{
  "id": "bbg-p0208-search-retrieval-and-rag-search",
  "title": "RAG and Agentic RAG Comparison",
  "chapter": "search-retrieval-and-rag",
  "batch": "02",
  "rank": 16,
  "sourcePage": 208,
  "sourcePointer": "p. 208",
  "status": "accepted",
  "reviewerStatus": "reviewed",
  "fidelityScore": 0.9,
  "canvas": {
    "width": 960,
    "height": 640
  },
  "fireworksTechGraph": {
    "style": "style-1-flat-icon",
    "diagramType": "comparison",
    "topologyNotes": [
      "source page render inspected",
      "extracted page text inspected",
      "source page render inspected",
      "preserve comparison: traditional RAG retrieves static context and answers, while agentic RAG uses memory, strategy, tools, and iterative retrieval before answering",
      "omit source branding, product logos, and copied panel text"
    ],
    "publicBoundary": [
      "original vector output",
      "no source pixels",
      "no source mark or long wording"
    ]
  },
  "callouts": [],
  "sourceReview": {
    "conceptAnchors": [
      "concept: RAG retrieval",
      "concept: vector database",
      "concept: prompt augmentation",
      "concept: agent memory",
      "concept: tool-based retrieval"
    ],
    "labelSource": "curated",
    "semanticStatus": "reviewed"
  },
  "groups": [
    {
      "id": "rag",
      "label": "Traditional RAG",
      "x": 64,
      "y": 122,
      "w": 376,
      "h": 324
    },
    {
      "id": "agentic",
      "label": "Agentic RAG",
      "x": 520,
      "y": 122,
      "w": 376,
      "h": 324
    }
  ],
  "shapes": [
    {
      "id": "query",
      "kind": "actor",
      "label": "User query",
      "x": 104,
      "y": 232,
      "w": 82,
      "h": 88,
      "tone": "blue"
    },
    {
      "id": "retrieve",
      "kind": "cylinder",
      "label": "Vector search",
      "detail": "static index",
      "x": 242,
      "y": 168,
      "w": 126,
      "h": 78,
      "tone": "teal"
    },
    {
      "id": "llm",
      "kind": "hex",
      "label": "LLM",
      "detail": "answer",
      "x": 242,
      "y": 332,
      "w": 126,
      "h": 78,
      "tone": "purple"
    },
    {
      "id": "agentQuery",
      "kind": "actor",
      "label": "User query",
      "x": 540,
      "y": 270,
      "w": 82,
      "h": 88,
      "tone": "blue"
    },
    {
      "id": "agent",
      "kind": "hex",
      "label": "AI agent",
      "detail": "plans",
      "x": 648,
      "y": 170,
      "w": 126,
      "h": 78,
      "tone": "purple"
    },
    {
      "id": "memory",
      "kind": "cylinder",
      "label": "Memory",
      "detail": "context",
      "x": 778,
      "y": 160,
      "w": 126,
      "h": 78,
      "tone": "green"
    },
    {
      "id": "tools",
      "kind": "rect",
      "label": "Tools",
      "detail": "search MCP",
      "x": 648,
      "y": 326,
      "w": 126,
      "h": 58,
      "tone": "orange"
    },
    {
      "id": "answer",
      "kind": "rect",
      "label": "Answer",
      "detail": "refined",
      "x": 778,
      "y": 326,
      "w": 126,
      "h": 58,
      "tone": "blue"
    }
  ],
  "connectors": [
    {
      "from": "query",
      "to": "retrieve",
      "label": "lookup",
      "flow": "data"
    },
    {
      "from": "retrieve",
      "to": "llm",
      "label": "context",
      "flow": "data"
    },
    {
      "from": "agentQuery",
      "to": "agent",
      "label": "delegate",
      "flow": "main"
    },
    {
      "from": "agent",
      "to": "memory",
      "label": "read write",
      "flow": "data"
    },
    {
      "from": "agent",
      "to": "tools",
      "label": "choose",
      "flow": "control"
    },
    {
      "from": "tools",
      "to": "answer",
      "label": "evidence",
      "flow": "data"
    },
    {
      "from": "memory",
      "to": "answer",
      "label": "context",
      "flow": "data"
    }
  ]
}