fix: make MacOS builds work (#61)

Signed-off-by: mudler <mudler@mocaccino.org>

.devcontainer/Dockerfile

@@ -0,0 +1,3 @@
+ARG GO_VERSION=1.20
+FROM mcr.microsoft.com/devcontainers/go:0-$GO_VERSION-bullseye
+RUN apt-get update && apt-get install -y cmake

.devcontainer/devcontainer.json

@@ -0,0 +1,46 @@
+// For format details, see https://aka.ms/devcontainer.json. For config options, see the
+// README at: https://github.com/devcontainers/templates/tree/main/src/docker-existing-docker-compose
+{
+	"name": "Existing Docker Compose (Extend)",
+
+	// Update the 'dockerComposeFile' list if you have more compose files or use different names.
+	// The .devcontainer/docker-compose.yml file contains any overrides you need/want to make.
+	"dockerComposeFile": [
+		"../docker-compose.yaml",
+		"docker-compose.yml"
+	],
+
+	// The 'service' property is the name of the service for the container that VS Code should
+	// use. Update this value and .devcontainer/docker-compose.yml to the real service name.
+	"service": "api",
+
+	// The optional 'workspaceFolder' property is the path VS Code should open by default when
+	// connected. This is typically a file mount in .devcontainer/docker-compose.yml
+	"workspaceFolder": "/workspace",
+
+	"features": {
+		"ghcr.io/devcontainers/features/go:1": {},
+		"ghcr.io/azutake/devcontainer-features/go-packages-install:0": {}
+	},
+
+	// Features to add to the dev container. More info: https://containers.dev/features.
+	// "features": {},
+
+	// Use 'forwardPorts' to make a list of ports inside the container available locally.
+	// "forwardPorts": [],
+
+	// Uncomment the next line if you want start specific services in your Docker Compose config.
+	// "runServices": [],
+
+	// Uncomment the next line if you want to keep your containers running after VS Code shuts down.
+	// "shutdownAction": "none",
+
+	// Uncomment the next line to run commands after the container is created.
+	"postCreateCommand": "make prepare"
+
+	// Configure tool-specific properties.
+	// "customizations": {},
+
+	// Uncomment to connect as an existing user other than the container default. More info: https://aka.ms/dev-containers-non-root.
+	// "remoteUser": "devcontainer"
+}

.devcontainer/docker-compose.yml

@@ -0,0 +1,26 @@
+version: '3.6'
+services:
+  # Update this to the name of the service you want to work with in your docker-compose.yml file
+  api:
+    # Uncomment if you want to override the service's Dockerfile to one in the .devcontainer 
+    # folder. Note that the path of the Dockerfile and context is relative to the *primary* 
+    # docker-compose.yml file (the first in the devcontainer.json "dockerComposeFile"
+    # array). The sample below assumes your primary file is in the root of your project.
+    #
+    build:
+      context: .
+      dockerfile: .devcontainer/Dockerfile
+
+    volumes:
+      # Update this to wherever you want VS Code to mount the folder of your project
+      - .:/workspace:cached
+
+    # Uncomment the next four lines if you will use a ptrace-based debugger like C++, Go, and Rust.
+    # cap_add:
+    #   - SYS_PTRACE
+    # security_opt:
+    #   - seccomp:unconfined
+
+    # Overrides default command so things don't shut down after the process ends.
+    command: /bin/sh -c "while sleep 1000; do :; done"
+ 

.env

@@ -1,3 +1,5 @@
-THREADS=14
-CONTEXT_SIZE=512
+# THREADS=14
+# CONTEXT_SIZE=512
 MODELS_PATH=/models
+# DEBUG=true
+# BUILD_TYPE=generic

.github/workflows/test.yml

@@ -0,0 +1,44 @@
+---
+name: 'tests'
+
+on:
+  pull_request:
+  push:
+    branches:
+      - master
+    tags:
+      - '*'
+
+jobs:
+  ubuntu-latest:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Clone
+        uses: actions/checkout@v1
+        with: 
+          submodules: true
+      - name: Dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install build-essential
+      - name: Test
+        run: |
+          make test
+
+  macOS-latest:
+    runs-on: macOS-latest
+
+    steps:
+      - name: Clone
+        uses: actions/checkout@v1
+        with: 
+          submodules: true
+
+      - name: Dependencies
+        run: |
+          brew update
+          brew install sdl2
+      - name: Test
+        run: |
+          make test

.gitignore

@@ -1,11 +1,15 @@
 # go-llama build artifacts
 go-llama
 go-gpt4all-j
+go-gpt2
 
 # LocalAI build binary
 LocalAI
 local-ai
+# prevent above rules from omitting the helm chart
+!charts/*
 
 # Ignore models
 models/*.bin
-models/ggml-*
+models/ggml-*
+test-models/

.vscode/launch.json

@@ -1,16 +1,20 @@
 {
     "version": "0.2.0",
     "configurations": [
-    
-    {
-        "name": "Launch Go",
-        "type": "go",
-        "request": "launch",
-        "mode": "debug",
-        "program": "${workspaceFolder}/main.go",
-        "args": [
-            "api"
-        ]
-    }
+        {
+            "name": "Launch Go",
+            "type": "go",
+            "request": "launch",
+            "mode": "debug",
+            "program": "${workspaceFolder}/main.go",
+            "args": [
+                "api"
+            ],
+            "env": {
+                "C_INCLUDE_PATH": "/workspace/go-llama:/workspace/go-gpt4all-j:/workspace/go-gpt2",
+                "LIBRARY_PATH": "/workspace/go-llama:/workspace/go-gpt4all-j:/workspace/go-gpt2",
+                "DEBUG": "true"
+            }
+        }
     ]
-}
+}

