feat: Return OpenAI errors and update docs (#80)

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

.github/workflows/test.yml

@@ -26,20 +26,19 @@ jobs:
         run: |
           make test
 
-  # macOS-latest:
-  #   runs-on: macOS-latest
+  macOS-latest:
+    runs-on: macOS-latest
 
-  #   steps:
-  #     - name: Clone
-  #       uses: actions/checkout@v1
-  #       with: 
-  #         submodules: true
+    steps:
+      - name: Clone
+        uses: actions/checkout@v1
+        with: 
+          submodules: true
 
-  #     - name: Dependencies
-  #       run: |
-  #         brew update
-  #         brew install sdl2
-
-  #     - name: Test
-  #       run: |
-  #         make test
+      - name: Dependencies
+        run: |
+          brew update
+          brew install sdl2
+      - name: Test
+        run: |
+          make test

Makefile

@@ -2,9 +2,12 @@ GOCMD=go
 GOTEST=$(GOCMD) test
 GOVET=$(GOCMD) vet
 BINARY_NAME=local-ai
-GOLLAMA_VERSION?=llama.cpp-8687c1f
-GOGPT4ALLJ_VERSION?=1f548782d80d48b9a0fac33aae6f129358787bc0
-GOGPT2_VERSION?=1c24f5b86ac428cd5e81dae1f1427b1463bd2b06
+# renovate: datasource=github-tags depName=go-skynet/go-llama.cpp
+GOLLAMA_VERSION?=llama.cpp-25d7abb
+# renovate: datasource=git-refs packageNameTemplate=https://github.com/go-skynet/go-gpt4all-j.cpp currentValueTemplate=master depNameTemplate=go-gpt4all-j.cpp
+GOGPT4ALLJ_VERSION?=1f7bff57f66cb7062e40d0ac3abd2217815e5109
+# renovate: datasource=git-refs packageNameTemplate=https://github.com/go-skynet/go-gpt2.cpp currentValueTemplate=master depNameTemplate=go-gpt2.cpp
+GOGPT2_VERSION?=245a5bfe6708ab80dc5c733dcdbfbe3cfd2acdaa
 
 GREEN  := $(shell tput -Txterm setaf 2)
 YELLOW := $(shell tput -Txterm setaf 3)

README.md

@@ -7,7 +7,12 @@
 
 > :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.
+
+[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml) [![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)
+
+[![](https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted)](https://discord.gg/uJAeKSAGDy) 
+
+**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
@@ -15,7 +20,7 @@ LocalAI is a straightforward, drop-in replacement API compatible with OpenAI for
 - 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)
+Reddit post: https://www.reddit.com/r/selfhosted/comments/12w4p2f/localai_openai_compatible_api_to_run_llm_models/
 
 ## Model compatibility
 
@@ -52,7 +57,7 @@ cp your-model.bin models/
 # vim .env
 
 # start with docker-compose
-docker compose up -d --build
+docker-compose up -d --build
 
 # Now API is accessible at localhost:8080
 curl http://localhost:8080/v1/models
@@ -65,25 +70,41 @@ 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.
+### Example: Use GPT4ALL-J model
 
-    Install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == false`.
+<details>
 
-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.
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
 
-    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.
+cd LocalAI
 
-    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.
+# Download gpt4all-j to models/
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# Use a template from the examples
+cp -rf prompt-templates/ggml-gpt4all-j.tmpl 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":"ggml-gpt4all-j","object":"model"}]}
+
+curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
+     "model": "ggml-gpt4all-j",
+     "messages": [{"role": "user", "content": "How are you?"}],
+     "temperature": 0.9 
+   }'
+
+# {"model":"ggml-gpt4all-j","choices":[{"message":{"role":"assistant","content":"I'm doing well, thanks. How about you?"}}]}
+```
+</details>
 
 ## Prompt templates 
 
@@ -142,6 +163,7 @@ The API takes takes the following parameters:
 | 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. |
+| debug | DEBUG         | false           | Enable debug mode. |
 
 Once the server is running, you can start making requests to it using HTTP, using the OpenAI API. 
 
@@ -151,10 +173,16 @@ Once the server is running, you can start making requests to it using HTTP, usin
 
 You can check out the [OpenAI API reference](https://platform.openai.com/docs/api-reference/chat/create). 
 
-Following the list of endpoints/parameters supported.
+Following the list of endpoints/parameters supported. 
+
+Note:
+
+- You can also specify the model a part of the OpenAI token.
+- If only one model is available, the API will use it for all the requests.
 
 #### Chat completions
 
+<details>
 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:
 
 ```
@@ -166,10 +194,12 @@ curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/jso
 ```
 
 Available additional parameters: `top_p`, `top_k`, `max_tokens`
+</details>
 
 #### 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:
+<details>
+For example, to generate a completion, 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",
@@ -180,14 +210,19 @@ curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d
 
 Available additional parameters: `top_p`, `top_k`, `max_tokens`
 
+</details>
+
 #### List models
 
+<details>
 You can list all the models available with:
 
 ```
 curl http://localhost:8080/v1/models
 ```
 
+</details>
+
 ## 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):
@@ -202,11 +237,32 @@ 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
+
+## 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.
+
+## 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
+## 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.
 
