# c-a-x/smartpaperai architecture

> Architecture diagram of the GitHub repository c-a-x/smartpaperai, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-06-24). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/c-a-x/smartpaperai
- Repository: https://github.com/c-a-x/smartpaperai

## Overview

1. **Overall shape**
   - This is a classic two-tier application: a **Vue 3 + TypeScript frontend** and a **Spring Boot backend**.
   - The frontend is a presentation/orchestration layer; the backend owns all document processing, AI/RAG logic, persistence, and integration with external services.

2. **Frontend boundary**
   - The frontend is organized by feature area under `src/views/` and talks to the backend through `src/api/*`.
   - `src/utils/request.ts` centralizes HTTP calls, auth headers, and error handling; `src/utils/stream.ts` supports streaming AI responses.
   - `src/router/` and `src/layouts/MainLayout.vue` define the user-facing navigation shell, while Pinia stores handle cross-page state such as auth.

3. **Backend API boundary**
   - Incoming requests hit Spring MVC controllers in `controller/` such as `DocumentController`, `KnowledgeBaseController`, `RAGController`, `OpenAIController`, `TeachingPlanController`, and `AuthController`.
   - These controllers are thin entry points that delegate to services; they are the main boundary between HTTP/API concerns and business logic.
   - `GlobalExceptionHandler` and `SaTokenAuthFilter` provide cross-cutting error and authentication handling.

4. **Core domain subsystems**
   - The backend is split into domain services for **documents**, **knowledge bases**, **chat/RAG**, **analysis**, **knowledge graphs**, and **teaching plans**.
   - `DocumentService`, `KnowledgeBaseService`, `ChatService`, `RAGService`, `PaperAnalysisService`, `KnowledgeGraphBuilderService`, and `TeachingPlanService` are the main orchestration points.
   - The `impl/` package contains the concrete implementations, indicating a service-interface boundary inside the backend.

5. **Document ingestion pipeline**
   - Document upload is the entry point for the most complex workflow: files are stored, parsed, chunked, enriched with metadata, and then indexed for retrieval.
   - `FileStorageService` handles uploaded files and the `uploads/` directory shows local file persistence is part of the runtime model.
   - `DocumentParserService`, `GrobidMetadataService`, and `SmartChunkingService` transform raw PDFs/DOCs/TXT into structured document chunks and metadata.

6. **Asynchronous processing boundary**
   - Document processing is not purely synchronous: `mq/DocumentProcessingProducer` and `mq/DocumentProcessingConsumer` show a queued background job flow.
   - `DocumentTaskService` and `DocumentProcessingMessage` indicate upload events are turned into processing tasks, likely to keep uploads responsive while heavier parsing/indexing runs asynchronously.
   - `RabbitMQConfig` confirms RabbitMQ is the messaging boundary for this workflow.

7. **Search and retrieval layer**
   - The repository uses **Elasticsearch** for document search and retrieval-oriented indexing, with `DocumentESRepository`, `DocumentESService`, and `ElasticsearchIndexInitializer`.
   - The `model/entity/DocumentES` and Elasticsearch config classes suggest documents are denormalized into search documents separate from the relational model.
   - `DynamicRetrievalService`, `RerankService`, and `RAGService` sit on top of this index to select relevant chunks for AI answers.

8. **RAG and LLM integration**
   - The AI-facing subsystem is centered around `ChatClientConfig`, `PromptTemplateConfig`, and the prompt files under `resources/prompts/`.
   - RAG flows combine retrieval from Elasticsearch plus optional graph context, then send prompts to the LLM through the chat client.
   - `GraphEnhancedRAGService` and `RAGConfiguration` suggest a configurable retrieval-augmented generation pipeline with prompt templates and tunable retrieval parameters.

9. **Knowledge graph subsystem**
   - The graph model is represented explicitly by `model/graph/*` nodes such as `DocumentNode`, `ConceptNode`, and `AuthorNode`.
   - `repository/graph/*` provides persistence access for graph entities, while `KnowledgeGraphBuilderService` and `ConceptExtractionService` construct the graph from parsed documents.
   - The frontend’s knowledge-graph views consume this model for visualization and exploration, so the graph store is a distinct read model rather than just a UI feature.

10. **Persistence model**
   - Relational data is handled through MyBatis-style mappers in `mapper/` and SQL scripts under `resources/db/`.
   - Domain entities include users, documents, tags, knowledge bases, chat sessions/messages, document tasks, vectors, and teaching plans.
   - `MyMetaObjectHandler` and the presence of separate DO/VO/DTO types show a deliberate boundary between database records, API payloads, and UI responses.

