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adding localAi v2.18.1, default values (#87)
Co-authored-by: Vishwanath S <[email protected]>
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**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by [Ettore Di Giacinto](https://github.com/mudler). | ||
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## [💻 Get Started here!](https://localai.io/basics/getting_started/index.html) | ||
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## 🚀 [Features](https://localai.io/features/) | ||
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- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `gpt4all.cpp`, ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table)) | ||
- 🗣 [Text to Audio](https://localai.io/features/text-to-audio/) | ||
- 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`) | ||
- 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation) | ||
- 🔥 [OpenAI-alike tools API](https://localai.io/features/openai-functions/) | ||
- 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/) | ||
- ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/) | ||
- 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/) | ||
- 🥽 [Vision API](https://localai.io/features/gpt-vision/) | ||
- 📈 [Reranker API](https://localai.io/features/reranker/) | ||
- 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/) | ||
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### 🔗 Resources | ||
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- [LLM finetuning guide](https://localai.io/docs/advanced/fine-tuning/) | ||
- [How to build locally](https://localai.io/basics/build/index.html) | ||
- [How to install in Kubernetes](https://localai.io/basics/getting_started/index.html#run-localai-in-kubernetes) | ||
- [Projects integrating LocalAI](https://localai.io/docs/integrations/) | ||
- [How tos section](https://io.midori-ai.xyz/howtos/) (curated by our community) | ||
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### 🔗 Community and integrations | ||
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Build and deploy custom containers: | ||
- https://github.com/sozercan/aikit | ||
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WebUIs: | ||
- https://github.com/Jirubizu/localai-admin | ||
- https://github.com/go-skynet/LocalAI-frontend | ||
- QA-Pilot(An interactive chat project that leverages LocalAI LLMs for rapid understanding and navigation of GitHub code repository) https://github.com/reid41/QA-Pilot | ||
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Model galleries | ||
- https://github.com/go-skynet/model-gallery | ||
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Other: | ||
- Helm chart https://github.com/go-skynet/helm-charts | ||
- VSCode extension https://github.com/badgooooor/localai-vscode-plugin | ||
- Terminal utility https://github.com/djcopley/ShellOracle | ||
- Local Smart assistant https://github.com/mudler/LocalAGI | ||
- Home Assistant https://github.com/sammcj/homeassistant-localai / https://github.com/drndos/hass-openai-custom-conversation / https://github.com/valentinfrlch/ha-gpt4vision | ||
- Discord bot https://github.com/mudler/LocalAGI/tree/main/examples/discord | ||
- Slack bot https://github.com/mudler/LocalAGI/tree/main/examples/slack | ||
- Shell-Pilot(Interact with LLM using LocalAI models via pure shell scripts on your Linux or MacOS system) https://github.com/reid41/shell-pilot | ||
- Telegram bot https://github.com/mudler/LocalAI/tree/master/examples/telegram-bot | ||
- Examples: https://github.com/mudler/LocalAI/tree/master/examples/ |
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{ | ||
"addonType": "system app", | ||
"annotations": { | ||
"commit_msg": "LocalAI - The free, Open Source OpenAI alternative", | ||
"source": "community", | ||
"contributor" : "pedro@spectrocloud" | ||
}, | ||
"charts": [ | ||
"charts/local-ai-3.3.0.tgz" | ||
], | ||
"cloudTypes": [ | ||
"all" | ||
], | ||
"displayName": "LocalAI", | ||
"layer":"addon", | ||
"name": "local-ai", | ||
"version": "2.18.1" | ||
} |
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# Default values for eck-elastic-operator | ||
# This is a YAML-formatted file | ||
pack: | ||
content: | ||
images: | ||
- image: quay.io/go-skynet/local-ai:v2.18.1 | ||
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charts: | ||
- repo: https://go-skynet.github.io/helm-charts/ | ||
name: local-ai | ||
version: 3.3.0 | ||
#The namespace (on the target cluster) to install this chart | ||
#When not found, a new namespace will be created | ||
namespace: "local-ui" | ||
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charts: | ||
local-ai: | ||
fullnameOverride: local-ai | ||
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replicaCount: 1 | ||
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deployment: | ||