Dockerfile

@@ -1,11 +1,12 @@
 ARG GO_VERSION=1.20
 ARG DEBIAN_VERSION=11
+ARG BUILD_TYPE=
+
 FROM golang:$GO_VERSION as builder
 WORKDIR /build
 RUN apt-get update && apt-get install -y cmake
 COPY . .
-ARG BUILD_TYPE=
-RUN make build${BUILD_TYPE}
+RUN make build
 
 FROM debian:$DEBIAN_VERSION
 COPY --from=builder /build/local-ai /usr/bin/local-ai

Makefile

@@ -2,7 +2,9 @@ GOCMD=go
 GOTEST=$(GOCMD) test
 GOVET=$(GOCMD) vet
 BINARY_NAME=local-ai
-GOLLAMA_VERSION?=llama.cpp-5ecff35
+GOLLAMA_VERSION?=llama.cpp-8687c1f
+GOGPT4ALLJ_VERSION?=1f7bff57f66cb7062e40d0ac3abd2217815e5109
+GOGPT2_VERSION?=245a5bfe6708ab80dc5c733dcdbfbe3cfd2acdaa
 
 GREEN  := $(shell tput -Txterm setaf 2)
 YELLOW := $(shell tput -Txterm setaf 3)
@@ -10,6 +12,20 @@ WHITE  := $(shell tput -Txterm setaf 7)
 CYAN   := $(shell tput -Txterm setaf 6)
 RESET  := $(shell tput -Txterm sgr0)
 
+C_INCLUDE_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-gpt4all-j:$(shell pwd)/go-gpt2
+LIBRARY_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-gpt4all-j:$(shell pwd)/go-gpt2
+
+# Use this if you want to set the default behavior
+ifndef BUILD_TYPE
+	BUILD_TYPE:=default
+endif
+
+ifeq ($(BUILD_TYPE), "generic")
+	GENERIC_PREFIX:=generic-
+else
+	GENERIC_PREFIX:=
+endif
+
 .PHONY: all test build vendor
 
 all: help
@@ -17,54 +33,75 @@ all: help
 ## Build:
 
 build: prepare ## Build the project
-	C_INCLUDE_PATH=$(shell pwd)/go-llama.cpp:$(shell pwd)/go-gpt4all-j LIBRARY_PATH=$(shell pwd)/go-llama.cpp:$(shell pwd)/go-gpt4all-j $(GOCMD) build -o $(BINARY_NAME) ./
+	$(info ${GREEN}I local-ai build info:${RESET})
+	$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
+	C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) build -o $(BINARY_NAME) ./
 
-buildgeneric: prepare-generic ## Build the project
-	C_INCLUDE_PATH=$(shell pwd)/go-llama.cpp:$(shell pwd)/go-gpt4all-j LIBRARY_PATH=$(shell pwd)/go-llama.cpp:$(shell pwd)/go-gpt4all-j $(GOCMD) build -o $(BINARY_NAME) ./
+generic-build: ## Build the project using generic
+	BUILD_TYPE="generic" $(MAKE) build
 
+## GPT4ALL-J
 go-gpt4all-j:
 	git clone --recurse-submodules https://github.com/go-skynet/go-gpt4all-j.cpp go-gpt4all-j
-# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
+	cd go-gpt4all-j && git checkout -b build $(GOGPT4ALLJ_VERSION)
+	# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
 	@find ./go-gpt4all-j -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
 	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
 	@find ./go-gpt4all-j -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
 	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
 	@find ./go-gpt4all-j -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
+	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gptj_/g' {} +
+	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/void replace/void json_gptj_replace/g' {} +
+	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/::replace/::json_gptj_replace/g' {} +
 
 go-gpt4all-j/libgptj.a: go-gpt4all-j
-	$(MAKE) -C go-gpt4all-j libgptj.a
+	$(MAKE) -C go-gpt4all-j $(GENERIC_PREFIX)libgptj.a
 
-go-gpt4all-j/libgptj.a-generic: go-gpt4all-j
-	$(MAKE) -C go-gpt4all-j generic-libgptj.a
+# CEREBRAS GPT
+go-gpt2:
+	git clone --recurse-submodules https://github.com/go-skynet/go-gpt2.cpp go-gpt2
+	cd go-gpt2 && git checkout -b build $(GOGPT2_VERSION)
+	# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
+	@find ./go-gpt2 -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
+	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
+	@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
+	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gpt2_/g' {} +
+	@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gpt2_/g' {} +
+	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gpt2_/g' {} +
+
+go-gpt2/libgpt2.a: go-gpt2
+	$(MAKE) -C go-gpt2 $(GENERIC_PREFIX)libgpt2.a
+	
 
 go-llama:
 	git clone -b $(GOLLAMA_VERSION) --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
-	$(MAKE) -C go-llama libbinding.a
 
-go-llama-generic:
-	git clone -b $(GOLLAMA_VERSION) --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
-	$(MAKE) -C go-llama generic-libbinding.a
+go-llama/libbinding.a: go-llama
+	$(MAKE) -C go-llama $(GENERIC_PREFIX)libbinding.a
 
-prepare: go-llama go-gpt4all-j/libgptj.a
+replace:
 	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
 	$(GOCMD) mod edit -replace github.com/go-skynet/go-gpt4all-j.cpp=$(shell pwd)/go-gpt4all-j
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-gpt2.cpp=$(shell pwd)/go-gpt2
+
+prepare: go-llama/libbinding.a go-gpt4all-j/libgptj.a go-gpt2/libgpt2.a replace
 
-prepare-generic: go-llama-generic go-gpt4all-j/libgptj.a-generic
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-gpt4all-j.cpp=$(shell pwd)/go-gpt4all-j
-	
 clean: ## Remove build related file
 	rm -fr ./go-llama
 	rm -rf ./go-gpt4all-j
+	rm -rf ./go-gpt2
 	rm -rf $(BINARY_NAME)
 
 ## Run:
 run: prepare
-	$(GOCMD) run ./ api
+	C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./main.go
 
-## Test:
-test: ## Run the tests of the project
-	$(GOTEST) -v -race ./... $(OUTPUT_OPTIONS)
+test-models/testmodel:
+	mkdir test-models
+	wget https://huggingface.co/concedo/cerebras-111M-ggml/resolve/main/cerberas-111m-q4_0.bin -O test-models/testmodel
+
+test: prepare test-models/testmodel
+	@C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} MODELS_PATH=$(abspath ./)/test-models $(GOCMD) test -v ./...
 
