107 lines
4.5 KiB
Markdown
Executable File
107 lines
4.5 KiB
Markdown
Executable File
# Infrastructure to deploy Research Projects
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The Infrastructure expects to be deployed in the same Pod / local environment as the analysis container and handles all outbound communication.
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## Configuration
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A configuration is located in `/config.yaml`. All relevant variables can be configured via exporting environment variables.
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| Environment Variable | Default | Description |
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| ----------------------------- | ------------------------------ | --------------------------------------------------------------------- |
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| LOGGING_LEVEL_ROOT | DEBUG | Logging level for service logger |
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| PROBING_WEBSERVER_HOST | "0.0.0.0" | Probe webserver address |
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| PROBING_WEBSERVER_PORT | 8080 | Probe webserver port |
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| PROBING_WEBSERVER_MODE | production | Webserver mode: {development, production} |
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| RABBITMQ_HOST | localhost | RabbitMQ host address |
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| RABBITMQ_PORT | 5672 | RabbitMQ host port |
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| RABBITMQ_USERNAME | user | RabbitMQ username |
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| RABBITMQ_PASSWORD | bitnami | RabbitMQ password |
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| RABBITMQ_HEARTBEAT | 7200 | Controls AMQP heartbeat timeout in seconds |
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| REQUEST_QUEUE | request_queue | Requests to service |
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| RESPONSE_QUEUE | response_queue | Responses by service |
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| DEAD_LETTER_QUEUE | dead_letter_queue | Messages that failed to process |
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| ANALYSIS_ENDPOINT | "http://127.0.0.1:5000" | Endpoint for analysis container |
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| STORAGE_BACKEND | s3 | The type of storage to use {s3, azure} |
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| STORAGE_BUCKET | "redaction" | The bucket / container to pull files specified in queue requests from |
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| STORAGE_ENDPOINT | "http://127.0.0.1:9000" | Endpoint for s3 storage |
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| STORAGE_KEY | root | User for s3 storage |
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| STORAGE_SECRET | password | Password for s3 storage |
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| STORAGE_AZURECONNECTIONSTRING | "DefaultEndpointsProtocol=..." | Connection string for Azure storage |
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| STORAGE_AZURECONTAINERNAME | "redaction" | AKS container |
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## Response Format
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### Expected AMQP input message:
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```json
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{
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"dossierId": "",
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"fileId": "",
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"targetFileExtension": "",
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"responseFileExtension": ""
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}
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```
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Optionally, the input message can contain a field with the key `"operations"`.
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### AMQP output message:
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```json
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{
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"dossierId": "",
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"fileId": "",
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...
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}
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```
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## Development
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Either run `src/serve.py` or the built Docker image.
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### Setup
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Install module.
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```bash
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pip install -e .
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pip install -r requirements.txt
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```
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or build docker image.
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```bash
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docker build -f Dockerfile -t pyinfra .
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```
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### Usage
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**Shell 1:** Start a MinIO and a RabbitMQ docker container.
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```bash
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docker-compose up
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```
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**Shell 2:** Add files to the local minio storage.
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```bash
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python scripts/manage_minio.py add <MinIO target folder> -d path/to/a/folder/with/PDFs
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```
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**Shell 2:** Run pyinfra-server.
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```bash
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python src/serve.py
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```
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or as container:
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```bash
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docker run --net=host pyinfra
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```
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**Shell 3:** Run analysis-container.
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**Shell 4:** Start a client that sends requests to process PDFs from the MinIO store and annotates these PDFs according to the service responses.
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```bash
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python scripts/mock_client.py
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```
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