
Alexander is a writer, traveler, and serial digital entrepreneur. He’s the founder of the Tushi, the Gen X personal growth newsletter Further, and offers small business advice at Unemployable.

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Linkedin

Facebook

Director and Chief Evangelist

Alexander Hipp


Anil is a content-obsessed marketer who loves driving organic traffic for outstanding companies. He is also the creator of Hack the Content, co-host of The Runner, and owner of several digital commerce sites.

Managing Partner

Anil Vugels


Monika is a writer, musician, and content strategist with a passion for language. When she isn’t helping clients, you can find her writing songs, hiking in a northern forest, or furiously journaling.

Director of Operations

Ann Monika

Programmer / Founder / Student

Tim Schupp


- [the python script](https://github.com/tbscode/tims-blog-posts/blob/main/assets/send_slack_message.py)

Need to notify your team about deployment status on Slack? Automate the process using the slack_sdk Python package with GitHub Actions. Here's how to set it up step by step:

### Creating Your Slack App for Notifications

1. **Create a Slack App**: Go to the [Slack API](https://api.slack.com/apps) section, select 'Create New App', input a name, and choose your workspace.

2. **Set Permissions**: In the Slack app settings, navigate to 'Features' > 'OAuth & Permissions'. Under 'Scopes', add `chat:write` for your bot to send messages. Once you save changes, click 'Install to Workspace'.

3. **Retrieve Your Slack Bot Token**: After installing the app to your workspace, grab your 'Bot User OAuth Token' from the 'OAuth & Permissions' page. Securely store this token as it will be used to authenticate your GitHub Actions script.

### Setting Up GitHub Actions to Send Slack Notifications

First, include your Slack API token as a secret in your GitHub repository:

1. In your GitHub repo, go to 'Settings', then 'Secrets'.
2. Select 'New Repository Secret', and add your Slack API token under `SLACK_API_TOKEN`.

Now, integrate the `send_slack_message.py` script with your deployment process:

```python
# send_slack_message.py
import os
from slack_sdk import WebClient

client = WebClient(token=os.environ["SLACK_API_TOKEN"])

response = client.chat_postMessage(
    channel=os.environ["CHANNEL_ID"],
    mrkdwn=True,
    text=os.environ["MESSAGE"],
)

print(response["message"]["text"])
```

Add a GitHub Actions step in your workflow to execute the notification script:

```yaml
jobs:
  deployment:
    runs-on: ubuntu-latest
    steps:
      # ... previous steps for deployment ...
      
      - name: Notify Slack Channel
        env:
          SLACK_API_TOKEN: ${{ secrets.SLACK_API_TOKEN }}
          CHANNEL_ID: 'your-channel-id'
          MESSAGE: "*Deployment Update*\nImage: ${{ steps.build.outputs.IMAGE_URL }}\nURL: ${{ steps.deploy.outputs.WEBSITE_URL }}"
        run: |
          pip install slack_sdk
          wget -qO- https://raw.githubusercontent.com/tbscode/tims-blog-posts/main/assets/send_slack_message.py | python3 -
```

Replace `your-channel-id` with the actual Slack channel ID where you wish to send notifications. 

> Replace the script url with a self hosted fork of [send_slack_message.py](https://github.com/tbscode/tims-blog-posts/blob/main/assets/send_slack_message.py)

Remember to update the `MESSAGE` variable with relevant details for your deployment, such as image URL or site URL.

Executing the GitHub Action with these configurations will automatically send your predefined message to the designated Slack channel, informing your team about the latest deployment status.

Your GitHub Actions workflow now works seamlessly with Slack for real-time notifications!

Set up Slack notifications for deployments using GitHub Actions and the Python slack_sdk package, keeping your team updated automatically.

Send Slack Notifications on Deployments with GitHub Actions


# Solid Authentication Overview

> A presentation prepared for the
> 'Data Ecosystems Lab'

## Content

This blog article delves into several key aspects of Solid authentication and OpenID Connect, providing insights into the mechanisms and practical implementation details:

- **Introduction to Solid and OpenID Connect**: An overview of the Solid framework and how OpenID Connect (OIDC) serves as a foundational technology for secure authentication.
- **The Solid Community Server's Authentication Process**: A closer look at how the Solid Community Server implements OIDC and the intricacies involved in user verification.
- **Reverse Engineering Authentication with Python**: Step-by-step guidance on how to reverse engineer client authentication processes using the Python `requests` library.
- **Jupyter Notebook Demonstration**: A practical example showcasing the authentication flow within a Jupyter notebook, accessible for interactive learning and experimentation.
- **Flow Charts and Visual Aids**: The inclusion of original and comprehensive flow charts to visualize the authentication sequence as defined by the Solid project.

