Docling is a powerful open-source library for document processing, supporting diverse formats and advanced PDF understanding, with seamless integrations with the gen AI ecosystem.
Powering the future of open-source AI agent development. Discover, run, and compose AI agents from any framework. Build production-grade AI agents in both Python and Typescript. Join our community on Discord, BlueSky, and YouTube.
This document details how to use function calling with Mistral AI models to connect to external tools and build more complex applications, outlining a four-step process: User query & tool specification, Model argument generation, User function execution, and Model final answer generation.
The project involves a software-defined GPS receiver using the legacy C/A code to produce clock bias and location estimates. It can run from pre-recorded sample files or an RTL-SDR with a web-based dashboard for visualization. The project is written in Python, utilizing libraries like aiohttp, NumPy, Pydantic, and pyrtlsdr.
The article describes a project where someone developed a software-defined GPS receiver from scratch using Python and an RTL-SDR dongle. The project tackles the 'coarse' positioning capability of GPS, achieving location resolution within 24 seconds from a cold start. The article highlights the project's accessibility and potential as a starting point for further exploration of GPS technology.
Browser Use is a library that enables AI agents to interact with web browsers, making websites accessible for automated tasks. It includes features for browser automation, agent memory, and various demos showcasing its capabilities.
A flexible Python library and CLI tool for interacting with Model Context Protocol (MCP) servers using OpenAI, Anthropic, and Ollama models.
This library provides a command-line interface (CLI) for managing the user settings of Meshtastic nodes and provides an easy API for sending and receiving messages over mesh radios.
Learn how to manage virtual environments in Python to avoid dependency conflicts and ensure smooth project management.
| Command | Description | Example |
|-------------------------------------|-|-------------------------------------------|
| `python -m venv ` | Creates a virtual environment. | `python -m venv venv` |
| `source venv/bin/activate` | Activates the virtual environment. | `source venv/bin/activate` |
| `deactivate` | Deactivates the virtual environment. | `deactivate` |
| `pip install ` | Installs a library. | `pip install pandas` |
| `pip install ==` | Installs a specific version of a library. | `pip install pandas==2.1.4` |
| `pip show ` | Shows information about an installed library. | `pip show pandas` |
| `pip uninstall ` | Uninstalls a library. | `pip uninstall pandas` |
| `pip freeze` | Lists all installed libraries and their versions. | `pip freeze` |
| `pip freeze > requirements.txt` | Saves the list of installed libraries to a requirements.txt file. | `pip freeze > requirements.txt` |
| `pip install -r requirements.txt` | Installs all libraries listed in a requirements.txt file. | `pip install -r requirements.txt` |
| Command | Description | Example |
|-------------------------------------|-|-------------------------------------------|
| `python -m venv ` | Creates a virtual environment. | `python -m venv venv` |
| `source venv/bin/activate` | Activates the virtual environment. | `source venv/bin/activate` |
| `deactivate` | Deactivates the virtual environment. | `deactivate` |
| `pip install ` | Installs a library. | `pip install pandas` |
| `pip install ==` | Installs a specific version of a library. | `pip install pandas==2.1.4` |
| `pip show ` | Shows information about an installed library. | `pip show pandas` |
| `pip uninstall ` | Uninstalls a library. | `pip uninstall pandas` |
| `pip freeze` | Lists all installed libraries and their versions. | `pip freeze` |
| `pip freeze > requirements.txt` | Saves the list of installed libraries to a requirements.txt file. | `pip freeze > requirements.txt` |
| `pip install -r requirements.txt` | Installs all libraries listed in a requirements.txt file. | `pip install -r requirements.txt` |
A terminal-based platform to experiment with the AI Software Engineer. It allows users to specify software in natural language, watch as an AI writes and executes the code, and implement improvements. Supports various models and customization options.
