semantic-qna

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A semantic FAQ assistant (CLI + web UI) using AWS Bedrock embeddings & TiDB Cloud vector search, with built-in progress bars and automated tests.

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// repository documentation

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# Semantic FAQ CLI

Think of this as your go-to command-line buddy that fetches answers based on what you *mean* not just the exact words you type. Under the hood, it taps into [TiDB Cloud’s](https://auth.tidbcloud.com/login) vector columns and [AWS Bedrock Titan-V2 embeddings](https://docs.aws.amazon.com/bedrock/latest/userguide/titan-embedding-models.html), all wrapped up in pure Python.

---

## 🚀 Features

- **Semantic search, minus the fluff**  
  Store question embeddings in TiDB and let vector lookups do the heavy lifting.

- **Raw Bedrock power**  
  No LangChain wrappers, just straight JSON calls so you see exactly what Titan-V2 returns.

- **Serverless-ready**  
  A free TiDB Serverless cluster and AWS keys are all you need to get started.

- **Pure Python CLI**  
  Fire it up, ask a question, get an answer. No extra services required.

---

## 🛠️ Quick Start Prerequisites

- **macOS** with **Python 3.8+**  
- AWS CLI v2 configured (`aws configure`)  
- A TiDB Cloud Serverless cluster (free tier works)  
- Root CA at `/etc/ssl/cert.pem` (macOS default)

### Install Dependencies

```bash
pip install -r requirements.txt
```

### Required Environment Variables

Create a `.env` file based on the .env.example template and fill in your own values:

```bash
cp .env.example .env
# edit .env with your secrets
```

- `DATABASE_URL` – TiDB connection string
- `AWS_REGION` – AWS region for Bedrock (defaults to `us-east-1`)
- `FAQ_FILE` – path to the FAQ JSON file (defaults to faqs.json)

## 🔍 Using the CLI

After configuring your environment variables and installing dependencies you can
run the interactive command-line assistant:

```bash
python app.py
```

Type a question and you'll get back the closest stored FAQ entry. Enter
`exit` to quit.
---

## 🌐 Web Interface

Prefer a web page over a terminal? Here’s how:

1. **Install dependencies**
   ```bash
   pip install -r requirements.txt
   ```

2. **Check that `server.py` and `index.html` live in your project folder.**

3. **Start the dev server with a progress bar**
   ```bash
   python run_with_bar.py
   ```

*(This script runs Uvicorn and waits for the `/health` endpoint to respond before handing over the logs.)*
4. **Run the server manually (alternative)**
   ```bash
   uvicorn server:app --reload --host 0.0.0.0 --port 8000
   ```

5. **Open your browser** to <http://localhost:8000> and start asking questions.

6. The included `index.html` uses React (loaded via CDN) so you get a modern UI
   with a growing history of your queries and results.

## Running Tests

Install development dependencies and run pytest:

```bash
pip install -r requirements.txt
pytest
```

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