@@ -224,13 +280,71 @@ Or build the binary with `make`:
 make build
 ```
 
+## Frequently asked questions
+
+Here are answers to some of the most common questions.
+
+
+### How do I get models? 
+
+<details>
+
+Most ggml-based models should work, but newer models may require additions to the API. If a model doesn't work, please feel free to open up issues. However, be cautious about downloading models from the internet and directly onto your machine, as there may be security vulnerabilities in lama.cpp or ggml that could be maliciously exploited. Some models can be found on Hugging Face: https://huggingface.co/models?search=ggml, or models from gpt4all should also work: https://github.com/nomic-ai/gpt4all.
+
+</details>
+
+### What's the difference with Serge, or XXX?
+
+
+<details>
+
+LocalAI is a multi-model solution that doesn't focus on a specific model type (e.g., llama.cpp or alpaca.cpp), and it handles all of these internally for faster inference,  easy to set up locally and deploy to Kubernetes.
+
+</details>
+
+
+### Can I use it with a Discord bot, or XXX?
+
+<details>
+
+Yes! If the client uses OpenAI and supports setting a different base URL to send requests to, you can use the LocalAI endpoint. This allows to use this with every application that was supposed to work with OpenAI, but without changing the application!
+
+</details>
+
+
+### Can this leverage GPUs? 
+
+<details>
+
+Not currently, as ggml doesn't support GPUs yet: https://github.com/ggerganov/llama.cpp/discussions/915.
+
+</details>
+
+### Where is the webUI? 
+
+<details> 
+We are working on to have a good out of the box experience - however as LocalAI is an API you can already plug it into existing projects that provides are UI interfaces to OpenAI's APIs. There are several already on github, and should be compatible with LocalAI already (as it mimics the OpenAI API)
+
+</details>
+
+### Does it work with AutoGPT? 
+
+<details>
+
+AutoGPT currently doesn't allow to set a different API URL, but there is a PR open for it, so this should be possible soon!
+
+</details>
+
+
 ## 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)
+- [ ] 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!
+- [ ] Have a webUI!
+- [ ] Allow configuration of defaults for models.
+- [ ] Enable automatic downloading of models from a curated gallery, with only free-licensed models.
 
 ## License
 

api/api.go

@@ -18,6 +18,18 @@ import (
 	"github.com/rs/zerolog/log"
 )
 
+// APIError provides error information returned by the OpenAI API.
+type APIError struct {
+	Code    any     `json:"code,omitempty"`
+	Message string  `json:"message"`
+	Param   *string `json:"param,omitempty"`
+	Type    string  `json:"type"`
+}
+
+type ErrorResponse struct {
+	Error *APIError `json:"error,omitempty"`
+}
+
 type OpenAIResponse struct {
 	Created int      `json:"created,omitempty"`
 	Object  string   `json:"chat.completion,omitempty"`
@@ -395,9 +407,11 @@ func App(loader *model.ModelLoader, threads, ctxSize int, f16 bool, debug, disab
 			}
 
 			// Send custom error page
-			return ctx.Status(code).JSON(struct {
-				Error string `json:"error"`
-			}{Error: err.Error()})
+			return ctx.Status(code).JSON(
+				ErrorResponse{
+					Error: &APIError{Message: err.Error(), Code: code},
+				},
+			)
 		},
 	})
 

api/api_test.go

@@ -49,5 +49,10 @@ var _ = Describe("API test", func() {
 			Expect(len(resp.Choices)).To(Equal(1))
 			Expect(resp.Choices[0].Text).ToNot(BeEmpty())
 		})
+		It("returns errors", func() {
+			_, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "foomodel", Prompt: "abcdedfghikl"})
+			Expect(err).To(HaveOccurred())
+			Expect(err.Error()).To(ContainSubstring("error, status code: 500, message: llama: model does not exist"))
+		})
 	})
 })

go.mod

@@ -3,16 +3,16 @@ 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/go-skynet/go-gpt2.cpp v0.0.0-20230422085954-245a5bfe6708
