semvec/pypi-packages huggingface dataset:
curso-fiap-package-santerio 1.0.0
curso-fiap-hello-word
License: MIT

# Curso-fiap
        
        A simple example library.
        
        ## Installation
        
        ```sh
        pip install curso-fiap
        ```
        
        ## Usage
        
        ```python
        from curso-fiap import hello_world
        
        print(hello_world())
        ```
cli_lm 0.1.4
A CLI tool for prompting an LLM
License: MIT
Requires Python: >=3.12

# cli_lm

Switch context less by using a really cheap LLM at the command line.

## Installation

```bash
# Install from source
git clone https://github.com/davenpi/cli_lm.git
cd cli_lm
pip install -e .

# Install from PyPI
pip install cli-lm
```

## Quick Start
The first run will prompt for your
<a href="https://platform.openai.com/docs/overview" target="_blank">Open AI API key</a>.
Just paste the key in. Or create the key directly in `~/.cli_lm/.env` with

```shell
echo "OPENAI_API_KEY=your_new_key" > ~/.cli_lm/.env
```

**Note** you'll have to pay Open AI to get an API key and start using their models.
For now this package sets `gpt-4o-mini` as the model of choice. It costs 0.15¢/0.60¢
per 1 million input/output tokens. 1 token ~ 1 word.

```shell
# Directly ask a question
clm "How do I amend a commit in git?"

# Interactive mode (input in python interpreter)
clm
> How do I list the processes listening on a given port?
```

Chat is assumed to be multiturn (i.e., you'll always be asked for your next prompt).
Just hit `Ctrl+c` or `Ctrl+d` to exit.

## Configuration
The package looks for your Open AI API key in `~/.cli_lm/.env`.

To quickly update your API key run:
```shell
echo "OPENAI_API_KEY=your_new_key" > ~/.cli_lm/.env
```

It works on a Mac, but it hasn't been tested on another system.

## Ongoing Improvements

- [x] Multi turn chat capability
- [ ] Improved multiline input
- [ ] Would be nice to arrow backward on input
- [ ] System prompting for really concise, helpful answers
- [ ] Make set up easier
- [ ] Add token/cost accounting
- [ ] Make it faster (imports can be slow)
- [ ] Add color

## License
MIT
mcp-read-pdf 0.1.1
PDF reader extension for MCP that can work with large PDFs and password protected.
License: MIT
Requires Python: >=3.12

# mcp-unlock-pdf

MCP server to give client the ability read protected (or un-unprotected) PDF
Works with large PDFs by extracting text to temp file.

Forked from the excellent upstream project https://github.com/algonacci/mcp-unlock-pdf

Published to pypi.

# Usage

```sh
uvx mcp-read-pdf
```

Will run from pypi. This can be used in `goose` or `claude`.

# Test

```sh
uv run python main.py --test
```

# Usage from source

## Running from cli (Goose, or to try it)

```sh
uv --directory /Users/micn/Documents/code/extractorb-py/mcp-unlock-pdf run python main.py
```

### Building and Publishing

1. Update version in `pyproject.toml`:

```toml
[project]
version = "x.y.z"  # Update this
```

2. Build the package:

```bash
# Clean previous builds
rm -rf dist/*


# Or build in a clean environment using uv
uv venv .venv
source .venv/bin/activate
uv pip install build
python -m build
```

3. Publish to PyPI:

```bash
# Install twine if needed
uv pip install twine

# Upload to PyPI
python -m twine upload dist/*
```