	"github.com/gofiber/fiber/v2/middleware/recover"
+	"github.com/rs/zerolog/log"
 )
 
 type OpenAIResponse struct {
@@ -66,7 +68,7 @@ type OpenAIRequest struct {
 }
 
 // https://platform.openai.com/docs/api-reference/completions
-func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16 bool, defaultMutex *sync.Mutex, mutexMap *sync.Mutex, mutexes map[string]*sync.Mutex) func(c *fiber.Ctx) error {
+func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16 bool, mutexMap *sync.Mutex, mutexes map[string]*sync.Mutex) func(c *fiber.Ctx) error {
 	return func(c *fiber.Ctx) error {
 		var err error
 		var model *llama.LLama
@@ -77,45 +79,52 @@ func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16
 		if err := c.BodyParser(input); err != nil {
 			return err
 		}
+		modelFile := input.Model
+		received, _ := json.Marshal(input)
 
-		if input.Model == "" {
+		log.Debug().Msgf("Request received: %s", string(received))
+
+		// Set model from bearer token, if available
+		bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
+		bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
+		if modelFile == "" && !bearerExists {
 			return fmt.Errorf("no model specified")
-		} else {
-			// Try to load the model with both
-			var llamaerr error
-			llamaOpts := []llama.ModelOption{}
-			if ctx != 0 {
-				llamaOpts = append(llamaOpts, llama.SetContext(ctx))
-			}
-			if f16 {
-				llamaOpts = append(llamaOpts, llama.EnableF16Memory)
-			}
+		}
 
-			model, llamaerr = loader.LoadLLaMAModel(input.Model, llamaOpts...)
-			if llamaerr != nil {
-				gptModel, err = loader.LoadGPTJModel(input.Model)
-				if err != nil {
-					return fmt.Errorf("llama: %s gpt: %s", llamaerr.Error(), err.Error()) // llama failed first, so we want to catch both errors
-				}
+		if bearerExists { // model specified in bearer token takes precedence
+			log.Debug().Msgf("Using model from bearer token: %s", bearer)
+			modelFile = bearer
+		}
+
+		// Try to load the model with both
+		var llamaerr error
+		llamaOpts := []llama.ModelOption{}
+		if ctx != 0 {
+			llamaOpts = append(llamaOpts, llama.SetContext(ctx))
+		}
+		if f16 {
+			llamaOpts = append(llamaOpts, llama.EnableF16Memory)
+		}
+
+		model, llamaerr = loader.LoadLLaMAModel(modelFile, llamaOpts...)
+		if llamaerr != nil {
+			gptModel, err = loader.LoadGPTJModel(modelFile)
+			if err != nil {
+				return fmt.Errorf("llama: %s gpt: %s", llamaerr.Error(), err.Error()) // llama failed first, so we want to catch both errors
 			}
 		}
 
 		// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
-		if input.Model != "" {
-			mutexMap.Lock()
-			l, ok := mutexes[input.Model]
-			if !ok {
-				m := &sync.Mutex{}
-				mutexes[input.Model] = m
-				l = m
-			}
-			mutexMap.Unlock()
-			l.Lock()
-			defer l.Unlock()
-		} else {
-			defaultMutex.Lock()
-			defer defaultMutex.Unlock()
+		mutexMap.Lock()
+		l, ok := mutexes[modelFile]
+		if !ok {
+			m := &sync.Mutex{}
+			mutexes[modelFile] = m
+			l = m
 		}
+		mutexMap.Unlock()
+		l.Lock()
+		defer l.Unlock()
 
 		// Set the parameters for the language model prediction
 		topP := input.TopP
@@ -140,6 +149,7 @@ func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16
 		predInput := input.Prompt
 		if chat {
 			mess := []string{}
+			// TODO: encode roles
 			for _, i := range input.Messages {
 				mess = append(mess, i.Content)
 			}
@@ -148,11 +158,12 @@ func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16
 		}
 
 		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
-		templatedInput, err := loader.TemplatePrefix(input.Model, struct {
+		templatedInput, err := loader.TemplatePrefix(modelFile, struct {
 			Input string
 		}{Input: predInput})
 		if err == nil {
 			predInput = templatedInput
+			log.Debug().Msgf("Template found, input modified to: %s", predInput)
 		}
 
 		result := []Choice{}
@@ -224,8 +235,6 @@ func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16
 		}
 
 		for i := 0; i < n; i++ {
-			var prediction string
-
 			prediction, err := predFunc()
 			if err != nil {
 				return err
@@ -242,30 +251,19 @@ func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16
 			}
 		}
 
