Unverified50% confidenceFactExact time
VaultRAG's tech stack is: LLM and embedding models run locally via Ollama (using Llama 3.1, Qwen and nomic-embed-text), the backend uses Python and FastAPI, RAG orchestration uses LangChain, the frontend uses React with Tailwind CSS, and deployment is managed by Docker Compose.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/13/2026
First Seen
Valid until: 1/11/2027
Sources
Related Entities
Related Claims
UnverifiedLlama 3.1引入了专门的工具调用token64% similarUnverifiedThe course's technology stack covers FastAPI, Vue3, LangChain, RAG, Agent, and Harness.61% similarUnverifiedOllama's core design philosophy draws on Docker's containerization concept, allowing users to pull and run various open-source large models with a single ollama run command.61% similarUnverifiedLocal runtime applications such as Ollama and LM Studio all call the llama.cpp engine under the hood.60% similarUnverifiedOllama 采用三层结构：底层是llama.cpp推理引擎，中间层是模型生命周期管理系统，上层是REST API与命令行界面60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1017583API
curl https://kongchang.com/api/v1/knowledge/claims/1017583MCP
get_claim(id=1017583)