#cplusplus #4_bits #attention_sink #chatbot #chatpdf #intel_optimized_llamacpp #large_language_model #llm_cpu #llm_inference #smoothquant #sparsegpt #speculative_decoding #stable_diffusion #streamingllm

https://github.com/intel/intel-extension-for-transformers

#jupyter_notebook #agent_based_framework #agent_oriented_programming #agentic #agentic_agi #chat #chat_application #chatbot #chatgpt #gpt #gpt_35_turbo #gpt_4 #llm_agent #llm_framework #llm_inference #llmops

AutoGen is a tool that helps you build AI systems where agents can work together and perform tasks on their own or with human help. It makes it easier to create scalable, distributed, and resilient AI applications. Here are the key benefits Agents can talk to each other using asynchronous messages.
- **Scalable** You can add your own agents, tools, and models to the system.
- **Multi-Language Support** It includes features to track and debug how the agents interact.

Using AutoGen, you can develop and test your AI systems locally and then move them to a cloud environment as needed. This makes it simpler to build and manage advanced AI projects.

https://github.com/microsoft/autogen

#cplusplus #ai_chat #llm_inference

GPT4All lets you run powerful AI language models directly on your own computer without needing internet, cloud services, or special GPUs. This means your data stays private and secure because nothing leaves your device. You can chat with the AI, ask questions, summarize documents, write code, or create content anytime, even offline. It works on Windows, macOS, and Linux with easy installation and supports many popular AI models. You can also customize it and use it with Python or other tools. This gives you full control, privacy, and flexibility for AI tasks without extra costs or dependencies.

https://github.com/nomic-ai/gpt4all

#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