# bhoomikakm04/interactive-lda-topic-explorer architecture

> Architecture diagram of the GitHub repository bhoomikakm04/interactive-lda-topic-explorer, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-30). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/bhoomikakm04/interactive-lda-topic-explorer
- Repository: https://github.com/bhoomikakm04/interactive-lda-topic-explorer

## Overview

This is a Streamlit dashboard for exploring LDA topics in a document collection. Users supply a CSV or use the bundled corpus, inspect preprocessing and document-term representations, configure and run topic modeling, then review topic-word lists, interpretation reports, and visualizations. The code is concentrated in app.py; the sampled excerpts show input validation, preprocessing helpers, and vectorization, while several later dashboard sections are documented but not excerpted. Dashed edges mark workflow links whose implementation details were not shown.

Main entry points: [`app.py`](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py) (Streamlit Dashboard), [`data/lda_corpus.csv`](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/data/lda_corpus.csv) (Default Corpus)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_input["Corpus Input"]
  node_corpus["Default Corpus<br/>[lda_corpus.csv]"]
  node_csv["CSV Upload<br/>[app.py]"]
  node_validation["Input Validation<br/>[app.py]"]
end

subgraph group_model["Topic Modeling"]
  node_preprocess["Text Preprocessing<br/>[app.py]"]
  node_dtm["Document-Term Matrix<br/>[app.py]"]
  node_lda["LDA Model<br/>[app.py]"]
end

subgraph group_results["Topic Results"]
  node_topicwords["Topic Word Lists<br/>[app.py]"]
  node_interpretation["Interpretation Reports<br/>[app.py]"]
  node_visualizations["Interactive Visualizations<br/>[app.py]"]
end

subgraph group_ui["Dashboard"]
  node_dashboard["Streamlit Dashboard<br/>[app.py]"]
end

node_user(("Dashboard User"))

node_user -->|"uses"| node_dashboard
node_corpus -.->|"loads by default"| node_validation
node_csv -->|"validates upload"| node_validation
node_dashboard -.->|"accepts upload"| node_csv
node_validation -.->|"prepares corpus"| node_preprocess
node_preprocess -->|"vectorizes text"| node_dtm
node_dtm -.->|"models counts"| node_lda
node_lda -.->|"produces topics"| node_topicwords
node_lda -.->|"informs report"| node_interpretation
node_lda -.->|"feeds charts"| node_visualizations
node_dashboard -.->|"shows preprocessing"| node_preprocess
node_dashboard -.->|"shows matrix"| node_dtm
node_dashboard -.->|"shows topics"| node_topicwords
node_dashboard -.->|"shows report"| node_interpretation
node_dashboard -.->|"shows charts"| node_visualizations

click node_dashboard "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py"
click node_corpus "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/data/lda_corpus.csv"
click node_csv "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py"
click node_validation "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py"
click node_preprocess "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py"
click node_dtm "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py"
click node_lda "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py"
click node_topicwords "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py"
click node_interpretation "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py"
click node_visualizations "https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.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_corpus,node_csv,node_validation,node_user toneBlue
class node_preprocess,node_dtm,node_lda toneAmber
class node_topicwords,node_interpretation,node_visualizations toneMint
class node_dashboard toneRose
```

## Components

### Corpus Input

- [Default Corpus](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/data/lda_corpus.csv): `data/lda_corpus.csv`
- [CSV Upload](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`
- [Input Validation](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`

### Topic Modeling

- [Text Preprocessing](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`
- [Document-Term Matrix](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`
- [LDA Model](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`

### Topic Results

- [Topic Word Lists](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`
- [Interpretation Reports](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`
- [Interactive Visualizations](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`

### Dashboard

- [Streamlit Dashboard](https://github.com/bhoomikakm04/interactive-lda-topic-explorer/blob/main/app.py): `app.py`

### Other components

- **Dashboard User**

## Connections

- Dashboard User → Streamlit Dashboard: uses (evidence: `README.md`)
- Default Corpus → Input Validation: loads by default
- CSV Upload → Input Validation: validates upload (evidence: `app.py`)
- Streamlit Dashboard → CSV Upload: accepts upload (evidence: `app.py`)
- Input Validation → Text Preprocessing: prepares corpus (evidence: `app.py`)
- Text Preprocessing → Document-Term Matrix: vectorizes text (evidence: `app.py`)
- Document-Term Matrix → LDA Model: models counts (evidence: `app.py`)
- LDA Model → Topic Word Lists: produces topics (evidence: `README.md`)
- LDA Model → Interpretation Reports: informs report (evidence: `README.md`)
- LDA Model → Interactive Visualizations: feeds charts (evidence: `README.md`)
- Streamlit Dashboard → Text Preprocessing: shows preprocessing (evidence: `README.md`)
- Streamlit Dashboard → Document-Term Matrix: shows matrix (evidence: `README.md`)
- Streamlit Dashboard → Topic Word Lists: shows topics (evidence: `README.md`)
- Streamlit Dashboard → Interpretation Reports: shows report (evidence: `README.md`)
- Streamlit Dashboard → Interactive Visualizations: shows charts (evidence: `README.md`)