+		jsonResult, _ := json.Marshal(result)
+		log.Debug().Msgf("Response: %s", jsonResult)
+
 		// Return the prediction in the response body
 		return c.JSON(OpenAIResponse{
-			Model:   input.Model,
+			Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
 			Choices: result,
 		})
 	}
 }
 
-func Start(loader *model.ModelLoader, listenAddr string, threads, ctxSize int, f16 bool) error {
-	app := fiber.New()
-
-	// Default middleware config
-	app.Use(recover.New())
-	app.Use(cors.New())
-
-	// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
-	var mutex = &sync.Mutex{}
-	mu := map[string]*sync.Mutex{}
-	var mumutex = &sync.Mutex{}
-
-	// openAI compatible API endpoint
-	app.Post("/v1/chat/completions", openAIEndpoint(true, loader, threads, ctxSize, f16, mutex, mumutex, mu))
-	app.Post("/v1/completions", openAIEndpoint(false, loader, threads, ctxSize, f16, mutex, mumutex, mu))
-	app.Get("/v1/models", func(c *fiber.Ctx) error {
+func listModels(loader *model.ModelLoader) func(ctx *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
 		models, err := loader.ListModels()
 		if err != nil {
 			return err
@@ -282,8 +280,48 @@ func Start(loader *model.ModelLoader, listenAddr string, threads, ctxSize int, f
 			Object: "list",
 			Data:   dataModels,
 		})
+	}
+}
+
+func Start(loader *model.ModelLoader, listenAddr string, threads, ctxSize int, f16 bool) error {
+	// Return errors as JSON responses
+	app := fiber.New(fiber.Config{
+		// Override default error handler
+		ErrorHandler: func(ctx *fiber.Ctx, err error) error {
+			// Status code defaults to 500
+			code := fiber.StatusInternalServerError
+
+			// Retrieve the custom status code if it's a *fiber.Error
+			var e *fiber.Error
+			if errors.As(err, &e) {
+				code = e.Code
+			}
+
+			// Send custom error page
+			return ctx.Status(code).JSON(struct {
+				Error string `json:"error"`
+			}{Error: err.Error()})
+		},
 	})
 
+	// Default middleware config
+	app.Use(recover.New())
+	app.Use(cors.New())
+
+	// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
+	mu := map[string]*sync.Mutex{}
+	var mumutex = &sync.Mutex{}
+
+	// openAI compatible API endpoint
+	app.Post("/v1/chat/completions", openAIEndpoint(true, loader, threads, ctxSize, f16, mumutex, mu))
+	app.Post("/chat/completions", openAIEndpoint(true, loader, threads, ctxSize, f16, mumutex, mu))
+
+	app.Post("/v1/completions", openAIEndpoint(false, loader, threads, ctxSize, f16, mumutex, mu))
+	app.Post("/completions", openAIEndpoint(false, loader, threads, ctxSize, f16, mumutex, mu))
+
+	app.Get("/v1/models", listModels(loader))
+	app.Get("/models", listModels(loader))
+
 	// Start the server
 	app.Listen(listenAddr)
 	return nil

docker-compose.yaml

@@ -1,18 +1,8 @@
 version: '3.6'
 
 services:
-
-  # chatgpt:
-  #   image: ghcr.io/mckaywrigley/chatbot-ui:main
-  #   # platform: linux/amd64
-  #   ports:
-  #     - 3000:3000
-  #   environment:
-  #     - 'OPENAI_API_KEY=sk-000000000000000'
-  #     - 'OPENAI_API_HOST=http://api:8080'
-
   api:
-    image: quay.io/go-skynet/llama-cli:latest
+    image: quay.io/go-skynet/local-ai:latest
     build:
       context: .
       dockerfile: Dockerfile
@@ -24,7 +14,6 @@ services:
       - MODELS_PATH=$MODELS_PATH
       - CONTEXT_SIZE=$CONTEXT_SIZE
       - THREADS=$THREADS
+      - DEBUG=$DEBUG
     volumes:
-      - ./models:/models:cached
-    command: api
-    
+      - ./models:/models:cached

go.mod

@@ -1,17 +1,18 @@
-module github.com/go-skynet/llama-cli
+module github.com/go-skynet/LocalAI
 
 go 1.19
 
 require (
+	github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230419091210-303cf2a59a94
 	github.com/go-skynet/go-llama.cpp v0.0.0-20230415213228-bac222030640
 	github.com/gofiber/fiber/v2 v2.42.0
+	github.com/rs/zerolog v1.29.1
 	github.com/urfave/cli/v2 v2.25.0
 )
 
