<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[LocalAI: A drop-in replacement for OpenAI]]></title><description><![CDATA[<h1><section class="align-center"> LocalAI </section></h1>
<h3><section class="align-center"> LaMA, alpaca, gpt4all, vicuna, koala, gpt4all-j</section></h3>
<hr />
<p dir="auto"><code>Self-hosted, community-driven simple local OpenAI-compatible API written in go. Can be used as a drop-in replacement for OpenAI, running on CPU with consumer-grade hardware. Supports ggml compatible models: LLaMA, alpaca, gpt4all, vicuna, koala, gpt4all-j</code></p>
<hr />
<p dir="auto">Using LocalAI is straightforward and easy. You can simply install LocalAI on your local machine or server via docker and start performing inferencing tasks immediately, no more talkings let's start ,</p>
<ol>
<li>
<p dir="auto">Install docker in your pc or server ( installation depend on the os type, <a href="https://docs.docker.com/get-docker/" target="_blank" rel="noopener noreferrer nofollow ugc">check here</a>)</p>
</li>
<li>
<p dir="auto">Open terminal or cmd and  clone the LocalAi repo from github</p>
<pre><code class="language-bash">  git clone https://github.com/go-skynet/LocalAI
</code></pre>
</li>
<li>
<p dir="auto">Go to the <code>LocalAi/models</code> folder in terminal</p>
<pre><code class="language-bash">  cd LocalAi/models
</code></pre>
</li>
<li>
<p dir="auto">Download the model ( in here i use <code>gpt4all-j model</code> , this model coming with Apache 2.0 Licensed , it can be used for commercial purposes.)</p>
<pre><code class="language-bash"> wget https://gpt4all.io/models/ggml-gpt4all-j.bin
</code></pre>
<p dir="auto">in here i use wget for download, you can download bin file manually and copy paste to the <code>LocalAi/models</code> folder</p>
</li>
<li>
<p dir="auto">Come back to the <code>LocalAi</code> root</p>
</li>
<li>
<p dir="auto">Start with docker-compose</p>
<pre><code class="language-bash">   docker compose up -d --build
</code></pre>
</li>
</ol>
<p dir="auto">After above process finished, let's call our LocalAi via terminal or cmd , in here i use curl you can use also any other tool can perform http request ( postman, etc.. )</p>
<pre><code class="language-bash">curl http://localhost:8080/v1/models
</code></pre>
<p dir="auto">This request showing what are the models we have added to the models directory</p>
<p dir="auto">Let's call the AI with actual Prompt.</p>
<pre><code class="language-bash">curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
     "model": "ggml-gpt4all-j",            
     "prompt": "Explain AI to me like A five-year-old",
     "temperature": 0.7
   }'
</code></pre>
<p dir="auto"><strong>Windows compatibility</strong></p>
<p dir="auto">It should work, however you need to make sure you give enough resources to the container. <a href="https://github.com/go-skynet/LocalAI/issues/2" target="_blank" rel="noopener noreferrer nofollow ugc">See</a></p>
<p dir="auto"><strong>Kubernetes</strong><br />
You can run the API in Kubernetes, see an example deployment in <a href="https://github.com/go-skynet/LocalAI/blob/master/kubernetes/deployment.yaml" target="_blank" rel="noopener noreferrer nofollow ugc">kubernetes</a></p>
<hr />
<p dir="auto"><strong>API Support</strong><br />
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.</p>
<p dir="auto">Example of starting the API with <code>docker</code>:</p>
<pre><code class="language-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
</code></pre>
<p dir="auto">Then you'll see:</p>
<pre><code>┌───────────────────────────────────────────────────┐ 
│                   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 │ 
└───────────────────────────────────────────────────┘ 
</code></pre>
<p dir="auto">if you want more info about API, go to the github page<br />
<a href="https://github.com/go-skynet/LocalAI#api" target="_blank" rel="noopener noreferrer nofollow ugc">https://github.com/go-skynet/LocalAI#api</a></p>
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