> If you want to deploy solid on a self hosted kubernetes cluster [checkout this blog post](todo)

## Presentation Slides

<iframe src="https://docs.google.com/presentation/d/e/2PACX-1vR9IbBdC5t9iGfPpiIm6voYEIJvfLBghO4rQoI1J57_cqfim40nndh1kjCajXyoTt77bQVvMgLaLkDJ/embed?start=false&loop=true&delayms=5000" frameborder="0" width="960" height="569" allowfullscreen="true" mozallowfullscreen="true" webkitallowfullscreen="true"></iframe>

## Flow Chart

- To view the original flow chart as published by the Solid project, please visit this link: [Solid OIDC Flow Chart](https://solidproject.org/TR/oidc)
- For a full-size preview of the flow chart, click here: [Full Size Flow Chart Preview](https://viewer.diagrams.net/?tags=%7B%7D&highlight=0000ff&edit=_blank&layers=1&nav=1&title=diagramm.xml#R7V3bcptIGn6WuVDV7oUozodLW46SbM3UeOKkUnuVQqIlsUFqBpDszNNvNydB8yNAAoRkchHbTQMN%2Ff3nAxNptn376Jnu5g9sIWci8tbbRHqaiKKgqgb5QUd%2BRSOywUcDa8%2B24knHgRf7HxQPJtP2toX83MQAYyew3fzgEu92aBnkxkzPw6%2F5aSvs5O%2FqmmtUGHhZmk5x9LttBZtoVFf44%2FgnZK83yZ0FPj6yNZPJ8YC%2FMS38mhmSPkykmYdxEP22fZshh7685L1E581LjqYL89AuqHOC%2BYfh%2FTpIbwdNdP%2FGb389ffn0YRpf5WA6%2B%2FiBJ6LqkOs9rjC5LHlh5jI6oP69pyt9nOHtCnuBaR6H6PaagTmlp0x9b5mbvwkCulUPdGHinE7xuTXGaweZru1zS7wlw0ufTJmvzK3tUJyA91DX9Oc3H3nJEuPrJYfi1xz8SvaOvHGX%2FrrfOr%2FbK%2BTYO%2FLXo4s8e4sCchnpyYmHn49jj68bO0AvbvTcrwTV4UNsHfKXQH4lQAtMcgo9nSd%2FWx52v5reGgXxwBI7jun69iJcBh3x0HLv%2BfYBfUF%2BBHA6ivcBvfUsBS4ddMljkxE%2F8Mg96CAy%2FeAV%2BfT5duj1g0XAmTyg9nh8PSg9cHxj9J2nx50Fzpydea0zZlLJBQ7IC2xCFiWnkgc8ICt3Lp%2Bb4OH9zirM0J4yh6L3W4R1glGyAvSWGYph%2FhFhsnXeLzIlPipLnCBFJyVcJ6bB1yMJp4S6yZCvnhCrGbONdXrxI2WRX2LiakBoIkBoDFwzIHMx2f1wCcrjRHliUEswssFrvDOdLG5BPAUhMl8oIfhFSniHYCvC6yRfrI85JQc4DQJcEW%2Ba0hXelCrG3gPHrik8Iu79SGX1yNvvjNxa5%2B0iL3K6UMncxV6Zu3ZrxEbePyU1%2FjtafLbqklyGUBLEPDj2ekfGFjgIyErpha0HqnXTMQcvf%2BbgSxCfh2oCS%2BkphWAKt5i8Uvzwp%2FDj470XP%2F1J8RskxFw2T43m0TWfRKOHHDMgVJ%2B3NwBcxac%2BU4F%2BRLFg5MWFIDHQjB4