#python #agent #llm #rag #tutorial

You can learn to build smart AI agents from scratch with a free, open-source tutorial called Hello-Agents by Datawhale. It covers everything from basic concepts and history to hands-on projects like creating your own AI agent framework and multi-agent systems. The course includes practical skills such as memory, context handling, communication protocols, and training large language models. By following it, you gain deep understanding and real coding experience, moving from just using AI models to designing intelligent systems yourself. This helps you develop advanced AI skills useful for jobs, research, or building innovative AI applications. The materials are online and easy to access anytime.

https://github.com/datawhalechina/hello-agents

#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 #datascience #formula1 #motorsport

FastF1 is a Python package that lets you easily access and analyze Formula 1 data like results, schedules, timing, telemetry, and more. It uses Pandas DataFrames with custom F1 tools, Matplotlib for charts, and caching for fast scripts—install via pip install fastf1. You benefit by quickly pulling historical and live F1 stats to build insights, visualizations, or apps without hassle.

https://github.com/theOehrly/Fast-F1

#python #help_wanted #looking_for_contributors

This M3U playlist gives you a single, regularly updated file of free, legal TV channels worldwide (grouped by country and marked for HD, geo-blocking, or YouTube live) so you can add it to an IPTV player and watch many working streams without hunting links; it focuses on quality (only free, mainstream channels, one URL per channel) and lets you contribute fixes or channel changes via GitHub pull requests, which helps you get reliable channels and keeps the list current for smoother viewing.

https://github.com/Free-TV/IPTV

#python #gym #gym_environment #reinforcement_learning #reinforcement_learning_agent #reinforcement_learning_environments #rl_environment #rl_training

NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior.

https://github.com/NVIDIA-NeMo/Gym

#python

**ty** is a super-fast Python type checker and language server built in Rust by Astral (makers of uv and Ruff). It's 10-100x faster than mypy or Pyright, with rich error messages, IDE features like auto-complete and hover help, and support for big projects or partial typing. Try it via `uvx ty check`. This helps you catch bugs early, code faster with real-time feedback, and boost productivity in editors like VS Code.

https://github.com/astral-sh/ty

#rich_text_format #lcd_display #python #serial_communication #smart_display #smart_screen #system_monitor #system_monitoring #turing_smart_screen #xuanfang

**turing-smart-screen-python** is free open-source Python software (3.9+) for small USB-C IPS smart screens like Turing 3.5"/5", XuanFang, and others on Windows, Linux, Raspberry Pi, or macOS. Use it as a standalone system monitor showing CPU/GPU usage, temps, memory, and custom data via easy themes (with editor and community shares), or integrate into your Python projects to display text, images, progress bars, brightness, rotation, and RGB LEDs. It auto-detects ports with a simple GUI wizard—no coding needed. You benefit by turning your screen into a customizable HW dashboard or app display affordably, cross-platform, without vendor limits.

https://github.com/mathoudebine/turing-smart-screen-python

#python #large_language_models #llm #penetration_testing #python

PentestGPT is a free, open-source AI tool that automates penetration testing like solving CTF challenges in web, crypto, and more. Install easily with Docker, add your API key (Anthropic, OpenAI, or local LLMs), then run pentestgpt --target [IP] for interactive guidance on scans, exploits, and reports. New v1.0 adds autonomous agents and session saving. It boosts your speed and accuracy in ethical hacking, helping beginners learn steps fast and pros tackle complex targets efficiently.

https://github.com/GreyDGL/PentestGPT

#python

Mini-SGLang is a compact, easy-to-read inference framework (~5,000 Python lines) that runs and serves large language models with high speed using optimizations like radix cache, chunked prefill, overlap scheduling, tensor parallelism, and FlashAttention/FlashInfer kernels. It’s CUDA-dependent, quick to install from source, and can launch an OpenAI-compatible API or interactive shell for single- or multi‑GPU serving, letting you test or deploy models (e.g., Qwen, Llama) with low latency and scalable throughput. Benefit: you get a transparent, modifiable engine to deploy fast, efficient LLM inference for development, benchmarking, or production use.

https://github.com/sgl-project/mini-sglang

#python #ai #bug_detection #code_audit #code_quality #code_review #developer_tools #devsecops #google_gemini #llm #react #sast #security_scanner #supabase #typescript #vite #vulnerability_scanner #xai

**DeepAudit** is an AI-powered code audit tool using multi-agent collaboration to deeply scan projects for vulnerabilities like SQL injection, XSS, and path traversal. Import code from GitHub/GitLab or paste snippets; agents plan, analyze with RAG knowledge, and verify issues via secure Docker sandbox PoCs, generating PDF reports with fix suggestions. Deploy easily with one Docker command, supports local Ollama models for privacy, and cuts traditional tools' high false positives. **You benefit** by automating secure audits like a pro hacker—saving time, reducing errors, ensuring real exploits are caught, and speeding safe releases without manual hassle.

https://github.com/lintsinghua/DeepAudit

#rust #ai #change_data_capture #context_engineering #data #data_engineering #data_indexing #data_infrastructure #data_processing #etl #hacktoberfest #help_wanted #indexing #knowledge_graph #llm #pipeline #python #rag #real_time #rust #semantic_search

