Upstash Python QStash SDK

QStash is an HTTP based messaging and scheduling solution for serverless and edge runtimes.

QStash Documentation

Install

pip install qstash

Usage

You can get your QStash token from the Upstash Console.

Publish a JSON message

from qstash import QStash

client = QStash("<QSTASH_TOKEN>")

res = client.message.publish_json(
    url="https://example.com",
    body={"hello": "world"},
    headers={
        "test-header": "test-value",
    },
)

print(res.message_id)

Create a scheduled message

from qstash import QStash

client = QStash("<QSTASH_TOKEN>")

schedule_id = client.schedule.create(
    destination="https://example.com",
    cron="*/5 * * * *",
)

print(schedule_id)

Receiving messages

from qstash import Receiver

# Keys available from the QStash console
receiver = Receiver(
    current_signing_key="CURRENT_SIGNING_KEY",
    next_signing_key="NEXT_SIGNING_KEY",
)

# ... in your request handler

signature, body = req.headers["Upstash-Signature"], req.body

receiver.verify(
    body=body,
    signature=signature,
    url="https://example.com",  # Optional
)

Create Chat Completions

from qstash import QStash
from qstash.chat import upstash

client = QStash("<QSTASH_TOKEN>")

res = client.chat.create(
    model="meta-llama/Meta-Llama-3-8B-Instruct",
    provider=upstash(),
    messages=[
        {
            "role": "user",
            "content": "What is the capital of Turkey?",
        }
    ],
)

print(res.choices[0].message.content)

Create Chat Completions Using Custom Providers

from qstash import QStash
from qstash.chat import openai

client = QStash("<QSTASH_TOKEN>")

res = client.chat.create(
    model="gpt-3.5-turbo",
    provider=openai("<OPENAI_API_KEY>"),
    messages=[
        {
            "role": "user",
            "content": "What is the capital of Turkey?",
        }
    ],
)

print(res.choices[0].message.content)

Publish a JSON message to LLM

from qstash import QStash
from qstash.chat import upstash

client = QStash("<QSTASH_TOKEN>")

res = client.message.publish_json(
    api={"name": "llm", "provider": upstash()},
    body={
        "model": "meta-llama/Meta-Llama-3-8B-Instruct",
        "messages": [
            {
                "role": "user",
                "content": "What is the capital of Turkey?",
            }
        ],
    },
    callback="https://example-cb.com",
)

print(res.message_id)

Publish a JSON message to LLM Using Custom Providers

from qstash import QStash
from qstash.chat import openai

client = QStash("<QSTASH_TOKEN>")

res = client.message.publish_json(
    api={"name": "llm", "provider": openai("<OPENAI_API_KEY>")},
    body={
        "model": "gpt-3.5-turbo",
        "messages": [
            {
                "role": "user",
                "content": "What is the capital of Turkey?",
            }
        ],
    },
    callback="https://example-cb.com",
)

print(res.message_id)

Additional configuration

from qstash import QStash

# Create a client with a custom retry configuration. This is
# for sending messages to QStash, not for sending messages to
# your endpoints.
# The default configuration is:
# {
#   "retries": 5,
#   "backoff": lambda retry_count: math.exp(retry_count) * 50,
# }
client = QStash(
    token="<QSTASH_TOKEN>",
    retry={
        "retries": 1,
        "backoff": lambda retry_count: (2 ** retry_count) * 20,
    },
)

# Publish to URL
client.message.publish_json(
    url="https://example.com",
    body={"key": "value"},
    # Retry sending message to API 3 times
    # https://upstash.com/docs/qstash/features/retry
    retries=3,
    # Schedule message to be sent 4 seconds from now
    delay="4s",
    # When message is sent, send a request to this URL
    # https://upstash.com/docs/qstash/features/callbacks
    callback="https://example.com/callback",
    # When message fails to send, send a request to this URL
    failure_callback="https://example.com/failure_callback",
    # Headers to forward to the endpoint
    headers={
        "test-header": "test-value",
    },
    # Enable content-based deduplication
    # https://upstash.com/docs/qstash/features/deduplication#content-based-deduplication
    content_based_deduplication=True,
)

Additional methods are available for managing url groups, schedules, and messages. See the examples folder for more.

Development

1. Clone the repository
2. Install Poetry
3. Install dependencies with poetry install
4. Create a .env file with cp .env.example .env and fill in the QSTASH_TOKEN
5. Run tests with poetry run pytest
6. Format with poetry run ruff format .