 ## Help:
 help: ## Show this help.

README.md

@@ -1,4 +1,9 @@
-## :camel: LocalAI
+<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!
 
@@ -7,13 +12,24 @@ LocalAI is a straightforward, drop-in replacement API compatible with OpenAI for
 - OpenAI compatible API
 - Supports multiple-models
 - Once loaded the first time, it keep models loaded in memory for faster inference
-- Provides a simple command line interface that allows text generation directly from the terminal
 - Support for prompt templates
 - Doesn't shell-out, but uses C bindings for a faster inference and better performance. Uses [go-llama.cpp](https://github.com/go-skynet/go-llama.cpp) and [go-gpt4all-j.cpp](https://github.com/go-skynet/go-gpt4all-j.cpp).
 
+Discord channel: [Discord](https://discord.gg/uJAeKSAGDy)
+
 ## Model compatibility
 
-It is compatible with the models supported by [llama.cpp](https://github.com/ggerganov/llama.cpp) and also [GPT4ALL-J](https://github.com/nomic-ai/gpt4all).
+It is compatible with the models supported by [llama.cpp](https://github.com/ggerganov/llama.cpp) supports also [GPT4ALL-J](https://github.com/nomic-ai/gpt4all) and [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml).
+
+Tested with:
+- Vicuna
+- Alpaca
+- [GPT4ALL](https://github.com/nomic-ai/gpt4all)
+- [GPT4ALL-J](https://gpt4all.io/models/ggml-gpt4all-j.bin)
+- Koala
+- [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml)
+
+It should also be compatible with StableLM and GPTNeoX ggml models (untested)
 
 Note: You might need to convert older models to the new format, see [here](https://github.com/ggerganov/llama.cpp#using-gpt4all) for instance to run `gpt4all`.
 
@@ -49,6 +65,26 @@ curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d
    }'
 ```
 
+## Helm Chart Installation (run LocalAI in Kubernetes)
+The local-ai Helm chart supports two options for the LocalAI server's models directory:
+1. Basic deployment with no persistent volume. You must manually update the Deployment to configure your own models directory.
+
+    Install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == false`.
+
+2. Advanced, two-phase deployment to provision the models directory using a DataVolume. Requires [Containerized Data Importer CDI](https://github.com/kubevirt/containerized-data-importer) to be pre-installed in your cluster.
+
+    First, install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == true`:
+    ```bash
+    helm install local-ai charts/local-ai -n local-ai --create-namespace
+    ```
+    Wait for CDI to create an importer Pod for the DataVolume and for the importer pod to finish provisioning the model archive inside the PV.
+
+    Once the PV is provisioned and the importer Pod removed, set `.Values.deployment.volumes.enabled == true` and `.Values.dataVolume.enabled == false` and upgrade the chart:
+    ```bash
+    helm upgrade local-ai -n local-ai charts/local-ai
+    ```
+    This will update the local-ai Deployment to mount the PV that was provisioned by the DataVolume.
+
 ## 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.
@@ -77,7 +113,7 @@ See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prom
 Example of starting the API with `docker`:
 
 ```bash
-docker run -p 8080:8080 -ti --rm quay.io/go-skynet/local-api:latest --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:
@@ -92,8 +128,6 @@ And you'll see:
 └───────────────────────────────────────────────────┘ 
 ```
 
-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:
 
 ```
@@ -105,7 +139,7 @@ The API takes takes the following parameters:
 | Parameter    | Environment Variable | Default Value | Description                            |
 | ------------ | -------------------- | ------------- | -------------------------------------- |
 | models-path        | MODELS_PATH           |               | The path where you have models (ending with `.bin`).      |
-| threads      | THREADS              | CPU cores     | The number of threads to use for text generation. |
+| threads      | THREADS              | Number of Physical cores     | The number of threads to use for text generation. |
 | address      | ADDRESS              | :8080         | The address and port to listen on. |
 | context-size | CONTEXT_SIZE         | 512           | Default token context size. |
 
@@ -172,10 +206,6 @@ python 828bddec6162a023114ce19146cb2b82/gistfile1.txt models tokenizer.model
 
 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 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.

api/api.go

@@ -1,16 +1,21 @@
 package api
 
 import (
+	"encoding/json"
+	"errors"
 	"fmt"
 	"strings"
 	"sync"
 
 	model "github.com/go-skynet/LocalAI/pkg/model"
+	gpt2 "github.com/go-skynet/go-gpt2.cpp"
 	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"
+	"github.com/rs/zerolog/log"
 )
 
 type OpenAIResponse struct {
@@ -44,6 +49,8 @@ type OpenAIRequest struct {
 	// Prompt is read only by completion API calls
 	Prompt string `json:"prompt"`
 
+	Stop string `json:"stop"`
+
 	// Messages is read only by chat/completion API calls
 	Messages []Message `json:"messages"`
 
