topk-sdk 0.9.3

Python SDK for topk.io

TopK Python SDK

The TopK Python library provides convenient access to the TopK API from any Python 3.9+ application. The library includes type definitions for all request params and response fields, and features both synchronous and asynchronous clients.

Documentation

The full documentation can be found at docs.topk.io.

The Python SDK reference can be found at docs.topk.io/sdk/topk-py.

Installation

pip install topk-sdk

# or

uv add topk-sdk

Prerequisites

• API key — sign in to console.topk.io and generate an API key.
• Region — available regions are listed at docs.topk.io/regions.

Usage

import os
from topk_sdk import Client

client = Client(
    api_key=os.environ.get("TOPK_API_KEY"),
    region="aws-us-east-1-elastica",
)

# Create a dataset
client.datasets().create("my-dataset")

# Upload a file
handle = client.dataset("my-dataset").upsert_file(
    "doc-1",
    input="/path/to/document.pdf",
    metadata={"kind": "report", "department": "finance"},  # optional metadata
)

# Wait for the file to process (optional)
client.dataset("my-dataset").wait_for_handle(handle)

# Ask a question
for message in client.ask(
    "What was the total net income of Bank of America in 2024?",
    datasets=["my-dataset"],
):
    print(message)

Async usage

Simply import AsyncClient instead of Client and use async for / await with each API call:

import os
import asyncio
from topk_sdk import AsyncClient

client = AsyncClient(
    api_key=os.environ.get("TOPK_API_KEY"),
    region="aws-us-east-1-elastica",
)

async def main() -> None:
    await client.datasets().create("my-dataset")

    handle = await client.dataset("my-dataset").upsert_file(
        "doc-1",
        input="/path/to/document.pdf",
        metadata={"kind": "report", "department": "finance"},
    )
    await client.dataset("my-dataset").wait_for_handle(handle)

    async for message in client.ask(
        "What was the total net income of Bank of America in 2024?",
        datasets=["my-dataset"],
    ):
        print(message)

asyncio.run(main())

Functionality between the synchronous and asynchronous clients is otherwise identical.

Handling errors

from topk_sdk.error import (
    DatasetNotFoundError,
    PermissionDeniedError,
    QuotaExceededError,
    SlowDownError,
)

try:
    for message in client.ask(
        "What was the total net income of Bank of America in 2024?",
        datasets=["my-dataset"],
    ):
        print(message)
except DatasetNotFoundError:
    print("Dataset does not exist")
except PermissionDeniedError:
    print("Check your API key")
except QuotaExceededError:
    print("Usage quota exceeded")
except SlowDownError:
    print("Rate limited — the client will retry automatically")

Error	Description
CollectionNotFoundError	Collection does not exist
CollectionAlreadyExistsError	Collection with this name already exists
CollectionValidationError	Invalid collection name or schema
DatasetNotFoundError	Dataset does not exist
DatasetAlreadyExistsError	Dataset with this name already exists
DocumentValidationError	Invalid document
SchemaValidationError	Invalid schema
PermissionDeniedError	Invalid or missing API key
QuotaExceededError	Usage quota exceeded
RequestTooLargeError	Request payload too large
SlowDownError	Rate limited by the server (retried automatically)
QueryLsnTimeoutError	Timed out waiting for write consistency

Retries

The client automatically retries on SlowDownError and on LSN consistency timeouts. Retry behaviour can be configured via RetryConfig:

from topk_sdk import Client, RetryConfig, BackoffConfig

client = Client(
    api_key=os.environ.get("TOPK_API_KEY"),
    region="aws-us-east-1-elastica",
    retry_config=RetryConfig(
        max_retries=5,        # default: 3
        timeout=60_000,       # total retry chain timeout in ms, default: 30,000
        backoff=BackoffConfig(
            init_backoff=200, # default: 100 ms
            max_backoff=5_000, # default: 10,000 ms
        ),
    ),
)

Requirements

Python 3.9 or higher.