Cleanup gh-pages branch

Signed-off-by: Dimitris Karakasilis <dimitris@spectrocloud.com>

.github/workflows/test.yml

@@ -15,7 +15,7 @@ jobs:
 
     steps:
       - name: Clone
-        uses: actions/checkout@v1
+        uses: actions/checkout@v3
         with: 
           submodules: true
       - name: Dependencies
@@ -31,7 +31,7 @@ jobs:
 
     steps:
       - name: Clone
-        uses: actions/checkout@v1
+        uses: actions/checkout@v3
         with: 
           submodules: true
 

Dockerfile

@@ -1,13 +0,0 @@
-ARG GO_VERSION=1.20
-ARG DEBIAN_VERSION=11
-ARG BUILD_TYPE=
-
-FROM golang:$GO_VERSION as builder
-WORKDIR /build
-RUN apt-get update && apt-get install -y cmake
-COPY . .
-RUN make build
-
-FROM debian:$DEBIAN_VERSION
-COPY --from=builder /build/local-ai /usr/bin/local-ai
-ENTRYPOINT [ "/usr/bin/local-ai" ]

Earthfile

@@ -1,5 +0,0 @@
-VERSION 0.7
-
-build:
-    FROM DOCKERFILE -f Dockerfile .
-    SAVE ARTIFACT /usr/bin/local-ai AS LOCAL local-ai

LICENSE

@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2023 go-skynet authors
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.

Makefile

@@ -1,116 +0,0 @@
-GOCMD=go
-GOTEST=$(GOCMD) test
-GOVET=$(GOCMD) vet
-BINARY_NAME=local-ai
-GOLLAMA_VERSION?=llama.cpp-8687c1f
-GOGPT4ALLJ_VERSION?=1f7bff57f66cb7062e40d0ac3abd2217815e5109
-GOGPT2_VERSION?=245a5bfe6708ab80dc5c733dcdbfbe3cfd2acdaa
-
-GREEN  := $(shell tput -Txterm setaf 2)
-YELLOW := $(shell tput -Txterm setaf 3)
-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
-
-## Build:
-
-build: prepare ## Build the project
-	$(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) ./
-
-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
-	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 $(GENERIC_PREFIX)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
-
-go-llama/libbinding.a: go-llama
-	$(MAKE) -C go-llama $(GENERIC_PREFIX)libbinding.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
-
-clean: ## Remove build related file
-	rm -fr ./go-llama
-	rm -rf ./go-gpt4all-j
-	rm -rf ./go-gpt2
-	rm -rf $(BINARY_NAME)
-
-## Run:
-run: prepare
-	C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./main.go
-
-test-models/testmodel:
-	mkdir test-models
-	wget https://huggingface.co/concedo/cerebras-111M-ggml/resolve/main/cerberas-111m-q4_0.bin -O test-models/testmodel
-
-test: prepare test-models/testmodel
-	@C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} MODELS_PATH=$(abspath ./)/test-models $(GOCMD) test -v ./...
-
-## Help:
-help: ## Show this help.
-	@echo ''
-	@echo 'Usage:'
-	@echo '  ${YELLOW}make${RESET} ${GREEN}<target>${RESET}'
-	@echo ''
-	@echo 'Targets:'
-	@awk 'BEGIN {FS = ":.*?## "} { \
-		if (/^[a-zA-Z_-]+:.*?##.*$$/) {printf "    ${YELLOW}%-20s${GREEN}%s${RESET}\n", $$1, $$2} \
-		else if (/^## .*$$/) {printf "  ${CYAN}%s${RESET}\n", substr($$1,4)} \
-		}' $(MAKEFILE_LIST)

