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## Introduction: The API Challenge
Building an AI-powered search engine is one thing. Making it accessible to developers through a clean, intuitive API is another challenge entirely. The underlying AI is complex—involving multi-step reasoning, dynamic web browsing, and sophisticated synthesis—but the API should hide this complexity behind a simple interface.
At Llama-Search, we obsess over developer experience. Here's how we think about API design for AI search.
---
## Principle 1: Simplicity First
The most basic search should require minimal code:
```python
import requests
response = requests.post(
"https://api.llama-search.com/v1/search",
headers={"Authorization": "Bearer YOUR_API_KEY"},
json={"query": "What are the latest developments in quantum computing?"}
)
print(response.json()["answer"])
```
That's it. One endpoint, one parameter. Everything else is optional. We call this the "two-minute integration"—a developer should be able to get their first successful API call within two minutes of reading our docs.
---
## Principle 2: Progressive Disclosure
Simple by default, powerful when needed. Our API supports three search depths:
| Depth | Tool Calls | Best For | Credits |
|-------|------------|----------|---------|
| **Basic** | 2 | Quick facts | 2 |
| **Standard** | 3 | Most queries | 5 |
| **Extensive** | 5 | Deep research | 12 |
Developers start with the defaults and customize as they learn what their use case requires.
---
## Principle 3: Transparency
AI can feel like a black box. We fight this with detailed response metadata:
```json
{
"answer": "...",
"sources": [
{"url": "https://...", "title": "...", "relevance": 0.94}
],
"reasoning_steps": 4,
"tokens_used": 2847,
"search_duration_ms": 3200
}
```
Every response includes the sources consulted, the reasoning steps taken, and the resources consumed. Developers can debug, optimize, and explain the results to their users.
---
## Principle 4: Predictable Pricing
AI costs can spiral unpredictably. We solve this with credit-based pricing:
- Each search depth has a fixed credit cost
- Credits are purchased upfront
- No surprise bills
Developers can budget confidently and implement rate limiting in their applications knowing exactly what each query costs.
---
## What We Learned
Building our API taught us several lessons:
1. **Defaults matter more than options.** Most developers use the defaults. Make them good.
2. **Error messages are documentation.** A clear error message teaches developers how to fix their code.
3. **Latency is a feature.** AI searches take time. We communicate progress and set accurate expectations.
---
## Conclusion
The best APIs disappear. They let developers focus on their application, not on wrestling with the tool. With Llama-Search, our goal is to make AI-powered search feel as natural as calling any other web service.
Check out our documentation to see these principles in action.
Designing APIs for AI-Powered Search
Key principles behind building developer-friendly APIs that expose powerful AI capabilities without complexity.
Ready to try AI-powered search?
Get started with Llama-Search API today.
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