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<@ULVA73B9P> when is prefect officially sunsetting...
# ask-marvin
m
@Marvin when is prefect officially sunsetting agents?
m
You want to know when Prefect agents are officially being retired. Are you using Prefect 2.x or 3.x?
m
@Marvin using this image prefecthq/prefect:2.14-python3.11
m
Prefect is recommending users to upgrade from agents to workers. The sunset date for agents is mentioned for March 2024. For more detailed info, you can refer to the upgrade guide. Links: - Prefect GCP Integration - Agents Documentation
m
@Marvin Hi, i've made no changes to infra but i am getting this error when submitting tasks : 
No such command 'agent'
assuming somewhere it's using an updated version of prefect-3.0.1
m
Your issue is likely related to the migration from agents to workers in Prefect. The 
prefect agent
command has been deprecated in newer versions. Instead, you should use the 
prefect worker
command. Here's an example:
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prefect worker start -p [work pool name]
Make sure your environment is consistent and not unintentionally using a Prefect 3.x version as it could cause such discrepancies. For more details, check out the Prefect docs on Agents and the migration instructions from agents to workers. Links: - Agents Documentation - Upgrade Guide
m
@Marvin reading the task logs it's installing
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Successfully installed aiobotocore-2.15.0 aiohappyeyeballs-2.4.0 aiohttp-3.10.5 aioitertools-0.12.0 aiosignal-1.3.1 annotated-types-0.7.0 anyio-4.4.0 async-timeout-4.0.3 boto3-1.35.16 botocore-1.35.16 fastapi-0.114.1 frozenlist-1.4.1 fsspec-2024.9.0 griffe-1.3.0 httpcore-1.0.5 httpx-0.27.2 humanize-4.10.0 jinja2-humanize-extension-0.4.0 jmespath-1.0.1 multidict-6.1.0 mypy-boto3-s3-1.35.16 mypy-boto3-secretsmanager-1.35.0 pendulum-3.0.0 prefect-3.0.1 prefect-aws-0.5.0 prometheus-client-0.20.0 pydantic-2.9.1 pydantic-core-2.23.3 pydantic-extra-types-2.9.0 pydantic-settings-2.5.2 pyparsing-3.1.4 python-dotenv-1.0.1 rfc3339-validator-0.1.4 s3fs-2024.9.0 s3transfer-0.10.2 shellingham-1.5.4 starlette-0.38.5 tenacity-9.0.0 time-machine-2.15.0 typer-0.12.5 tzdata-2024.1 ujson-5.10.0 wrapt-1.16.0 yarl-1.11.1
m
Your message was too long by 105 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:
reading the task logs it's installing
```Successfully installed aiobotocore-2.15.0 aiohappyeyeballs-2.4.0 aiohttp-3.10.5 aioitertools-0.12.0 aiosignal-1.3.1 annotated-types-0.7.0 anyio-4.4.0 async-timeout-4.0.3 boto3-1.35.16 botocore-1.35.16 fastapi-0.114.1 frozenlist-1.4.1 fsspec-2024.9.0 griffe-1.3.0 httpcore-1.0.5 httpx-0.27.2 humanize-4.10.0 jinja2-humanize-extension-0.4.0 jmespath-1.0.1 multidict-6.1.0 mypy-boto3-s3-1.35.16 mypy-boto3-secretsmanager-1.35.0 pendulum-3.0.0 prefect-3.0.1 prefect-aws-0.5.0 prometheus-client-0.20.0 pydantic-2.9.1 pydantic-core-2.23.3 pydantic-extra-types-2.9.0 pydantic-settings-2.5.2 pyparsing-3.1.4 python-dotenv-1
m
@Marvin reading the task logs ic it's installing prefect-3.0.1
m
It sounds like there's an inconsistency with the Prefect version being used. If task logs mention installing 
prefect-3.0.1
but your setup should be using Prefect 2.x, that's likely why you're seeing the 
No such command 'agent'
error. Prefect 3.x has completely removed agents in favor of workers. Here's what you can do: 1. Check Environment Configuration: Ensure all environments (e.g., containers, virtual environments) are using Prefect 2.x. 2. Pin Prefect Version: Explicitly pin the Prefect version in your environment setup files (e.g., 
requirements.txt
or Dockerfile). Example for `requirements.txt`:
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prefect==2.14.0
Example for Dockerfile:
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Dockerfile
FROM prefecthq/prefect:2.14-python3.11
Resolve the version mismatch, and you should no longer encounter the error with 
prefect agent
. ### Links - Prefect Agents Documentation - Upgrade Guide to Workers Feel free to ask if you need further assistance!
