auralynq-rag / deploy /huggingface /README_SPACE_TEMPLATE.md
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---
title: Auralynq
emoji: πŸŽ™οΈ
colorFrom: blue
colorTo: purple
sdk: docker
app_port: 7860
pinned: false
license: apache-2.0
short_description: "Local-first, voice-native, agentic RAG with visual citation grounding"
---
# Auralynq (demo Space)
This Space runs [Auralynq](https://github.com/MHHamdan/Auralynq), a
local-first, voice-native, agentic RAG platform, in its **lightweight
offline demo configuration**:
- Hash embeddings + in-memory vector store + extractive answering β€” no GPU,
no model downloads, no paid API keys.
- Pre-loaded with the project's small, original, CC0-licensed
[demo corpus](https://github.com/MHHamdan/Auralynq/tree/main/examples/demo_corpus)
(three documents β€” no private or third-party data).
- Document uploads are **disabled by default** on this Space
(`AURALYNQ_ALLOW_UPLOADS=false`) β€” you can browse and ask questions, but
can't add your own files, so nothing you type gets stored beyond the
current session.
## What data is stored, and for how long
- **This Space has no persistent storage attached.** Everything under
`AURALYNQ_DATA_DIR` β€” the demo corpus's vector index, any chat history β€”
is held in memory/container-local disk only and is **wiped on every
restart or redeploy** of the Space. Nothing survives a rebuild.
- No analytics, no logging of your questions to a third party, no data sent
anywhere except (if you've set an LLM key) to that provider's API.
## Try it
- Ask a question from
[`examples/demo_corpus/expected_questions.md`](https://github.com/MHHamdan/Auralynq/blob/main/examples/demo_corpus/expected_questions.md).
- Click a citation to open the Source Workspace and see the exact
bounding-box highlight in the sample PDF.
- Visit `/modelfit` to see the hardware-aware model-selection tool (numbers
reflect this Space's container, not your own machine).
## Limitations of this demo
- Offline extractive answering verifies pipeline correctness, not answer
quality β€” see the Limitations section in the main repo's `README.md`.
- CPU-only; ModelFit's speed/recommendation numbers reflect this container,
not any GPU you may have.
- No uploads, no persistence, single small demo corpus.
## Duplicate this Space to make it your own
Click **"Duplicate this Space"** (top right). Duplicating copies the
Variables above but **not** Secrets β€” you'll start with the same safe
defaults. From there you can:
- **Enable uploads**: set `AURALYNQ_ALLOW_UPLOADS=true` as a Variable β€”
understand first that a public, unauthenticated Space would let anyone
upload documents that persist for as long as the container runs.
- **Add real model quality**: set `AURALYNQ_LLM__PROVIDER` and the matching
key (`OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, `COHERE_API_KEY`) as **Secrets**
(never Variables).
- **Add persistent storage**: attach Hugging Face Persistent Storage and
point `AURALYNQ_DATA_DIR` at the mounted path β€” read the storage-ownership
caveat in
[`deploy/huggingface/README.md`](https://github.com/MHHamdan/Auralynq/blob/main/deploy/huggingface/README.md)
first; the container runs as a non-root user and the mount may need its
ownership fixed on first boot.
- **Upgrade hardware**: this demo needs no GPU; only upgrade if you've also
configured a real embedding/LLM provider that would benefit from it.
## Source
Full source, docs, and the no-Podman / Podman / server run modes:
<https://github.com/MHHamdan/Auralynq>. License: Apache-2.0 (code);
CC0-1.0 (this Space's demo corpus).