🦙 API Documentation

Integrate powerful AI search capabilities into your applications with our simple REST API and Python SDK

🛠️ cURL Examples

Use your API key from your dashboard to make API calls.

Basic Search Request

bash
curl -X POST "https://llama-search.com/search/web" \
  -H "Authorization: Bearer your-api-key-here" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "find information about RayBan Meta Smart Glass (weight, size)",
    "search_depth": "standard"
  }'

Advanced Search with Options

bash
curl -X POST "https://llama-search.com/search/web" \
  -H "Authorization: Bearer your-api-key-here" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Tesla Model 3 battery specifications",
    "search_depth": "extensive",
    "domain": "reddit.com",
    "with_full_content": true
  }'

Response Example

json
{
  "success": true,
  "sources": [
    {
      "url": "https://www.reddit.com/r/RayBanStories/comments/1crmdlk",
      "content": "• Product: Ray‑Ban Meta Smart Glasses\n• Camera: 12 MP\n• Feature: Meta AI capabilities (described as \"growing Meta AI capabilities\")\n• Weight: 48.6g to 50.8g",
      "full_content": ""
    },
    {
      "url": "https://www.ray-ban.com/usa/smart-glasses/ray-ban-meta",
      "content": "• Ray-Ban Meta Smart Glasses Official Specs\n• Weight: 49.6g (Wayfarer), 50.8g (Headliner)\n• Dimensions: 150mm temple length\n• Frame materials: Acetate and metal options\n• Available in prescription and non-prescription",
      "full_content": ""
    },
    {
      "url": "https://about.meta.com/realitylabs/ray-ban-meta/",
      "content": "• Meta partnership with Ray-Ban\n• Smart glasses with built-in camera and speakers\n• Weight range: 48.6g - 50.8g depending on frame style\n• Size options: Multiple frame sizes available\n• Battery life: All-day use with charging case",
      "full_content": ""
    }
  ],
  "raw_data": "",
  "error_message": "",
  "id": "search_67890",
  "query": "find information about RayBan Meta Smart Glass (weight, size)",
  "credits_consumed": 8,
  "processing_time_ms": 2840,
  "status": "completed"
}

Search Depth Options

Search Depth Credits Cost Description
basic 5 Efficient search across multiple sources with focused results and quick delivery
standard 8 Balanced search with deeper analysis and contextual understanding (default)
extensive 15 Comprehensive search with recursive exploration and detailed source analysis

Request Parameters

Parameter Type Required Default Description
query string required - The search query to execute
search_depth string optional "standard" Search depth: "basic", "standard", or "extensive"
domain string optional "" Optional domain filter (e.g., "reddit.com")
with_full_content boolean optional false Whether to fetch full content from URLs

🐍 Python Examples

Simple Python examples using requests library.

Installation

$ pip install llama-search

Async Usage (Recommended)

python
from llama_search import AsyncLlamaSearch
import asyncio

async def main():
    # API key loaded from LLAMA_SEARCH_API_KEY environment variable
    async with AsyncLlamaSearch() as client:
        # Perform a web search with different depths
        result = await client.web_search(
            query="find information about RayBan Meta Smart Glass (weight, size)",
            search_depth="extensive"  # "basic", "standard", or "extensive"
        )

        print(f"Found {len(result.sources)} sources")
        print(f"Credits used: {result.credits_consumed}")
        print(f"Processing time: {result.processing_time_ms}ms")

        for i, source in enumerate(result.sources, 1):
            print(f"\n--- Source {i} ---")
            print(f"URL: {source.url}")
            print(f"Content: {source.content[:200]}...")

asyncio.run(main())

Sync Usage

python
from llama_search import LlamaSearch

with LlamaSearch() as client:
    # Perform a web search
    result = client.web_search(
        query="Tesla Model 3 battery specifications",
        search_depth="standard",
        domain="reddit.com",  # Optional domain filter
        with_full_content=True  # Fetch full content from URLs
    )

    if result.success:
        print(f"Found {len(result.sources)} sources")
        print(f"Credits used: {result.credits_consumed}")

        for source in result.sources:
            print(f"URL: {source.url}")
            print(f"Content: {source.content}")
            if source.full_content:
                print(f"Full content: {len(source.full_content)} chars")
    else:
        print(f"Search failed: {result.error_message}")

Example Output

text
Found 3 sources
Credits used: 15
Processing time: 3240ms

--- Source 1 ---
URL: https://www.reddit.com/r/RayBanStories/comments/1crmdlk
Content: • Product: Ray‑Ban Meta Smart Glasses
• Camera: 12 MP
• Feature: Meta AI capabilities (described as "growing Meta AI capabilities")
• Weight: 48.6g to 50.8g...

--- Source 2 ---
URL: https://www.ray-ban.com/usa/smart-glasses/ray-ban-meta
Content: • Ray-Ban Meta Smart Glasses Official Specs
• Weight: 49.6g (Wayfarer), 50.8g (Headliner)
• Dimensions: 150mm temple length
• Frame materials: Acetate and metal options...

--- Source 3 ---
URL: https://about.meta.com/realitylabs/ray-ban-meta/
Content: • Meta partnership with Ray-Ban
• Smart glasses with built-in camera and speakers
• Weight range: 48.6g - 50.8g depending on frame style
• Size options: Multiple frame sizes available...

Usage Statistics & History

python
# Check account usage
stats = await client.get_usage_stats()
print(f"Credits remaining: {stats.credits_remaining}")
print(f"Total searches: {stats.total_searches}")
print(f"Searches this month: {stats.searches_this_month}")

# Get search history
history = await client.get_search_history(limit=5)
for search in history.searches:
    print(f"{search.created_at}: {search.query} ({search.credits_consumed} credits)")

# Get available search types
types = await client.get_search_types()
for search_type in types.search_types:
    print(f"{search_type.name}: {search_type.credits} credits")

Need Help?

Visit your dashboard to manage API keys and monitor usage.

For technical support, please contact our development team.