# bigsnake47/aiwithrag architecture

> Architecture diagram of the GitHub repository bigsnake47/aiwithrag, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-29). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/bigsnake47/aiwithrag
- Repository: https://github.com/bigsnake47/aiwithrag

## Overview

AIwithRAG is an in-development RAG project, but its README documents no capabilities and the sampled API, generation, retrieval, ingestion-pipeline, and storage modules are empty or lack implementation. The supported behavior is limited to a document-loader entry point whose file dispatcher is a stub, and a standalone sentence-transformer embedding service. No end-to-end ingestion, retrieval, or answer-generation flow can be established from the available evidence.

Main entry points: [`app/ingestion/loaders.py`](https://github.com/bigsnake47/aiwithrag/blob/main/app/ingestion/loaders.py) (Document loader), [`app/embeddings/service.py`](https://github.com/bigsnake47/aiwithrag/blob/main/app/embeddings/service.py) (Embedding service)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_ingestion["Document loading"]
  node_loader["Document loader<br/>[loaders.py]"]
end

subgraph group_embeddings["Embeddings"]
  node_embedding_service["Embedding service<br/>[service.py]"]
end

node_local_files["Local files"]
node_loaded_docs["Loaded documents"]
node_text_input["Text input"]
node_vectors["Text vectors"]

node_local_files -->|"loads paths"| node_loader
node_loader -->|"returns documents"| node_loaded_docs
node_text_input -->|"encodes text"| node_embedding_service
node_embedding_service -->|"returns vectors"| node_vectors

click node_loader "https://github.com/bigsnake47/aiwithrag/blob/main/app/ingestion/loaders.py"
click node_embedding_service "https://github.com/bigsnake47/aiwithrag/blob/main/app/embeddings/service.py"

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_loader toneBlue
class node_embedding_service toneAmber
class node_local_files,node_loaded_docs,node_text_input,node_vectors toneIndigo
```

## Components

### Document loading

- [Document loader](https://github.com/bigsnake47/aiwithrag/blob/main/app/ingestion/loaders.py): `app/ingestion/loaders.py`

### Embeddings

- [Embedding service](https://github.com/bigsnake47/aiwithrag/blob/main/app/embeddings/service.py): `app/embeddings/service.py`

### Other components

- **Local files**
- **Loaded documents**
- **Text input**
- **Text vectors**

## Connections

- Local files → Document loader: loads paths
- Document loader → Loaded documents: returns documents
- Text input → Embedding service: encodes text
- Embedding service → Text vectors: returns vectors