Rewrite README: lightweight RAG demo, sample corpus, medical disclaimer, no Merck content

README.md

@@ -1,6 +1,6 @@
 ---
 title: FetchMerck AI Demo
-emoji: 💬
+emoji: 🩺
 colorFrom: yellow
 colorTo: purple
 sdk: gradio
@@ -11,7 +11,58 @@ hf_oauth: true
 hf_oauth_scopes:
 - inference-api
 license: apache-2.0
-short_description: RAG clinical decision support from the Merck Manuals
+short_description: Lightweight RAG demo for clinical decision support
 ---
 
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+# FetchMerck AI — Demo
+
+A lightweight, public **demonstration** of a Retrieval-Augmented Generation (RAG)
+pipeline for clinical decision support.
+
+This Space uses:
+
+- A small in-memory **sample corpus** of original, paraphrased clinical
+  reference snippets (no copyrighted source material).
+- `sentence-transformers/all-MiniLM-L6-v2` for embeddings.
+- Cosine-similarity retrieval over a NumPy matrix (no vector DB).
+- A hosted generation model via the Hugging Face Inference API.
+
+## ⚠️ Medical Disclaimer
+
+This Space is an **educational prototype only**. It is **not a medical device**
+and must **not** be used for diagnosis, treatment, triage, or any clinical
+decision-making. Outputs may be inaccurate or incomplete. Always consult a
+licensed clinician for medical questions.
+
+## How it works
+
+1. The user enters a clinical question.
+2. The query is embedded and compared against the sample corpus by cosine similarity.
+3. The top-k passages are concatenated as grounded context.
+4. A hosted instruction-tuned LLM is asked to answer **only** from that context.
+5. The response is shown along with the source section names and a disclaimer.
+
+## Configuration
+
+Optional environment variables / Space secrets:
+
+- `HF_TOKEN` — Hugging Face token (needed only for gated or private generation models).
+- `GEN_MODEL` — override the generation model (default: `meta-llama/Llama-3.1-8B-Instruct`).
+
+## Roadmap
+
+This is the v0 publishable baseline. Planned upgrades, in order:
+
+1. Replace the sample corpus with a **legally publishable** medical reference
+   corpus (e.g., openly licensed clinical guidelines, public-domain references,
+   or content the project is licensed to redistribute).
+2. Move retrieval to a persistent vector store (e.g., Chroma) once the corpus grows.
+3. Pre-build and ship a vector index alongside the Space.
+4. Optionally add local GGUF inference on GPU hardware.
+
+## What this Space deliberately does **not** do
+
+- It does **not** include or redistribute the Merck Manuals or any other
+  restricted, paywalled, or copyrighted clinical reference content.
+- It does **not** persist user data; the in-memory index is rebuilt each cold start.
+- It does **not** provide medical advice.