#typescript#12_factor#12_factor_agents#agents#ai#context_window#framework#llms#memory#orchestration#prompt_engineering#rag
The 12-Factor Agents are a set of proven principles to build reliable, scalable, and maintainable AI applications powered by large language models (LLMs). They help you combine the creativity of AI with the stability of traditional software by managing prompts, context, tool calls, error handling, and human collaboration effectively. Instead of relying solely on complex frameworks, you can apply these modular concepts to improve your existing products quickly and reach high-quality AI performance for real users. This approach makes AI software easier to develop, debug, and scale, ensuring it works well in production environments[1][3][5].
https://github.com/humanlayer/12-factor-agents
#python#agents#graph#llms#rag
Graphiti helps AI systems handle constantly changing information by building real-time knowledge graphs that track relationships and historical data, allowing them to integrate user interactions, business data, and external sources seamlessly. Unlike traditional methods, it updates information instantly without needing full recomputations, enabling precise historical queries and efficient hybrid searches. This helps AI applications stay context-aware, automate tasks effectively, and manage complex, evolving data with minimal delay.
https://github.com/getzep/graphiti
#typescript#csv#diagrams#graph#json#nextjs#react#tool#visualization#yaml
JSON Crack is a free, open-source tool that instantly turns complex JSON, YAML, CSV, XML, or TOML data into clear, interactive graphs, making it easier to explore and understand your information. It lets you convert between formats, validate data, generate code (like TypeScript interfaces), run queries, and export visuals as images—all while keeping your data private since everything processes locally on your device[1][2][5].
https://github.com/AykutSarac/jsoncrack.com
#cplusplus#arduino#cansat#csv#embedded#graph#ground_station#iot#microcontroller#network#projects#qt#serial#serial_studio
Serial Studio is a free, easy-to-use tool that lets you visualize real-time data from devices like microcontrollers via serial ports, Bluetooth, or network connections. It works on Windows, macOS, and Linux, and offers customizable dashboards with various widgets to monitor sensor data, debug info, or telemetry. You can quickly plot data, export it as CSV for analysis, and even use advanced features like checksum validation and JavaScript data processing. It supports hobbyists, educators, and professionals by simplifying data monitoring and debugging, saving you time and effort in understanding your device’s output. Pro versions add commercial use and extra features[1][4][5].
https://github.com/Serial-Studio/Serial-Studio
#rust#ai#ai_ocr#attention_mechanism#gnn#gnn_model#gnns#graph#graph_neural_networks#llm_inference#low_latency#mincut#neo4j#ocr#onnx#rust#vector#wasm
RuVector is a free, open-source vector database that gets smarter with every query. Unlike static databases, it learns from usage via GNN layers, runs LLMs locally with no cloud costs, supports graph queries like Neo4j, scales freely across nodes, and deploys as a single self-booting file (125ms startup). Run with `npx ruvector`. You benefit from faster, more accurate AI search that improves automatically, zero operating costs, full offline/privacy control, and easy scaling—perfect for RAG, agents, or edge apps without vendor lock-in.
https://github.com/ruvnet/ruvector