The RAG stack
Retrieval-augmented generation grounds an LLM in your own data. A production RAG pipeline is four layers: ingestion, a vector store, orchestration, and evaluation.
Ingestion & retrieval - parse, chunk, and load documents into a retrievable form.
When not to use: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
graphrag
microsoft/graphrag
A modular graph-based Retrieval-Augmented Generation (RAG) system
ChatGLM2-6B
zai-org/ChatGLM2-6B
ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
easy-dataset
ConardLi/easy-dataset
A powerful tool for creating datasets for LLM fine-tuning 、RAG and Eval
orama
oramasearch/orama
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search
Vector store - persist embeddings and run similarity search at query time.
When not to use: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
ECC
affaan-m/ECC
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Code
hermes-agent
NousResearch/hermes-agent
The agent that grows with you
ollama
ollama/ollama
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
langflow
langflow-ai/langflow
Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
Orchestration - assemble retrieval, prompting, and the model into a chain.
When not to use: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
ECC
affaan-m/ECC
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Code
hermes-agent
NousResearch/hermes-agent
The agent that grows with you
AutoGPT
Significant-Gravitas/AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on w
ollama
ollama/ollama
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
Evaluation & tracing - measure answer quality, cost, and latency before and after changes.
When not to use: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
toon
toon-format/toon
🎒 Token-Oriented Object Notation (TOON) – Compact, human-readable, schema-aware JSON for LLM prompts. Spec, benchmarks, TypeScript SDK.
VAR
FoundationVision/VAR
[NeurIPS 2024 Best Paper Award][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeli
LLM4Decompile
albertan017/LLM4Decompile
Reverse Engineering: Decompiling Binary Code with Large Language Models
tree-of-thought-llm
princeton-nlp/tree-of-thought-llm
[NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models