# Structured Log Parser

This project demonstrates how to parse raw log lines into typed events using **Pydantic v2** and **LangChain**'s structured output.  
It supports two event types:

| Event | Fields |
|-------|--------|
| `HttpOkEvent` | `kind="ok"`, `status=200`, `path`, `duration_ms` |
| `HttpErrorEvent` | `kind="error"`, `status` (4xx/5xx), `path`, `error_message` |

The parser uses a LangChain prompt to convert each log line into a JSON object that matches one of the schemas. The output is then validated with Pydantic.

## Features

- **Discriminated Union**: `ApiEvent` is a union of `HttpOkEvent` and `HttpErrorEvent` with a `kind` discriminator.
- **Structured Output**: Uses LangChain's `PydanticOutputParser` to enforce schema.
- **Batch Parsing**: Handles multiple log lines in a single run.
- **CLI**: Accepts example logs, a file, or custom text and prints a table of parsed events.

## Installation

```bash
# Clone the repo
git clone https://github.com/yourusername/structured-log-parser.git
cd structured-log-parser

# Create a virtual environment (optional but recommended)
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt
```

## Usage

### 1. Using the built‑in example

```bash
python -m src.main --example
```

### 2. Parsing a log file

```bash
python -m src.main --file path/to/log.txt
```

### 3. Parsing custom text

```bash
python -m src.main --text "2026-08-31 12:00:01 INFO /api/users 200 123ms"
```

The output will be a Markdown‑style table:

```
| kind | path          | status | duration_ms / error_message |
|------|---------------|--------|-----------------------------|
| ok   | /api/users    | 200    | 123 ms                      |
| error| /api/orders   | 404    | Not Found                   |
| error| /api/payments | 500    | Internal Server Error       |
| ok   | /api/products | 200    | 45 ms                       |
```

## Environment Variables

The project uses OpenAI's API. Set the following variable before running:

```bash
export OPENAI_API_KEY="sk-..."
```

Alternatively, create a `.env` file in the project root:

```
OPENAI_API_KEY=sk-...
```

The `python-dotenv` package will load it automatically.

## Project Structure

```
src/
├── __init__.py
├── main.py          # CLI entry point
├── cli.py           # Argument parsing and table rendering
├── parser.py        # Log parsing logic
└── models.py        # Pydantic event models
```

## License

MIT License