Flowchart template · local export
RAG Application Architecture Mermaid Template
RAG flowchart: chunking, embeddings, vector search, reranking, and LLM answer generation. Edit the code below, choose a publish preset, then export without signup, watermark, or cloud upload.
RAGLLMvector search
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Flowchart
Mode
Default renderNative MermaidOptimized exportStyled download
Export style
Clean DocsGitHub READMETransparent DocsWarm Editorial✦ ProWhiteboard Sketch✦ ProAurora Noir✦ ProBlueprint✦ ProChampagne✦ ProEmerald Suite✦ ProEditorial✦ Pro
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1x2x4x
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Output: White · comfortable padding
Size: calculated after render
Filename: mermaid-flowchart-white-2x.png
When to use the RAG Application Architecture template
A retrieval-augmented generation pipeline in two halves: the ingestion path chunks and cleans Source Documents, generates Embeddings, and stores them in the Vector Database; the query path embeds the User Question, runs Similarity Search against the store, reranks the context, builds the prompt, and generates a grounded answer with citations.
- •Architecting a RAG feature and needing the team to agree on the ingestion-versus-query split.
- •Explaining to stakeholders why answers cite sources and where hallucination risk is reduced by retrieval.
- •Debugging answer quality, since the diagram shows every stage where context can be lost or improved.
Template code
The full Mermaid source for this template — copy it into any Mermaid-compatible tool, or edit and export it in the editor above.
flowchart LR
Docs[Source Documents] --> Chunk[Chunk + Clean Text]
Chunk --> Embed[Generate Embeddings]
Embed --> VectorDB[(Vector Database)]
User[User Question] --> QueryEmbed[Query Embedding]
QueryEmbed --> Search[Similarity Search]
VectorDB --> Search
Search --> Rerank[Rerank Context]
Rerank --> Prompt[Build Prompt]
Prompt --> LLM[LLM]
LLM --> Answer[Grounded Answer]
Answer --> Citations[Show Citations]How to customize this template
- •Name the specific reranker or embedding model you use by renaming the Embed and Rerank nodes.
- •Add a cache node between QueryEmbed and Search if you serve repeated questions from a query cache.
- •Extend the Citations step to your UI component, or add a feedback loop into Chunk for ingestion tuning.
- •Split the Vector Database into write and read paths if ingestion runs offline while queries are online.