| Name | ingrain JSON |
| Version |
0.2.3
JSON |
| download |
| home_page | None |
| Summary | Python client for the ingrain server |
| upload_time | 2025-09-08 07:51:36 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11 |
| license | None |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Ingrain Python Client
[](https://pypi.org/project/ingrain/)
This is the Python client for the Ingrain API. It provides a simple interface to interact with the Ingrain API.
## Install
```bash
pip install ingrain
```
## Dev Setup
```bash
uv sync --dev
```
### Testing
#### Unit tests
```bash
uv run pytest
```
#### Integration tests and unit tests
This requires that Ingrain Server is running. You can start it with Docker Compose:
```yml
services:
ingrain-models:
image: owenpelliott/ingrain-models:latest
container_name: ingrain-models
ports:
- "8687:8687"
environment:
- TRITON_GRPC_URL=triton:8001
- MAX_BATCH_SIZE=16
- MODEL_INSTANCES=1
- INSTANCE_KIND=KIND_GPU # Change to KIND_CPU if using a CPU
depends_on:
- triton
volumes:
- ./model_repository:/app/model_repository
- ${HOME}/.cache/huggingface:/app/model_cache/
ingrain-inference:
image: owenpelliott/ingrain-inference:latest
container_name: ingrain-inference
ports:
- "8686:8686"
environment:
- TRITON_GRPC_URL=triton:8001
depends_on:
- triton
volumes:
- ./model_repository:/app/model_repository
triton:
image: nvcr.io/nvidia/tritonserver:25.06-py3
container_name: triton
runtime: nvidia # Remove if using a CPU
environment:
- NVIDIA_VISIBLE_DEVICES=all
shm_size: "256m"
command: >
tritonserver
--model-repository=/models
--model-control-mode=explicit
ports:
- "8000:8000"
- "8001:8001"
- "8002:8002"
volumes:
- ./model_repository:/models
restart:
unless-stopped
```
```bash
uv run pytest --integration
```
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"description": "# Ingrain Python Client\n\n[](https://pypi.org/project/ingrain/)\n\n\nThis is the Python client for the Ingrain API. It provides a simple interface to interact with the Ingrain API.\n\n## Install\n \n```bash\npip install ingrain\n```\n\n## Dev Setup\n```bash\nuv sync --dev\n```\n\n### Testing\n\n#### Unit tests\n\n```bash\nuv run pytest\n```\n\n#### Integration tests and unit tests\n\nThis requires that Ingrain Server is running. You can start it with Docker Compose:\n\n```yml\nservices:\n ingrain-models:\n image: owenpelliott/ingrain-models:latest\n container_name: ingrain-models\n ports:\n - \"8687:8687\"\n environment:\n - TRITON_GRPC_URL=triton:8001\n - MAX_BATCH_SIZE=16\n - MODEL_INSTANCES=1\n - INSTANCE_KIND=KIND_GPU # Change to KIND_CPU if using a CPU\n depends_on:\n - triton\n volumes:\n - ./model_repository:/app/model_repository \n - ${HOME}/.cache/huggingface:/app/model_cache/\n ingrain-inference:\n image: owenpelliott/ingrain-inference:latest\n container_name: ingrain-inference\n ports:\n - \"8686:8686\"\n environment:\n - TRITON_GRPC_URL=triton:8001\n depends_on:\n - triton\n volumes:\n - ./model_repository:/app/model_repository \n triton:\n image: nvcr.io/nvidia/tritonserver:25.06-py3\n container_name: triton\n runtime: nvidia # Remove if using a CPU\n environment:\n - NVIDIA_VISIBLE_DEVICES=all\n shm_size: \"256m\"\n command: >\n tritonserver\n --model-repository=/models\n --model-control-mode=explicit\n ports:\n - \"8000:8000\"\n - \"8001:8001\"\n - \"8002:8002\"\n volumes:\n - ./model_repository:/models\n restart:\n unless-stopped\n```\n\n```bash\nuv run pytest --integration\n```\n",
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