README.md

@@ -1,244 +0,0 @@
-<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!
-
-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
-- Once loaded the first time, it keep models loaded in memory for faster inference
-- 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) 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`.
-
-## Usage
-
-> `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/LocalAI
-
-cd LocalAI
-
-# copy your models to models/
-cp your-model.bin models/
-
-# (optional) Edit the .env file to set things like context size and threads
-# vim .env
-
-# start with docker-compose
-docker compose up -d --build
-
-# Now API is accessible at localhost:8080
-curl http://localhost:8080/v1/models
-# {"object":"list","data":[{"id":"your-model.bin","object":"model"}]}
-
-curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
-     "model": "your-model.bin",            
-     "prompt": "A long time ago in a galaxy far, far away",
-     "temperature": 0.7
-   }'
-```
-
-## 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.
-
-<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:
-
-```
-Below is an instruction that describes a task. Write a response that appropriately completes the request.
-
-### Instruction:
-{{.Input}}
-
-### Response:
-```
-
-See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prompt-templates) directory in this repository for templates for most popular models.
-
-</details>
-
-## API
-
-`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/local-ai:latest --models-path /path/to/models --context-size 700 --threads 4
-```
-
-And you'll see:
-```
-┌───────────────────────────────────────────────────┐ 
-│                   Fiber v2.42.0                   │ 
-│               http://127.0.0.1:8080               │ 
-│       (bound on host 0.0.0.0 and port 8080)       │ 
-│                                                   │ 
-│ Handlers ............. 1  Processes ........... 1 │ 
-│ Prefork ....... Disabled  PID ................. 1 │ 
-└───────────────────────────────────────────────────┘ 
-```
-
-You can control the API server options with command line arguments:
-
-```
-local-api --models-path <model_path> [--address <address>] [--threads <num_threads>]
-```
-
-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              | 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. |
-
-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). 
-
-Following the list of endpoints/parameters supported.
-
-#### Chat completions
-
-For example, to generate a chat completion, you can send a POST request to the `/v1/chat/completions` endpoint with the instruction as the request body:
-
-```
-curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
-     "model": "ggml-koala-7b-model-q4_0-r2.bin",
-     "messages": [{"role": "user", "content": "Say this is a test!"}],
-     "temperature": 0.7
-   }'
-```
-
-Available additional parameters: `top_p`, `top_k`, `max_tokens`
-
-#### Completions
-
-For example, to generate a comletion, you can send a POST request to the `/v1/completions` endpoint with the instruction as the request body:
-```
-curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
-     "model": "ggml-koala-7b-model-q4_0-r2.bin",
-     "prompt": "A long time ago in a galaxy far, far away",
-     "temperature": 0.7
-   }'
-```
-
-Available additional parameters: `top_p`, `top_k`, `max_tokens`
-
-#### List models
-
-You can list all the models available with:
-
-```
-curl http://localhost:8080/v1/models
-```
-
-## Using other models
-
-gpt4all (https://github.com/nomic-ai/gpt4all) works as well, however the original model needs to be converted (same applies for old alpaca models, too):
-
-```bash
-wget -O tokenizer.model https://huggingface.co/decapoda-research/llama-30b-hf/resolve/main/tokenizer.model
-mkdir models
-cp gpt4all.. models/
-git clone https://gist.github.com/eiz/828bddec6162a023114ce19146cb2b82
-pip install sentencepiece
-python 828bddec6162a023114ce19146cb2b82/gistfile1.txt models tokenizer.model
-# There will be a new model with the ".tmp" extension, you have to use that one!
-```
-
-### Windows compatibility
-
-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
-
-### 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 `LocalAI` container image locally you can use `docker`:
-
-```
-# build the image
-docker build -t LocalAI .
-docker run LocalAI
-```
-
-Or build the binary with `make`:
-
-```
-make build
-```
-
-## Short-term roadmap
-
-- [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!
-
-## License
-
-MIT
-
-## Acknowledgements
-
-- [llama.cpp](https://github.com/ggerganov/llama.cpp)
-- https://github.com/tatsu-lab/stanford_alpaca
-- https://github.com/cornelk/llama-go for the initial ideas
-- https://github.com/antimatter15/alpaca.cpp for the light model version (this is compatible and tested only with that checkpoint model!)

