targetai 0.0.5

Python SDK for working with TargetAI tokens

TargetAI Python SDK

Python SDK for working with TargetAI tokens. Provides simple tools for retrieving tokens from TOS backend and deploying token distribution endpoints.

Installation

pip install targetai

Quick Start

TargetAITokenClient - Token Retrieval

from targetai import TargetAITokenClient

# Simplest way - uses default URL https://app.targetai.ai
async def example_simple():
    async with TargetAITokenClient() as client:
        token_response = await client.get_token()
        print(f"Token: {token_response.token}")

# With API key
async def example_with_api_key():
    async with TargetAITokenClient(api_key="your-api-key") as client:
        token_response = await client.get_token()
        print(f"Token: {token_response.token}")

# With custom URL
async def example_custom_url():
    async with TargetAITokenClient("https://your-tos.example.com", api_key="your-api-key") as client:
        token_response = await client.get_token()
        print(f"Token: {token_response.token}")

TargetAITokenServer - Token Distribution Server

from targetai import TargetAITokenServer

# Simplest startup (uses default URL)
def run_server():
    server = TargetAITokenServer(port=8001)
    server.run()  # Blocking startup

# With API key for TOS backend
def run_server_with_key():
    server = TargetAITokenServer(api_key="your-tos-api-key", port=8001)
    server.run()

# With custom TOS backend URL
def run_server_custom():
    server = TargetAITokenServer(
        tos_base_url="https://your-tos.example.com",
        api_key="your-api-key",
        port=8001
    )
    server.run()

# Or asynchronously
async def run_server_async():
    async with TargetAITokenServer(port=8001) as server:
        await server.start()

After starting the server, the following endpoints are available:

• POST /token - token retrieval
• GET /health - health check
• GET /docs - Swagger documentation

Using the /token endpoint

# Simple token request
curl -X POST http://localhost:8001/token

# Response:
{
  "token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."
}

API Reference

TargetAITokenClient

class TargetAITokenClient:
    def __init__(self, 
                 tos_base_url: str = "https://app.targetai.ai",
                 api_key: Optional[str] = None)
    async def get_token(self) -> TokenResponse
    async def close(self)

TargetAITokenServer

class TargetAITokenServer:
    def __init__(self, 
                 tos_base_url: str = "https://app.targetai.ai", 
                 api_key: Optional[str] = None,
                 host: str = "0.0.0.0",
                 port: int = 8001)
    async def start(self)
    async def stop(self)
    def run(self)  # synchronous version

Data Schemas

class TokenResponse:
    token: str

Error Handling

from targetai import TargetAITokenClient, TargetAITokenClientError

try:
    async with TargetAITokenClient() as client:  # Uses default URL
        token = await client.get_token()
except TargetAITokenClientError as e:
    print(f"Error: {e}")

Possible errors:

• TargetAITokenClientError - base client error
• TargetAITokenServerError - base server error

Requirements

• Python 3.8+
• aiohttp >= 3.8.0
• pydantic >= 2.0.0
• fastapi >= 0.100.0
• uvicorn >= 0.20.0

License

MIT