README.md

metadata

title: InstaAutoApp TeamDataMavericks
emoji: 🚗
colorFrom: red
colorTo: yellow
sdk: gradio
sdk_version: 4.44.1
python_version: '3.11'
app_file: app.py
pinned: false
license: mit
short_description: AI-Powered Symptom Triage for 2023 Ford Bronco

🚗 Insta-AutoApp

AI-Powered Symptom Triage for 2023 Ford Bronco

Insta-AutoApp is a RAG-based (Retrieval-Augmented Generation) application that helps 2023 Ford Bronco owners understand warning lights and vehicle symptoms. Describe your issue in plain English and receive structured, OEM-grounded triage guidance in under 60 seconds.

---

🌟 Features

• OEM-Grounded Responses: All answers are based on the official 2023 Ford Bronco Owner's Manual
• Structured Triage Output: Every response includes Urgency Level, Likely Meaning, Next Step, and OEM Citation
• Vehicle-Specific Follow-ups: AI asks Bronco-specific clarifying questions (GOAT modes, Sasquatch package, etc.)
• Safety-First Design: Conservative defaults for brake, steering, and drivetrain issues
• No Fabrication: If the manual doesn't cover it, the app says so

---

🚀 Quick Start

Prerequisites

• Python 3.10+
• HuggingFace API token (get one here)
• 2023 Ford Bronco Owner's Manual PDF

Installation

1. Clone or download this repository

git clone https://github.com/your-repo/insta-autoapp.git
cd insta-autoapp

2. Create a virtual environment (recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Configure environment

cp .env.example .env
# Edit .env and add your HuggingFace API token

5. Ingest the OEM Manual (one-time setup)

# Place your Bronco manual PDF in a convenient location
python ingest.py path/to/bronco_2023_manual.pdf

6. Launch the app

python app.py

7. Open in browser: http://localhost:7860

---

📁 Project Structure

insta-autoapp/
├── app.py              # Main Gradio application
├── config.py           # Configuration constants
├── prompts.py          # LLM system prompts
├── llm_client.py       # HuggingFace Inference API client
├── rag_pipeline.py     # FAISS retrieval logic
├── ingest.py           # PDF preprocessing script
├── requirements.txt    # Python dependencies
├── .env.example        # Environment template
├── README.md           # This file
└── data/               # FAISS index (created by ingest.py)
    ├── index.faiss
    └── index.pkl

---

🔧 Configuration

Environment Variables

Variable	Required	Default	Description
HF_API_TOKEN	Yes	-	HuggingFace API token for LLM inference
HF_MODEL_ID	No	Qwen/Qwen2.5-72B-Instruct	Model ID for inference
TOP_K	No	5	Number of chunks to retrieve

Vehicle Profile Options

The app only accepts valid 2023 Ford Bronco configurations:

• Trim: Base, Big Bend, Black Diamond, Badlands, Outer Banks, Wildtrak, Raptor
• Engine: 2.3L EcoBoost, 2.7L EcoBoost
• Package: None, Sasquatch, Lux, Sasquatch + Lux
• Top Type: Soft Top, Hard Top, Modular Top
• Mileage: 0 - 300,000

---

🤖 How It Works

Architecture

User Input (Symptom)
       │
       ▼
┌──────────────────┐
│ Follow-up Gen    │ ◄── LLM (Qwen2.5-72B)
│ (1-2 questions)  │
└────────┬─────────┘
         │
         ▼
┌──────────────────┐
│ Combined Query   │ = Symptom + Vehicle Profile + Follow-up Answers
└────────┬─────────┘
         │
         ▼
┌──────────────────┐
│ FAISS Retrieval  │ ◄── Top-5 OEM manual chunks
│ (all-MiniLM-L6)  │
└────────┬─────────┘
         │
         ▼
┌──────────────────┐
│ Triage Gen       │ ◄── LLM with retrieved context
│ (4-field output) │
└────────┬─────────┘
         │
         ▼
   Structured Response
   + Disclaimer

Urgency Levels

Level	Meaning	Action
Safe	Cosmetic or informational	No action required
Monitor	Non-critical issue	Check within 7 days if persists
Urgent	Needs attention	Schedule service, limit driving
Do Not Drive	Safety-critical	Stop immediately, seek assistance

---

🚀 Deployment to HuggingFace Spaces

1. Create a new Space at https://huggingface.co/new-space

   • Select "Gradio" as the SDK
   • Choose a name (e.g., insta-autoapp)

2. Clone the Space repository

git clone https://huggingface.co/spaces/YOUR_USERNAME/insta-autoapp
cd insta-autoapp

3. Copy all files from this project into the Space folder

4. Add your FAISS index (from running ingest.py locally)

   • Copy data/index.faiss and data/index.pkl to the Space

5. Set Space Secrets

   • Go to Settings → Variables and secrets
   • Add HF_API_TOKEN as a secret

6. Push to deploy

git add .
git commit -m "Initial deployment"
git push

---

⚠️ Limitations

• Single Vehicle: V1 supports only 2023 Ford Bronco. Multi-vehicle support planned for V2.
• Text Only: No image/photo upload. No voice input.
• Ephemeral Sessions: Vehicle profile and history are not saved across sessions.
• Table Extraction: Table-heavy manual sections (fluid specs, fuse layouts) may have degraded extraction quality.
• Not a Diagnosis: This is triage guidance, not professional mechanical advice.

---

🔒 Privacy

• No PII Collected: No names, emails, or personal data stored
• Ephemeral Sessions: All session data is lost when browser closes
• Local Data: FAISS index stored locally, not transmitted
• API Calls: Only symptom text is sent to HuggingFace API for inference

---

📝 License

MIT License - See LICENSE file for details.

---

👥 Team

Data Mavericks - ANLY 601 Advanced Coding for Business
Texas A&M University, Mays Business School

• Nasser Chaudhry
• Miriam Camacho
• Neil Driscoll

---

🙏 Acknowledgments

• OEM Manual Source: CarManualsOnline.info
• Embedding Model: sentence-transformers/all-MiniLM-L6-v2
• LLM: Qwen/Qwen2.5-72B-Instruct