11. **Caching and session/state**
   - `RedisConfig` indicates Redis is used as an infrastructure layer for ephemeral state such as cache, session, or task-related data.
   - Authentication uses token-based access with Sa-Token support, and the frontend stores token/user info locally to attach on each request.
   - This keeps interactive features like chat and multi-step document workflows resilient without relying only on request-scoped state.

12. **Analysis and report generation**
   - The `analysis/` controllers and services produce higher-level academic outputs: summaries, comparisons, innovation clustering, literature reviews, and teaching-plan generation.
   - These features are template/LLM driven, using prompt resources plus structured DTO/VO contracts to return report-like results.
   - The analysis layer is mostly read-heavy and generated-content oriented, separate from the core document storage and retrieval pipeline.

13. **External integration points**
   - The backend integrates with **Grobid** for scholarly document parsing/metadata extraction, **RabbitMQ** for async processing, **Elasticsearch** for search, and likely a graph database for knowledge graph persistence.
   - The frontend is a pure SPA that relies on the backend for all data and AI capabilities; deployment can place it behind Nginx with API proxying.
   - These infrastructure dependencies are architecturally important because they define the main runtime boundaries and data flows.

14. **Typical end-to-end flow**
   - A user uploads a paper in the frontend → backend stores the file → async processing parses/chunks/enriches it → metadata/search/graph records are written → the document becomes available in lists, search, graph views, and RAG chat.
   - A chat or analysis request then goes from UI → controller → retrieval/prompting services → LLM response → streamed or structured response back to the client.
   - In short, the system is built around one central domain object, the academic paper, with multiple read models layered on top: search, graph, chat context, and generated analysis.

Main entry points: [`SmartPaperAi-frontend/src/router/index.ts`](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/router/index.ts) (Router), [`SmartPaperAi-frontend/src/utils/request.ts`](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/utils/request.ts) (HTTP client), [`SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/config/ChatClientConfig.java`](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/config/ChatClientConfig.java) (Infra config), [`SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentService.java`](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentService.java) (Domain services)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_frontend["Frontend"]
  node_fe_app["App shell<br/>Vue SPA shell<br/>[App.vue]"]
  node_fe_layout["Main layout<br/>navigation shell<br/>[MainLayout.vue]"]
  node_fe_router["Router<br/>route map<br/>[index.ts]"]
  node_fe_request["HTTP client<br/>api transport<br/>[request.ts]"]
  node_fe_stream["Stream utils<br/>streaming helper<br/>[stream.ts]"]
  node_fe_auth["Auth store<br/>Pinia state<br/>[auth.ts]"]
  node_fe_doc["Document views<br/>feature views"]
  node_fe_knowledge["Knowledge views<br/>feature views"]
  node_fe_graph["Graph view<br/>visualization"]
  node_fe_chat["Chat UI<br/>conversation view<br/>[ChatView.vue]"]
  node_fe_rag["RAG chat<br/>retrieval UI<br/>[RagChatView.vue]"]
  node_fe_analysis["Analysis views<br/>report views"]
  node_fe_teach["Teaching views<br/>planning views"]
end

subgraph group_backend["Backend"]
  node_be_api["Controllers<br/>HTTP boundary"]
  node_be_core["Domain services<br/>business orchestration"]
  node_be_ingest["Ingestion pipeline<br/>document processing"]
  node_be_async["Async worker<br/>message flow"]
  node_be_search["Search index<br/>Elasticsearch read model"]
  node_be_rag["RAG engine<br/>retrieval+LLM<br/>[RAGService.java]"]
  node_be_graph["Knowledge graph<br/>graph model"]
  node_be_store["Persistence<br/>relational storage"]
  node_be_config["Infra config<br/>runtime config"]
end

node_fe_app -->|"uses"| node_fe_layout
node_fe_layout -->|"hosts"| node_fe_router
node_fe_router -->|"routes"| node_fe_doc
node_fe_router -->|"routes"| node_fe_knowledge
node_fe_router -->|"routes"| node_fe_graph
node_fe_router -->|"routes"| node_fe_chat
node_fe_router -->|"routes"| node_fe_rag
node_fe_router -->|"routes"| node_fe_analysis
node_fe_router -->|"routes"| node_fe_teach
node_fe_doc -->|"calls"| node_fe_request
node_fe_knowledge -->|"calls"| node_fe_request
node_fe_graph -->|"calls"| node_fe_request
node_fe_chat -->|"streams"| node_fe_stream
node_fe_chat -->|"calls"| node_fe_request
node_fe_rag -->|"streams"| node_fe_stream
node_fe_analysis -->|"calls"| node_fe_request
node_fe_teach -->|"calls"| node_fe_request
node_fe_auth -->|"auths"| node_fe_request
node_be_api -->|"delegates"| node_be_core
node_be_core -->|"orchestrates"| node_be_ingest
node_be_ingest -->|"enqueues"| node_be_async
node_be_async -->|"updates"| node_be_store
node_be_core -->|"indexes"| node_be_search
node_be_core -->|"uses"| node_be_rag
node_be_rag -->|"retrieves"| node_be_search
node_be_rag -->|"augments"| node_be_graph
node_be_graph -->|"persists"| node_be_store
node_be_ingest -->|"writes"| node_be_store
node_be_config -->|"cross-cuts"| node_be_api
node_be_config -->|"supports"| node_be_ingest
node_be_config -->|"supports"| node_be_search
node_be_config -->|"supports"| node_be_rag