m
@Marvin what is this about? ModuleNotFoundError: No module named 'griffe.dataclasses' and why would it be absent from a prefect install
m
The error you're encountering, 
ModuleNotFoundError: No module named 'griffe.dataclasses'
, is due to recent changes in the 
griffe
module. This module underwent updates that resulted in breaking changes for new Prefect installs. ### Solution: - Ensure Correct Version: Prefect should pin the 
griffe
version to one that's compatible. For example, versions prior to 1.0.0. ### How to Fix: 1. Modify 
requirements.txt
:
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    griffe<1.0.0
    prefect==2.14.0  # or your specific Prefect version
2. OR Use a Compatible Docker Image: Specify a compatible Prefect Docker image that doesn't pull in the latest 
griffe
. ### Example Commands: If you manage dependencies using a `requirements.txt`:
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pip install "griffe<1.0.0"
pip install "prefect==2.14.0"
### Additional Context: - Issue #14978 on GitHub - Related Issue #14975 on GitHub These changes should resolve the 
griffe.dataclasses
module not found error. Let me know if you need further assistance!
m
@Marvin hi, i noticed that with https://github.com/PrefectHQ/prefect-aws ; that this was archived? what was it replaced with
m
The 
prefect-aws
repository has been archived and its functionalities are integrated into the main Prefect repository. ### Replacement: Most likely, the AWS integration functionalities are now part of the core offerings or have been moved to a newer package or configuration model. You'll need to check the main Prefect documentation for current AWS-related setup and configurations. For any transition details and specific migration steps, refer to the Prefect AWS integration documentation or related sections in the main docs. ### Relevant Links: - Archived Issue on GitHub - Transition Details This should help you smoothly transition from the archived setup to the current supported model. If you have more specific questions, feel free to ask!
m
@Marvin How does EXTRA_PIP_PACKAGES run? if i were to try to re-create locally is it just pip install prefect-aws s3fs
m
The 
EXTRA_PIP_PACKAGES
environment variable allows Prefect to install additional Python packages at runtime. This is specified in your deployment configuration. ### How it Works: When you set the 
EXTRA_PIP_PACKAGES
environment variable in your deployment's job variables, Prefect will use it to install the specified packages when your flow runs. ### Example: In a deployment configuration, it could look something like this:
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python
if __name__ == "__main__":
    get_repo_info.deploy(
        name="my-deployment",
        work_pool_name="my-pool",
        job_variables={"env": {"EXTRA_PIP_PACKAGES": "prefect-aws s3fs"}},
        image="my-image:my-tag",
        push=False
    )
### Recreate Locally: To replicate the behavior locally, you can simply use `pip install`:
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pip install prefect-aws s3fs
### Documentation Link: For more information, refer to Prefect Deployment Guide. This should help you extend your Prefect environment with the necessary dependencies. Let me know if you need further information!
m
@Marvin so pip install prefect-aws is updating my prefect version. how can i prevent this?
m
To prevent 
pip install prefect-aws
from updating your Prefect version, you should pin the version of Prefect explicitly in your installation command. This can be done using pip's version specifiers. ### Example Command:
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pip install prefect-aws s3fs prefect==2.14.0
This command will install 
prefect-aws
and 
s3fs
while ensuring 
Prefect
stays at version 
2.14.0
. ### Dockerfile Example: If you're using a Dockerfile, you can set it up like this:
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Dockerfile
FROM prefecthq/prefect:2.14-python3.11

# Ensure Prefect version remains 2.14.x
RUN pip install prefect-aws s3fs prefect==2.14.0
### requirements.txt Example: If you manage dependencies with a 
requirements.txt
file:
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prefect==2.14.0
prefect-aws
s3fs
Then run:
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pip install -r requirements.txt
By pinning the Prefect version, you ensure other package installations don't inadvertently update it. Feel free to reach out if you have more questions!
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