README.md

metadata

title: Fist-aid assitant
emoji: 🚀
colorFrom: blue
colorTo: green
sdk: streamlit
sdk_version: 1.33.0
app_file: app.py
pinned: false

Snakebit Firstaid 🚀

Short description: Web application that provides quick, essential first-aid guidance for snakebite (poisoned wound) and normal wounds, and then offers an advanced ChatGPT-powered assistant to deliver tailored next-step guidance.

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Features

• Simple, two-panel quick-first-aid interface:

  • Left: Snakebite (poisoned wound) — short essential steps.
  • Right: Normal wound — short essential steps.
  • Users confirm completion and press Next → Advanced which forwards the wound type to the advanced assistant.

• Advanced assistant powered by OpenAI ChatGPT (via the openai package):

  • Confirms basic-first-aid steps completed.
  • Collects victim information (name, age, height, weight, notes).
  • Saves victim info to ./data/victims.json.
  • Provides in-depth, concise first-aid & monitoring steps and supports follow-up questions.

• Safe defaults for deployment (server settings in .streamlit/config.toml).

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Files in the repo

• app.py — main Streamlit app (single-file app).
• requirements.txt — project dependencies.
• .streamlit/config.toml — UI theme + server defaults.
• .streamlit/secrets.toml — (empty by default; store OPENAI_API_KEY here locally if needed — do not commit).
• data/victims.json — auto-created and appended with victim records by the app (add data/.gitkeep if you want the empty folder tracked).
• .gitignore — prevents committing secrets, virtualenvs, and local data.
• README.md — this document.

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Quick start (local)

Tested with Python 3.10+ (recommend 3.11). Adjust if your environment differs.

1. Create a virtual environment and activate it:

python -m venv .venv
# macOS / Linux
source .venv/bin/activate
# Windows (PowerShell)
.\.venv\Scripts\Activate.ps1

2. Install dependencies:

pip install -r requirements.txt

3. Provide your OpenAI API key securely. Recommended options:

• Add to environment (temporary):

export OPENAI_API_KEY="sk-..."
# Windows PowerShell
$env:OPENAI_API_KEY = "sk-..."

• OR (local only, not for public repos) add to .streamlit/secrets.toml:

OPENAI_API_KEY = "sk-REPLACE_WITH_YOUR_KEY"
# Optionally set the model
# OPENAI_MODEL = "gpt-4o-mini"

4. Run the app:

streamlit run app.py

Open the address printed by Streamlit (usually http://localhost:8501).

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Deploying to Hugging Face Spaces (Streamlit)

1. Create a new Space on Hugging Face and choose Streamlit as the SDK.
2. Push this repository (all files except secrets) to the Space.
3. In the Space settings, add a secret named OPENAI_API_KEY with your OpenAI key. Do not commit secrets.toml to the repo.
4. Start the Space — it will use app.py automatically.

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Configuration & secrets

• .streamlit/config.toml contains the UI theme and safe server defaults (headless mode, address 0.0.0.0, disabled XSRF for certain container environments).
• Never commit .streamlit/secrets.toml (contains API keys). Add it to .gitignore (already provided).

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Security & emergency notes

• This app is not a substitute for professional medical care. It gives short, essential guidance to assist non-professionals.
• If a victim is deteriorating, losing consciousness, has severe bleeding, or you suspect life-threatening poisoning, call local emergency services immediately.
• The app stores victim records in ./data/victims.json. Treat this as potentially sensitive information; if you deploy publicly, review data retention policies and consider adding encryption or removing storage.

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Requirements

See requirements.txt. Minimal runtime packages include streamlit and openai. Optionally include toml, python-dotenv, and Pillow.

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Development notes

• The app accepts OPENAI_MODEL environment variable to override the default model used.
• The app supports both the modern openai.OpenAI(api_key=...) client shape and the classic openai package usage (the code tries both imports).
• data/victims.json is appended; if you want the directory tracked but empty, create data/.gitkeep and commit it.

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Contributing

If you want improvements (multi-page separation, richer UI, persistent DB, authentication, localization), open an issue or send a pull request. I can help implement features such as:

• Separate pages for the simple/advanced parts (actual next.py pages).
• Better UX: progress indicators, larger touch targets, i18n (Vietnamese + English).
• Replace local JSON file with small database (SQLite) or cloud storage for multi-user deployments.

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License

Add a license (e.g., MIT) — currently not set in this repo.