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MMORE is an open-source, end-to-end pipeline to ingest, process, index, and retrieve knowledge from heterogeneous files: PDFs, Office docs, spreadsheets, emails, images, audio, video, and web pages. It standardizes content into a unified multimodal format, supports distributed CPU/GPU processing, and provides hybrid dense+sparse retrieval with an integrated RAG service (CLI, APIs).
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👉 Read the paper for more details (OpenReview): [MMORE: Massive Multimodal Open RAG & Extraction](https://openreview.net/forum?id=6j1HjfIdKn)
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👉 Read the paper for more details (arXiv): [MMORE: Massive Multimodal Open RAG & Extraction](https://arxiv.org/abs/2509.11937)
> :warning:**Check the instructions for contributors directly at [`docs/for_devs.md`](./docs/for_devs.md)**
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### Interactive TUI
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Prefer a guided experience over editing YAML by hand? Install the `tui` extra and launch the interactive Terminal UI:
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```bash
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uv sync --extra tui
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mmore tui
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```
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From the launcher you can:
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- run any stage (process / postprocess / index / rag / chat) interactively,
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- chain the full pipeline (process → postprocess → index → chat),
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- generate stage YAML configs through a guided wizard,
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- pick from existing example configs without leaving the terminal.
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### Minimal Example
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You can use our predefined CLI commands to execute parts of the pipeline. Note that you might need to prepend `python -m` to the command if the package does not properly create bash aliases.
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