---
title: Ai Econsult Demo
emoji: 🚀
colorFrom: red
colorTo: red
sdk: streamlit
app_port: 8501
tags:
- streamlit
pinned: false
short_description: Streamlit template space
sdk_version: 1.51.0
---

# AI‑Native E‑Consult Prototype (V1)

This Space hosts a Streamlit app for an AI‑native e‑consult workflow (PCP ↔ Specialist).

- **UI:** Streamlit
- **AI:** MedGemma‑27B‑text + optional RAG grounding
- **Storage:** Hugging Face Spaces persistent volume (`/data/econsult/...`)

## Modes available
- **🧠 Guideline‑grounded (RAG):** Injects top guideline snippets into the prompt. Expects inline bracket citations `[1]..[k]` plus a compact reference list.
- **✨ AI‑only (post‑hoc):** No in‑prompt evidence. Performs post‑hoc claim→guideline mapping and returns a compact reference list.

> The previous **Hybrid (AI → RAG)** option has been removed (redundant for this prototype).

## Hardware
- Primary: **1× L40s** (works well for `google/medgemma-27b-text-it`)
- Optional upgrade: **A100 (large)**
- Budget fallback for demos: **L4** with `google/medgemma-4b-it`

> CPU fallback is supported **for resilience only** and will cap tokens for responsiveness. You can disable CPU generation with `ALLOW_CPU_GENERATION=false`.

## Setup
1. Add your Hugging Face token in **Settings → Variables** as `HF_TOKEN` (required to pull gated models).
2. (Optional) Set environment variables:
   - `ALLOW_CPU_GENERATION=true|false` (default: `true`)
   - `FORCE_CPU_LLM=1` to force CPU fallback to the 4B model
   - `MODEL_FALLBACK_ID=google/medgemma-4b-it` to override the fallback id
3. Upload guideline PDFs on the **“Step 1 – RAG Corpus Prep”** page. Filenames should follow:  
   `[specialty]_guideline_[condition]_year.pdf`

## What changed in this revision
- Removed **AI triage** across UI and storage. The PCP must choose a **Consult specialty**.
- Removed the **Hybrid** button on the Specialist tab.
- Added a **demo‑only / de‑identified** banner to all pages.
- Preserved citations from AI‑only generation (post‑hoc mapping).
- Improved guideline filename parsing to your taxonomy (`[specialty]_guideline_...`).
- Added a per‑specialty count widget on the RAG page.
- Cleaned up docs for native Spaces runtime. **Removed the Dockerfile** (not used).

## Notes
- This prototype is **not for clinical use**. Use only de‑identified/mock data in demos.
- After you confirm stability on Spaces, we can pin dependency minor versions for reproducibility.