#go #a2a #agents #agents_sdk #ai #aiagentframework #gemini #genai #go #llm #mcp #multi_agent_collaboration #multi_agent_systems #sdk #vertex_ai

The Agent Development Kit (ADK) for Go is an open-source toolkit that makes it easy to build, test, and deploy smart AI agents using the Go programming language. It lets you create simple or complex agent workflows, use ready-made or custom tools, and run your agents anywhere, especially in cloud environments. With ADK, you get full control, flexibility, and the ability to scale your applications, making it faster and simpler to develop powerful AI solutions for real-world tasks.

https://github.com/google/adk-go

#python #ai #faiss #gpt_oss #langchain #llama_index #llm #localstorage #offline_first #ollama #privacy #python #rag #retrieval_augmented_generation #vector_database #vector_search #vectors

LEANN is a tiny, powerful vector database that lets you turn your laptop into a personal AI assistant capable of searching millions of documents using 97% less storage than traditional systems without losing accuracy. It works by storing a compact graph and computing embeddings only when needed, saving huge space and keeping your data private on your device. You can search your files, emails, browser history, chat logs, live data from platforms like Slack and Twitter, and even codebases—all locally without cloud costs. This means fast, private, and efficient AI-powered search and retrieval on your own laptop.

https://github.com/yichuan-w/LEANN

#python #agent #ai #aiagent #awesome #chatgpt #hacktoberfest #hacktoberfest2025 #llm #long_short_term_memory #memori_ai #memory #memory_management #python #rag #state_management

Memori is an open-source memory engine that gives AI language models human-like memory using standard SQL databases like PostgreSQL, MySQL, or SQLite.[1][2] With just one line of code, you can enable any LLM to remember conversations, learn from interactions, and maintain context across sessions.[1] The key benefits are significant cost savings of 80-90% compared to expensive vector databases, complete data ownership and transparency since memories are stored in SQL databases you control, and zero vendor lock-in allowing you to export and move your data anywhere.[1][3] Memori works with popular frameworks like OpenAI, Anthropic, and LangChain, making it easy to integrate into existing projects without complex setup.[1]

https://github.com/GibsonAI/Memori

#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 #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

#typescript #agent #agentic #agentic_ai #agents #agents_sdk #ai #ai_agents #aiagentframework #genai #genai_chatbot #llm #llms #multi_agent #multi_agent_systems #multi_agents #multi_agents_collaboration

Agent Development Kit (ADK) for TypeScript is an open-source toolkit to build, test, and deploy advanced AI agents with full control in code. Key features include rich tools like Google Search, custom functions, and multi-agent hierarchies for scalable apps, plus a dev UI for easy debugging. Install via npm install @google/adk. You benefit by creating flexible, versioned AI agents that integrate tightly with Google Cloud, run anywhere from laptop to cloud, and speed up development like regular software.

https://github.com/google/adk-js

#go #gemma3 #go #gpt_oss #granite4 #llama #llama3 #llm #on_device_ai #phi3 #qwen3 #qwen3vl #sdk #stable_diffusion #vlm

NexaSDK runs AI models locally on CPUs, GPUs, and NPUs with a single command, supports GGUF/MLX/.nexa formats, and offers NPU-first Android and macOS support for fast, multimodal (text, image, audio) inference, plus an OpenAI‑compatible API for easy integration. This gives you low-latency, private on-device AI across laptops, phones, and embedded systems, reduces cloud costs and data exposure, and lets you deploy and test new models immediately on target hardware for faster development and better user experience.

https://github.com/NexaAI/nexa-sdk

#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 #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 #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