oPuuITvJuzV%2BZabGeUHqfVOgk91EYG4Fdl8rMl0%2FPT2kPvj75JVoxc3ayfLxa%2BSiYsOSXvufzKVJvpG7VgTN20Y6KBNPfpPyMHI4tVv0KQN8j5eXpBf81fVlMZ%2Fajo60%2B4uTBuwawqDIAVhkAR5R2MYAlFpBqLYAlSplYscoSMjsDhac243bkQiwP%2BGcPH2zrqI0tvGTGw57IWJF%2FQQS7wGGiBUUILZ8yanh3rOHFb0g5ycQaWFWyxuVJGFL2JEjZ41tQ9kCiNhqJltGS78%2BSP8mDa2OOlThGPVNeEFoA3M7531ravL18M5T%2FPqFv%2F3w7vO6nYjNlZkRct4grIKkuCE8gjpPyJq0hJmyvAnWJ26l1LidADstB6y4e%2BntP8ZdatfwTXu63KFQx7t7AjQ3XrIF7kpn0biCwns6WLFxJOcsCLTMQ2FWWmDEdmbIwJd6cd%2BlIiX9%2BnpFTaHB2Za%2FPNwXujDBPqZWd06WWpxexK7pkPENihSdJUhRwXTXpmL3bEOm40htAbE%2Fs5YhsIkp8%2BC9Hi0fKSAYj4g9tL0LrvMC7bxF5NSXg%2FgL5Hz98nVCH%2FNxCWzx1MRHYc9fDK5tqffOl6ZEBaYuaegsIiZqOgxy89swto%2FvmjjVwGqzsN5Q4%2BqK%2FHWeW7pW00pdouaTGb%2BDhnyhzZKErclumsGjAgi6rIYpQTLsNuwQEtHiDgmlt%2B1HkY%2BbYGc1wFEkDEklSR8EQiYnRJ%2Fc5T1UsrHIAIqahp%2BCOwh5GEdLXjO%2BxTqRUG2o7PMJoTZLcCNISfHZf4ZGEgkaNKJQxz3%2B%2BxCoRh%2B0l1YeIvBr1nwTqYomUyKV9pOGCXjQgSaoCcBPtxN7ZgenQ10yAH6snvBnG2zrRSXY49OS2yL99wtYCVuUJB%2Be2kyyNrCD%2Ba1gpHTHOeI7n4yVcmuTBM4g1utFrROY%2BMl%2BR5CE2nK8p4HPUEzKiUvEWBqA3SVBMrz9BNDQzKX9XHzu2pXA%2BYSSmMyX35Sx0CA%2BNkimiH0HnGBKBYoZ6v7JJrpRN7wrTzLMP9ZmixXIcV0pdt%2B8vsxSkWzJElbq4kFT1QqpM%2FGPCAGhQbosGz4G675q7M6EeXSjYutO9701DCTCR%2Ba1pO1wgbLktPfMr8gNBlH7LIC6643lpXvcHxPjoVJBY8SDLxei%2BmJnWCzgVyPpuxaLox1mUMzZiN1XW1uDr2xqMbVDDqBDhLb%2FQYmCywuWaqnJTg0HQNPA%2BdRX6Qk5eTcOmLXVdaZaCdztuzu7dkuzW1Q2UNve1S%2BB96kFMYSzaukHq1vzorTkmh6MGV%2BsBRokakEZquVfy7qY%2Fd%2FiVSPk5JRnbmka5HXuP4BLvbkDo9xSt1QtCH0pd7ixgC%2Bd%2BVaH6ltCql6A1ahBAKxioaURYVL7IrXmkN5%2FgXgG%2BEpwAaCp3dKscE2rUgVzQEm2xjRJHEDuV3oQ7ws4HWh1JkfM7XtvUhJp5yPJvCEHF%2FgcqYAx3CKFTjvgxjX0QaeyXibeCDSCI9RLWRa2rjHV5LMy5Y3zJIsDBIOWJLfFsD18j%2F7obfCl8AV9gi6Be8VWZTtnECUwAsfO3Nj3NibUYqqF1lEoQxvq%2Fbuxdu46SnIsvdi6Wu%2FhOdhjp37Ui6zSVIPNPzV%2BzraxGNvofOxFLE%2B2ZlhCyXjHfYOc38%2BQUnYWMAjCA%2BL9y3Vjp0BLRyGTbcsn%2FMecYQ%2F3HVJsCnFVI7%2B01jlMZZOwyeFhmStM%2BEeQ9Ex4f0Hy2bNtG0IA%2BJ3R4hl19YV%2FB%2FN6nburs3iu97v1YUwQyrtAp7W1H1nWKdSlQhkRXrMvfLIld8pNoerP51zfnO7%2F7tAe7z16miA4yjpdPZgXfhNSRUlqIQiiSwWmMJto45leqLCp8rRt2HR%2BubH55DYn4Ja2KnkXcKY6Y8XNMnc5JQRr%2FsFwi%2F7S3%2BSaEpViEAuTD0cCUrDac0CChiW1CIxUz79SorizLSnyylaWGcm%2BFWUVU1mwK19gwl%2FKGs6JVVMDrOiugGzW7g3hvza58HdnaIAEOkjd%2F3tmBHdbeWGTWV6KF0ct9QZbtUUfszfNiRWBjyooG2K2i2FV6LAiFcoenZR9qb%2FHCXP5ch290Ghs7dKftaEcjAyQz7q0X%2F4o8zXzy49%2BxMUOhklgZD6GYTnB3PF4ja3aiPEq8RF3%2BSS2ftSQ%2Fo0IuYo%2FIE%2B0xKu%2F64cUA%2B7H3bOrbPo0qEH65N%2FXebBpB4TlVqsR1NqWin84ILX1Wo2UmZ1GHzIo8nmpu6XbuFj79kWqeX8L2CEkmF%2F9hZ7mRWLgpZifoeU4H9uKHvDRt6Jxw55cbasbfBryStk%2BffX9%2FSQfYayNHAJEDJTV0lXVVzkdccKtoVHiarCzcLLIyBRZT12dIrofoflGpbO4simR%2BohJhbaEfyw2VSjtiDFAVlieHo4PEUAnoGEfVtE2opS32tkOPJmHOvedcrrClw26b6Lwoq4tFpwQ0AAL5GtuopD0xN5YYMmSRJC9kBOkPdBSjxxOG7pO2TKSvQP1NXeposWqJ4WqFXFewdFbtrGwP5Lo31NfqfOb7gpzQtOXnYQUpMW%2BoF3LvOti0ehXZLSdLaxCA%2Bs6Wruwn0ISvuB7euuFJ0U754c5lqi067142oE4hhdBKfay019mDqdPTtG48iIIgc%2FCdyr%2FfYrBnNPIhFvMuC8%2FWrwsR1orfaeXqOdhvGel6PxWpWqMkMwC17DrbizjCiIRyg89m%2BDGfT2Qxb1Fwjry%2BtTZRoDPa6Et2sDxd7yj%2BxLaF0qu%2B%2FSXI4LpOyJpT129Ms4X3MIDEULHSc3dnlisNVqRuu9sxV1VZU3UNMlclQZYUOd6WbIAi%2FNeOGctSGvjJGOiLlJ1ZsNW9xocGQTuNwGZceRMxjN5BvRBvt2PzFbQ4oDghcRS23mOZFW%2FJnc6uF2BXOgQD5C4akAwDiGq97W3eGbkARPVCILIr7dimAIPIo5Xbg5UrCwaX9K%2FpuvXS8VZnd18CVttxgq1cmd%2FQWuCn2JRmcKpLU4vgOo%2FUQmvXpC15ksokzeM8phAsp5pWDsdS6CkxSSwk3MlAv3LR6DewlUiQdtxUx898HTX0XO766Jmq9kxdw%2BPUVcazYLDRB6XKhyQ0PkMrPM2FfqcrJ0nDhAplVoy6X8GTe73enErNuNilCiJTNdAc3TVjk60hF6pGvkPTuE7xi9oJEKkNrec%2FF6wkdTatG9ECl7StYG5V14qWyy7QASDLKyvHCmmgQnoZ6mxjhfSJCmnoG0P9Vkg3UwTGplMDbzrFMG4NBFgRX%2ByH2doLFDUT1yO%2BusXXRbmQRZe1XrOpWWfV1mNLxiGh6%2BKWjAz3UsEGIgC82uiZB%2BKrWUvGgRob59sWBUOlh4Cd0tFHKYoBO6XRZykUvmKdHdsZQke%2B1cSlygdRVfo7bTXRB9ALypnBaUItEDUFuyzznFR6t9IOEUrxLKX6LKF4llx9lnjWCjWt%2Bl6VhGywPgNoJwbQyqK6rvdd%2BRZy3y8Oex40Yll3718Q9CKwIQ1K7jMkCNl%2F91Nh7JF3ZKMDzSmcqLEo%2FRGh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## Jupyter Notebook

- For a hands-on demonstration of the reverse-engineered authentication using the Python `requests` library, access the Jupyter Notebook here: [Presentation: Reverse-Engineered Authentication Notebook](https://colab.research.google.com/drive/17H9eaPhxgqb4yonFpfEle39pQjWghL_o?usp=sharing)


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Exploring the workings of OpenID Connect, the Solid Community Server implementation, and reverse-engineering client authentication with Python requests.

Understanding Solid Authentication


## Intro 

Sentry is an incredibly nice error tracking tool; it can significantly increase the speed of bug fixing and debugging. It also offers a bunch of other features. You should also check out [their service](https://sentry.io)

Since I like to know how the stuff works and willing to take it appart; I would always prefer to self-host if I can. This also gives me more comfort about controlling my own data which by the way also aids GDPR compliance (though this is also possible using Sentry's service directly).

Fortunately, there [still is a Helm chart](https://github.com/sentry-kubernetes/charts/tree/develop). 
'Still', because for example: [the deprecated Posthog chart](https://github.com/PostHog/charts-clickhouse), but also the originally (officially maintained?) [sentry chart](https://github.com/helm/charts/tree/master/stable/sentry) seems deprecated now.

## Setup

I prepared a script that will:

1. Configure an ingress with a cluster issuer annotation to serve under a specific `$HOSTNAME`
2. Configure a Postgres password
3. Enable session recordings and its interface

## Installation

Use the following script to install Sentry:

```bash
./install_sentry_microk8s.sh \
  K8_NAMESPACE="<installation-namespace>" \
  RELEASE_NAME="<release-name>" \
  SENTRY_HOSTNAME="<...>" \
  SENTRY_HOSTNAME="<...>" \
  POSTGRES_PASSWORD="<...>" \
  SMTP_USERNAME="<...>" \
  SMTP_PASSWORD="<...>" \
  SMTP_PORT="<...>" \
  SMTP_FROM_EMAIL="<...>" \
  SENTRY_ADMIN_EMAIL="<...>" \
  SENTRY_ADMIN_PASSWORD="<...>"
```

I found out about having to set and update the admin Postgres password using a secret; [in this Github issue](https://github.com/sentry-kubernetes/charts/issues/554).
That's why we create a simple secret for the Postgres-password here:

```bash
apiVersion: v1
kind: Secret
metadata:
  name: postgres
  namespace: $K8_NAMESPACE
stringData:
  postgres-password: "$POSTGRES_PASSWORD"
```

For enabling the session feature and directly setting the Python config, I read [over here](https://github.com/getsentry/self-hosted/issues/2057) and [here](https://github.com/getsentry/self-hosted/blob/master/sentry/sentry.conf.example.py) and [here](https://github.com/sentry-kubernetes/charts/issues/918), ending up with:

```yaml
config:
  sentryConfPy: |
    SENTRY_FEATURES["organizations:session-replay"] = True
    SENTRY_FEATURES["organizations:session-replay-ui"] = True
```

Ingress setup follows a pretty standard procedure:

```yaml
nginx:
  ingress:
    annotations:
      cert-manager.io/cluster-issuer: "letsencrypt-prod"
    enabled: true
    hostname: $SENTRY_HOSTNAME
    ingressClassName: "public"
    tls: true
    extraTls:
      - hosts:
          - $SENTRY_HOSTNAME
        secretName: sentry-tls
```

As in some of my other scripts, I like to assume the cluster issuer is named `"letsencrypt-prod"`. To me, that's a reasonable sacrifice for adding fewer inputs ;).

Also, **to get the install to succeed** I needed to increase the `hooks.activeDeadlineSeconds`; otherwise, it would time out and the installation would fail.

```yaml
hooks:
  activeDeadlineSeconds: 3500
```

## Open Issues

Currently, I still experience one of the metrics services failing. I'm not sure about the impact yet, but tracking seems to work just fine:

```bash
microk8s kubectl logs sentry-snuba-metrics-consumer -n sentry
snuba.clickhouse.errors.ClickhouseWriterError: Method write is not supported by storage Distributed with more than one shard and no sharding key provided (version 21.8.13.6 (official build))
```

seems like an issue with my storage provisioning possibly; no impact seen so-far.


Self Hosted Error Tracking and Reporting using Sentry Kubernetes and Helm

Self Host Sentry using Helm


Since launching [Msgmate.io](https://msgmate.io) at the end of March, we've seen a lot of activity and received a myriad of feedback regarding its services and development.

However, the development of the direct Msgmate feature has been quite restricted. As a result, the updates that are visible to the public have also been very limited. Therefore, I am writing this article to shed some light on what's in store for Msgmate's future.

Please note that this article is somewhat technical in nature!

### Statistics

<div style="
    display: flex;
    flex-wrap: wrap;
    justify-content: space-around;
">
    <div style="
        background-color: #2C333A;
        padding: 20px;
        border-radius: 10px;
        width: 20%;
        text-align: center;
        min-width: 320px;
    ">
        <h2 style="color: #E88388; font-size: 24px;">
            <strong>Registered Users:</strong>
        </h2>
        <p>300</p>
    </div>
    <div style="
        background-color: #2C333A;
        padding: 20px;
        border-radius: 10px;
        width: 20%;
        text-align: center;
        min-width: 320px;
    ">
        <h2 style="color: #E88388; font-size: 24px;">
            <strong>Messages Exchanged:</strong>
        </h2>
        <p>6,331</p>
    </div>
    <div style="
        background-color: #2C333A;
        padding: 20px;
        border-radius: 10px;
        width: 20%;
        text-align: center;
        min-width: 320px;
    ">
        <h2 style="color: #E88388; font-size: 24px;">
            <strong>Tokens Used:</strong>
        </h2>
        <p>579,807+</p>
    </div>
    <div style="
        background-color: #2C333A;
        padding: 20px;
        border-radius: 10px;
        width: 20%;
        text-align: center;
        min-width: 320px;
        margin-bottom: 0 !important;
    ">
        <h2 style="color: #E88388; font-size: 24px;">
            <strong>Images Generated:</strong>
        </h2>
        <p>192</p>
    </div>
</div>

Since the alpha launch in March, we've had 300 users register. A total of 6,331 messages have been exchanged, using over 579,807+ tokens for prompts and completions. Furthermore, a total of 192 images have been generated.

> I've received feedback indicating interest in such a service.
> However, there were also critical comments concerning the current reliability and limited range of features available.

Rest assured, I am taking all feedback seriously and am actively working to bring you a better and enhanced user experience.

<strong style="color: red;">For now we limited msgmate.io alpha registrations untill we scaled our bot service to handle more chats in paralel</strong>


### Development in the Software Stack

My interest in large language models and their immediate applications in everyday life led me to initiate Msgmate as an experiment. Having considerable experience in development operations and infrastructure, I've managed to evolve my stack through several iterations based on the backend + infrastructure definitions I've developed over the years.

**Here's a look at the evolution of the stack:**

|Iteration|Link|Description|
|--|--|--|
|1|[Django Clean Slate](https://github.com/tbscode/django-clean-slate)|First stack iteration which involved Django + Webpack + React.|
|2|[Django NextJS Setup](https://github.com/tbscode/django_nextjssetup)|First experimental combination of Django + NextJS + React.|
|3|[Tiny Django](https://github.com/tbscode/tiny-django)|Evolution into the first version of 'Tim's Stack' initially dubbed 'tiny-django'.|
|4|[AnySearch Stack](https://github.com/tbscode/anysearch-stack)|First Live application using the stack for a submission to the tum.ai hackathon. The stack proved to be instantly viable for rapid development and easy deployment to microk8s Kubernetes clusters.|
|5|[Tim's Stack Anystack](https://github.com/tbscode/tims-stack-anystack)|Clean re-write of the stack, adding automation documentation, and more. During the Bunnyshell Jamstack Hackathon, I had the unique opportunity to|
|6|[Tim's Stack V2](https://github.com/tbscode/tims-stack-v2)|Dawn of a new age ;) Finalization work on the stack has started with the objective of making it out-of-the-box ready, usable state.|

All these updated work towards shaping the backend that msgmate.io uses and making it more robust and scalable! The bigger beta update planned for msgmate will be using the update Tims Stack V2 and there are plans for launching an android and ios app along side the new backend and interface.

### The Stack Won 2. Place!

As mentioned in the Above list [I've participated in a Hackathon using my Stack](https://blog.t1m.me/blog/tims-stack). 

> 🥳 Checkout [the hackathon page](https://devpost.com/software/tim-s-stack-anystack).

My efforts in the Bunnyshell hackathon didn't go to waste, as we managed to secure second place and win `$4000`, which I'll be reinvesting in the development of Msgmate.io!

### Msgmate.io Vision

I envision msgmate.io as the premier platform for innovators and casual users a like - who wish to engage with large language models - automated agents - and seamlessly incorporate them into their applications and everyday life. 
Msgmate should provide user-friendly developer APIs, websockets, and client applications. Fundamentally, interaction with language models and agents should be as straightforward as possible. Yet beneath the surface, the platform should offer abundant interfaces and configuration options.

### Development in the Team

Given my commitments to other projects, the time I can invest in Msgmate development is limited.
So, to advance this service further, I need more development power!

Using the prize money from the hackathon, I've already hired a NextJS + React developer to help me revamp the Msgmate interface. 

**However, I still need more developers motivated to work on LLm tooling and software.**

> I am looking for motivated (self) taught developers or students who have experience working on their own projects.
> You need to be a fast learner. Having knowledge of Docker, NextJS, React, Django would be advantageous but not a requirement.
> If you are interested in collaborating with us, get in touch at tim.timschupp@gmail.com

### Want to Stay Updated? Have Feedback or Issues to Report?

We've set up a simple form over at [`msgmate.io/newsletter`](https://msgmate.io/newsletter/). By signing up, you'll receive the next update straight to your inbox.

Feel free to add a comment to the signup request for any feedback or bugs. You can fill out the newsletter request as often as you like! Happy messaging with Msgmate.io!


A progress and state update on the development of my msgmate.io plattform

Msgmate.io Development Update Oct 2023


Different command I've used over the year to quickly create pdfs from local note files.

## Raw Pandoc

```bash
pandoc -V geometry:margin=1cm <mardown-file> -o <pdf-file>
```

## Pandoc + `wkhtmltopdf`-engine

- html support, e.g.: tables etc
- dynmaic margin

```bash
pandoc --pdf-engine=wkhtmltopdf -V papersize=a4 -V margin-top=0.1 -V margin-left=0.1 -V margin-right=0.1 -V margin-bottom=0.1 --from markdown-markdown_in_html_blocks+raw_html <markdown-file> -o <pdf-file>
```

## Quick TXT file to dense readable pdf

```bash
pandoc --wrap=preserve $1 -V geometry:margin=1cm -V fontsize=8pt -o $1.pdf -f markdown+hard_line_breaks
```

## Github markdown using `grip`

```bash
sudo snap install grip
grip <markdown-file>
```

then visit the browser page and export the page as pdf.
Or `curl -X <page> > rendered.html`.

## HTML to pdf with

```bash
pandoc --pdf-engine=wkhtmltopdf rendered.html -o <pdf-file>
```

## TXT to pdf with `enscript` and `ps2pdf`

```bash
find . -type f -name $1 | while read ONELINE; do enscript "$ONELINE" -p "$(echo "$ONELINE" | sed 's/.txt/.ps/g')"; done
find . -type f -name "$(echo "$1" | sed 's/.txt/.ps/g')" | while read ONELINE; do ps2pdf "$ONELINE" "$(echo "$ONELINE" | sed 's/.ps/.pdf/g')"; done
```

A collection of strategies to quickly produce pdf's from markdown files

PDF's from markdown, pandoc and more


Simulate a webcam even in your deveice doesn't have one!
The video input can even work to simulate video inputs on remote development devices.

You'll need to install and anable `v4l2loopback`.

```bash
sudo apt install v4l2loopback-dkms
sudo modprobe v4l2loopback
```

## Live video from screen

```bash
sudo ffmpeg -f x11grab -r 15 -s 1280x720 -i :1 -vcodec rawvideo -pix_fmt yuv420p -threads 0 -f v4l2 /dev/video2
```

## From Video File


```bash
ffmpeg -re -i <some-video>.mp4 -map 0:v -f v4l2 /dev/video2
```

> Where to go from here? Loop a video of you listen patiently in your zoom meetings? ;)

How to use `ffmpeg` to funnel screen or video data as video input.

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Simulate secondary webcam on linux