**CocoIndex** is a fast, open-source Python tool (Rust core) for transforming data into AI formats like vector indexes or knowledge graphs. Define simple data flows in ~100 lines of code using plug-and-play blocks for sources, embeddings, and targets—install via `pip install cocoindex`, add Postgres, and run. It auto-syncs fresh data with minimal recompute on changes, tracking lineage. **You save time building scalable RAG/semantic search pipelines effortlessly, avoiding complex ETL and stale data issues for production-ready AI apps.**

https://github.com/cocoindex-io/cocoindex

#python

**Reachy Mini** is an open-source desktop robot, 11 inches tall and 3.3 lbs, with a 6-DoF expressive head, 360° body rotation, animated antennas, wide-angle camera, microphones, speaker, and Hugging Face AI integration for 1.7M+ models. Assemble in 2-3 hours as a kit; choose Lite (USB-powered) or Wireless (Raspberry Pi, battery). Use simple Python SDK for quick control, apps like conversation or hand-tracking, and simulation. **You benefit** by easily building, testing, and sharing AI robots at home or work, speeding up embodied AI experiments affordably.

https://github.com/pollen-robotics/reachy_mini

#python #cv #cv_builder #cv_generator #cv_template #python #resume #resume_builder #resume_generator #resume_template #typst

RenderCV lets you write your CV as simple YAML text, then run one command like rendercv render yourfile.yaml to get a perfect PDF with pro typography—no layout fights or formatting hassle. Version-control it easily, focus purely on content, customize themes/colors/fonts, validate strictly, and use any language. You save time, get pixel-perfect resumes every time, and maintain versions without chaos.

https://github.com/rendercv/rendercv

#python #gemini #gemini_ai #gemini_api #gemini_flash #gemini_pro #information_extration #large_language_models #llm #nlp #python #structured_data

**LangExtract** is a free Python library that uses AI models like Gemini to pull structured data—like names, emotions, or meds—from messy text such as reports or books. It links every fact to its exact spot in the original, creates interactive visuals for easy checks, handles huge files fast with chunking and parallel runs, and works with cloud or local models without fine-tuning. You benefit by quickly turning unstructured docs into reliable, organized data for analysis, saving time and boosting accuracy in fields like healthcare or research.

https://github.com/google/langextract

#python

This repository offers Anthropic's Claude Skills—folders with instructions, scripts, and resources that dynamically teach Claude specialized tasks like branded documents, data analysis, or workflows. Examples cover creative, technical, and enterprise uses; install via Claude Code, .ai, or API, or create your own with a simple SKILL.md template. You benefit by automating repetitive work, boosting productivity, ensuring consistent results, and capturing your team's knowledge for reliable, scalable AI performance.

https://github.com/anthropics/skills

#python #docker #fastapi #kbqa #kgqa #llms #neo4j #rag #vue

Yuxi-Know (语析) is a free, open-source platform built with LangGraph, Vue.js, FastAPI, and LightRAG to create smart agents using RAG knowledge bases and knowledge graphs. The latest v0.4.0-beta (Dec 2025) adds file uploads, multimodal image support, mind maps from files, evaluation tools, dark mode, and better graph visuals. It helps you quickly build and deploy custom AI agents for Q&A, analysis, and searches without starting from scratch, saving time and effort on development.

https://github.com/xerrors/Yuxi-Know

#python #audio_generation #diffusion #image_generation #inference #model_serving #multimodal #pytorch #transformer #video_generation

vLLM-Omni is a free, open-source tool that makes serving AI models for text, images, videos, and audio fast, easy, and cheap. It builds on vLLM for top speed using smart memory tricks, overlapping tasks, and flexible resource sharing across GPUs. You get 2x higher throughput, 35% less delay, and simple setup with Hugging Face models via OpenAI API—perfect for building quick multi-modal apps like chatbots or media generators without high costs.

https://github.com/vllm-project/vllm-omni

#python

Bloom is a free, open-source tool that automates testing AI models for bad behaviors like bias or sycophancy. You define the behavior in a simple config file, add example chats if you want, and it runs four steps: understanding it, creating varied test scenarios, simulating talks with your target model (like Claude or GPT via APIs), and scoring results with metrics like how often the issue appears. View interactive transcripts easily. This saves you hours of manual work, lets you quickly compare models on fresh tests to avoid overfitting, and gives reliable, reproducible insights into AI safety—perfect for researchers building trustworthy systems.

https://github.com/safety-research/bloom

#python #ai_tool #darkweb #darkweb_osint #investigation_tool #llm_powered #osint #osint_tool

Robin is an AI tool that searches and scrapes the dark web, refines queries with large language models, filters results, and produces a concise investigation summary you can save or export, with Docker and CLI options and support for multiple LLMs (OpenAI, Anthropic, Gemini, local models) to fit your workflow. This helps you save hours of manual searching by automating multi-engine dark-web searches, scraping Onion sites via Tor, filtering noise with AI, and producing ready-to-use reports for faster, more focused OSINT investigations.

https://github.com/apurvsinghgautam/robin