@@ -57,64 +64,94 @@ type OpenAIRequest struct {
 	N int `json:"n"`
 
 	// Custom parameters - not present in the OpenAI API
-	Batch     int  `json:"batch"`
-	F16       bool `json:"f16kv"`
-	IgnoreEOS bool `json:"ignore_eos"`
+	Batch         int     `json:"batch"`
+	F16           bool    `json:"f16kv"`
+	IgnoreEOS     bool    `json:"ignore_eos"`
+	RepeatPenalty float64 `json:"repeat_penalty"`
+	Keep          int     `json:"n_keep"`
 
 	Seed int `json:"seed"`
 }
 
 // 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, debug 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
 		var gptModel *gptj.GPTJ
+		var gpt2Model *gpt2.GPT2
+		var stableLMModel *gpt2.StableLM
 
 		input := new(OpenAIRequest)
 		// Get input data from the request body
 		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 no model was specified, take the first available
+		if modelFile == "" {
+			models, _ := loader.ListModels()
+			if len(models) > 0 {
+				modelFile = models[0]
+				log.Debug().Msgf("No model specified, using: %s", modelFile)
+			}
+		}
+
+		// If no model is found or specified, we bail out
+		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 a model is found in bearer token takes precedence
+		if bearerExists {
+			log.Debug().Msgf("Using model from bearer token: %s", bearer)
+			modelFile = bearer
+		}
+
+		// Try to load the model
+		var llamaerr, gpt2err, gptjerr, stableerr error
+		llamaOpts := []llama.ModelOption{}
+		if ctx != 0 {
+			llamaOpts = append(llamaOpts, llama.SetContext(ctx))
+		}
+		if f16 {
+			llamaOpts = append(llamaOpts, llama.EnableF16Memory)
+		}
+
+		// TODO: this is ugly, better identifying the model somehow! however, it is a good stab for a first implementation..
+		model, llamaerr = loader.LoadLLaMAModel(modelFile, llamaOpts...)
+		if llamaerr != nil {
+			gptModel, gptjerr = loader.LoadGPTJModel(modelFile)
+			if gptjerr != nil {
+				gpt2Model, gpt2err = loader.LoadGPT2Model(modelFile)
+				if gpt2err != nil {
+					stableLMModel, stableerr = loader.LoadStableLMModel(modelFile)
+					if stableerr != nil {
+						return fmt.Errorf("llama: %s gpt: %s gpt2: %s stableLM: %s", llamaerr.Error(), gptjerr.Error(), gpt2err.Error(), stableerr.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
@@ -139,6 +176,7 @@ 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)
 			}
@@ -147,11 +185,12 @@ 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{}
@@ -164,6 +203,54 @@ func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16
 
 		var predFunc func() (string, error)
 		switch {
+		case stableLMModel != nil:
+			predFunc = func() (string, error) {
+				// Generate the prediction using the language model
+				predictOptions := []gpt2.PredictOption{
+					gpt2.SetTemperature(temperature),
+					gpt2.SetTopP(topP),
+					gpt2.SetTopK(topK),
+					gpt2.SetTokens(tokens),
+					gpt2.SetThreads(threads),
+				}
+
+				if input.Batch != 0 {
+					predictOptions = append(predictOptions, gpt2.SetBatch(input.Batch))
+				}
+
+				if input.Seed != 0 {
+					predictOptions = append(predictOptions, gpt2.SetSeed(input.Seed))
+				}
+
+				return stableLMModel.Predict(
+					predInput,
+					predictOptions...,
+				)
+			}
+		case gpt2Model != nil:
+			predFunc = func() (string, error) {
+				// Generate the prediction using the language model
+				predictOptions := []gpt2.PredictOption{
+					gpt2.SetTemperature(temperature),
+					gpt2.SetTopP(topP),
+					gpt2.SetTopK(topK),
+					gpt2.SetTokens(tokens),
+					gpt2.SetThreads(threads),
+				}
+
+				if input.Batch != 0 {
+					predictOptions = append(predictOptions, gpt2.SetBatch(input.Batch))
+				}
+
+				if input.Seed != 0 {
+					predictOptions = append(predictOptions, gpt2.SetSeed(input.Seed))
+				}
+
+				return gpt2Model.Predict(
+					predInput,
+					predictOptions...,
+				)
+			}
 		case gptModel != nil:
 			predFunc = func() (string, error) {
 				// Generate the prediction using the language model
@@ -199,6 +286,22 @@ func openAIEndpoint(chat bool, loader *model.ModelLoader, threads, ctx int, f16
 					llama.SetThreads(threads),
 				}
 
+				if debug {
+					predictOptions = append(predictOptions, llama.Debug)
+				}
+
+				if input.Stop != "" {
+					predictOptions = append(predictOptions, llama.SetStopWords(input.Stop))
+				}
+
+				if input.RepeatPenalty != 0 {
+					predictOptions = append(predictOptions, llama.SetPenalty(input.RepeatPenalty))
+				}
+
+				if input.Keep != 0 {
+					predictOptions = append(predictOptions, llama.SetNKeep(input.Keep))
+				}
+
 				if input.Batch != 0 {
 					predictOptions = append(predictOptions, llama.SetBatch(input.Batch))
 				}
@@ -223,8 +326,6 @@ 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
@@ -241,30 +342,19 @@ 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
@@ -281,9 +371,53 @@ func Start(loader *model.ModelLoader, listenAddr string, threads, ctxSize int, f
 			Object: "list",
 			Data:   dataModels,
 		})
+	}
+}
+
+func App(loader *model.ModelLoader, threads, ctxSize int, f16 bool, debug, disableMessage bool) *fiber.App {
+	zerolog.SetGlobalLevel(zerolog.InfoLevel)
+	if debug {
+		zerolog.SetGlobalLevel(zerolog.DebugLevel)
+	}
+
+	// Return errors as JSON responses
+	app := fiber.New(fiber.Config{
+		DisableStartupMessage: disableMessage,
+		// 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()})
+		},
 	})
 