 require (
 	github.com/andybalholm/brotli v1.0.4 // indirect
 	github.com/cpuguy83/go-md2man/v2 v2.0.2 // indirect
-	github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230419091210-303cf2a59a94 // indirect
 	github.com/google/uuid v1.3.0 // indirect
 	github.com/klauspost/compress v1.15.9 // indirect
 	github.com/mattn/go-colorable v0.1.13 // indirect

go.sum

@@ -1,5 +1,6 @@
 github.com/andybalholm/brotli v1.0.4 h1:V7DdXeJtZscaqfNuAdSRuRFzuiKlHSC/Zh3zl9qY3JY=
 github.com/andybalholm/brotli v1.0.4/go.mod h1:fO7iG3H7G2nSZ7m0zPUDn85XEX2GTukHGRSepvi9Eig=
+github.com/coreos/go-systemd/v22 v22.5.0/go.mod h1:Y58oyj3AT4RCenI/lSvhwexgC+NSVTIJ3seZv2GcEnc=
 github.com/cpuguy83/go-md2man/v2 v2.0.2 h1:p1EgwI/C7NhT0JmVkwCD2ZBK8j4aeHQX2pMHHBfMQ6w=
 github.com/cpuguy83/go-md2man/v2 v2.0.2/go.mod h1:tgQtvFlXSQOSOSIRvRPT7W67SCa46tRHOmNcaadrF8o=
 github.com/go-logr/logr v1.2.3 h1:2DntVwHkVopvECVRSlL5PSo9eG+cAkDCuckLubN+rq0=
@@ -8,6 +9,7 @@ github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230419091210-303cf2a59a94/go.mod
 github.com/go-skynet/go-llama.cpp v0.0.0-20230415213228-bac222030640 h1:8SSVbQ3yvq7JnfLCLF4USV0PkQnnduUkaNCv/hHDa3E=
 github.com/go-skynet/go-llama.cpp v0.0.0-20230415213228-bac222030640/go.mod h1:35AKIEMY+YTKCBJIa/8GZcNGJ2J+nQk1hQiWo/OnEWw=
 github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 h1:tfuBGBXKqDEevZMzYi5KSi8KkcZtzBcTgAUUtapy0OI=
+github.com/godbus/dbus/v5 v5.0.4/go.mod h1:xhWf0FNVPg57R7Z0UbKHbJfkEywrmjJnf7w5xrFpKfA=
 github.com/gofiber/fiber/v2 v2.42.0 h1:Fnp7ybWvS+sjNQsFvkhf4G8OhXswvB6Vee8hM/LyS+8=
 github.com/gofiber/fiber/v2 v2.42.0/go.mod h1:3+SGNjqMh5VQH5Vz2Wdi43zTIV16ktlFd3x3R6O1Zlc=
 github.com/google/go-cmp v0.5.9 h1:O2Tfq5qg4qc4AmwVlvv0oLiVAGB7enBSJ2x2DqQFi38=
@@ -16,8 +18,10 @@ github.com/google/uuid v1.3.0 h1:t6JiXgmwXMjEs8VusXIJk2BXHsn+wx8BZdTaoZ5fu7I=
 github.com/google/uuid v1.3.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
 github.com/klauspost/compress v1.15.9 h1:wKRjX6JRtDdrE9qwa4b/Cip7ACOshUI4smpCQanqjSY=
 github.com/klauspost/compress v1.15.9/go.mod h1:PhcZ0MbTNciWF3rruxRgKxI5NkcHHrHUDtV4Yw2GlzU=
+github.com/mattn/go-colorable v0.1.12/go.mod h1:u5H1YNBxpqRaxsYJYSkiCWKzEfiAb1Gb520KVy5xxl4=
 github.com/mattn/go-colorable v0.1.13 h1:fFA4WZxdEF4tXPZVKMLwD8oUnCTTo08duU7wxecdEvA=
 github.com/mattn/go-colorable v0.1.13/go.mod h1:7S9/ev0klgBDR4GtXTXX8a3vIGJpMovkB8vQcUbaXHg=
+github.com/mattn/go-isatty v0.0.14/go.mod h1:7GGIvUiUoEMVVmxf/4nioHXj79iQHKdU27kJ6hsGG94=
 github.com/mattn/go-isatty v0.0.16/go.mod h1:kYGgaQfpe5nmfYZH+SKPsOc2e4SrIfOl2e/yFXSvRLM=
 github.com/mattn/go-isatty v0.0.17 h1:BTarxUcIeDqL27Mc+vyvdWYSL28zpIhv3RoTdsLMPng=
 github.com/mattn/go-isatty v0.0.17/go.mod h1:kYGgaQfpe5nmfYZH+SKPsOc2e4SrIfOl2e/yFXSvRLM=
@@ -27,8 +31,12 @@ github.com/onsi/ginkgo/v2 v2.9.2 h1:BA2GMJOtfGAfagzYtrAlufIP0lq6QERkFmHLMLPwFSU=
 github.com/onsi/gomega v1.27.6 h1:ENqfyGeS5AX/rlXDd/ETokDz93u0YufY1Pgxuy/PvWE=
 github.com/philhofer/fwd v1.1.1 h1:GdGcTjf5RNAxwS4QLsiMzJYj5KEvPJD3Abr261yRQXQ=
 github.com/philhofer/fwd v1.1.1/go.mod h1:gk3iGcWd9+svBvR0sR+KPcfE+RNWozjowpeBVG3ZVNU=
+github.com/pkg/errors v0.9.1/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINEl0=
 github.com/rivo/uniseg v0.2.0 h1:S1pD9weZBuJdFmowNwbpi7BJ8TNftyUImj/0WQi72jY=
 github.com/rivo/uniseg v0.2.0/go.mod h1:J6wj4VEh+S6ZtnVlnTBMWIodfgj8LQOQFoIToxlJtxc=
+github.com/rs/xid v1.4.0/go.mod h1:trrq9SKmegXys3aeAKXMUTdJsYXVwGY3RLcfgqegfbg=
+github.com/rs/zerolog v1.29.1 h1:cO+d60CHkknCbvzEWxP0S9K6KqyTjrCNUy1LdQLCGPc=
+github.com/rs/zerolog v1.29.1/go.mod h1:Le6ESbR7hc+DP6Lt1THiV8CQSdkkNrd3R0XbEgp3ZBU=
 github.com/russross/blackfriday/v2 v2.1.0 h1:JIOH55/0cWyOuilr9/qlrm0BSXldqnqwMsf35Ld67mk=
 github.com/russross/blackfriday/v2 v2.1.0/go.mod h1:+Rmxgy9KzJVeS9/2gXHxylqXiyQDYRxCVz55jmeOWTM=
 github.com/savsgio/dictpool v0.0.0-20221023140959-7bf2e61cea94 h1:rmMl4fXJhKMNWl+K+r/fq4FbbKI+Ia2m9hYBLm2h4G4=
@@ -67,6 +75,8 @@ golang.org/x/sys v0.0.0-20200930185726-fdedc70b468f/go.mod h1:h1NjWce9XRLGQEsW7w
 golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20210423082822-04245dca01da/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20210615035016-665e8c7367d1/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
+golang.org/x/sys v0.0.0-20210630005230-0f9fa26af87c/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
+golang.org/x/sys v0.0.0-20210927094055-39ccf1dd6fa6/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.0.0-20220728004956-3c1f35247d10/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.0.0-20220811171246-fbc7d0a398ab/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.6.0 h1:MVltZSvRTcU2ljQOhs94SXPftV6DCNnZViHeQps87pQ=

