RAG System Architecture
Knowledge Ingestion & AI Retrieval Workflow
flowchart TD
%% Styling Definitions - Modern Light Palette
classDef prep fill:#eef2ff,stroke:#6366f1,stroke-width:2px,color:#312e81;
classDef storage fill:#ecfeff,stroke:#0891b2,stroke-width:2px,color:#164e63;
classDef logic fill:#fffbeb,stroke:#f59e0b,stroke-width:2px,color:#78350f;
classDef result fill:#f0fdf4,stroke:#22c55e,stroke-width:2px,color:#14532d;
subgraph Ingestion ["Data Pipeline"]
A(["1. Source Data"])
B["2. Chunking"]
C["3. Embedding"]
D[("4. Vector DB")]
A --> B --> C --> D
end
subgraph Inference ["Query Intelligence"]
E[/"User Query"/]
F["5. Query Vector"]
G{"6. Retrieval"}
H["7. RAG Prompt"]
E --> F --> G
D -.->|Semantic Context| G
G --> H
end
subgraph Output ["Response"]
I(["8. Grounded Answer"])
H --> I
end
%% Apply Classes
class A,B,C prep;
class D storage;
class E,F,G,H logic;
class I result;
%% Link Styling
linkStyle default stroke:#cbd5e1,stroke-width:2px,fill:none;
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