-	// Start the server
-	app.Listen(listenAddr)
-	return nil
+	// 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, debug, loader, threads, ctxSize, f16, mumutex, mu))
+	app.Post("/chat/completions", openAIEndpoint(true, debug, loader, threads, ctxSize, f16, mumutex, mu))
+
+	app.Post("/v1/completions", openAIEndpoint(false, debug, loader, threads, ctxSize, f16, mumutex, mu))
+	app.Post("/completions", openAIEndpoint(false, debug, loader, threads, ctxSize, f16, mumutex, mu))
+
+	app.Get("/v1/models", listModels(loader))
+	app.Get("/models", listModels(loader))
+
+	return app
 }

api/api_test.go

@@ -0,0 +1,53 @@
+package api_test
+
+import (
+	"context"
+	"os"
+
+	. "github.com/go-skynet/LocalAI/api"
+	"github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/gofiber/fiber/v2"
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+
+	"github.com/sashabaranov/go-openai"
+)
+
+var _ = Describe("API test", func() {
+
+	var app *fiber.App
+	var modelLoader *model.ModelLoader
+	var client *openai.Client
+	Context("API query", func() {
+		BeforeEach(func() {
+			modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
+			app = App(modelLoader, 1, 512, false, false, true)
+			go app.Listen("127.0.0.1:9090")
+
+			defaultConfig := openai.DefaultConfig("")
+			defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
+
+			// Wait for API to be ready
+			client = openai.NewClientWithConfig(defaultConfig)
+			Eventually(func() error {
+				_, err := client.ListModels(context.TODO())
+				return err
+			}, "2m").ShouldNot(HaveOccurred())
+		})
+		AfterEach(func() {
+			app.Shutdown()
+		})
+		It("returns the models list", func() {
+			models, err := client.ListModels(context.TODO())
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(models.Models)).To(Equal(1))
+			Expect(models.Models[0].ID).To(Equal("testmodel"))
+		})
+		It("can generate completions", func() {
+			resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: "abcdedfghikl"})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Text).ToNot(BeEmpty())
+		})
+	})
+})

api/apt_suite_test.go

@@ -0,0 +1,13 @@
+package api_test
+
+import (
+	"testing"
+
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+)
+
+func TestLocalAI(t *testing.T) {
+	RegisterFailHandler(Fail)
+	RunSpecs(t, "LocalAI test suite")
+}

charts/local-ai/Chart.yaml

@@ -0,0 +1,6 @@
+apiVersion: v2
+appVersion: 0.1.0
+description: A Helm chart for LocalAI
+name: local-ai
+type: application
+version: 1.0.0

charts/local-ai/templates/_helpers.tpl

@@ -0,0 +1,44 @@
+{{/*
+Expand the name of the chart.
+*/}}
+{{- define "local-ai.name" -}}
+{{- default .Chart.Name .Values.nameOverride | trunc 63 | trimSuffix "-" }}
+{{- end }}
+
+{{/*
+Create a default fully qualified app name.
+We truncate at 63 chars because some Kubernetes name fields are limited to this (by the DNS naming spec).
+If release name contains chart name it will be used as a full name.
+*/}}
+{{- define "local-ai.fullname" -}}
+{{- if .Values.fullnameOverride }}
+{{- .Values.fullnameOverride | trunc 63 | trimSuffix "-" }}
+{{- else }}
+{{- $name := default .Chart.Name .Values.nameOverride }}
+{{- if contains $name .Release.Name }}
+{{- .Release.Name | trunc 63 | trimSuffix "-" }}
+{{- else }}
+{{- printf "%s-%s" .Release.Name $name | trunc 63 | trimSuffix "-" }}
+{{- end }}
+{{- end }}
+{{- end }}
+
+{{/*
+Create chart name and version as used by the chart label.
+*/}}
+{{- define "local-ai.chart" -}}
+{{- printf "%s-%s" .Chart.Name .Chart.Version | replace "+" "_" | trunc 63 | trimSuffix "-" }}
+{{- end }}
+
+{{/*
+Common labels
+*/}}
+{{- define "local-ai.labels" -}}
+helm.sh/chart: {{ include "local-ai.chart" . }}
+app.kubernetes.io/name: {{ include "local-ai.name" . }}
+app.kubernetes.io/instance: "{{ .Release.Name }}"
+app.kubernetes.io/managed-by: {{ .Release.Service }}
+{{- if .Chart.AppVersion }}
+app.kubernetes.io/version: {{ .Chart.AppVersion | quote }}
+{{- end }}
+{{- end }}

charts/local-ai/templates/data-volume.yaml

@@ -0,0 +1,39 @@
+{{- if .Values.dataVolume.enabled }}
+apiVersion: cdi.kubevirt.io/v1beta1
+kind: DataVolume
+metadata:
+  name: {{ template "local-ai.fullname" . }}
+  namespace: {{ .Release.Namespace | quote }}
+  labels:
+    {{- include "local-ai.labels" . | nindent 4 }}
+spec:
+  contentType: archive
+  source:
+    {{ .Values.dataVolume.source.type }}:
+      url: {{ .Values.dataVolume.source.url }}
+      secretRef: {{ template "local-ai.fullname" . }}
+      {{- if and (eq .Values.dataVolume.source.type "http") .Values.dataVolume.source.secretExtraHeaders }}
+      secretExtraHeaders: {{ .Values.dataVolume.source.secretExtraHeaders }}
+      {{- end }}
+      {{- if .Values.dataVolume.source.caCertConfigMap }}
+      caCertConfigMap: {{ .Values.dataVolume.source.caCertConfigMap }}
+      {{- end }}
+  pvc:
+    accessModes: {{ .Values.dataVolume.pvc.accessModes }}
+    resources:
+      requests:
+        storage: {{ .Values.dataVolume.pvc.size }}
+---
+{{- if .Values.dataVolume.secret.enabled }}
+apiVersion: v1
+kind: Secret
+metadata:
+  name: {{ template "local-ai.fullname" . }}
+  namespace: {{ .Release.Namespace | quote }}
+  labels:
+    {{- include "local-ai.labels" . | nindent 4 }}
+data:
+  accessKeyId: {{ .Values.dataVolume.secret.username }}
+  secretKey: {{ .Values.dataVolume.secret.password }}
+{{- end }}
+{{- end }}