kubernetes/data-volume.yaml

@@ -0,0 +1,28 @@
+# Create a PVC containing a model binary, sourced from an arbitrary HTTP server
+# (requires https://github.com/kubevirt/containerized-data-importer)
+apiVersion: cdi.kubevirt.io/v1beta1
+kind: DataVolume
+metadata:
+  name: models
+  namespace: local-ai
+spec:
+  contentType: archive
+  source:
+    http:
+      url: http://<model_server>/koala-7B-4bit-128g.GGML.tar
+      secretRef: model-secret
+  pvc:
+    accessModes:
+    - ReadWriteOnce
+    resources:
+      requests:
+        storage: 5Gi
+---
+apiVersion: v1
+kind: Secret
+metadata:
+  name: model-secret
+  namespace: local-ai
+data:
+  accessKeyId: <model_server_username_base64_encoded>
+  secretKey: <model_server_password_base64_encoded>

kubernetes/deployment.yaml

@@ -1,40 +1,55 @@
 apiVersion: v1
 kind: Namespace
 metadata:
-  name: llama
+  name: local-ai
 ---
 apiVersion: apps/v1
 kind: Deployment
 metadata:
-  name: llama
-  namespace: llama
+  name: local-ai
+  namespace: local-ai
   labels:
-    app: llama
+    app: local-ai
 spec:
   selector:
     matchLabels:
-      app: llama
+      app: local-ai
   replicas: 1
   template:
     metadata:
       labels:
-        app: llama
-      name: llama
+        app: local-ai
+      name: local-ai
     spec:
       containers:
-        - name: llama
-          args:
-          - api
-          image: quay.io/go-skynet/llama-cli:latest
+        - name: local-ai
+          image: quay.io/go-skynet/local-ai:latest
+          env:
+          - name: THREADS
+            value: "14"
+          - name: CONTEXT_SIZE
+            value: "512"
+          - name: MODELS_PATH
+            value: /models
+          volumeMounts:
+          - mountPath: /models
+            name: models
+      volumes:
+      - name: models
+        persistentVolumeClaim:
+          claimName: models
 ---
 apiVersion: v1
 kind: Service
 metadata:
-  name: llama
-  namespace: llama
+  name: local-ai
+  namespace: local-ai
+  # If using AWS, you'll need to override the default 60s load balancer idle timeout
+  # annotations:
+  #   service.beta.kubernetes.io/aws-load-balancer-connection-idle-timeout: "1200"
 spec:
   selector:
-    app: llama
+    app: local-ai
   type: LoadBalancer
   ports:
     - protocol: TCP

main.go

@@ -1,232 +1,89 @@
 package main
 
 import (
-	"bytes"
-	"fmt"
-	"io/ioutil"
 	"os"
 	"runtime"
-	"text/template"
 
-	llama "github.com/go-skynet/go-llama.cpp"
-	api "github.com/go-skynet/llama-cli/api"
-	model "github.com/go-skynet/llama-cli/pkg/model"
+	api "github.com/go-skynet/LocalAI/api"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/rs/zerolog"
+	"github.com/rs/zerolog/log"
 
 	"github.com/urfave/cli/v2"
 )
 
