<?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>
]]></description><link>https://lankadevelopers.lk/topic/973/localai-a-drop-in-replacement-for-openai</link><generator>RSS for Node</generator><lastBuildDate>Mon, 20 Jul 2026 18:51:33 GMT</lastBuildDate><atom:link href="https://lankadevelopers.lk/topic/973.rss" rel="self" type="application/rss+xml"/><pubDate>Wed, 19 Apr 2023 22:26:40 GMT</pubDate><ttl>60</ttl><item><title><![CDATA[Reply to LocalAI: A drop-in replacement for OpenAI on Mon, 29 Jun 2026 05:59:40 GMT]]></title><description><![CDATA[<p dir="auto"><a href="https://www.adultscare.com/antarvasna/" target="_blank" rel="noopener noreferrer nofollow ugc">antarvasna audio sex story</a> captures every gasp, moan, and whisper with crystal clarity. the narrative flows naturally, pulling you into a world of secret encounters and unrestrained passion. each episode of antarvasna audio sex story builds tension slowly before exploding into explicit moments. the voice acting makes everything feel frighteningly real and dangerously addictive.</p>
]]></description><link>https://lankadevelopers.lk/post/9277</link><guid isPermaLink="true">https://lankadevelopers.lk/post/9277</guid><dc:creator><![CDATA[ananyamitter]]></dc:creator><pubDate>Mon, 29 Jun 2026 05:59:40 GMT</pubDate></item></channel></rss>