+	github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230422090028-1f7bff57f66c
+	github.com/go-skynet/go-llama.cpp v0.0.0-20230424120713-e45cebe33c04
 	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
+	github.com/urfave/cli/v2 v2.25.1
 )
 
 require (

go.sum

@@ -21,10 +21,16 @@ github.com/go-ole/go-ole v1.2.6 h1:/Fpf6oFPoeFik9ty7siob0G6Ke8QvQEuVcuChpwXzpY=
 github.com/go-ole/go-ole v1.2.6/go.mod h1:pprOEPIfldk/42T2oK7lQ4v4JSDwmV0As9GaiUsvbm0=
 github.com/go-skynet/go-gpt2.cpp v0.0.0-20230420213900-1c24f5b86ac4 h1:GkGuqnhDFKlCsT6Bo8sdY00A7rFXCzfU1nBOSS4ZnYM=
 github.com/go-skynet/go-gpt2.cpp v0.0.0-20230420213900-1c24f5b86ac4/go.mod h1:1Wj/xbkMfwQSOrhNYK178IzqQHstZbRfhx4s8p1M5VM=
+github.com/go-skynet/go-gpt2.cpp v0.0.0-20230422085954-245a5bfe6708 h1:cfOi4TWvQ6JsAm9Q1A8I8j9YfNy10bmIfwOiyGyU5wQ=
+github.com/go-skynet/go-gpt2.cpp v0.0.0-20230422085954-245a5bfe6708/go.mod h1:1Wj/xbkMfwQSOrhNYK178IzqQHstZbRfhx4s8p1M5VM=
 github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230419091210-303cf2a59a94 h1:rtrrMvlIq+g0/ltXjDdLeNtz0uc4wJ4Qs15GFU4ba4c=
 github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230419091210-303cf2a59a94/go.mod h1:5VZ9XbcINI0XcHhkcX8GPK8TplFGAzu1Hrg4tNiMCtI=
+github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230422090028-1f7bff57f66c h1:48I7jpLNGiQeBmF0SFVVbREh8vlG0zN13v9LH5ctXis=
+github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230422090028-1f7bff57f66c/go.mod h1:5VZ9XbcINI0XcHhkcX8GPK8TplFGAzu1Hrg4tNiMCtI=
 github.com/go-skynet/go-llama.cpp v0.0.0-20230421172644-351a5a40eead h1:C+lcH1srw+c0qPDx1WF8zjGiiOqoPxVICt7bI1sj5cM=
 github.com/go-skynet/go-llama.cpp v0.0.0-20230421172644-351a5a40eead/go.mod h1:35AKIEMY+YTKCBJIa/8GZcNGJ2J+nQk1hQiWo/OnEWw=
+github.com/go-skynet/go-llama.cpp v0.0.0-20230424120713-e45cebe33c04 h1:NPiv7mcIjU71MhEv3v4RRWKSBNXnnCyu6VX4CaaHz2I=
+github.com/go-skynet/go-llama.cpp v0.0.0-20230424120713-e45cebe33c04/go.mod h1:35AKIEMY+YTKCBJIa/8GZcNGJ2J+nQk1hQiWo/OnEWw=
 github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 h1:tfuBGBXKqDEevZMzYi5KSi8KkcZtzBcTgAUUtapy0OI=
 github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572/go.mod h1:9Pwr4B2jHnOSGXyyzV8ROjYa2ojvAY6HCGYYfMoC3Ls=
 github.com/godbus/dbus/v5 v5.0.4/go.mod h1:xhWf0FNVPg57R7Z0UbKHbJfkEywrmjJnf7w5xrFpKfA=
@@ -89,6 +95,8 @@ github.com/tinylib/msgp v1.1.6 h1:i+SbKraHhnrf9M5MYmvQhFnbLhAXSDWF8WWsuyRdocw=
 github.com/tinylib/msgp v1.1.6/go.mod h1:75BAfg2hauQhs3qedfdDZmWAPcFMAvJE5b9rGOMufyw=
 github.com/urfave/cli/v2 v2.25.0 h1:ykdZKuQey2zq0yin/l7JOm9Mh+pg72ngYMeB0ABn6q8=
 github.com/urfave/cli/v2 v2.25.0/go.mod h1:GHupkWPMM0M/sj1a2b4wUrWBPzazNrIjouW6fmdJLxc=
+github.com/urfave/cli/v2 v2.25.1 h1:zw8dSP7ghX0Gmm8vugrs6q9Ku0wzweqPyshy+syu9Gw=
+github.com/urfave/cli/v2 v2.25.1/go.mod h1:GHupkWPMM0M/sj1a2b4wUrWBPzazNrIjouW6fmdJLxc=
 github.com/valyala/bytebufferpool v1.0.0 h1:GqA5TC/0021Y/b9FG4Oi9Mr3q7XYx6KllzawFIhcdPw=
 github.com/valyala/bytebufferpool v1.0.0/go.mod h1:6bBcMArwyJ5K/AmCkWv1jt77kVWyCJ6HpOuEn7z0Csc=
 github.com/valyala/fasthttp v1.44.0 h1:R+gLUhldIsfg1HokMuQjdQ5bh9nuXHPIfvkYUu9eR5Q=

renovate.json

@@ -0,0 +1,17 @@
+{
+  "$schema": "https://docs.renovatebot.com/renovate-schema.json",
+  "extends": [
+    "config:base"
+  ],
+  "regexManagers": [
+    {
+      "fileMatch": [
+        "^Makefile$"
+      ],
+      "matchStrings": [
+        "#\\s*renovate:\\s*datasource=(?<datasource>.*?) depName=(?<depName>.*?)( datasourceTemplate=(?<datasourceTemplate>.*?))?( packageNameTemplate=(?<packageNameTemplate>.*?))?( depNameTemplate=(?<depNameTemplate>.*?))?( valueTemplate=(?<currentValueTemplate>.*?))?( versioning=(?<versioning>.*?))?\\s+.+_VERSION=(?<currentValue>.*?)\\s"
+      ],
+      "versioningTemplate": "{{#if versioning}}{{versioning}}{{/if}}"
+    }
+  ]
+}