llama-search 0.3.2

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

Async Usage (Recommended)

from llama_search import AsyncLlamaSearch

async def main():
    async with AsyncLlamaSearch(api_key="your_api_key_here") 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(api_key="your_api_key_here") 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)")

Billing Information

get_credit_packages()

Get available credit packages for purchase.

Returns: CreditPackagesResponse containing available packages

packages = await client.get_credit_packages()
for package in packages.packages:
    print(f"{package.name}: {package.credits} credits for {package.price_display}")

get_purchase_history(limit=10)

Get your credit purchase history.

Parameters:

• limit (int): Maximum number of purchases to return (1-50, default: 10)

Returns: PurchaseHistory containing purchase records and totals

history = await client.get_purchase_history()
print(f"Total spent: ${history.total_spent_cents / 100:.2f}")
for purchase in history.purchases:
    print(f"{purchase.created_at}: {purchase.package_name} - {purchase.credits} credits")

Error Handling

The SDK provides specific exceptions for different error scenarios:

from llama_search._exceptions import (
    InsufficientCreditsError,
    ValidationError,
    AuthenticationError,
    RateLimitError
)

try:
    result = await client.web_search("example query")
except InsufficientCreditsError as e:
    print(f"Need {e.credits_required} credits, have {e.credits_available}")
except ValidationError as e:
    print(f"Invalid request: {e}")
except AuthenticationError:
    print("Invalid API key")
except RateLimitError as e:
    print(f"Rate limited, retry after {e.retry_after} seconds")

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]