Running LLMs Locally with Ollama

alexshank@alex-desktop:~/Desktop/main/repos/blog-astro$ curl -fsSL https://ollama.com/install.sh | sh
>>> Installing ollama to /usr/local
[sudo] password for alexshank:
>>> Downloading Linux amd64 bundle
######################################################################## 100.0%
>>> Creating ollama user...
>>> Adding ollama user to render group...
>>> Adding ollama user to video group...
>>> Adding current user to ollama group...
>>> Creating ollama systemd service...
>>> Enabling and starting ollama service...
Created symlink /etc/systemd/system/default.target.wants/ollama.service → /etc/systemd/system/ollama.service.
>>> NVIDIA GPU installed.
alexshank@alex-desktop:~/Desktop/main/repos/blog-astro$ ollama run mistral-small3.1
pulling manifest
pulling 1fa8532d986d... 100% ▕████████████████████████████████▏  15 GB
pulling 6db27cd4e277... 100% ▕████████████████████████████████▏  695 B
pulling 70a4dab5e1d1... 100% ▕████████████████████████████████▏ 1.5 KB
pulling a00920c28dfd... 100% ▕████████████████████████████████▏   17 B
pulling 9b6ac0d4e97e... 100% ▕████████████████████████████████▏  494 B
verifying sha256 digest
writing manifest
success
>>> hello
Hello! How can I assist you today?

> > > What's the capital of italy?
> > > The capital of Italy is Rome.

>>> hello
Hello! How can I assist you today?

>>> What's the capital of italy?
The capital of Italy is Rome.

>>> how do you make a for loop in python?
In Python, a `for` loop is used to iterate over a sequence (such as a list, tuple,
dictionary, set, or string). Here is the basic syntax for a `for` loop:

```python
for item in sequence:
    # Code block to be executed for each item in the sequence
```

Here are a few examples to illustrate how to use a `for` loop in different contexts:

### Iterating over a list:

```python
fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
    print(fruit)
```

### Iterating over a range of numbers:

```python
for i in range(5):
    print(i)
```

### Iterating over a string:

```python
for char in "hello":
    print(char)
```

### Iterating over a dictionary:

```python
person = {"name": "Alice", "age": 30, "city": "New York"}
for key, value in person.items():
    print(f"{key}: {value}")
```

### Using `enumerate` to get both index and value:

```python
fruits = ["apple", "banana", "cherry"]
for index, fruit in enumerate(fruits):
    print(f"Index {index}: {fruit}")
```

### Using `zip` to iterate over multiple sequences:

```python
list1 = [1, 2, 3]
list2 = ['a', 'b', 'c']
for item1, item2 in zip(list1, list2):
    print(item1, item2)
```

>>> What's your favorite vim trick?
I don't have personal favorites or preferences, but I can certainly share a popular and
useful Vim trick that many users find helpful!

One of the most powerful features of Vim is the ability to perform complex text
manipulations using macros. Macros allow you to record a series of keystrokes and then
play them back to automate repetitive tasks.

Here's how you can record and use a macro in Vim:

1. **Start recording a macro**:
   - Press `q` followed by a register name (e.g., `a`, `b`, `c`, etc.). For example, to
start recording into register `a`, press `qa`.

2. **Perform the actions you want to record**:
   - Perform the series of keystrokes or commands you want to automate.

3. **Stop recording**:
   - Press `q` again to stop recording.

4. **Play back the macro**:
   - To play back the macro, press `@` followed by the register name. For example, to play
back the macro recorded in register `a`, press `@a`.
   - To play back the macro multiple times, you can use a count prefix. For example, to
play back the macro recorded in register `a` ten times, press `10@a`.

### Example
Suppose you want to automate the process of commenting out a series of lines. You can
record a macro to do this:

1. Start recording into register `a` by pressing `qa`.
2. Move to the beginning of the line you want to comment out by pressing `I`.
3. Insert the comment character (e.g., `#` for shell scripts or `//` for C-like languages)
and press `Esc`.
4. Move to the next line by pressing `j`.
5. Stop recording by pressing `q`.

Now, you can play back the macro to comment out multiple lines by pressing `@a` for each
line or `10@a` to comment out ten lines.

This is just one of many powerful features in Vim that can greatly enhance your
productivity once you get the hang of it!

>>> What is the MCP protocol for LLMs?
As of my last update in October 2023, there isn't a widely recognized or standardized protocol specifically named "MCP" for Large
Language Models (LLMs). It's possible that "MCP" could refer to a specific internal protocol, framework, or concept within a
particular organization or research context that hasn't gained widespread recognition or documentation.

If you're referring to a specific protocol, framework, or concept related to LLMs, could you provide more context or clarify what you
mean by "MCP protocol"? This will help me give you a more accurate and helpful response.

Alternatively, if you're interested in general protocols or frameworks related to LLMs, here are a few notable ones:

1. **API Protocols**: Many LLMs are accessed via APIs (Application Programming Interfaces) provided by companies like OpenAI, Google,
and others. These APIs typically use RESTful protocols over HTTP/HTTPS.

2. **Model Serving Frameworks**: Frameworks like TensorFlow Serving, TorchServe, and ONNX Runtime are used to deploy and serve
machine learning models, including LLMs, in production environments.

3. **Communication Protocols**: For distributed training and inference of LLMs, protocols like gRPC (Google Remote Procedure Call)
are often used to facilitate communication between different components of a system.

4. **Data Formats**: Common data formats for interacting with LLMs include JSON (JavaScript Object Notation) for API requests and
responses, and protocols like Protocol Buffers (protobuf) for efficient serialization of structured data.

If you provide more details or clarify your question, I can offer more targeted information!