polymathy 0.2.0

Turn search results into answers - a web service that fetches, chunks, and returns semantic content from search queries
Documentation
# Examples

Practical examples for using Polymathy in different scenarios.

## Available Examples

<div class="grid cards" markdown>

-   :material-magnify:{ .lg .middle } __Basic Search__

    ---

    Simple search queries using curl, Python, and JavaScript

    [:octicons-arrow-right-24: Basic Search]basic-search.md

-   :material-library:{ .lg .middle } __Library Usage__

    ---

    Using Polymathy as a Rust library in your project

    [:octicons-arrow-right-24: Library Usage]library-usage.md

-   :material-docker:{ .lg .middle } __Docker Deployment__

    ---

    Containerized deployment with Docker Compose

    [:octicons-arrow-right-24: Docker Deployment]docker-deployment.md

</div>

## Quick Examples

### curl

```bash
curl "http://localhost:8080/v1/search?q=artificial+intelligence"
```

### Python

```python
import requests

response = requests.get(
    "http://localhost:8080/v1/search",
    params={"q": "machine learning"}
)
print(response.json())
```

### JavaScript

```javascript
const response = await fetch(
    'http://localhost:8080/v1/search?q=web+development'
);
const data = await response.json();
console.log(data);
```

## Common Patterns

### Error Handling

Always handle potential errors:

```python
try:
    response = requests.get(url, params=params, timeout=30)
    response.raise_for_status()
    return response.json()
except requests.RequestException as e:
    print(f"Search failed: {e}")
    return {}
```

### Processing Results

Results come as a dictionary of `{id: [url, content]}`:

```python
results = search("your query")
for chunk_id, (url, content) in results.items():
    # Process each chunk
    print(f"From: {url}")
    print(f"Content: {content}")
```