ssh root@YOUR_DROPLET_IP

# Update system packages
apt update && apt upgrade -y

# Install Docker (official method)
apt install -y ca-certificates curl gnupg lsb-release
mkdir -p /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | \
  gpg --dearmor -o /etc/apt/keyrings/docker.gpg

echo "deb [arch=$(dpkg --print-architecture) \
  signed-by=/etc/apt/keyrings/docker.gpg] \
  https://download.docker.com/linux/ubuntu \
  $(lsb_release -cs) stable" | \
  tee /etc/apt/sources.list.d/docker.list > /dev/null

apt update
apt install -y docker-ce docker-ce-cli containerd.io docker-compose-plugin

# Verify Docker installation
docker --version

# Add user to docker group (optional, but convenient)
usermod -aG docker root

# Install essential tools
apt install -y wget curl git htop nano

# Enable Docker service
systemctl enable docker
systemctl start docker

free -h
df -h
cat /proc/cpuinfo | grep processor | wc -l

# Download and install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Start Ollama service
systemctl enable ollama
systemctl start ollama

# Verify it's running
systemctl status ollama

netstat -tlnp | grep 11434
# or
ss -tlnp | grep 11434

ollama pull llama2:7b-chat-q4_K_M

# In another terminal
watch -n 1 'du -sh /root/.ollama/models/'

ollama run llama2:7b-chat-q4_K_M

>>> What is the capital of France?

The capital of France is Paris. It is located in the north-central part of the country 
and is the largest city in France. Paris is known for its rich history, culture, art, 
and architecture, and is often referred to as the "City of Light."

apt install -y nginx
systemctl enable nginx
systemctl start nginx

mkdir -p /etc/nginx/ssl
openssl req -x509 -nodes -days 365 -newkey rsa:2048 \
  -keyout /etc/nginx/ssl/private.key \
  -out /etc/nginx/ssl/certificate.crt \
  -subj "/C=US/ST=State/L=City/O=Org/CN=localhost"

# Rate limiting zone
limit_req_zone $binary_remote_addr zone=api_limit:10m rate=10r/s;

upstream ollama {
    server 127.0.0.1:11434;
}

server {
    listen 80;
    listen [::]:80;
    server_name _;

    # Redirect HTTP to HTTPS
    return 301 https://$host$request_uri;
}

server {
    listen 443 ssl http2;
    listen [::]:443 ssl http2;
    server_name _;

    # SSL configuration
    ssl_certificate /etc/nginx/ssl/certificate.crt;
    ssl_certificate_key /etc/nginx/ssl/private.key;
    ssl_protocols TLSv1.2 TLSv1.3;
    ssl_ciphers HIGH:!aNULL:!MD5;
    ssl_prefer_server_ciphers on;

    # Security headers
    add_header X-Frame-Options "SAMEORIGIN" always;
    add_header X-Content-Type-Options "nosniff" always;
    add_header X-XSS-Protection "1; mode=block" always;
    add_header Referrer-Policy "no-referrer-when-downgrade" always;

    # Rate limiting
    limit_req zone=api_limit burst=20 nodelay;

    # Logging
    access_log /var/log/nginx/ollama_access.log;
    error_log /var/log/nginx/ollama_error.log;

    # Proxy settings
    location / {
        proxy_pass http://ollama;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;

        # Streaming support
        proxy_buffering off;
        proxy_request_buffering off;
        proxy_http_version 1.1;
        proxy_set_header Connection "";

        # Timeouts for long-running requests
        proxy_connect_timeout 60s;
        proxy_send_timeout 300s;
        proxy_read_timeout 300s;
    }

    # Health check endpoint
    location /health {
        access_log off;
        proxy_pass http://ollama/api/tags;
        proxy_set_header Host $host;
    }
}

ln -s /etc/nginx/sites-available/ollama /etc/nginx/sites-enabled/
rm -f /etc/nginx/sites-enabled/default

# Test Nginx config
nginx -t

# Reload Nginx
systemctl reload nginx

apt install -y python3 python3-pip python3-venv

# Create virtual environment
python3 -m venv /opt/llama-api
source /opt/llama-api/bin/activate

# Install dependencies
pip install fastapi uvicorn requests pydantic python-dotenv

python
#!/usr/bin/env python3
"""
Production-grade Llama 2 API wrapper
Handles authentication, rate limiting, and error handling
"""

import os
import logging
from typing import Optional
from datetime import datetime
import requests
from fastapi import FastAPI, HTTPException, Header, BackgroundTasks
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
import uvicorn

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

app = FastAPI(title="Llama 2 API", version="1.0.0")

# Configuration
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://127.0.0.1:11434")
API_KEY = os.getenv("API_KEY", "your-secret-key-change-this")
MODEL_NAME = os.getenv("MODEL_NAME", "llama2:7b-chat-q4_K_M")

# Request/Response models
class ChatMessage(BaseModel):
    role: str
    content: str

class ChatRequest(BaseModel):
    messages: list[ChatMessage]
    temperature: float = 0.7
    top_p: float = 0.9
    top_k: int = 40
    max_tokens: int = 512
    stream: bool = False

class ChatResponse(BaseModel):
    id: str
    object: str = "chat.completion"
    created: int
    model: str
    choices: list
    usage: dict

# Middleware for authentication
def verify_api_key(authorization: Optional[str] = Header(None)):
    """Verify Bearer token"""
    if not authorization:
        raise HTTPException(status_code=401, detail="Missing API key")

    scheme, _, credentials = authorization.partition(" ")
    if scheme.lower() != "bearer":
        raise HTTPException(status_code=401, detail="Invalid auth scheme")

    if credentials != API_KEY:
        raise HTTPException(status_code=401, detail="Invalid API key")

    return credentials

@app.get("/health")
async def health_check():
    """Health check endpoint"""
    try:
        response = requests.get(f"{OLLAMA_URL}/api/tags", timeout=5)
        if response.status_code == 200:
            return {"status": "healthy", "timestamp": datetime.now().isoformat()}
    except Exception as e:
        logger.error(f"Health check failed: {e}")
        raise HTTPException(status_code=503, detail="Service unavailable")

@app.post("/v1/chat/completions")
async def chat_completion(
    request: ChatRequest,
    background_tasks: BackgroundTasks,
    api_key: str = Header(None)
):
    """
    OpenAI-compatible chat completion endpoint
    """
    # Authenticate
    verify_api_key(f"Bearer {api_key}")

    # Validate input
    if not request.messages:
        raise HTTPException(status_code=400, detail="Messages required")

    if len(request.messages) > 50:
        raise HTTPException(status_code=400, detail="Too many messages")

    # Format messages for Llama
    formatted_messages = []
    for msg in request.messages:
        formatted_messages.append(f"{msg.role}: {msg.content}")

    prompt = "\n".join(formatted_messages) + "\nassistant:"

    # Call Ollama
    try:
        response = requests.post(
            f"{OLLAMA_URL}/api/generate",
            json={
                "model": MODEL_NAME,
                "prompt": prompt,
                "stream": request.stream,
                "temperature": request.temperature,
                "top_p": request.top_p,
                "top_k": request.top_k,
                "num_predict": request.max_tokens,
            },
            timeout=300
        )

        if response.status_code != 200:
            logger.error(f"Ollama error

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