api/api.go

@@ -1,423 +0,0 @@
-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 {
-	Created int      `json:"created,omitempty"`
-	Object  string   `json:"chat.completion,omitempty"`
-	ID      string   `json:"id,omitempty"`
-	Model   string   `json:"model,omitempty"`
-	Choices []Choice `json:"choices,omitempty"`
-}
-
-type Choice struct {
-	Index        int      `json:"index,omitempty"`
-	FinishReason string   `json:"finish_reason,omitempty"`
-	Message      *Message `json:"message,omitempty"`
-	Text         string   `json:"text,omitempty"`
-}
-
-type Message struct {
-	Role    string `json:"role,omitempty"`
-	Content string `json:"content,omitempty"`
-}
-
-type OpenAIModel struct {
-	ID     string `json:"id"`
-	Object string `json:"object"`
-}
-
-type OpenAIRequest struct {
-	Model string `json:"model"`
-
-	// 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"`
-
-	Echo bool `json:"echo"`
-	// Common options between all the API calls
-	TopP        float64 `json:"top_p"`
-	TopK        int     `json:"top_k"`
-	Temperature float64 `json:"temperature"`
-	Maxtokens   int     `json:"max_tokens"`
-
-	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"`
-	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, 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)
-
-		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")
-		}
-
-		// 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
-		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
-		if topP == 0 {
-			topP = 0.7
-		}
-		topK := input.TopK
-		if topK == 0 {
-			topK = 80
-		}
-
-		temperature := input.Temperature
-		if temperature == 0 {
-			temperature = 0.9
-		}
-
-		tokens := input.Maxtokens
-		if tokens == 0 {
-			tokens = 512
-		}
-
-		predInput := input.Prompt
-		if chat {
-			mess := []string{}
-			// TODO: encode roles
-			for _, i := range input.Messages {
-				mess = append(mess, i.Content)
-			}
-
-			predInput = strings.Join(mess, "\n")
-		}
-
-		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
-		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{}
-
-		n := input.N
-
-		if input.N == 0 {
-			n = 1
-		}
-
-		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
-				predictOptions := []gptj.PredictOption{
-					gptj.SetTemperature(temperature),
-					gptj.SetTopP(topP),
-					gptj.SetTopK(topK),
-					gptj.SetTokens(tokens),
-					gptj.SetThreads(threads),
-				}
-
-				if input.Batch != 0 {
-					predictOptions = append(predictOptions, gptj.SetBatch(input.Batch))
-				}
-
-				if input.Seed != 0 {
-					predictOptions = append(predictOptions, gptj.SetSeed(input.Seed))
-				}
-
-				return gptModel.Predict(
-					predInput,
-					predictOptions...,
-				)
-			}
-		case model != nil:
-			predFunc = func() (string, error) {
-				// Generate the prediction using the language model
-				predictOptions := []llama.PredictOption{
-					llama.SetTemperature(temperature),
-					llama.SetTopP(topP),
-					llama.SetTopK(topK),
-					llama.SetTokens(tokens),
-					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))
-				}
-
-				if input.F16 {
-					predictOptions = append(predictOptions, llama.EnableF16KV)
-				}
-
-				if input.IgnoreEOS {
-					predictOptions = append(predictOptions, llama.IgnoreEOS)
-				}
-
-				if input.Seed != 0 {
-					predictOptions = append(predictOptions, llama.SetSeed(input.Seed))
-				}
-
-				return model.Predict(
-					predInput,
-					predictOptions...,
-				)
-			}
-		}
-
-		for i := 0; i < n; i++ {
-			prediction, err := predFunc()
-			if err != nil {
-				return err
-			}
-
-			if input.Echo {
-				prediction = predInput + prediction
-			}
-
-			if chat {
-				result = append(result, Choice{Message: &Message{Role: "assistant", Content: prediction}})
-			} else {
-				result = append(result, Choice{Text: prediction})
-			}
-		}
-
-		jsonResult, _ := json.Marshal(result)
-		log.Debug().Msgf("Response: %s", jsonResult)
-
-		// Return the prediction in the response body
-		return c.JSON(OpenAIResponse{
-			Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
-			Choices: result,
-		})
-	}
-}
-
-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
-		}
-
-		dataModels := []OpenAIModel{}
-		for _, m := range models {
-			dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
-		}
-		return c.JSON(struct {
-			Object string        `json:"object"`
-			Data   []OpenAIModel `json:"data"`
-		}{
-			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()})
-		},
-	})
-
-	// 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

@@ -1,53 +0,0 @@
-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

@@ -1,13 +0,0 @@
-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

@@ -1,6 +0,0 @@
-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

@@ -1,44 +0,0 @@
-{{/*
-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

@@ -1,39 +0,0 @@
-{{- 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

@@ -1,39 +0,0 @@
-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

@@ -1,19 +0,0 @@
-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

@@ -1,38 +0,0 @@
-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

@@ -1,15 +0,0 @@
-version: '3.6'
-
-services:
-  api:
-    image: quay.io/go-skynet/local-ai:latest
-    build:
-      context: .
-      dockerfile: Dockerfile
-    ports:
-      - 8080:8080
-    env_file:
-      - .env
-    volumes:
-      - ./models:/models:cached
-    command: ["/usr/bin/local-ai" ]

go.mod

@@ -1,54 +0,0 @@
-module github.com/go-skynet/LocalAI
-
-go 1.19
-
-require (
-	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/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
-	github.com/savsgio/gotils v0.0.0-20220530130905-52f3993e8d6d // indirect
-	github.com/tinylib/msgp v1.1.6 // indirect
-	github.com/valyala/bytebufferpool v1.0.0 // indirect
-	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

@@ -1,155 +0,0 @@
-github.com/StackExchange/wmi v1.2.1 h1:VIkavFPXSjcnS+O8yTq7NI32k0R5Aj+v39y29VYDOSA=
-github.com/StackExchange/wmi v1.2.1/go.mod h1:rcmrprowKIVzvc+NUiLncP2uuArMWLCbu9SBzvHz7e8=
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-golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
-golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
-golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
-golang.org/x/text v0.3.7/go.mod h1:u+2+/6zg+i71rQMx5EYifcz6MCKuco9NR6JIITiCfzQ=
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-golang.org/x/tools v0.7.0 h1:W4OVu8VVOaIO0yzWMNdepAulS7YfoS3Zabrm8DOXXU4=
-golang.org/x/tools v0.7.0/go.mod h1:4pg6aUX35JBAogB10C9AtvVL+qowtN4pT3CGSQex14s=
-golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
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-google.golang.org/protobuf v1.28.0 h1:w43yiav+6bVFTBQFZX0r7ipe9JQ1QsbMgHwbBziscLw=
-gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
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-gopkg.in/yaml.v1 v1.0.0-20140924161607-9f9df34309c0/go.mod h1:WDnlLJ4WF5VGsH/HVa3CI79GS0ol3YnhVnKP89i0kNg=
-gopkg.in/yaml.v2 v2.4.0 h1:D8xgwECY7CYvx+Y2n4sBz93Jn9JRvxdiyyo8CTfuKaY=
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-gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
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-howett.net/plist v1.0.0/go.mod h1:lqaXoTrLY4hg8tnEzNru53gicrbv7rrk+2xJA/7hw9g=