# For Nvidia GPUs uncomment one of the following (cuda11 or cuda12): | ||
# image: localai/localai:v2.18.1-cublas-cuda11 | ||
# image: localai/localai:v2.18.1-cublas-cuda12 | ||
# image: localai/localai:v2.18.1-cublas-cuda11-ffmpeg (Video Acceleration) | ||
# image: localai/localai:v2.18.1-cublas-cuda12-ffmpeg (Video Acceleration) | ||
# More info in Docs: https://localai.io/features/gpu-acceleration/#cudanvidia-acceleration | ||
image: | ||
repository: quay.io/go-skynet/local-ai # Example: "docker.io/myapp" | ||
tag: v2.18.1 | ||
env: | ||
threads: 4 | ||
context_size: 512 | ||
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# # Inject Secrets into Environment: | ||
# secretEnv: | ||
# - name: HF_TOKEN | ||
# valueFrom: | ||
# secretKeyRef: | ||
# name: some-secret | ||
# key: hf-token | ||
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modelsPath: "/models" | ||
download_model: | ||
# To use cloud provided (eg AWS) image, provide it like: 1234356789.dkr.ecr.us-REGION-X.amazonaws.com/busybox | ||
image: busybox | ||
prompt_templates: | ||
# To use cloud provided (eg AWS) image, provide it like: 1234356789.dkr.ecr.us-REGION-X.amazonaws.com/busybox | ||
image: busybox | ||
pullPolicy: IfNotPresent | ||
imagePullSecrets: [] | ||
# - name: secret-names | ||
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## Needed for GPU Nodes | ||
#runtimeClassName: gpu | ||
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resources: | ||
{} | ||
# We usually recommend not to specify default resources and to leave this as a conscious | ||
# choice for the user. This also increases chances charts run on environments with little | ||
# resources, such as Minikube. If you do want to specify resources, uncomment the following | ||
# lines, adjust them as necessary, and remove the curly braces after 'resources:'. | ||
# limits: | ||
# cpu: 100m | ||
# memory: 128Mi | ||
# requests: | ||
# cpu: 100m | ||
# memory: 128Mi | ||
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# Prompt templates to include | ||
# Note: the keys of this map will be the names of the prompt template files | ||
promptTemplates: | ||
{} | ||
# ggml-gpt4all-j.tmpl: | | ||
# 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: | ||
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# Models to download at runtime | ||
models: | ||
# Whether to force download models even if they already exist | ||
forceDownload: false | ||
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# The list of URLs to download models from | ||
# Note: the name of the file will be the name of the loaded model | ||
list: | ||
# - url: "https://gpt4all.io/models/ggml-gpt4all-j.bin" | ||
# basicAuth: base64EncodedCredentials | ||
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initContainers: [] | ||
# Example: | ||
# - name: my-init-container | ||
# image: my-init-image | ||
# imagePullPolicy: IfNotPresent | ||
# command: ["/bin/sh", "-c", "echo init"] | ||
# volumeMounts: | ||
# - name: my-volume | ||
# mountPath: /path/to/mount | ||
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sidecarContainers: [] | ||
# Example: | ||
# - name: my-sidecar-container | ||
# image: my-sidecar-image | ||
# imagePullPolicy: IfNotPresent | ||
# ports: | ||
# - containerPort: 1234 | ||
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# Persistent storage for models and prompt templates. | ||
# PVC and HostPath are mutually exclusive. If both are enabled, | ||
# PVC configuration takes precedence. If neither are enabled, ephemeral | ||
# storage is used. | ||
persistence: | ||
models: | ||
enabled: true | ||
annotations: {} | ||
storageClass: hostPath | ||
accessModes: ReadWriteMany | ||
size: 10Gi | ||
globalMount: /models | ||
output: | ||
enabled: true | ||
annotations: {} | ||
storageClass: hostPath | ||
accessModes: ReadWriteMany | ||
size: 5Gi | ||
globalMount: /tmp/generated | ||
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service: | ||
type: ClusterIP | ||
# If deferring to an internal only load balancer | ||
# externalTrafficPolicy: Local | ||
port: 80 | ||
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" | ||
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ingress: | ||
enabled: false | ||
className: "" | ||
annotations: | ||
{} | ||
# nginx.ingress.kubernetes.io/proxy-body-size: "25m" # This value determines the maxmimum uploadable file size | ||
# kubernetes.io/ingress.class: nginx | ||
# kubernetes.io/tls-acme: "true" | ||
hosts: | ||
- host: chart-example.local | ||
paths: | ||
- path: / | ||
pathType: ImplementationSpecific | ||
tls: [] | ||
# - secretName: chart-example-tls | ||
# hosts: | ||
# - chart-example.local | ||
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nodeSelector: {} | ||
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tolerations: [] | ||
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affinity: {} |