atemate

Like in tutorial: https://huggingface.co/docs/google-cloud/en/examples/vertex-ai-notebooks-deploy-llama-3-1-405b-on-vertex-ai

uv venv
source .venv/bin/activate
uv pip install -r requirements.txt

source .env
gcloud auth login

atemate

{
  "attribution": {
    "commit": "",
    "pr": ""
  },
  "includeCoAuthoredBy": false,
  "model": "claude-opus-4-5@20251101",
  "hooks": {
    "PreCompact": [
      {

atemate

This is a very common hurdle when setting up WhatsApp Business API (WABA) accounts. Meta is extremely strict during the initial setup phase to prevent spam and ensure legitimate businesses are using the platform.

Based on the screenshot you provided and your description, here is an analysis of the situation and the steps to fix it.

---

1. What could be the reason for this rejection and how to fix it?

There appears to be a contradiction between what you were told (document rejection) and what the screenshot shows (activity restriction). However, they are usually linked.

atemate

tokens,cost_aws_managed,cost_gcp_managed,cost_L4_self_hosted,cost_A10G_self_hosted,latency_L4_seconds,latency_L4_hours,latency_A10G_seconds,latency_A10G_hours,latency_T4_seconds,latency_T4_hours,latency_H100_seconds,latency_H100_hours,latency_GCP_Vertex_seconds,latency_GCP_Vertex_hours
1000000,4.0,11.249999999999998,0.27777777777777773,6.733333333333333,2000.0,0.5555555555555556,20000.0,5.555555555555555,33333.333333333336,9.25925925925926,1600.0,0.4444444444444444,1600.0,0.4444444444444444
2000000,8.0,22.499999999999996,0.5555555555555555,13.466666666666667,4000.0,1.1111111111111112,40000.0,11.11111111111111,66666.66666666667,18.51851851851852,3200.0,0.8888888888888888,3200.0,0.8888888888888888
3000000,12.0,33.75,0.8333333333333333,20.2,6000.0,1.6666666666666667,60000.0,16.666666666666668,100000.0,27.77777777777778,4800.0,1.3333333333333333,4800.0,1.3333333333333333
4000000,16.0,44.99999999999999,1.111111111111111,26.933333333333334,8000.0,2.2222222222222223,80000.0,22.22222222222222,133333.33333333334,37.03

atemate

Service	Purpose	Key Features	Common Use Cases	Integration
Dataflow	Stream and batch data processing using Apache Beam.	Serverless, autoscaling, unified stream and batch processing, supports windowing and watermarking.	ETL,

atemate

>>> from os import PathLike
>>> class MyPath(PathLike):
...     def __init__(self, prefix, path):
...         self._prefix = prefix
...         self._path = path
...
...     def __fspath__(self):
...         return self._prefix + self._path
...

atemate

import importlib

# require installation of 'gcp' extras
try:
    importlib.util.find_spec("google.cloud")
except ImportError:
    raise ValueError("Please install package[gcp]")

atemate

Documentation: https://cloud.google.com/pubsub/docs/subscription-message-filter

Usage:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Publish:

atemate

version: "0.1"
services:
  sns:
    image: localstack/localstack
    environment:
      # LocalStack configuration: https://docs.localstack.cloud/references/configuration/
      - DEBUG=${DEBUG:-0}
      - SERVICES=sns
    ports:
      - "4566:4566"

atemate

from typing import Any, Dict, List


def iter_dict_in_chunks(input_dict: Dict[Any, List], chunk_size: int, total_size: int):
    """Iterates a dict of lists and yields key:values pairs where len of values
    is at most `chunk_size`, until `total_size` is exhausted.
    Examples:
    # Realistic cases:
    >>> d = {'a': [1, 2], 'b': [3, 4, 5, 6, 7, 8, 9]}
    >>> list(iter_dict_in_chunks(d, 3, 5))