charts/local-ai/templates/deployment.yaml

@@ -0,0 +1,39 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: {{ template "local-ai.fullname" . }}
+  namespace: {{ .Release.Namespace | quote }}
+  labels:
+    {{- include "local-ai.labels" . | nindent 4 }}
+spec:
+  selector:
+    matchLabels:
+      app.kubernetes.io/name: {{ include "local-ai.name" . }}
+      app.kubernetes.io/instance: {{ .Release.Name }}
+  replicas: 1
+  template:
+    metadata:
+      name: {{ template "local-ai.fullname" . }}
+      labels:
+        app.kubernetes.io/name: {{ include "local-ai.name" . }}
+        app.kubernetes.io/instance: {{ .Release.Name }}
+    spec:
+      containers:
+        - name: {{ template "local-ai.fullname" . }}
+          image: {{ .Values.deployment.image }}
+          env:
+          - name: THREADS
+            value: {{ .Values.deployment.env.threads | quote }}
+          - name: CONTEXT_SIZE
+            value: {{ .Values.deployment.env.contextSize | quote }}
+          - name: MODELS_PATH
+            value: {{ .Values.deployment.env.modelsPath }}
+{{- if .Values.deployment.volume.enabled }}
+          volumeMounts:
+          - mountPath: {{ .Values.deployment.env.modelsPath }}
+            name: models
+      volumes:
+      - name: models
+        persistentVolumeClaim:
+          claimName: {{ template "local-ai.fullname" . }}
+{{- end }}

charts/local-ai/templates/service.yaml

@@ -0,0 +1,19 @@
+apiVersion: v1
+kind: Service
+metadata:
+  name: {{ template "local-ai.fullname" . }}
+  namespace: {{ .Release.Namespace | quote }}
+  labels:
+    {{- include "local-ai.labels" . | nindent 4 }}
+{{- if .Values.service.annotations }}
+  annotations:
+  {{ toYaml .Values.service.annotations | indent 4 }}
+{{- end }}
+spec:
+  selector:
+    app.kubernetes.io/name: {{ include "local-ai.name" . }}
+  type: "{{ .Values.service.type }}"
+  ports:
+    - protocol: TCP
+      port: 8080
+      targetPort: 8080

charts/local-ai/values.yaml

@@ -0,0 +1,38 @@
+deployment:
+  image: quay.io/go-skynet/local-ai:latest
+  env:
+    threads: 14
+    contextSize: 512
+    modelsPath: "/models"
+  volume:
+    enabled: false
+
+service:
+  type: ClusterIP
+  annotations: {}
+  # If using an AWS load balancer, you'll need to override the default 60s load balancer idle timeout
+  # service.beta.kubernetes.io/aws-load-balancer-connection-idle-timeout: "1200"
+
+# Optionally create a PVC containing a model binary, sourced from an arbitrary HTTP server or S3 bucket
+# (requires https://github.com/kubevirt/containerized-data-importer)
+dataVolume:
+  enabled: false
+  source:
+    type: "http" # Source type. One of: [ http | s3 ]
+    url: "http://<model_server>/<model_archive>" # e.g. koala-7B-4bit-128g.GGML.tar
+
+    # CertConfigMap is an optional ConfigMap reference, containing a Certificate Authority (CA) public key
+    # and a base64 encoded pem certificate
+    caCertConfigMap: ""
+
+    # SecretExtraHeaders is an optional list of Secret references, each containing an extra HTTP header
+    # that may include sensitive information. Only applicable for the http source type.
+    secretExtraHeaders: []
+  pvc:
+    accessModes:
+    - ReadWriteOnce
+    size: 5Gi
+  secret:
+    enabled: false
+    username: "" # base64 encoded
+    password: "" # base64 encoded

docker-compose.yaml

@@ -6,13 +6,10 @@ services:
     build:
       context: .
       dockerfile: Dockerfile
-      # args:
-        # BUILD_TYPE: generic # Uncomment to build CPU generic code that works on most HW
     ports:
       - 8080:8080
-    environment:
-      - MODELS_PATH=$MODELS_PATH
-      - CONTEXT_SIZE=$CONTEXT_SIZE
-      - THREADS=$THREADS
+    env_file:
+      - .env
     volumes:
-      - ./models:/models:cached
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai" ]

go.mod

@@ -3,21 +3,38 @@ module github.com/go-skynet/LocalAI
 go 1.19
 
 require (
-	github.com/go-skynet/go-llama.cpp v0.0.0-20230415213228-bac222030640
+	github.com/go-skynet/go-gpt2.cpp v0.0.0-20230420213900-1c24f5b86ac4
+	github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230419091210-303cf2a59a94
+	github.com/go-skynet/go-llama.cpp v0.0.0-20230421172644-351a5a40eead
 	github.com/gofiber/fiber/v2 v2.42.0
+	github.com/jaypipes/ghw v0.10.0
+	github.com/onsi/ginkgo/v2 v2.9.2
+	github.com/onsi/gomega v1.27.6
+	github.com/rs/zerolog v1.29.1
+	github.com/sashabaranov/go-openai v1.9.0
 	github.com/urfave/cli/v2 v2.25.0
 )
 
 require (
+	github.com/StackExchange/wmi v1.2.1 // indirect
 	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/ghodss/yaml v1.0.0 // indirect
+	github.com/go-logr/logr v1.2.3 // indirect
+	github.com/go-ole/go-ole v1.2.6 // indirect
+	github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 // indirect
+	github.com/google/go-cmp v0.5.9 // indirect
+	github.com/google/pprof v0.0.0-20210407192527-94a9f03dee38 // indirect
 	github.com/google/uuid v1.3.0 // indirect
+	github.com/jaypipes/pcidb v1.0.0 // indirect
 	github.com/klauspost/compress v1.15.9 // indirect
+	github.com/kr/text v0.2.0 // indirect
 	github.com/mattn/go-colorable v0.1.13 // indirect
 	github.com/mattn/go-isatty v0.0.17 // indirect
 	github.com/mattn/go-runewidth v0.0.14 // indirect
+	github.com/mitchellh/go-homedir v1.1.0 // indirect
 	github.com/philhofer/fwd v1.1.1 // indirect
+	github.com/pkg/errors v0.9.1 // indirect
 	github.com/rivo/uniseg v0.2.0 // indirect
 	github.com/russross/blackfriday/v2 v2.1.0 // indirect
 	github.com/savsgio/dictpool v0.0.0-20221023140959-7bf2e61cea94 // indirect
@@ -27,5 +44,11 @@ require (
 	github.com/valyala/fasthttp v1.44.0 // indirect
 	github.com/valyala/tcplisten v1.0.0 // indirect
 	github.com/xrash/smetrics v0.0.0-20201216005158-039620a65673 // indirect
+	golang.org/x/net v0.8.0 // indirect
 	golang.org/x/sys v0.6.0 // indirect
+	golang.org/x/text v0.8.0 // indirect
+	golang.org/x/tools v0.7.0 // indirect
+	gopkg.in/yaml.v2 v2.4.0 // indirect
+	gopkg.in/yaml.v3 v3.0.1 // indirect
+	howett.net/plist v1.0.0 // indirect
 )

go.sum

@@ -1,40 +1,90 @@
+github.com/StackExchange/wmi v1.2.1 h1:VIkavFPXSjcnS+O8yTq7NI32k0R5Aj+v39y29VYDOSA=
+github.com/StackExchange/wmi v1.2.1/go.mod h1:rcmrprowKIVzvc+NUiLncP2uuArMWLCbu9SBzvHz7e8=
 github.com/andybalholm/brotli v1.0.4 h1:V7DdXeJtZscaqfNuAdSRuRFzuiKlHSC/Zh3zl9qY3JY=
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@@ -59,14 +109,19 @@ golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwY
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+gopkg.in/yaml.v2 v2.4.0 h1:D8xgwECY7CYvx+Y2n4sBz93Jn9JRvxdiyyo8CTfuKaY=
+gopkg.in/yaml.v2 v2.4.0/go.mod h1:RDklbk79AGWmwhnvt/jBztapEOGDOx6ZbXqjP6csGnQ=
+gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
 gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
+gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
+howett.net/plist v1.0.0 h1:7CrbWYbPPO/PyNy38b2EB/+gYbjCe2DXBxgtOOZbSQM=
+howett.net/plist v1.0.0/go.mod h1:lqaXoTrLY4hg8tnEzNru53gicrbv7rrk+2xJA/7hw9g=

kubernetes/deployment.yaml

@@ -1,40 +0,0 @@
-apiVersion: v1
-kind: Namespace
-metadata:
-  name: llama
----
-apiVersion: apps/v1
-kind: Deployment
-metadata:
-  name: llama
-  namespace: llama
-  labels:
-    app: llama
-spec:
-  selector:
-    matchLabels:
-      app: llama
-  replicas: 1
-  template:
-    metadata:
-      labels:
-        app: llama
-      name: llama
-    spec:
-      containers:
-        - name: llama
-          image: quay.io/go-skynet/local-ai:latest
----
-apiVersion: v1
-kind: Service
-metadata:
-  name: llama
-  namespace: llama
-spec:
-  selector:
-    app: llama
-  type: LoadBalancer
-  ports:
-    - protocol: TCP
-      port: 8080
-      targetPort: 8080

main.go

@@ -1,23 +1,31 @@
 package main
 
 import (
-	"fmt"
 	"os"
-	"runtime"
 
 	api "github.com/go-skynet/LocalAI/api"
 	model "github.com/go-skynet/LocalAI/pkg/model"
-
+	"github.com/jaypipes/ghw"
+	"github.com/rs/zerolog"
+	"github.com/rs/zerolog/log"
 	"github.com/urfave/cli/v2"
 )
 
 func main() {
+	log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
+
 	path, err := os.Getwd()
 	if err != nil {
-		fmt.Println(err)
+		log.Error().Msgf("error: %s", err.Error())
 		os.Exit(1)
 	}
 
+	threads := 4
+	cpu, err := ghw.CPU()
+	if err == nil {
+		threads = int(cpu.TotalCores)
+	}
+
 	app := &cli.App{
 		Name:  "LocalAI",
 		Usage: "OpenAI compatible API for running LLaMA/GPT models locally on CPU with consumer grade hardware.",
@@ -26,11 +34,15 @@ func main() {
 				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(),
+				Value:       threads,
 			},
 			&cli.StringFlag{
 				Name:        "models-path",
@@ -59,20 +71,22 @@ Some of the models compatible are:
 - Koala
 - GPT4ALL
 - GPT4ALL-J
+- Cerebras
 - Alpaca
+- StableLM (ggml quantized)
 
