pumpwood-deploy-model-llm
Satellite deploy package for the Pumpwood Model LLM microservice on
Kubernetes. It generates manifests for the API application, three LLM
workers (embedding, extraction, segmentation), and model-llm secrets —
then hands them to
pumpwood-deploy
for apply.
Developed by Murabei Data Science. BSD-3-Clause.
What it deploys
| Manifest | Kubernetes resources |
|---|---|
pumpwood_model_llm__secrets |
Secret pumpwood-model-llm-secrets |
pumpwood_model_llm__deploy |
Deployment + Service pumpwood-llm-model-app |
pumpwood_llm_model_embedding_worker |
Deployment pumpwood-llm-model-embedding-worker |
pumpwood_llm_model_extraction_worker |
Deployment pumpwood-llm-model-extraction-worker |
pumpwood_llm_model_segmentation_worker |
Deployment pumpwood-llm-model-segmentation-worker |
Model LLM exposes HTTP APIs for large-language-model workflows. Workers consume RabbitMQ messages for embedding, extraction, and segmentation tasks.
flowchart LR
subgraph pkg [pumpwood-deploy-model-llm]
A[PumpWoodModelLLMMicroservice]
end
subgraph core [pumpwood-deploy]
B[DeployPumpWood]
end
subgraph cluster [Cluster]
S[pumpwood-model-llm-secrets]
APP[pumpwood-llm-model-app]
E[embedding worker]
X[extraction worker]
G[segmentation worker]
RMQ[rabbitmq-main]
end
A --> B
B --> S
B --> APP
B --> E
B --> X
B --> G
RMQ --> APP
RMQ --> E
RMQ --> X
RMQ --> G
Prerequisites
This package does not stand alone. Before model-llm pods can start, the cluster must already provide:
| Resource | Provided by |
|---|---|
storage ConfigMap |
StandardMicroservices in pumpwood-deploy |
general-secrets |
StandardMicroservices |
rabbitmq-main-secrets |
StandardMicroservices |
| Storage keys (GCP / Azure / AWS) | DeployPumpWood storage config |
| Postgres for model llm | PostgresDatabase + PGBouncerDatabase |
| Auth (typical) | pumpwood-deploy-auth |
Storage bucket name and type are read from the cluster storage
ConfigMap — they are not passed to PumpWoodModelLLMMicroservice.
Installation
pip install pumpwood-deploy-model-llm
Requires pumpwood-deploy.
Quick start
import os
import simplejson as json
from dotenv import load_dotenv
from pumpwood_deploy.deploy import DeployPumpWood
from pumpwood_deploy.microservices.postgres.deploy import (
PostgresDatabase, PGBouncerDatabase)
from pumpwood_deploy_model_llm import PumpWoodModelLLMMicroservice
with open("secrets/production.json", "r") as file:
secrets = json.loads(file.read())
load_dotenv()
deploy = DeployPumpWood(
model_user_password=secrets["microservices--model"],
rabbitmq_secret=secrets["rabbitmq_secret"],
hash_salt=secrets["hash_salt"],
storage_type="aws_s3",
storage_deploy_args={
"storage_bucket_name": "my-pumpwood-bucket",
"access_key_id": secrets["aws_access_key_id"],
"secret_access_key": secrets["aws_secret_access_key"],
},
k8_provider="aws",
k8_deploy_args={
"region": "us-east-1",
"cluster_name": "my-cluster",
},
k8_namespace="pumpwood",
)
deploy.add_microservice(
PostgresDatabase(
db_username="pumpwood",
db_password=secrets["postgres_password"],
name="postgres-main",
disk_name="postgres-disk",
disk_size="150Gi",
))
deploy.add_microservice(
PGBouncerDatabase(
name="pgbouncer-pumpwood-model-llm",
postgres_database="pumpwood_model_llm",
postgres_secret="postgres-main",
postgres_host="postgres-main",
))
deploy.add_microservice(
PumpWoodModelLLMMicroservice(
app_version=os.getenv("PUMPWOOD_MODEL_LLM_APP"),
worker_embedding_version=os.getenv("PUMPWOOD_MODEL_LLM_EMBEDDING"),
worker_extraction_version=os.getenv("PUMPWOOD_MODEL_LLM_EXTRACTION"),
worker_segmentation_version=os.getenv(
"PUMPWOOD_MODEL_LLM_SEGMENTATION"),
repository="my-registry.example.com",
db_host="pgbouncer-pumpwood-model-llm",
db_database="pumpwood_model_llm",
db_password=secrets["postgres_password"],
microservice_password=secrets["microservice--model-llm"],
))
deploy.create_deploy_files()
deploy.deploy_microservices()
Environment variables
PUMPWOOD_MODEL_LLM_APP=2.1.0
PUMPWOOD_MODEL_LLM_EMBEDDING=1.4.0
PUMPWOOD_MODEL_LLM_EXTRACTION=1.4.0
PUMPWOOD_MODEL_LLM_SEGMENTATION=1.4.0
If the rendered manifest matches what is already on the cluster, kubectl apply produces no changes — safe for rolling image updates.