click node_fe_app "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/App.vue"
click node_fe_layout "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/layouts/MainLayout.vue"
click node_fe_router "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/router/index.ts"
click node_fe_request "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/utils/request.ts"
click node_fe_stream "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/utils/stream.ts"
click node_fe_auth "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/stores/auth.ts"
click node_fe_doc "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/document/DocumentListView.vue"
click node_fe_knowledge "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/knowledge/KnowledgeListView.vue"
click node_fe_graph "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/knowledge-graph/KnowledgeGraphView.vue"
click node_fe_chat "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/chat/ChatView.vue"
click node_fe_rag "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/rag/RagChatView.vue"
click node_fe_analysis "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/analysis/PaperSummaryView.vue"
click node_fe_teach "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/teaching/TeachingListView.vue"
click node_be_api "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/controller/DocumentController.java"
click node_be_core "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentService.java"
click node_be_ingest "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentParserService.java"
click node_be_async "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/mq/DocumentProcessingProducer.java"
click node_be_search "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentESService.java"
click node_be_rag "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/RAGService.java"
click node_be_graph "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/KnowledgeGraphBuilderService.java"
click node_be_store "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/mapper/DocumentMapper.java"
click node_be_config "https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/config/ChatClientConfig.java"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_fe_app,node_fe_layout,node_fe_router,node_fe_request,node_fe_stream,node_fe_auth,node_fe_doc,node_fe_knowledge,node_fe_graph,node_fe_chat,node_fe_rag,node_fe_analysis,node_fe_teach toneBlue
class node_be_api,node_be_core,node_be_ingest,node_be_async,node_be_search,node_be_rag,node_be_graph,node_be_store,node_be_config toneAmber
```

## Components

### Frontend

Vue 3 single-page app for browsing documents, chat, analysis, knowledge graphs, and teaching plans.

- [App shell](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/App.vue): Vue SPA shell · Root Vue application and global composition entry. · `SmartPaperAi-frontend/src/App.vue`
- [Main layout](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/layouts/MainLayout.vue): navigation shell · Primary application frame and shared UI layout. · `SmartPaperAi-frontend/src/layouts/MainLayout.vue`
- [Router](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/router/index.ts): route map · Client-side navigation between feature views. · `SmartPaperAi-frontend/src/router/index.ts`
- [HTTP client](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/utils/request.ts): api transport · Shared request layer with auth headers and error handling. · `SmartPaperAi-frontend/src/utils/request.ts`
- [Stream utils](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/utils/stream.ts): streaming helper · Helpers for streaming AI responses to the UI. · `SmartPaperAi-frontend/src/utils/stream.ts`
- [Auth store](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/stores/auth.ts): Pinia state · Cross-page authentication and user session state. · `SmartPaperAi-frontend/src/stores/auth.ts`
- [Document views](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/document/DocumentListView.vue): feature views · Document list and detail screens for paper browsing. · `SmartPaperAi-frontend/src/views/document/DocumentListView.vue`
- [Knowledge views](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/knowledge/KnowledgeListView.vue): feature views · Knowledge base list and detail screens. · `SmartPaperAi-frontend/src/views/knowledge/KnowledgeListView.vue`
- [Graph view](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/knowledge-graph/KnowledgeGraphView.vue): visualization · Knowledge graph exploration and visualization UI. · `SmartPaperAi-frontend/src/views/knowledge-graph/KnowledgeGraphView.vue`
- [Chat UI](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/chat/ChatView.vue): conversation view · Interactive chat experience for document and RAG questions. · `SmartPaperAi-frontend/src/views/chat/ChatView.vue`
- [RAG chat](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/rag/RagChatView.vue): retrieval UI · Dedicated retrieval-augmented chat interface. · `SmartPaperAi-frontend/src/views/rag/RagChatView.vue`
- [Analysis views](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/analysis/PaperSummaryView.vue): report views · Paper summary, comparison, literature review, and innovation clustering screens. · `SmartPaperAi-frontend/src/views/analysis/PaperSummaryView.vue`
- [Teaching views](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAi-frontend/src/views/teaching/TeachingListView.vue): planning views · Teaching plan list, edit, and detail interfaces. · `SmartPaperAi-frontend/src/views/teaching/TeachingListView.vue`