-It uses llama.cpp and gpt4all as backend, supporting all the models supported by both.
+It uses llama.cpp, ggml and gpt4all as backend with golang c bindings.
 `,
 		UsageText: `local-ai [options]`,
 		Copyright: "go-skynet authors",
 		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"))
+			return api.App(model.NewModelLoader(ctx.String("models-path")), ctx.Int("threads"), ctx.Int("context-size"), ctx.Bool("f16"), ctx.Bool("debug"), false).Listen(ctx.String("address"))
 		},
 	}
 
 	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

@@ -10,20 +10,39 @@ import (
 	"sync"
 	"text/template"
 
+	"github.com/rs/zerolog/log"
+
+	gpt2 "github.com/go-skynet/go-gpt2.cpp"
 	gptj "github.com/go-skynet/go-gpt4all-j.cpp"
 	llama "github.com/go-skynet/go-llama.cpp"
 )
 
 type ModelLoader struct {
-	modelPath        string
-	mu               sync.Mutex
-	models           map[string]*llama.LLama
-	gptmodels        map[string]*gptj.GPTJ
+	modelPath string
+	mu        sync.Mutex
+
+	models            map[string]*llama.LLama
+	gptmodels         map[string]*gptj.GPTJ
+	gpt2models        map[string]*gpt2.GPT2
+	gptstablelmmodels map[string]*gpt2.StableLM
+
 	promptsTemplates map[string]*template.Template
 }
 
 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)}
+	return &ModelLoader{
+		modelPath:         modelPath,
+		gpt2models:        make(map[string]*gpt2.GPT2),
+		gptmodels:         make(map[string]*gptj.GPTJ),
+		gptstablelmmodels: make(map[string]*gpt2.StableLM),
+		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) {
@@ -34,9 +53,12 @@ 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 +70,7 @@ 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 +81,21 @@ 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
 	}
@@ -87,41 +110,117 @@ func (ml *ModelLoader) loadTemplate(modelName, modelFile string) error {
 	return nil
 }
 
+func (ml *ModelLoader) LoadStableLMModel(modelName string) (*gpt2.StableLM, error) {
+	ml.mu.Lock()
+	defer ml.mu.Unlock()
+
+	// Check if we already have a loaded model
+	if !ml.ExistsInModelPath(modelName) {
+		return nil, fmt.Errorf("model does not exist")
+	}
+
+	if m, ok := ml.gptstablelmmodels[modelName]; ok {
+		log.Debug().Msgf("Model already loaded in memory: %s", modelName)
+		return m, nil
+	}
+
+	// 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 := gpt2.NewStableLM(modelFile)
+	if err != nil {
+		return nil, err
+	}
+
+	// If there is a prompt template, load it
+	if err := ml.loadTemplateIfExists(modelName, modelFile); err != nil {
+		return nil, err
+	}
+
+	ml.gptstablelmmodels[modelName] = model
+	return model, err
+}
+
+func (ml *ModelLoader) LoadGPT2Model(modelName string) (*gpt2.GPT2, error) {
+	ml.mu.Lock()
+	defer ml.mu.Unlock()
+
+	// Check if we already have a loaded model
+	if !ml.ExistsInModelPath(modelName) {
+		return nil, fmt.Errorf("model does not exist")
+	}
+
+	if m, ok := ml.gpt2models[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 GPTStable model loaded instead - if we do we return an error so the API tries with StableLM
+	if _, ok := ml.gptstablelmmodels[modelName]; ok {
+		log.Debug().Msgf("Model is GPTStableLM: %s", modelName)
+		return nil, fmt.Errorf("this model is a GPTStableLM one")
+	}
+
+	// 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 := gpt2.New(modelFile)
+	if err != nil {
+		return nil, err
+	}
+
+	// If there is a prompt template, load it
+	if err := ml.loadTemplateIfExists(modelName, modelFile); err != nil {
+		return nil, err
+	}
+
+	ml.gpt2models[modelName] = model
+	return model, err
+}
+
 func (ml *ModelLoader) LoadGPTJModel(modelName string) (*gptj.GPTJ, error) {
 	ml.mu.Lock()
 	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
-		}
+	// TODO: This needs refactoring, it's really bad to have it in here
+	// Check if we have a GPT2 model loaded instead - if we do we return an error so the API tries with GPT2
+	if _, ok := ml.gpt2models[modelName]; ok {
+		log.Debug().Msgf("Model is GPT2: %s", modelName)
+		return nil, fmt.Errorf("this model is a GPT2 one")
+	}
+	if _, ok := ml.gptstablelmmodels[modelName]; ok {
+		log.Debug().Msgf("Model is GPTStableLM: %s", modelName)
+		return nil, fmt.Errorf("this model is a GPTStableLM one")
 	}
 
 	// 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 +228,47 @@ 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 {
-		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 {
-		return nil, fmt.Errorf("this model is a GPTJ one")
+	if !ml.ExistsInModelPath(modelName) {
+		return nil, fmt.Errorf("model does not exist")
 	}
 
-	// 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
-		}
+	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 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")
+	}
+	if _, ok := ml.gpt2models[modelName]; ok {
+		log.Debug().Msgf("Model is GPT2: %s", modelName)
+		return nil, fmt.Errorf("this model is a GPT2 one")
+	}
+	if _, ok := ml.gptstablelmmodels[modelName]; ok {
+		log.Debug().Msgf("Model is GPTStableLM: %s", modelName)
+		return nil, fmt.Errorf("this model is a GPTStableLM one")
 	}
 
 	// 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
 }