-// Define the template string
-var emptyInput string = `Below is an instruction that describes a task. Write a response that appropriately completes the request.
-
-### Instruction:
-{{.Instruction}}
-
-### Response:`
-
-var nonEmptyInput string = `Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
-
-### Instruction:
-{{.Instruction}}
-
-### Input:
-{{.Input}}
-
-### Response:
-`
-
-func templateString(t string, in interface{}) (string, error) {
-	// Parse the template
-	tmpl, err := template.New("prompt").Parse(t)
-	if err != nil {
-		return "", err
-	}
-
-	var buf bytes.Buffer
-	err = tmpl.Execute(&buf, in)
-	if err != nil {
-		return "", err
-	}
-	return buf.String(), nil
-}
-
-var modelFlags = []cli.Flag{
-	&cli.StringFlag{
-		Name:    "model",
-		EnvVars: []string{"MODEL"},
-	},
-	&cli.IntFlag{
-		Name:    "tokens",
-		EnvVars: []string{"TOKENS"},
-		Value:   128,
-	},
-	&cli.IntFlag{
-		Name:    "context-size",
-		EnvVars: []string{"CONTEXT_SIZE"},
-		Value:   512,
-	},
-	&cli.IntFlag{
-		Name:    "threads",
-		EnvVars: []string{"THREADS"},
-		Value:   runtime.NumCPU(),
-	},
-	&cli.Float64Flag{
-		Name:    "temperature",
-		EnvVars: []string{"TEMPERATURE"},
-		Value:   0.95,
-	},
-	&cli.Float64Flag{
-		Name:    "topp",
-		EnvVars: []string{"TOP_P"},
-		Value:   0.85,
-	},
-	&cli.IntFlag{
-		Name:    "topk",
-		EnvVars: []string{"TOP_K"},
-		Value:   20,
-	},
-}
-
 func main() {
+	log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
+
+	path, err := os.Getwd()
+	if err != nil {
+		log.Error().Msgf("error: %s", err.Error())
+		os.Exit(1)
+	}
+
 	app := &cli.App{
-		Name:    "llama-cli",
-		Version: "0.1",
-		Usage:   "llama-cli --model ... --instruction 'What is an alpaca?'",
-		Flags: append(modelFlags,
-			&cli.StringFlag{
-				Name:    "template",
-				EnvVars: []string{"TEMPLATE"},
+		Name:  "LocalAI",
+		Usage: "OpenAI compatible API for running LLaMA/GPT models locally on CPU with consumer grade hardware.",
+		Flags: []cli.Flag{
+			&cli.BoolFlag{
+				Name:    "f16",
+				EnvVars: []string{"F16"},
+			},
+			&cli.BoolFlag{
+				Name:    "debug",
+				EnvVars: []string{"DEBUG"},
+			},
+			&cli.IntFlag{
+				Name:        "threads",
+				DefaultText: "Number of threads used for parallel computation. Usage of the number of physical cores in the system is suggested.",
+				EnvVars:     []string{"THREADS"},
+				Value:       runtime.NumCPU(),
 			},
 			&cli.StringFlag{
-				Name:    "instruction",
-				EnvVars: []string{"INSTRUCTION"},
+				Name:        "models-path",
+				DefaultText: "Path containing models used for inferencing",
+				EnvVars:     []string{"MODELS_PATH"},
+				Value:       path,
 			},
 			&cli.StringFlag{
-				Name:    "input",
-				EnvVars: []string{"INPUT"},
-			}),
-		Description: `Run llama.cpp inference`,
-		UsageText: `
-llama-cli --model ~/ggml-alpaca-7b-q4.bin --instruction "What's an alpaca?"
-
-	An Alpaca (Vicugna pacos) is a domesticated species of South American camelid, related to llamas and originally from Peru but now found throughout much of Andean region. They are bred for their fleeces which can be spun into wool or knitted items such as hats, sweaters, blankets etc
-		
-echo "An Alpaca (Vicugna pacos) is a domesticated species of South American camelid, related to llamas and originally from Peru but now found throughout much of Andean region. They are bred for their fleeces which can be spun into wool or knitted items such as hats, sweaters, blankets etc" | llama-cli --model ~/ggml-alpaca-7b-q4.bin --instruction "Proofread, improving clarity and flow" --input "-"
-
-	An Alpaca (Vicugna pacos) is a domesticated species from South America that's related to llamas. Originating in Peru but now found throughout the Andean region, they are bred for their fleeces which can be spun into wool or knitted items such as hats and sweaters—blankets too!
