PART 2 of 2: Eureka Plan to do of today!
CHAT GPT
OFFLINE LLM (OLLAMA API) for (ex.PRIVATE) OFFLINE WEBSITE
*special purposive is for FREE API/Application Programming Interface PURPOSE

on

🧠 Offline LLM (Ollama API) for Offline Website
— WITHOUT Docker, etc.

This guide shows how to run a local AI (LLM) using Ollama directly on your system (no Docker), and connect it to your offline website.

⬇️ 1. Install Ollama (Native Installation)

Download and install Ollama from the official site:

  • Windows: run installer (.exe)
  • Linux:
curl -fsSL https://ollama.com/install.sh | sh
  • macOS: install via .pkg

After installation, start Ollama:

ollama serve

👉 This starts your local AI API server at:

http://localhost:11434

🤖 2. Download & Run a Model

ollama run llama3

👉 First run will download the model (internet required once), then works fully offline.

🔌 3. Offline Website Structure

[ Offline Website (HTML/JS) ]
            ↓
[ Ollama API (localhost:11434) ]
            ↓
[ Local LLM Model ]

✅ No Docker
✅ No Internet (after model download)

💻 4. Connect Website to Ollama API

Add this JavaScript into your offline HTML file:

<script>
async function askAI() {
  const prompt = document.getElementById("input").value;

  const response = await fetch("http://localhost:11434/api/generate", {
    method: "POST",
    headers: {
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      model: "llama3",
      prompt: prompt
    })
  });

  const data = await response.json();
  document.getElementById("output").innerText = data.response;
}
</script>

<input id="input" placeholder="Ask something">
<button onclick="askAI()">Send</button>
<div id="output"></div>

⚠️ 5. Run Website Locally (Avoid CORS Issues)

Do NOT open HTML file directly (file://), instead run a local server:

python -m http.server 8000

Then open:

http://localhost:8000

⚙️ 6. Optional: Add Local Backend (Better Practice)

Example Node.js server:

// server.js
import express from "express";
import fetch from "node-fetch";

const app = express();
app.use(express.json());

app.post("/api/ai", async (req, res) => {
  const response = await fetch("http://localhost:11434/api/generate", {
    method: "POST",
    headers: {"Content-Type": "application/json"},
    body: JSON.stringify({
      model: "llama3",
      prompt: req.body.prompt
    })
  });

  const data = await response.json();
  res.json(data);
});

app.listen(3000);

Frontend calls:

http://localhost:3000/api/ai

💡 Example Offline Use Cases

  • Private chatbot (no internet)
  • Offline AI assistant
  • Local document processor
  • Secure internal tools

🧾 Simple Summary

Ollama (no Docker) = local AI server

Website = offline frontend

Connection = http://localhost:11434

👉 Fully offline AI system: Private + Free + No Docker

Comments

Post a Comment