#python#agents#gcp#gemini#genai_agents#generative_ai#llmops#mlops#observability
You can quickly create and deploy AI agents using the Agent Starter Pack, a Python package with ready-made templates and full infrastructure on Google Cloud. It handles everything except your agent’s logic, including deployment, monitoring, security, and CI/CD pipelines. You can start a project in just one minute, customize agents for tasks like document search or real-time chat, and extend them as needed. This saves you time and effort by providing production-ready tools and integration with Google Cloud services, letting you focus on building smart AI agents without worrying about backend setup or deployment details.
https://github.com/GoogleCloudPlatform/agent-starter-pack
#python#dictionary_attack#password#password_strength#weak_passwords#wordlist#wordlist_generator
**CUPP** is a free Python 3 tool that creates custom password wordlists from personal details like names, birthdays, pet names, or nicknames, using interactive questions or existing dictionaries. Run it with options like `-i` for profiling or `-l` to download huge wordlists. This helps you in legal penetration tests or investigations by generating targeted lists for efficient brute-force or dictionary attacks, cracking weak passwords faster than generic ones.
https://github.com/Mebus/cupp
#python#deep_learning#inference#openai#quantization#speech_recognition#speech_to_text#transformer#whisper
Faster-Whisper is a fast version of OpenAI's Whisper that transcribes audio up to 4x quicker with the same accuracy, using less memory on CPU or GPU—benchmarks show it beats original Whisper (e.g., 1m03s vs 2m23s for 13-min audio on GPU). Install via `pip install faster-whisper`, no FFmpeg needed, and use simple Python code like `WhisperModel("large-v3").transcribe("audio.mp3")` for segments with timestamps. You benefit by getting quick, efficient speech-to-text for real-time apps, saving time and resources on long files or batches.
https://github.com/SYSTRAN/faster-whisper
#python#agent#chatbot#large_language_models#llm#llm_agent#mcp#multi_agent#multi_modal#react_agent
AgentScope is a simple, production-ready framework to build AI agents fast. Install with `pip install agentscope` (Python 3.10+), then create ReAct agents with tools, memory, voice, human steering, multi-agent workflows, and finetuning in 5 minutes. It supports realtime voice, A2A protocols, RL training, and easy deployment locally, in cloud, or Kubernetes. You benefit by quickly making robust, scalable agents for tasks like games, research, or chats without complex coding, saving time and enabling real-world apps.
https://github.com/agentscope-ai/agentscope
https://docs.python.org/3/library/gettext.html
The #gettext module provides internationalization (#I18N) and localization (#L10N) services for your #Python modules and applications. It supports both the #GNU gettext message catalog #API and a higher level, class-based API that may be more appropriate for Python files. The interface described below allows you to write your module and application messages in one natural #language, and provide a catalog of #translated messages for running under different natural languages.
Some hints on localizing your Python modules and applications are also given.
#python#agents#ai#ai_ux#autogen#browser_use#computer_use_agent#cua#ui
Magentic-UI is a tool that helps you automate complex web tasks by working together with you. It lets you plan step-by-step actions, watch the progress, and approve sensitive steps to keep control and safety. You can interact with it through a browser, upload files, and even run multiple tasks at once. It learns from past tasks to improve future automation. This means you save time on repetitive or complicated web activities while staying in control, making your work easier and more efficient. It supports Python 3.10+ and works best with Docker or WSL2 on Windows.
https://github.com/microsoft/magentic-ui
#typescript#agent#agent_development#ai_agent#claude#claude_code#educational#llm#python#teaching#tutorial
Claude Code is an AI agent framework that uses a simple loop: send messages to Claude, check if it needs tools, execute those tools, and repeat. The benefit is that you can build powerful autonomous agents by layering one feature at a time—from basic tool use to multi-agent teams—without rewriting the core loop. This modular approach lets you start simple with bash commands and scale to complex workflows with planning, skill loading, background tasks, and team coordination, making it easier to automate development work and delegate entire projects to AI agents.
https://github.com/shareAI-lab/learn-claude-code
#python#okww#wuthering_waves#wuthering_waves_hack#wuthering_waves_software#wutheringwaves#wuwa
This tool helps automate gameplay in "Wuthering Waves" by simulating user clicks on Windows. It doesn't read or modify game data, keeping the game fair. The tool is free, open-source, and designed for personal use only. It supports various screen resolutions and can run in the background. Users can download it from GitHub or other platforms. The benefit is that it simplifies gameplay interactions without cheating, making it easier for players to manage their game time.
https://github.com/ok-oldking/ok-wuthering-waves
#typescript#agents#agi#ai#api#backend#developer_tools#framework#genai#javascript#python#ruby
Motia is a modern backend framework that helps simplify complex systems by combining APIs, background jobs, events, and AI agents into one unified system. It allows developers to write code in multiple languages like JavaScript, TypeScript, and Python, all within the same project. This makes it easier to manage and deploy applications, reducing complexity and errors. With Motia, you get built-in observability and one-click deployments, making it easier to monitor and debug your workflows. This means you can focus on your business logic without worrying about the underlying infrastructure.
https://github.com/MotiaDev/motia
#python#agent#llm#llm_agent#llm_reasoning#machine_learning_systems#mlsys#reinforcement_learning#rl
AReaL is a free, open-source system for fast asynchronous reinforcement learning to train large AI models in math, coding, search, and agents. It decouples generation and training for up to 2.77x speedup, stable performance, and easy setup on single or 1000+ GPUs with algorithms like GRPO/PPO. Install via git/pip, run examples like GSM8K math instantly. You benefit by building top AI agents affordably and quickly, reproducing results with shared data/models, saving time/money vs. slow synchronous tools.
https://github.com/inclusionAI/AReaL
http://www.kdnuggets.com/2017/09/essential-data-science-machine-learning-deep-learning-cheat-sheets.html
#Cheat_Sheet, #Data_Science, #Deep_Learning, #Machine_Learning, #Neural_Networks, #Probability, #Python, R, #SQL, #Statistics
This collection of data science cheat sheets is not a cheat sheet dump, but a curated list of reference materials spanning a number of disciplines and tools
#python#agent#ai#ai_coding#claude#claude_code#language_server#llms#mcp_server#programming#vibe_coding
Serena is a free, open-source toolkit that turns large language models (LLMs) into powerful coding agents able to work directly on your codebase with IDE-like precision. It uses semantic code analysis to understand code structure and symbols, enabling efficient code search and editing without reading entire files. Serena supports many programming languages and integrates flexibly with various LLMs and development environments via the Model Context Protocol (MCP). This means you can automate complex coding tasks, improve productivity, and reduce costs without subscriptions, making your coding workflow faster and smarter.
https://github.com/oraios/serena