-`,
-		Copyright: "go-skynet authors",
-		Commands: []*cli.Command{
-			{
-
-				Name: "api",
-				Flags: []cli.Flag{
-					&cli.BoolFlag{
-						Name:    "f16",
-						EnvVars: []string{"F16"},
-					},
-					&cli.IntFlag{
-						Name:    "threads",
-						EnvVars: []string{"THREADS"},
-						Value:   runtime.NumCPU(),
-					},
-					&cli.StringFlag{
-						Name:    "models-path",
-						EnvVars: []string{"MODELS_PATH"},
-					},
-					&cli.StringFlag{
-						Name:    "address",
-						EnvVars: []string{"ADDRESS"},
-						Value:   ":8080",
-					},
-					&cli.IntFlag{
-						Name:    "context-size",
-						EnvVars: []string{"CONTEXT_SIZE"},
-						Value:   512,
-					},
-				},
-				Action: func(ctx *cli.Context) error {
-					return api.Start(model.NewModelLoader(ctx.String("models-path")), ctx.String("address"), ctx.Int("threads"), ctx.Int("context-size"), ctx.Bool("f16"))
-				},
+				Name:        "address",
+				DefaultText: "Bind address for the API server.",
+				EnvVars:     []string{"ADDRESS"},
+				Value:       ":8080",
+			},
+			&cli.IntFlag{
+				Name:        "context-size",
+				DefaultText: "Default context size of the model",
+				EnvVars:     []string{"CONTEXT_SIZE"},
+				Value:       512,
 			},
 		},
+		Description: `
+LocalAI is a drop-in replacement OpenAI API which runs inference locally.
+
+Some of the models compatible are:
+- Vicuna
+- Koala
+- GPT4ALL
+- GPT4ALL-J
+- Alpaca
+
+It uses llama.cpp and gpt4all as backend, supporting all the models supported by both.
+`,
+		UsageText: `local-ai [options]`,
+		Copyright: "go-skynet authors",
 		Action: func(ctx *cli.Context) error {
-
-			instruction := ctx.String("instruction")
-			input := ctx.String("input")
-			templ := ctx.String("template")
-
-			promptTemplate := ""
-
-			if input != "" {
-				promptTemplate = nonEmptyInput
-			} else {
-				promptTemplate = emptyInput
+			zerolog.SetGlobalLevel(zerolog.InfoLevel)
+			if ctx.Bool("debug") {
+				zerolog.SetGlobalLevel(zerolog.DebugLevel)
 			}
-
-			if templ != "" {
-				dat, err := os.ReadFile(templ)
-				if err != nil {
-					fmt.Printf("Failed reading file: %s", err.Error())
-					os.Exit(1)
-				}
-				promptTemplate = string(dat)
-			}
-
-			if instruction == "-" {
-				dat, err := ioutil.ReadAll(os.Stdin)
-				if err != nil {
-					fmt.Printf("reading stdin failed: %s", err)
-					os.Exit(1)
-				}
-				instruction = string(dat)
-			}
-
-			if input == "-" {
-				dat, err := ioutil.ReadAll(os.Stdin)
-				if err != nil {
-					fmt.Printf("reading stdin failed: %s", err)
-					os.Exit(1)
-				}
-				input = string(dat)
-			}
-
-			str, err := templateString(promptTemplate, struct {
-				Instruction string
-				Input       string
-			}{Instruction: instruction, Input: input})
-
-			if err != nil {
-				fmt.Println("Templating the input failed:", err.Error())
-				os.Exit(1)
-			}
-
-			opts := []llama.ModelOption{llama.SetContext(ctx.Int("context-size"))}
-			l, err := llama.New(ctx.String("model"), opts...)
-			if err != nil {
-				fmt.Println("Loading the model failed:", err.Error())
-				os.Exit(1)
-			}
-
-			res, err := l.Predict(
-				str,
-				llama.SetTemperature(ctx.Float64("temperature")),
-				llama.SetTopP(ctx.Float64("topp")),
-				llama.SetTopK(ctx.Int("topk")),
-				llama.SetTokens(ctx.Int("tokens")),
-				llama.SetThreads(ctx.Int("threads")),
-			)
-			if err != nil {
-				fmt.Printf("predicting failed: %s", err)
-				os.Exit(1)
-			}
-			fmt.Println(res)
-			return nil
+			return api.Start(model.NewModelLoader(ctx.String("models-path")), ctx.String("address"), ctx.Int("threads"), ctx.Int("context-size"), ctx.Bool("f16"))
 		},
 	}
 
