llama-search 0.3.4

Official Python SDK for Llama Search AI Platform

Llama Search Python SDK

The official Python SDK for the Llama Search AI Platform. This SDK provides a simple, intuitive interface for integrating AI-powered web search capabilities into your applications.

Installation

pip install llama-search

Quick Start

First, set your API key as an environment variable:

export LLAMA_SEARCH_API_KEY="your_api_key_here"

Or create a .env file:

LLAMA_SEARCH_API_KEY=your_api_key_here

Async Usage (Recommended)

from llama_search import AsyncLlamaSearch

async def main():
    # API key loaded from LLAMA_SEARCH_API_KEY environment variable
    async with AsyncLlamaSearch() as client:
        # Perform a web search
        result = await client.web_search(
            query="Tesla Model 3 battery specifications",
            search_depth="standard"
        )

        print(f"Found {len(result.sources)} sources")
        for source in result.sources:
            print(f"- {source.url}: {source.content[:100]}...")

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

import asyncio
asyncio.run(main())

Sync Usage

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"
    )

    print(f"Found {len(result.sources)} sources")
    for source in result.sources:
        print(f"- {source.url}: {source.content[:100]}...")

    # Check account usage
    stats = client.get_usage_stats()
    print(f"Credits remaining: {stats.credits_remaining}")
    print(f"Total searches: {stats.total_searches}")

API Reference

Core Search Methods

web_search(query, search_depth="standard", domain="", with_full_content=False)

Perform intelligent web search using AI.

Parameters:

• query (str): The search query to execute
• search_depth (str): Search depth level affecting cost and quality
  • "basic": 5 credits, 2 tool calls, low context
  • "standard": 8 credits, 3 tool calls, medium context (default)
  • "extensive": 15 credits, 5 tool calls, high context
• domain (str): Optional domain filter (e.g., "reddit.com")
• with_full_content (bool): Whether to fetch full content from URLs

Returns: WebSearchResult containing sources and metadata

result = await client.web_search("Python asyncio best practices", search_depth="extensive")
print(f"Credits consumed: {result.credits_consumed}")

get_search_types()

Get available search types and their costs.

Returns: SearchTypesResponse containing 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")

Account Management

get_usage_stats()

Get current usage statistics for your account.

Returns: UsageStats containing search counts, credits used/remaining, monthly usage

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

get_search_history(limit=10)

Get your recent search history.

Parameters:

• limit (int): Maximum number of searches to return (1-100, default: 10)

Returns: SearchHistory containing list of recent searches

history = await client.get_search_history(limit=20)
for search in history.searches:
    print(f"{search.created_at}: {search.query} ({search.credits_consumed} credits)")

Requirements

• Python 3.10+
• httpx >= 0.24.0
• pydantic >= 2.0.0

Development

Running Tests

# Install development dependencies
pip install -e ".[dev]"

# Run tests
make test

# Run tests with coverage
pytest --cov=llama_search

Code Quality

# Format code
make format

# Lint code
make lint

# Type checking
make typecheck

License

MIT License - see LICENSE file for details.

Support

• Documentation: https://llama-search.com/docs
• GitHub Issues: https://github.com/llama-search/llama-search/issues
• Email: [e-mail]