Configuration reference
Required
| Parameter | Description |
|---|---|
app_version |
Image tag for pumpwood-llm-model-app |
worker_embedding_version |
Image tag for embedding worker |
worker_extraction_version |
Image tag for extraction worker |
worker_segmentation_version |
Image tag for segmentation worker |
Database
| Parameter | Default | Description |
|---|---|---|
db_host |
pgbouncer-pumpwood-model-llm |
Postgres host |
db_port |
5432 |
Postgres port |
db_database |
pumpwood |
Database name |
db_username |
pumpwood |
Database user |
db_password |
pumpwood |
Database password |
microservice_password |
microservice--model-llm |
Service user password |
repository |
GCR default | Docker registry |
Application
| Parameter | Default | Description |
|---|---|---|
app_replicas |
1 |
App pod count |
app_debug |
FALSE |
Debug flag |
app_workers |
10 |
Granian workers |
app_timeout |
300 |
Request timeout (seconds) |
app_limits_memory |
60Gi |
Memory limit |
app_limits_cpu |
12000m |
CPU limit |
Each worker (worker_embedding_*, worker_extraction_*,
worker_segmentation_*) supports debug, replicas, n_parallel,
chunk_size, query_limit, and resource limit/request parameters with
defaults matching the datalake dataloader pattern.
Health check
The app Deployment exposes a readiness probe at:
GET /health-check/pumpwood-llm-model-app/ (port 5000)
Migration note
This is a new satellite package. Import from:
from pumpwood_deploy_model_llm import PumpWoodModelLLMMicroservice
Related packages
| Package | Role |
|---|---|
pumpwood-deploy |
Orchestrator, Kong, RabbitMQ, Postgres |
pumpwood-deploy-auth |
Authorization microservice |
pumpwood-deploy-datalake |
Standard datalake |
Development
pip install -e ../pumpwood-deploy
pip install -e .
PYTHONPATH="src:../pumpwood-deploy/src" \
python3 -m unittest discover \
-s src/pumpwood_deploy_model_llm/tests -p "test_*.py" -v
ruff check src/
License
BSD-3-Clause — see LICENSE.
Metadata
Release files for pumpwood-deploy-model-llm 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pumpwood_deploy_model_llm-0.0.2.tar.gz | 11.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pumpwood_deploy_model_llm-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 26.4 kB
Release files / pumpwood_deploy_model_llm-0.0.2.tar.gz
| Download URL | pumpwood_deploy_model_llm-0.0.2.tar.gz |
|---|---|
| Size | 11.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
6a41006aeae66c7d8ef8708af370c3c91d48ba8356049e9d54c98db228f65cf2
|
|
BLAKE2b-256 checksum How to use checksums |
69143dff514ab7af447317d0ab6bace50e8010c1f4d8e6849690c4289e85b7ce
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.4.1 CPython/3.12.13 Linux/6.17.0-1022-azure
|
Release files / pumpwood_deploy_model_llm-0.0.2-py3-none-any.whl
| Download URL | pumpwood_deploy_model_llm-0.0.2-py3-none-any.whl |
|---|---|
| Size | 14.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
753cda1bc0a83c17dfbfe47fb35be0f77380e9fb8c1d93287cef58d999426632
|
|
BLAKE2b-256 checksum How to use checksums |
bb55b592d98b96eeac47fcb20bbfc507123d58f8ecdb785aa9bcd8303f2385a4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.4.1 CPython/3.12.13 Linux/6.17.0-1022-azure
|