-	err := app.Run(os.Args)
+	err = app.Run(os.Args)
 	if err != nil {
-		fmt.Println(err)
+		log.Error().Msgf("error: %s", err.Error())
 		os.Exit(1)
 	}
 }

pkg/model/loader.go

@@ -10,6 +10,8 @@ import (
 	"sync"
 	"text/template"
 
+	"github.com/rs/zerolog/log"
+
 	gptj "github.com/go-skynet/go-gpt4all-j.cpp"
 	llama "github.com/go-skynet/go-llama.cpp"
 )
@@ -26,6 +28,11 @@ func NewModelLoader(modelPath string) *ModelLoader {
 	return &ModelLoader{modelPath: modelPath, gptmodels: make(map[string]*gptj.GPTJ), models: make(map[string]*llama.LLama), promptsTemplates: make(map[string]*template.Template)}
 }
 
+func (ml *ModelLoader) ExistsInModelPath(s string) bool {
+	_, err := os.Stat(filepath.Join(ml.modelPath, s))
+	return err == nil
+}
+
 func (ml *ModelLoader) ListModels() ([]string, error) {
 	files, err := ioutil.ReadDir(ml.modelPath)
 	if err != nil {
@@ -34,9 +41,12 @@ func (ml *ModelLoader) ListModels() ([]string, error) {
 
 	models := []string{}
 	for _, file := range files {
-		if strings.HasSuffix(file.Name(), ".bin") {
-			models = append(models, strings.TrimRight(file.Name(), ".bin"))
+		// Skip templates, YAML and .keep files
+		if strings.HasSuffix(file.Name(), ".tmpl") || strings.HasSuffix(file.Name(), ".keep") || strings.HasSuffix(file.Name(), ".yaml") || strings.HasSuffix(file.Name(), ".yml") {
+			continue
 		}
+
+		models = append(models, file.Name())
 	}
 
 	return models, nil
@@ -48,12 +58,7 @@ func (ml *ModelLoader) TemplatePrefix(modelName string, in interface{}) (string,
 
 	m, ok := ml.promptsTemplates[modelName]
 	if !ok {
-		// try to find a s.bin
-		modelBin := fmt.Sprintf("%s.bin", modelName)
-		m, ok = ml.promptsTemplates[modelBin]
-		if !ok {
-			return "", fmt.Errorf("no prompt template available")
-		}
+		return "", fmt.Errorf("no prompt template available")
 	}
 
 	var buf bytes.Buffer
@@ -64,15 +69,21 @@ func (ml *ModelLoader) TemplatePrefix(modelName string, in interface{}) (string,
 	return buf.String(), nil
 }
 
-func (ml *ModelLoader) loadTemplate(modelName, modelFile string) error {
-	modelTemplateFile := fmt.Sprintf("%s.tmpl", modelFile)
-
-	// Check if the model path exists
-	if _, err := os.Stat(modelTemplateFile); err != nil {
+func (ml *ModelLoader) loadTemplateIfExists(modelName, modelFile string) error {
+	// Check if the template was already loaded
+	if _, ok := ml.promptsTemplates[modelName]; ok {
 		return nil
 	}
 
