#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

#python #agent #agentic_ai #agentic_framework #agentic_workflow #ai #ai_agents #ai_companion #ai_roleplay #benchmark #framework #llm #mcp #memory #open_source #python #sandbox

MemU lets AI systems take in conversations, documents, and media, turn them into structured memories, and store them in a clear three-layer file system. It offers both fast embedding search and deeper LLM-based retrieval, works with many data types, and supports cloud or self-hosted setups with simple APIs. This helps you build AI agents that truly remember past interactions, retrieve the right context when needed, and improve over time, making your applications more accurate, personal, and efficient.

https://github.com/NevaMind-AI/memU

#javascript #agent #agentic #agentic_ai #ai #ai_agents #automation #cursor #design #figma #generative_ai #llm #llms #mcp #model_context_protocol

Cursor Talk to Figma MCP lets Cursor AI read and edit your Figma designs directly, using tools like `get_selection` for info, `set_text_content` for bulk text changes, `create_rectangle` for shapes, and `set_instance_overrides` for components. Setup is quick: install Bun, run `bun setup` and `bun socket`, add the Figma plugin. This saves you hours by skipping context switches, automating repetitive tasks like text replacement or override propagation, speeding up design-to-code workflows, and keeping everything in sync for faster, precise builds.

https://github.com/grab/cursor-talk-to-figma-mcp

#typescript #acp #ai #ai_agent #banana #chat #chatbot #claude_code #codex #cowork #excel #gemini #gemini_cli #gemini_pro #llm #multi_agent #nano_banana #office #qwen_code #skills #webui

AionUi is a free, open-source app that gives your CLI AI tools like Gemini CLI, Claude Code, and Qwen Code a simple graphical interface on macOS, Windows, or Linux. It auto-detects them for easy chatting, saves talks locally with multi-sessions, organizes files smartly, previews 9+ formats like PDF or code instantly, generates/editing images, and offers web access. You benefit by ditching complex commands for quick, secure AI help in office tasks, coding, or data work—saving time and boosting productivity without data leaving your device.

https://github.com/iOfficeAI/AionUi

#jupyter_notebook #chinese_llm #chinese_nlp #finetune #generative_ai #instruct_gpt #instruction_set #llama #llm #lora #open_models #open_source #open_source_models #qlora

AirLLM is a tool that lets you run very large AI models on computers with limited memory by using a smart layer-by-layer loading technique instead of traditional compression methods. You can run a 70-billion-parameter model on just 4GB of GPU memory, or even a 405-billion-parameter model on 8GB, without losing model quality. The benefit is that you can use powerful AI models on affordable hardware without expensive upgrades, and the tool also offers optional compression features that can speed up performance by up to 3 times while maintaining accuracy.

https://github.com/lyogavin/airllm

#python #deepseek #demo #easy #embedding #flask #gpt #huggingface_transformers #llm #mcp #multimodal #openai #qwen #rag #sentence_transformers #ui #vllm #vlm

UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles.

https://github.com/OpenBMB/UltraRAG