Practical overview
When it fits
Use PoRAG when you want to prototype or build a configurable Bengali RAG workflow over plain-text files and can manage its Python environment and model choices.
Who it is for
- Developers building Bengali-language question-answering tools over text collections.
- Teams seeking configurable, self-hosted retrieval and generation for Bengali documents.
Documented uses
- Ask questions in Bengali about information in a Bengali text corpus.
- Build a knowledge-search or question-answering workflow over .txt documents.
- Tune model selection, retrieval count, chunking and generation parameters.
Requirements & limits
PoRAG is a public GitHub repository with an MIT license; the documented workflow is self-hosted.
- Input ingestion is documented for .txt files only; other formats require text conversion.
- The pipeline uses ChromaDB for vector storage and Sentence Transformers-compatible embeddings with a stated dimension of 768.
- The README documents a quantization option and configurable generation and retrieval parameters.
- Installation is via Python dependencies in the repository; a Hugging Face token may be needed for some model choices.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Run questions against a Bengali text file
Use the documented command-line workflow to ask questions about a Bengali .txt corpus.
Before you start
- Python and Git
- A clone of the PoRAG repository with its requirements installed
- A Bengali text corpus saved as a .txt file
- A Hugging Face token if required by the selected model
Steps
Clone the repository and change into its directory.
Install the listed dependencies with the command below.
pip install -r requirements.txtPrepare a Bengali text file and run the command below, replacing the filename with your file’s path.
python main.py --text_path test.txtType a question when prompted; add
--show_contextto display retrieved context.
Expected outcome
An interactive terminal workflow returns an answer based on information retrieved from the supplied text file.
Guide limitations
- The documented ingestion format is .txt only; the README notes Bengali PDF parsing limitations.
- Model and embedding choices must be compatible with the supported Transformers and Sentence Transformers integrations.
Compare options for Retrieval-augmented applications
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Porag | Ask questions in Bengali about information in a Bengali text corpus. | Self-hosted | PoRAG is a public GitHub repository with an MIT license; the documented workflow is self-hosted. |
| Langsearch | Crawl website or local data for a knowledge base. | CLI, Self-hosted, Server | |
| Hybrid Search Rag | Combine document retrieval and language-model generation in a configurable workflow. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 16 October 2026
- Original website title
- Bangla-RAG/PoRAG · Official homepage title · retained in its source language