-	dat, err := os.ReadFile(modelTemplateFile)
+	// Check if the model path exists
+	// skip any error here - we run anyway if a template is not exist
+	modelTemplateFile := fmt.Sprintf("%s.tmpl", modelName)
+
+	if !ml.ExistsInModelPath(modelTemplateFile) {
+		return nil
+	}
+
+	dat, err := os.ReadFile(filepath.Join(ml.modelPath, modelTemplateFile))
 	if err != nil {
 		return err
 	}
@@ -92,36 +103,30 @@ func (ml *ModelLoader) LoadGPTJModel(modelName string) (*gptj.GPTJ, error) {
 	defer ml.mu.Unlock()
 
 	// Check if we already have a loaded model
-	modelFile := filepath.Join(ml.modelPath, modelName)
+	if !ml.ExistsInModelPath(modelName) {
+		return nil, fmt.Errorf("model does not exist")
+	}
 
-	if m, ok := ml.gptmodels[modelFile]; ok {
+	if m, ok := ml.gptmodels[modelName]; ok {
+		log.Debug().Msgf("Model already loaded in memory: %s", modelName)
 		return m, nil
 	}
 
-	// Check if the model path exists
-	if _, err := os.Stat(modelFile); os.IsNotExist(err) {
-		// try to find a s.bin
-		modelBin := fmt.Sprintf("%s.bin", modelFile)
-		if _, err := os.Stat(modelBin); os.IsNotExist(err) {
-			return nil, err
-		} else {
-			modelName = fmt.Sprintf("%s.bin", modelName)
-			modelFile = modelBin
-		}
-	}
-
 	// Load the model and keep it in memory for later use
+	modelFile := filepath.Join(ml.modelPath, modelName)
+	log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
+
 	model, err := gptj.New(modelFile)
 	if err != nil {
 		return nil, err
 	}
 
 	// If there is a prompt template, load it
-	if err := ml.loadTemplate(modelName, modelFile); err != nil {
+	if err := ml.loadTemplateIfExists(modelName, modelFile); err != nil {
 		return nil, err
 	}
 
-	ml.gptmodels[modelFile] = model
+	ml.gptmodels[modelName] = model
 	return model, err
 }
 
@@ -129,40 +134,39 @@ func (ml *ModelLoader) LoadLLaMAModel(modelName string, opts ...llama.ModelOptio
 	ml.mu.Lock()
 	defer ml.mu.Unlock()
 
+	log.Debug().Msgf("Loading model name: %s", modelName)
+
 	// Check if we already have a loaded model
-	modelFile := filepath.Join(ml.modelPath, modelName)
-	if m, ok := ml.models[modelFile]; ok {
+	if !ml.ExistsInModelPath(modelName) {
+		return nil, fmt.Errorf("model does not exist")
+	}
+
+	if m, ok := ml.models[modelName]; ok {
+		log.Debug().Msgf("Model already loaded in memory: %s", modelName)
 		return m, nil
 	}
+
 	// TODO: This needs refactoring, it's really bad to have it in here
-	// Check if we have a GPTJ model loaded instead
-	if _, ok := ml.gptmodels[modelFile]; ok {
+	// Check if we have a GPTJ model loaded instead - if we do we return an error so the API tries with GPTJ
+	if _, ok := ml.gptmodels[modelName]; ok {
+		log.Debug().Msgf("Model is GPTJ: %s", modelName)
 		return nil, fmt.Errorf("this model is a GPTJ one")
 	}
 
-	// Check if the model path exists
-	if _, err := os.Stat(modelFile); os.IsNotExist(err) {
-		// try to find a s.bin
-		modelBin := fmt.Sprintf("%s.bin", modelFile)
-		if _, err := os.Stat(modelBin); os.IsNotExist(err) {
-			return nil, err
-		} else {
-			modelName = fmt.Sprintf("%s.bin", modelName)
-			modelFile = modelBin
-		}
-	}
-
 	// Load the model and keep it in memory for later use
+	modelFile := filepath.Join(ml.modelPath, modelName)
+	log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
+
 	model, err := llama.New(modelFile, opts...)
 	if err != nil {
 		return nil, err
 	}
 
 	// If there is a prompt template, load it
-	if err := ml.loadTemplate(modelName, modelFile); err != nil {
+	if err := ml.loadTemplateIfExists(modelName, modelFile); err != nil {
 		return nil, err
 	}
 
-	ml.models[modelFile] = model
+	ml.models[modelName] = model
 	return model, err
 }