### Backend

Spring Boot API and processing engine for documents, retrieval, AI, persistence, and integrations.

- [Controllers](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/controller/DocumentController.java): HTTP boundary · Spring MVC entry points for auth, documents, knowledge, chat, RAG, analysis, and teaching plans. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/controller/DocumentController.java`
- [Domain services](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentService.java): business orchestration · Main service layer for document, knowledge base, chat, analysis, graph, and teaching workflows. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentService.java`
- [Ingestion pipeline](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentParserService.java): document processing · Storage, parsing, metadata extraction, chunking, and task creation for uploaded papers. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentParserService.java`
- [Async worker](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/mq/DocumentProcessingProducer.java): message flow · RabbitMQ-backed producer/consumer flow for background document processing. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/mq/DocumentProcessingProducer.java`
- [Search index](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentESService.java): Elasticsearch read model · Document search and retrieval index plus index initialization. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/DocumentESService.java`
- [RAG engine](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/RAGService.java): retrieval+LLM · Dynamic retrieval, reranking, prompt assembly, and chat response generation. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/RAGService.java`
- [Knowledge graph](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/KnowledgeGraphBuilderService.java): graph model · Concept/document graph extraction and persistence for graph-enhanced retrieval and visualization. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/service/KnowledgeGraphBuilderService.java`
- [Persistence](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/mapper/DocumentMapper.java): relational storage · MyBatis mappers and entity model for users, documents, tasks, chats, knowledge bases, tags, and plans. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/mapper/DocumentMapper.java`
- [Infra config](https://github.com/c-a-x/smartpaperai/blob/main/SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/config/ChatClientConfig.java): runtime config · Chat client, Grobid, Redis, RabbitMQ, Elasticsearch, file storage, token auth, and exception handling configuration. · `SmartPaperAI-backend/src/main/java/com/GeekPaperAssistant/config/ChatClientConfig.java`

## Connections

- App shell → Main layout: uses · Application composes the shared navigation shell.
- Main layout → Router: hosts · Layout renders routed feature pages.
- Router → Document views: routes · Navigation exposes document screens.
- Router → Knowledge views: routes · Navigation exposes knowledge base screens.
- Router → Graph view: routes · Navigation exposes graph exploration.
- Router → Chat UI: routes · Navigation exposes chat screens.
- Router → RAG chat: routes · Navigation exposes RAG chat.
- Router → Analysis views: routes · Navigation exposes analysis reports.
- Router → Teaching views: routes · Navigation exposes teaching plan pages.
- Document views → HTTP client: calls · Document pages use shared API transport.
- Knowledge views → HTTP client: calls · Knowledge pages fetch data through the API client.
- Graph view → HTTP client: calls · Graph view loads backend graph data.
- Chat UI → Stream utils: streams · Chat UI consumes streamed responses.
- Chat UI → HTTP client: calls · Chat UI also uses API requests for session and history data.
- RAG chat → Stream utils: streams · RAG chat renders incremental model output.
- Analysis views → HTTP client: calls · Analysis pages request generated reports.
- Teaching views → HTTP client: calls · Teaching pages load and save plan data.
- Auth store → HTTP client: auths · Stored tokens are attached to outbound requests.
- Controllers → Domain services: delegates · Controllers forward business work to services.
- Domain services → Ingestion pipeline: orchestrates · Document and knowledge workflows start with ingestion.
- Ingestion pipeline → Async worker: enqueues · Heavy processing is handed off to queued jobs.
- Async worker → Persistence: updates · Background processing persists task and document state.
- Domain services → Search index: indexes · Services write and query the Elasticsearch read model.
- Domain services → RAG engine: uses · Chat and retrieval features are built on the RAG engine.
- RAG engine → Search index: retrieves · RAG pulls candidate chunks from the search index.
- RAG engine → Knowledge graph: augments · Graph context can enrich retrieval and prompting.
- Knowledge graph → Persistence: persists · Graph data is stored through repositories and mappers.
- Ingestion pipeline → Persistence: writes · Parsed documents, chunks, metadata, and tasks are persisted.
- Infra config → Controllers: cross-cuts · Auth and exception handling wrap API entry points.
- Infra config → Ingestion pipeline: supports · File storage, Grobid, and RabbitMQ enable ingestion.
- Infra config → Search index: supports · Elasticsearch client and index init support retrieval.
- Infra config → RAG engine: supports · Chat client and prompt configuration support generation.