Metadata-Version: 2.4
Name: vela-sdk
Version: 0.1.1
Summary: Observability and runtime governance for AI agent pipelines
License: MIT
Project-URL: Homepage, https://dashboard-one-tau-97.vercel.app
Project-URL: Repository, https://github.com/bowensam155-3751/vela-ai
Keywords: ai,agents,observability,llm,tracing
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: requests>=2.28.0

# Vela

See inside your AI pipelines. Know what's slow, what's failing, and what's costing you money.

## Install

```bash
# Create and activate a virtual environment
python3 -m venv venv
source venv/bin/activate

# Install vela-sdk
pip3 install vela-sdk
```

On Python 3.11+, virtual environments are required due to system protection. On Windows, use `venv\Scripts\activate` instead.

## Get your API key

https://dashboard-one-tau-97.vercel.app/keys

## Instrument your pipeline

```python
import vela

vela.init(api_key='your-key-here')

@vela.trace
def researcher(topic):
    # your existing code — unchanged
    ...

@vela.trace
def writer(research):
    # your existing code — unchanged
    ...

vela.new_session()
result = researcher('your topic')
output = writer(result)
vela.end_session()
```

## See your traces

https://dashboard-one-tau-97.vercel.app?key=your-key-here

That's it. No other changes to your code.

## Optional: label your sessions

```python
vela.new_session(label='production run')
```

## Optional: track model and cost

```python
@vela.trace(name='researcher', model='gpt-4o')
def researcher(topic):
    ...
```
