Routing

Alle Routen anzeigen

php artisan route:list

Routen dynamisch erzeugen

composer require illuminate/support

use Illuminate\Support\Facades\File;

function generateRoutes($basePath, $baseNamespace = 'Pages', $routePrefix = '/')
{
    $files = File::allFiles($basePath);

    foreach ($files as $file) {
        $relativePath = str_replace([$basePath, '.vue'], '', $file->getRelativePathname());
        $routeName = str_replace(DIRECTORY_SEPARATOR, '.', $relativePath);
        $routeUri = str_replace(DIRECTORY_SEPARATOR, '/', $relativePath);

        // Example: if file is `resources/js/Pages/Examples/layout-discord.vue`
        // $routeName = 'Examples.layout-discord';
        // $routeUri = 'examples/layout-discord'

        Route::get($routePrefix . $routeUri, function () use ($relativePath, $baseNamespace) {
            return Inertia::render($baseNamespace . str_replace('/', '\\', $relativePath));
        })->name($routeName);
    }
}

generateRoutes(resource_path('js/Pages'));

Mail / SMTP

Lokaler Mailserver für SMTP Testing

MailHog: Web and API based SMTP testing

Allgemeines

Vue and CSS

Styling with CSS Variables

<script setup>
const theme = {
    "menu": {
        "background": 'black',
        "item": {
            "background": "green"
        },
        "subitem": {
            "background": "green"
        }
    }
}
</script>

<style scoped>
.menu {
    background-color: v-bind('theme.menu.background');
}

Allgemeines

Installation

Installation mit der vue-cli

yarn global add @vue/cli
# OR
npm install -g @vue/cli

Neues Projekt erstellen

vue create my-project
# OR
vue ui

Installation mit Vite

Vite

Vite ist ein Build-Tool für die Webentwicklung, das aufgrund seines nativen ES-Modul-Importansatzes eine blitzschnelle Bereitstellung von Code ermöglicht.

Installation mit npm:

npm init @vitejs/app <project-name>
cd <project-name>
npm install
npm run dev

Oder mit Yarn

$ yarn create @vitejs/app <project-name>
$ cd <project-name>
$ yarn
$ yarn dev

Wenn der Projektname Leerzeichen ehthält, kann es zu Fehlern kommen. Dann hilft das nachfolgende Kommando

$ create-vite-app <project-name>

Vue Frameworks

Description:

Setting up VS Code Environment

Debugging

Create a file launch.json and add this to configuration

"configurations": [
        {
            "name": "Streamlit",
            "type": "debugpy",
            "request": "launch",
            "module": "streamlit",
            "args": [
                "run",
                "${file}",
                "--server.port",
                "2000"
            ]
        }
    ]

Ollama und Python

Beispiele

• Ollama Python Library

• Ollama JavaScript Library

Getting Started

_Python

pip install ollama

import ollama

response = ollama.chat(model='llama2', messages=[
  {
    'role': 'user',
    'content': 'Why is the sky blue?',
  },
])

print(response['message']['content'])

_JavaScript

npm install ollama

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'llama2',
  messages: [{ role: 'user', content: 'Why is the sky blue?' }],
})
console.log(response.message.content)

Use cases

Both libraries support Ollama’s full set of features. Here are some examples in Python:

Streaming

for chunk in chat('mistral', messages=messages, stream=True):
    print(chunk['message']['content'], end='', flush=True)

Multi-modal

with open('image.png', 'rb') as file:
  response = ollama.chat(
    model='llava',
    messages=[
      {
        'role': 'user',
        'content': 'What is strange about this image?',
        'images': [file.read()],
      },
    ],
  )

print(response['message']['content'])

Text Completion

result = ollama.generate(
  model='stable-code',
  prompt='// A c function to reverse a string\n',
)

print(result['response'])

Creating custom models

modelfile='''
FROM llama2
SYSTEM You are mario from super mario bros.
'''

ollama.create(model='example', modelfile=modelfile)

Custom client

ollama = Client(host='my.ollama.host')

More examples are available in the GitHub repositories for the Python and JavaScript libraries.

Tipps und Tricks

ollama serve

OLLAMA_ORIGINS=https://webml-demo.vercel.app
OLLAMA_HOST=127.0.0.1:11435 ollama serve

Docker

Run Ollama in Docker container

CPU only

docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

Nvidia GPU

Install the Nvidia container toolkit.
Run Ollama inside a Docker container

docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

Run a model

Now you can run a model like Llama 2 inside the container.

docker exec -it ollama ollama run llama2

OpenAI

OpenAI Compatibility

from openai import OpenAI

client = OpenAI(
    base_url = 'http://localhost:11434/v1',
    api_key='ollama', # required, but unused
)

response = client.chat.completions.create(
  model="llama2",
  messages=[
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Who won the world series in 2020?"},
    {"role": "assistant", "content": "The LA Dodgers won in 2020."},
    {"role": "user", "content": "Where was it played?"}
  ]
)

print(response.choices[0].message.content)

Using Streamlit

LangChain

from langchain_community.llms import Ollama
llm = Ollama(model="gemma2")
llm.invoke("Why is the sky blue?")

LlamaIndex

from llama_index.llms.ollama import Ollama

llm = Ollama(model="gemma2")
llm.complete("Why is the sky blue?")

LLMs and Models by Example

wizard-math

ollama run wizard-math 'Expand the following expression: $7(3y+2)$'