main.go

@@ -1,92 +0,0 @@
-package main
-
-import (
-	"os"
-
-	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 {
-		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.",
-		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:       threads,
-			},
-			&cli.StringFlag{
-				Name:        "models-path",
-				DefaultText: "Path containing models used for inferencing",
-				EnvVars:     []string{"MODELS_PATH"},
-				Value:       path,
-			},
-			&cli.StringFlag{
-				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
-- Cerebras
-- Alpaca
-- StableLM (ggml quantized)
-
-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.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 {
-		log.Error().Msgf("error: %s", err.Error())
-		os.Exit(1)
-	}
-}

pkg/model/loader.go

@@ -1,274 +0,0 @@
-package model
-
-import (
-	"bytes"
-	"fmt"
-	"io/ioutil"
-	"os"
-	"path/filepath"
-	"strings"
-	"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
-	gpt2models        map[string]*gpt2.GPT2
-	gptstablelmmodels map[string]*gpt2.StableLM
-
-	promptsTemplates map[string]*template.Template
-}
-
-func NewModelLoader(modelPath string) *ModelLoader {
-	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) {
-	files, err := ioutil.ReadDir(ml.modelPath)
-	if err != nil {
-		return []string{}, err
-	}
-
-	models := []string{}
-	for _, file := range files {
-		// 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
-}
-
-func (ml *ModelLoader) TemplatePrefix(modelName string, in interface{}) (string, error) {
-	ml.mu.Lock()
-	defer ml.mu.Unlock()
-
-	m, ok := ml.promptsTemplates[modelName]
-	if !ok {
-		return "", fmt.Errorf("no prompt template available")
-	}
-
-	var buf bytes.Buffer
-
-	if err := m.Execute(&buf, in); err != nil {
-		return "", err
-	}
-	return buf.String(), nil
-}
-
-func (ml *ModelLoader) loadTemplateIfExists(modelName, modelFile string) error {
-	// Check if the template was already loaded
-	if _, ok := ml.promptsTemplates[modelName]; ok {
-		return nil
-	}
-
-	// 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
-	}
-
-	// Parse the template
-	tmpl, err := template.New("prompt").Parse(string(dat))
-	if err != nil {
-		return err
-	}
-	ml.promptsTemplates[modelName] = tmpl
-
-	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
-	if !ml.ExistsInModelPath(modelName) {
-		return nil, fmt.Errorf("model does not exist")
-	}
-
-	if m, ok := ml.gptmodels[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 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.loadTemplateIfExists(modelName, modelFile); err != nil {
-		return nil, err
-	}
-
-	ml.gptmodels[modelName] = model
-	return model, err
-}
-
-func (ml *ModelLoader) LoadLLaMAModel(modelName string, opts ...llama.ModelOption) (*llama.LLama, error) {
-	ml.mu.Lock()
-	defer ml.mu.Unlock()
-
-	log.Debug().Msgf("Loading model name: %s", modelName)
-
-	// Check if we already have a loaded model
-	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 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.loadTemplateIfExists(modelName, modelFile); err != nil {
-		return nil, err
-	}
-
-	ml.models[modelName] = model
-	return model, err
-}

prompt-templates/alpaca.tmpl

@@ -1,6 +0,0 @@
-Below is an instruction that describes a task. Write a response that appropriately completes the request.
-
-### Instruction:
-{{.Input}}
-
-### Response:

prompt-templates/ggml-gpt4all-j.tmpl

@@ -1,4 +0,0 @@
-The prompt below is a question to answer, a task to complete, or a conversation to respond to; decide which and write an appropriate response.
-### Prompt:
-{{.Input}}
-### Response:

prompt-templates/koala.tmpl

@@ -1 +0,0 @@
-BEGINNING OF CONVERSATION: USER: {{.Input}} GPT:

prompt-templates/vicuna.tmpl

@@ -1,6 +0,0 @@
-Below is an instruction that describes a task. Write a response that appropriately completes the request.
-
-### Instruction:
-{{.Input}}
-
-### Response: