In this AI tutorial post we are going to detail how to install and perform the first steps with LMStudio, which is an open source desktop application similar to Ollama that we detail in chapter 1.1 of this tutorial, and which allows, like Ollama, to download, run and manage large open source language models (LLMs) directly on your own computer, without depending on cloud servers or internet connections, and with a graphical interface unlike Ollama.

Access lmstudio.ai with a web browser or through curl, and download the installer to the OS and install it.

In my case I am installing it on Ubuntu 25 and I have downloaded a file with the name LM-Studio-0.3.39-2-x64.AppImage.

This file should be in the 'Downloads' folder on the user's home page with the session from which we downloaded it with the web browser or with curl:

operatorfeitam@ubuntudesktop-tutorialia:~$ pwd
/home/operatorfeitam
operatorfeitam@ubuntudesktop-tutorialia:~$ cd Downloads
operatorfeitam@ubuntudesktop-tutorialia:~/Downloads$ ls -la
total 1026708
drwxr-xr-x  2 operatorfeitam operatorfeitam       4096 Jan 19 14:40 .
drwxr-x--- 22 operatorfeitam operatorfeitam       4096 Jan 19 14:38 ..
-rw-rw-r--  1 operatorfeitam operatorfeitam 1051334741 Jan 19 14:40 LM-Studio-0.3.39-2-x64.AppImage
operatorfeitam@ubuntudesktop-tutorialia:~/Downloads$ 

And from a command console we execute the following to install it:

./LM-Studio-0.3.39-2-x64.AppImage

But we do not want to run it from the 'Downloads' folder, so we create the 'tools' folder within the user's home, and within this folder a subfolder called 'appimages' (it can be in any other folder, but in this tutorial we will have LMStudio available in this folder) which is where we will move the file LM-Studio-0.3.39-2-x64.AppImage:

operatorfeitam@ubuntudesktop-tutorialia:~$ pwd
/home/operatorfeitam
operatorfeitam@ubuntudesktop-tutorialia:~$ mkdir -p tools/appimages
operatorfeitam@ubuntudesktop-tutorialia:~$ cd tools
operatorfeitam@ubuntudesktop-tutorialia:~/tools$ cd appimages
operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ pwd
/home/operatorfeitam/tools/appimages
operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ ls -la
total 8
drwxrwxr-x 2 operatorfeitam operatorfeitam 4096 Jan 19 16:13 .
drwxrwxr-x 3 operatorfeitam operatorfeitam 4096 Jan 19 16:13 ..
operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ mv $HOME/Downloads/LM-Studio-0.3.39-2-x64.AppImage $HOME/tools/appimages/LM-Studio-0.3.39-2-x64.AppImage
operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ ls -la
total 1026708
drwxrwxr-x 2 operatorfeitam operatorfeitam       4096 Jan 19 16:18 .
drwxrwxr-x 3 operatorfeitam operatorfeitam       4096 Jan 19 16:13 ..
-rw-rw-r-- 1 operatorfeitam operatorfeitam 1051334741 Jan 19 14:40 LM-Studio-0.3.39-2-x64.AppImage
operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ 

Before proceeding to execute it, you must give execution permissions to the file with the AppImage extension, for example with:

chmod +x LM-Studio-0.3.39-2-x64.AppImage

Where we see the change of file permissions:

operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ ls -la
total 1026708
drwxrwxr-x 2 operatorfeitam operatorfeitam       4096 Jan 19 16:18 .
drwxrwxr-x 3 operatorfeitam operatorfeitam       4096 Jan 19 16:13 ..
-rw-rw-r-- 1 operatorfeitam operatorfeitam 1051334741 Jan 19 14:40 LM-Studio-0.3.39-2-x64.AppImage
operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ chmod +x LM-Studio-0.3.39-2-x64.AppImage
operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ ls -la
total 1026708
drwxrwxr-x 2 operatorfeitam operatorfeitam       4096 Jan 19 16:18 .
drwxrwxr-x 3 operatorfeitam operatorfeitam       4096 Jan 19 16:13 ..
-rwxrwxr-x 1 operatorfeitam operatorfeitam 1051334741 Jan 19 14:40 LM-Studio-0.3.39-2-x64.AppImage
operatorfeitam@ubuntudesktop-tutorialia:~/tools/appimages$ 

Then run "./LM-Studio-0.3.39-2-x64.AppImage --no-sandbox" which will raise a window of the LMStudio program:

We click on "Skip" and it shows us the following:

Where we see a GUI where we can chat and select conversation lists. But for now we cannot do anything until we load a model to use, for which we will click on "Select a model to load (Ctrl + L)" and a modal window will open where we have the option to download the "qwen-3b" model " to download it and be able to use it, where we will press the "Download" button:

We wait for the model to download, and we select the model and close the modal window on the "X" icon. Once with the selected model we can start a conversion with it, such as "Explain to me the concept of the Napierian logarithm" in the text box where it says "Send a message to the model...":

We see in the image above that we asked him the question appearing in the chat content block on the right, and he is already answering, and still thinking as he reports. This conversation for now is called "Unnamed Chat", but in the three dots icon (...) you can change the name to recover it at any time and go deeper.

If we press the folder icon on the left we see the view of the models that we have available locally:

In the searched element we can write the model that we want to download, such as "LLama3" which we do not yet have, where it informs us that "No matching results" because we do not have it, but it shows you a "Search more results for Llama3" button where we can download it and install it for LM Studio:

Pressing the "Search more result for Llama3" button gives you the results, in a new modal window, where we can select the one we want to download and install it in the "Download" button:

Once you have downloaded it available in LM Studio, you can use it by selecting it in the top selector of the conversations view.

We see that LM Studio with its simple graphical interface will allow us to use multiple models locally in a simple way just as we do with Ollama from the command console.

AI has changed the way we carry out many of the actions that we commonly carry out in our lives in all areas: family, social and work. It is here to stay just as robotization or the Internet is, although we are still in a phase of discovering all the new capabilities it brings us.

This tutorial, available in both feitam.es (only in English) and tibidico.com (both in English and Spanish), is a vibe AI tutorial reflecting its current evolution as new elements and aspects appear, and I am discovering them, testing and delving into its use and exploitation.

I want to emphasize that AI gives us more efficiency and productivity if we know how to use it properly, but we must never fall into the idea that it is an oracle of what it contributes; and that he really is an educated snitch, and focused by someone, on a correlation of the specific data source he uses, and precisely for this reason I consider that it does not generate R&D by providing the correlation of something that already exists. We must not fall into extreme enthusiasm in using it for everything, avoiding excessive acquisition of unnecessary computing, taking special care regarding cybersecurity aspects such as sharing sensitive or important information for us in its use.

This tutorial attempts to give all the options available so that you can adapt the use of AI to your use scenarios, with the use of local and non-local LLMs, characteristics of the different LLM models available, use of development models, use of models visual detection, etc.

• Section 1: Local/private LLM Managers
  • 1.1: Hello world to AI with Ollama
  • 1.2: LM Studio, first steps

Content planned to be published soon, these are my concerns in AI in the short and medium term:

• Section: Virtual assistants in the cloud
  • ChatGPT
• Section: Cloud LLMs
  • GPT-5
  • Claude
  • Gemini
  • Gork
  • Kimi
  • Yolo
  • Qwen
• Section: AI for dev
  • VS Code
  • Antigravity
• Section: Fundamentals
• Section: RAG
• Section: MCP
• Section: Agents
• Section: Vibe coding

We are currently in a time of continuous evolution of artificial intelligence (AI) languages, with new models and evolutions of existing ones constantly appearing, such as the different versions of GPT (GPT-3.5, GPT-4, etc.) from OpenAI, Gemini from Google, Claude from Anthropic, Grok from X, DeepSeek-V3 from DeepSeek or Copilot from Microsoft.

These models are available online with a subscription fee based on token usage, but some models, or versions (usually earlier ones), are available for download and local use.

For this local use, it is necessary to have applications that manage AI language models, such as:

• Ollama. Very important: Ollama is an AI language model management application, and it also has models called "llama." Don't confuse the two.
• LMStudio
• Jan
• GPT4All

We'll explain how to install an AI language model management application, specifically Ollama, and how to download and use AI language models locally.

To install Ollama, visit the following URL:

This page shows how to install Ollama for each operating system and the available models to use with Ollama.

First, we install Ollama, which will install the CLI for the Ollama console and a REST API to interact and manage everything.

All the actions detailed in this article were performed on an Ubuntu 25.04 desktop virtualized with VirtualBox with 154 GB RAM and 4 CPUs, but it should work on most operating systems with the changes you apply.

We will perform the installation as detailed at https://ollama.com/download/linux by running:

curl -fsSL https://ollama.com/install.sh | sh

This installation will create an ollama service that must be running for this console CLI and REST API to be available:

llm-04@ubuntu2504desktop-llm-04-ts04:~$ sudo systemctl status ollama
● ollama.service - Ollama Service
     Loaded: loaded (/etc/systemd/system/ollama.service; enabled; preset: enabled)
     Active: active (running) since Fri 2025-09-19 11:57:22 CEST; 1h 32min ago
 Invocation: 1e26e8d051b443d2b8c9ba46e07725af
   Main PID: 2143 (ollama)
      Tasks: 11 (limit: 16054)
     Memory: 4.5G (peak: 9.5G)
        CPU: 34.230s
     CGroup: /system.slice/ollama.service
             └─2143 /usr/local/bin/ollama serve

Once Ollama is installed on our computer, we look at the "Models" link on the ollama.com website for the available models and proceed to download the one we prefer. For this explanation, we'll download two models:

• llama3:8b
• llama3:instruct

If you consider yourself to have powerful hardware, you can try downloading llama3:70b or any other model with a high number of parameters. With a greater number of parameters on the same hardware, the token generation rate per second is lower, but it can handle more complex tasks and generate more detailed responses.

The "ollama pull" command is used to download the model you want to use, and after the model you have the ability to specify tags, which are reported in each model which are available for it, such as the following:

• To specify the size of the parameters you have, and in general the larger they are, the more knowledge they have but the more resources they require: they can be values ​​like 1b, 8b, 70b, etc.
• To specify quantization: which serves to reduce the size of the model and speed up its execution, at the cost of reducing numerical precision. Example values ​​are 16, q2_K, q4_K_, etc. Lower numerical values ​​mean more compression and therefore greater loss of precision. For example, f16 is 16-bit floating-point quantization and is therefore minimally compromised, as is f32, but they require a greater amount of resources. Generally, the K variants (_K_S, _K_M, _K_L) are a good balance between size and quality.
• To specify the variant
  • instruct: to follow instructions
  • chat: to chat
  • code: for programming
  • vision: for images
  • uncensored: with less security filtering
  • latest: is the default if nothing is specified

We download the models with the following commands:

ollama pull llama3:8b
ollama pull llama3:instruct

These models are stored, each with its Modelfile and other files they need, in different locations depending on the OS and installation type:

• macOS: in the user's home directory at /.ollama/models
• Windows: in the user's home directory at /.ollama/models
• Linux with a non-Systemd service installation: in the user's home directory at /.ollama/models
• Linux with a Systemd service installation (as detailed in this article): in /usr/share/ollama/.ollama/models
• Docker installation: in /root/.ollama/models inside the container

Once we have downloaded the two models with Ollama, we can check that they are ready with the following command:

ollama list

An example of the execution of the previous command is the following, where we see that it provides the name of the model, its ID, the size and the modification date:

llm-04@ubuntu2504desktop-llm-04-ts04:~$ ollama list
NAME               ID              SIZE      MODIFIED    
llama3:instruct    365c0bd3c000    4.7 GB    3 weeks ago    
llama3:8b          365c0bd3c000    4.7 GB    3 weeks ago    
llm-04@ubuntu2504desktop-llm-04-ts04:~$ 

A model on our computer can be deleted with the following command, for example deleting the "llama3:instruct" model:

ollama rm llama3:instruct

A model on our computer can be duplicated to customize it to our needs with the evolution we consider with the following command:

ollama cp llama3:instruct llama3:instruct-evo

Once we have the model we want to run available on our computer, we proceed to run it with the following command, example for the model "llama3:8b":

ollama run llama3:8b

This presents us with a prompt to interact with:

llm-04@ubuntu2504desktop-llm-04-ts04:~$ ollama run llama3:8b
>>> Send a message (/? for help)

This model, when executed, is loaded into memory and remains available in memory for a period of time until it is removed from memory, taking into account the last time it was accessed. Generally, 5 minutes of inactivity removes it from memory and it is no longer active.

And now is the time to ask him any question like "Explain to me the concept of the Napierian logarithm" (you can interact in different languages, I have tried in English and Spanish and he has responded without problems in both, although it seemed to me that he is more explanatory in English):

llm-04@ubuntu2504desktop-llm-04-ts04:~$ ollama run llama3:8b
>>> Explain to me the concept of the Napierian logarithm
A delightful topic!

The Napierian logarithm, also known as the natural logarithm (ln), is a fundamental concept in mathematics that plays a crucial role in many areas of 
science and engineering. It's named after John Napier, a Scottish mathematician who introduced it in 1614.

**What is the Napierian logarithm?**

The Napierian logarithm is a mathematical function that maps any positive real number to its logarithmic value with respect to the base e, where e ≈ 
2.71828 (Euler's number). In other words, it measures the power to which the base e must be raised to produce the original value.

Formally, for any positive real number x, the Napierian logarithm is defined as:

ln(x) = loge(x)

**Key properties:**

1. **Base**: The Napierian logarithm has a base of e, which is an irrational number approximately equal to 2.71828.
2. **Monotonicity**: The function is monotonically increasing, meaning that ln(x) increases as x increases.
3. **Continuity**: The Napierian logarithm is continuous at all points in its domain (all positive real numbers).
4. **Invertibility**: The function is invertible, meaning that there exists a unique value of x for each given value of ln(x).

**Relationship to other logarithms**

The Napierian logarithm is closely related to other types of logarithms:

1. **Common logarithm (log10)**: This is the logarithm with base 10, which is commonly used in everyday applications. The relationship between log10 
and ln is:

log10(x) = ln(x) / ln(10)

2. **Binary logarithm (log2)**: This is the logarithm with base 2, which is used in computer science and information theory. The relationship between 
log2 and ln is:

log2(x) = ln(x) / ln(2)

**Importance in mathematics and science**

The Napierian logarithm has numerous applications across various fields:

1. **Calculus**: It appears in the study of limits, derivatives, and integrals.
2. **Probability theory**: The logarithmic function is used to model random processes and calculate probabilities.
3. **Information theory**: The entropy of a probability distribution is closely related to the Napierian logarithm.
4. **Physics**: Logarithms appear in problems involving exponential growth or decay, such as population dynamics, chemical reactions, and 
thermodynamics.

In conclusion, the Napierian logarithm is a fundamental mathematical function that plays a crucial role in many areas of science and engineering. Its 
unique properties and relationships to other logarithmic functions make it an essential tool for solving problems in various fields.

>>> Send a message (/? for help)

To exit you can press Ctrl+D.

Within the model execution we have commands that are called with "/" followed by the command and the options of each command, some basic examples:

• /?: displays a help menu.
• /show info: displays information about the current model on the screen. This command, within the running model, provides the same information as the "ollama show" command detailed below.
• /bye: exits the interactive chat session and unloads the model from memory.
• /exit: the same as /bye.
• /save name_sesion: creates a new model with the current chat history.
• /load name_sesion: loads a saved model and starts in the saved state to restore the conversation history and continue where you left off. Note: It can also be run with "ollama run session_name".

We can see the active models in memory with the following command:

ollama ps

An example of its output is this:

llm-04@ubuntu2504desktop-llm-04-ts04:~$ ollama ps
NAME         ID              SIZE      PROCESSOR    CONTEXT    UNTIL              
llama3:8b    365c0bd3c000    5.3 GB    100% CPU     4096       4 minutes from now    
llm-04@ubuntu2504desktop-llm-04-ts04:~$ 

We can see all the details of a model with the following command, in this example asking for the model "llama3:8b":

ollama show llama3:8b

Which returns an output like the following:

llm-04@ubuntu2504desktop-llm-04-ts04:~$ ollama show llama3:8b
  Model
    architecture        llama    
    parameters          8.0B     
    context length      8192     
    embedding length    4096     
    quantization        Q4_0     

  Capabilities
    completion    

  Parameters
    num_keep    24                       
    stop        "<|start_header_id|>"    
    stop        "<|end_header_id|>"      
    stop        "<|eot_id|>"             

  License
    META LLAMA 3 COMMUNITY LICENSE AGREEMENT             
    Meta Llama 3 Version Release Date: April 18, 2024    
    ...                                                  

llm-04@ubuntu2504desktop-llm-04-ts04:~$ 

We see in this information that it is a Q4_0 quantization model, with 8 billion parameters, and that it has configuration parameters, and four of these appear: one num_keep and three stop.

Therefore we see that the models present internal configuration through configuration parameters.

In this example, we see a value of 24 in the "num_keep" configuration parameter, which specifies the number of tokens to keep in memory during inference. A lower number of tokens means the model is faster and consumes fewer resources, but its quality is lower. A higher number of tokens means greater coherence, as it has more context to work with. This num_keep parameter depends heavily on the hardware capabilities and the type of task the model is performing.

The "stop" configuration parameter is used to identify specific text sequences that the model will immediately stop producing further output upon generating, thus avoiding generating unwanted or irrelevant content. You can specify keywords to stop when you reach that word, or specify keywords to prevent unwanted content due to sensitive topics.

A list of parameters for Ollama's models (not the AI ​​language management tool) is specified at https://ollama.readthedocs.io/en/modelfile/#valid-parameters-and-values .

These parameters can be modified within the running model with the command "set parameter", an example:

/set parameter num_keep 30

This change is temporary for the current model to run. This change is lost upon restart.

Parameters can be permanently changed via the Ollama API or in the model's Modelfile.

You can ask for the Modelfile of a model with the following command, example with "llama3:8b":

ollama show --modelfile llama3:8b

Which returns the following, where you can see the location of the Modelfile and the parameters on the lines that begin with "PARAMETER":

llm-04@ubuntu2504desktop-llm-04-ts04:~$ ollama show --modelfile llama3:8b
# Modelfile generated by "ollama show"
# To build a new Modelfile based on this, replace FROM with:
# FROM llama3:8b

FROM /usr/share/ollama/.ollama/models/blobs/sha256-6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa
TEMPLATE "{{ if .System }}<|start_header_id|>system<|end_header_id|>

{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>

{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>

{{ .Response }}<|eot_id|>"
PARAMETER num_keep 24
PARAMETER stop <|start_header_id|>
PARAMETER stop <|end_header_id|>
PARAMETER stop <|eot_id|>
LICENSE "META LLAMA 3 COMMUNITY LICENSE AGREEMENT

Meta Llama 3 Version Release Date: April 18, 2024
“Agreement” means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.

“Documentation” means the specifications, manuals and documentation accompanying Meta Llama 3 distributed by Meta at https://llama.meta.com/get-started/.

“Licensee” or “you” means you, or your employer or any other person or 
...
...
of Meta Llama 3: LlamaUseReport@meta.com
"

llm-04@ubuntu2504desktop-llm-04-ts04:~$ 

Ollama, as a model manager for artificial intelligence languages, allows you to create your own model from a Modelfile with the "ollama create" command, an aspect we will not go into in depth now.

The Ollama tool also has a REST API that is available locally at "http://localhost:11434", and we can verify its operation with a "curl" or in the browser for GET requests or using an API manager such as Postman or similar:

llm-04@ubuntu2504desktop-llm-04-ts04:~$ curl http://localhost:11434
Ollama is running
llm-04@ubuntu2504desktop-llm-04-ts04:~$ 

With this API you can, for example, consult the available models in a similar way to how the Ollama CLI does in the console with "ollama list" with a call to the REST API with the get method "/v1/models":

llm-04@ubuntu2504desktop-llm-04-ts04:~$ curl http://localhost:11434/v1/models | jq
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100   189  100   189    0     0  29329      0 --:--:-- --:--:-- --:--:-- 31500
{
  "object": "list",
  "data": [
    {
      "id": "llama3:instruct",
      "object": "model",
      "created": 1756027924,
      "owned_by": "library"
    },
    {
      "id": "llama3:8b",
      "object": "model",
      "created": 1756027280,
      "owned_by": "library"
    }
  ]
}
llm-04@ubuntu2504desktop-llm-04-ts04:~$ 

Just like you can see with the models, you can create a model with a REST API call using the POST /api/create method. You can perform the same Ollama functions with its REST API as with its console CLI.

curl http://localhost:11434/api/chat -d '{
  "model": "llama3:8b",
  "messages": [
    { "role": "user", "content": "Explain to me the concept of the Napierian logarithm" }
  ]
}'

Which gives the following response, as JSON:

llm-04@ubuntu2504desktop-llm-04-ts04:~$ curl http://localhost:11434/api/chat -d '{
  "model": "llama3:8b",
  "messages": [
    { "role": "user", "content": "Explain to me the concept of the Napierian logarithm" }
  ]
}'
{"model":"llama3:8b","created_at":"2025-09-19T14:38:36.319638065Z","message":{"role":"assistant","content":"A"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:38:36.648205025Z","message":{"role":"assistant","content":" fascinating"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:38:36.977830334Z","message":{"role":"assistant","content":" topic"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:38:37.319596095Z","message":{"role":"assistant","content":"!\n\n"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:38:37.691332083Z","message":{"role":"assistant","content":"The"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:38:38.038542472Z","message":{"role":"assistant","content":" Nap"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:38:38.374558726Z","message":{"role":"assistant","content":"ier"},"done":false}

...
...

{"model":"llama3:8b","created_at":"2025-09-19T14:42:51.954438674Z","message":{"role":"assistant","content":" and"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:42:52.367103924Z","message":{"role":"assistant","content":" mathematical"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:42:52.808416659Z","message":{"role":"assistant","content":" models"},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:42:53.274296402Z","message":{"role":"assistant","content":"."},"done":false}
{"model":"llama3:8b","created_at":"2025-09-19T14:42:53.678305521Z","message":{"role":"assistant","content":""},"done_reason":"stop","done":true,"total_duration":260023194239,"load_duration":271466683,"prompt_eval_count":23,"prompt_eval_duration":2388628695,"eval_count":563,"eval_duration":257362217533}
llm-04@ubuntu2504desktop-llm-04-ts04:~$ ollama list

With this, we have a basic understanding of how to manage and work with the different AI models available to us. In this tutorial, we'll go deeper into the different aspects.

NOTE: The author of this article also has it published at feitam.es.

So that git does not ask you on your computer for the username and passwords every time it is required, you can cache it for a while with:

git config --global credential.helper 'cache --timeout=86400'

or

git config --global credential.helper cache

In this command we are telling it to keep the passwords of the users in memory for 86400 seconds, which is 24 hours. If no timeout is specified, the default cache time is 15 minutes.

Once echoed on the first use of the user and password for a git server domain they will be persisted in memory for the specified time without prompting the system again.

To clear the credentials cache, you must execute:

git credential-cache exit

NOTE: The author of this article also has it published at feitam.es.

To get all the subdomains of a domain I use the following command based on the assetfinder tools and massdns, both available on github. It is required to have git and python installed.

With git you clone the two github tools as detailed in each tool (in the case of assetfinder you can download a compilation for your OS version, there is a version for Windows), and they are obtained by executing, for example, the following, it is an executed example on linux Kali:

┌──(kali㉿kali)-[~/tools/massdns]
└─$ assetfinder --subs-only feitam.es | massdns -r $HOME/tools/massdns/lists/resolvers.txt -o S -w results.txt
Concurrency: 10000
Processed queries: 23
Received packets: 15
Progress: 100.00% (00 h 00 min 02 sec / 00 h 00 min 02 sec)
Current incoming rate: 9 pps, average: 7 pps
Current success rate: 7 pps, average: 6 pps
Finished total: 13, success: 13 (100.00%)
Mismatched domains: 1 (6.67%), IDs: 0 (0.00%)
Failures: 0: 46.15%, 1: 38.46%, 2: 7.69%, 3: 7.69%, 4: 0.00%, 5: 0.00%, 6: 0.00%, 7: 0.00%, 8: 0.00%, 9: 0.00%, 10: 0.00%, 11: 0.00%, 12: 0.00%, 13: 0.00%, 14: 0.00%, 15: 0.00%, 16: 0.00%, 17: 0.00%, 18: 0.00%, 19: 0.00%, 20: 0.00%, 21: 0.00%, 22: 0.00%, 23: 0.00%, 24: 0.00%, 25: 0.00%, 26: 0.00%, 27: 0.00%, 28: 0.00%, 29: 0.00%, 30: 0.00%, 31: 0.00%, 32: 0.00%, 33: 0.00%, 34: 0.00%, 35: 0.00%, 36: 0.00%, 37: 0.00%, 38: 0.00%, 39: 0.00%, 40: 0.00%, 41: 0.00%, 42: 0.00%, 43: 0.00%, 44: 0.00%, 45: 0.00%, 46: 0.00%, 47: 0.00%, 48: 0.00%, 49: 0.00%, 50: 0.00%, 
Response: | Success:               | Total:
OK:       |            8 ( 61.54%) |            9 ( 60.00%)
NXDOMAIN: |            5 ( 38.46%) |            5 ( 33.33%)
SERVFAIL: |            0 (  0.00%) |            0 (  0.00%)
REFUSED:  |            0 (  0.00%) |            1 (  6.67%)
FORMERR:  |            0 (  0.00%) |            0 (  0.00%)
                                                                                                                               
┌──(kali㉿kali)-[~/tools/massdns]
└─$ cat results.txt | grep -v 127.0.0   
www.feitam.es. A 91.126.72.12
sftp.feitam.es. A 91.126.72.12
wiki.feitam.es. A 91.126.72.12
mail.feitam.es. A 91.126.72.12
feitam.es. A 91.126.72.12
                                                                                                                               
┌──(kali㉿kali)-[~/tools/massdns]
└─$ 

The links to the tools on github are:

NOTE: The author of this article also has it published at feitam.es.

If man sets his mind to it, he can accomplish great feats that mark his advancement as a civilization, and I believe this is a clear example, due to its sheer scale and its continued improvement over time.

In the 19th century, Chicago authorities decided to change the course of the Chicago River that flowed into Lake Michigan, for health reasons to avoid epidemics due to contamination of the source of drinking water for the city of Chicago, Lake Michigan.

In 1850, part of the flow began to be diverted to the Illinois and Michigan Canal to mitigate sanitary problems, and in 1990, Chicago sanitary officials decided to install floodgates at the mouth to prevent the water from flowing into Lake Michigan, and to completely reverse the flow to the new Chicago Sanitary and Ship Canal, which poured water into the Mississippi River basin, through the Des Plaines River and finally emptying into the Gulf of Mexico... what a change in the course of the water.

The following video from https://www.youtube.com/@wttw tells the story in detail:

Throughout the 20th century, the Chicago River's water quality has improved, but it was not until the last decade of the 20th century that the riverbed was clean and free of trash.

And in the cinema we have many movies available where you can see the Chicago River in all its current splendor, like in the movie "Bridesmaids." Here's the trailer:

182 kilometers from Madrid is one of the most charming medieval towns in Spain, a town fortunate for the water of two rivers: Duero and Duratón.

It is the ideal place to visit on a long weekend, and repeat since you will surely want to return.

It is always advisable to visit its tourist website https://www.turismopenafiel.es/ to see all the cultural, hiking, gastronomic and wine tourism options it offers. This website details the location and telephone number of the Tourist Office where the different tickets and schedules are purchased.

The essential things not to miss in Peñafiel:

• Peñafiel Castle, whose origin dates back to the 10th century plus all its evolution. It is home to the Valladolid Provincial Wine Museum.
• Plaza del Coso, declared of Cultural Interest in 1999. Inside it you enter the medieval atmosphere of the town.
• Ribera House Museum, this is a must-see. A spectacular theatrical representation of the life and customs of the people of Peñafiel at the beginning of the 20th century. Greetings to "Mariano and Tomasa". You will learn a lot.
• The Regional Museum of Sacred Art located in the Church of Santa María in the town's Plaza de España, where the visitor can see much of the religious-themed artistic heritage of both Peñafiel and the entire Region.

• Its banks, both of the Duero River and the Duratón River. I recommend starting on the wooden bridge near the Molino de Palacios grill along the Senda del Duratón route and reaching the mouth of the Duero, about 3 kilometers. You will see mills, magnificent wooden bridges and a spectacular riverside. And if you dare you can reach Pesquera del Duero.
• Its beaches, yes its beaches. I recommend Valdobar beach, where the town's San Roque hermitage and a beautiful stone bridge are located. Landscaped so that kids and not-so-kids can take a dip, have a snack or read a book quietly on the grass.
• The archaeological area of ​​Pintia, which was declared a Site of Cultural Interest in 1993, where you can see the history of the Vacceo-Roman and Visigoth settlers between the 4th centuries BC to the turn of the Era.
• Any of the local wineries to learn about the world of wine making and the history of the winery that is the origin of the Ribera del Duero designation of origin: Protos.

Walking through its streets is what is most enjoyed in Peñafiel. Its smells, its streets, its houses, its parks, the wineries dug into the side of the mountain of its castle, enter its bakeries and buy its breads and rolls, in its stores, and of course in its wine cellars buy its wines, and in its bars and restaurants stop to have a wine or a suckling lamb.

During festivals, like any town, the population is even more beautiful, especially during Holy Week and its patron saint festivals of Nuestra Señora and San Roque from August 14 to 18.

I leave here a video of the movie "Nothing ever happens" filmed by Juan Antonio Bardem in 1963 where you can see scenes of Peñafiel from its outskirts and the castle, where we can appreciate during the visit all the improvements that the castle has had:

Visit Peñafiel: it does not disappoint, and will force you to return.

Two film greats, Federico Fellini and Quentin Tarantino, have two spectacular scenes that many moviegoers see as reasonable similarities.

Let's look at the spectacular twist scene in Tarantino's Pulp Fiction:

and the dance scene in 'Otto e mezzo' also known as 'Fellini ocho y medio' is not far behind:

According to Tarantino it is not a reasonable resemblance on purpose nor is it inspired by 'Otto e mezzo' since he had never seen Fellini's film before 'Pulp Fiction'.

They're two great movies, with two great dance scenes. In Fellini's the protagonists give off more heat, and in Tarantino's they give off the coldness between both dancers in the context of the film's story.

This trick is certified by my mother with my clothes when I was a kid, which I remember a few times.

Only required:

• Vinegar of any kind: wine, apple, etc. Of course, white vinegar, without color so as not to leave stain on clothes.
• A glass
• A microwave
• A toothbrush or similar
• 5 minutes

Heat the vinegar a little in the microwave, without boiling.

And then pour the vinegar into the gum stain on the clothes with the toothbrush and always scratch in the same direction until it disappears from the clothes.

In order not to have to use this trick, you don't need to swallow the gum...

... you can leave it in its packaging in a trash can. If you have time.

According to the Salvat Universal Encyclopedia:

• Tornado: atmospheric whirlpool of small horizontal extension and great intensity that extends towards the earth's surface from a storm cloud. True column of rising air, they usually cause great havoc. It is due to the contact of warm, moist air with cold air of high levels.
• Cyclone: atmospheric disturbance that originates above warm seas, and in which winds revolve around a center of low pressure at speeds exceeding 120 km / h.
• Hurricane: dynamic weather system that originates in tropical regions, characterized mainly by the rotation of air around a center of very low pressure, at speeds of the order of 150 km / h.
• Typhoon: tropical cyclone, frequent in the China Sea. It devastates the coastal regions of southern China and the Philippines. It is characterized by very strong winds and torrential rains.

Therefore, hurricane and typhoon is the same as cyclone since they are generated in the sea with great winds in a great amplitude, generically hundreds of kilometers, of space by rotations in the hands of the clock in the southern hemisphere, and in the opposite direction in the northern hemisphere, and according to their area of origin on earth they receive one denomination or another:

• Southwest Indian Ocean: Tropical Cyclone
• Southwest Pacific Ocean: Tropical Cyclone
• Remaining Indian Ocean (non-southwest): Typhoon-
• Western Pacific Ocean: Typhoon
• Arabian Sea: Typhoon
• North Atlantic Ocean: Hurricane
• North Pacific Ocean, East Zone: Hurricane
• Central Pacific Ocean, Gulf of Mexico: Hurricane
• Caribbean Sea: hurricane

The tornado is another meteorological phenomenon other than cyclones, hurricanes and typhoons. Since its origin is on land, not in the sea. Its amplitude is much smaller, usually a few meters. The winds of both are comparable, but in the case of tornadoes they are absorbent winds, as shown in many films where the tornado "swallows" everything it finds on the ground... returning it to gravity.

Tornadoes unlike cyclones are difficult to predict.

A variant of tornadoes are the sleeves or waterspouts that form over the sea, rather than over land.

Below is a scene from the 1996 film Twister, where you can see very well what a tornado is:

They all cause a lot of destruction, and the only defense today is to predict them as soon as possible and in the most reliable way.

... Spain, specifically in Madrid. And its name is Casa Botín. This merit is confirmed by the Guinness Book of Records.

Its location is behind the Plaza Mayor, in the typical Madrid street of Cuchilleros belonging to Madrid of the Austrias.

Its origin dates back to 1725, when the French chef Jean Botín created the restaurant, and the current restaurant's wood-fired oven is from that year.

The restaurant has three floors, with dining rooms on the lower floor in typical Spanish caves like many restaurants, its origin being the old cellars previously used as warehouses. It also has a dining room on the entrance floor with the decoration of the 19th century reform with polychrome wood friezes in gold leaf, as well as the window and counter of the time. Eating there both for the restaurant and for its cuisine takes you back 200 years, and it is a balm for the heart.

It is the typical Castilian cuisine restaurant with main products such as roast lamb and suckling pig made in its old wood oven.

An anecdote that certifies the Guinness Book of Records: the famous painter Francisco de Goya worked as a teenager in the restaurant in 1765.

This is its website, where you can check its schedules, menu, prices and information to reserve:

Hallacas is a typical Venezuelan recipe that is usually taken at Christmas... but that can be taken at any time of the year.

It is spectacular, has very little fat, very nutritious because it has a high number of foods, it is easy to preserve when it can be frozen, and it is easy to take by only requiring boiling the hallacas before eating them warm.

Being a stew with many foods it is really laborious to make, and in certain areas there may be problems to find some of its components such as banana leaves, achiote seeds or sweet chili; but all these foods can be purchased through the internet or replaced by similar foods from the area. Like any recipe in each area or area is made with different variations in the foods that compose it and the elaboration: I think you have to dare to try different changes. In the end, each family usually has its own recipe. This is the recipe of grandma Ignacia, from Valencia, in Venezuela.

It is a stew to make with family or friends, for example on a weekend since it takes a couple of days without many to do. With many collaborating it becomes faster and more fun... the same when eating it all together, as at Christmas.

Once done there are two options: eat or freeze.

The frozen ones are healthy "fast food" that with 10 minutes of cooking in water are prepared: in less time than in what they bring you some pizas or hamburgers ... I'm sure you like them.

The 8 vitamins of vitamin group B are essential for the correct conversion of food into energy for the body and are catalysts for a wide number of biochemical processes in our body, which help to:

• Healthy skin, helping proper wound healing
• Strong hair
• Regulation of the nervous system, helping processes of anxiety, stress and depression, and even in cases of back pain because it is essential for the spinal cord, as well as for the brain
• Improvement of blood cholesterol levels, especially vitamin B12, lowering the risk of stroke, and avoiding high blood pressure.
• Decreased frequency of migraines according to some studies, especially B6, B9 and B12.

Group B vitamins are found in the following foods:

• Vitamin B1 or thiamine: whole grains, legumes, nuts, seeds, trout, tuna, eggs, meat
• Vitamin B2 or riboflavin: dairy, yeast, meat, cereals, legumes, green leafy vegetables
• Vitamin B3 or niacin: dairy, eggs, fish, nuts, rice, legumes
• Vitamin B5 or pantothenic acid: broccoli, liver, kidneys, eggs
• Vitamin B6 or pyridoxine: poultry, fish, bananas, chickpeas, potatoes, avocado
• Vitamin B7 or biotin: nuts, peanuts, dairy, eggs, cauliflower, sardines
• Vitamin B9 or folic acid: green leafy vegetables, legumes, citrus
• Vitamin B12 or combalamin: salmon, meat, liver, seafood, eggs, dairy

If you are a smoker or a regular drinker of alcohol, the body assimilates it with greater difficulty, so you must bear in mind that you need more foods with vitamin B to have acceptable levels.

The usual recommendation: variable and balanced diet, in not excessive amounts will allow you to consume the recommended amounts.

You can always take a vitamin supplement but it won't be as tasty and fun as a food.

And you must bear in mind that the consumption of any vitamin supplement should be consulted with a doctor to certify that it has no possible side effects. And doctors know a lot just by looking at us:

The side effects of an excessive intake of B vitamins are:

• Diarrhea
• Increased menstrual bleeding
• Vomiting
• Liver problems
• Low blood pressure
• Fatigue
• Headache
• Raise blood sugar levels: especially dangerous in people with diabetes or high blood sugar levels
• Bright yellow urine

There is a queen, betrayed by those closest to her, and surely very badly treated by history, who is also one of the women ... and queen, who has spawned more kings and queens.

This woman was the first queen of Spain: Juana "la Loca".

Already the "nickname" that the story has assigned it tells us a little about how the story treats it. Possibly she was not as crazy as has been said, and it greatly influenced that her husband and King Philip the Fair was very given to multiple extramarital love affairs in a repetitive way. She really was a woman, betrayed by almost everyone around her, without saving her father, husband and even her children.

Juana "la Loca" was queen heir of Castilla, Aragon, Navarra, Valencia, Mallorca, Naples, Sicily, Sardinia and, Countess of Barcelona and titular Duchess consort of Burgundy, uniting the crowns that made up Spain, as of January 25, 1516, thus becoming the first queen of Spain together with her son Carlos I.

His offspring were:

• Leonor: queen consort of Portugal being the wife of Manuel I of Portugal, and on his death she was queen consort of France when she married Francisco I of France
• Carlos: King of Spain with the name Carlos I and Holy Roman Emperor with the name Carlos V
• Isabel: queen consort of Denmark being wife of Christian II
• Fernando: Holy Roman Emperor with the name of Fernando I as successor to Carlos V once it is decided to divide the empire
• María: Queen of Hungary as wife of Luis II
• Catalina: Queen of Portugal as wife of Juan III

Obviously, he had many heirs on thrones, as it was one of the times when more tradition of political marriages existed. Coupled with the fact of being one of the main protagonists of one of the most powerful courts at that time, which facilitated all this marriage "management". But I don't think he could have been more successful when it comes to the power marriages of his offspring.

Winston Churchil is for me one of the characters in history that I admire the most, my first contact with all "his work" was reading the biography of Winston Churchil by Roy Jenkins. I recommend reading it.

Like every man he has positive actions for the social common, and others of dubious general benefit, but with a clear predominance of the positive. I believe he was a very bold and determined man to follow a certain path in the first half of the bellicose twentieth century, when other leaders were very hesitant at crucial moments for a more human future.

I will not tell here their successes and failures, which are detailed in multiple books and web pages. But it has always struck me that a man with his responsibilities to relax, still working with his secretary, will dedicate himself to masonry work, especially to make constructions with bricks: he put bricks and at the same time dictated to his secretary. Impressive. I can't imagine any great leader of a nation today laying bricks.

I think it indicates a lot his character: always active, even to relax, and followed his criteria not the canons ... at least in terms of how to relax.

Search online for "Churchill bricks" and you will find multiple photos with the palette with cement... and smoking a cigar, laying bricks.