Remove async-tasks.mdx and update sidebars.js
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import Admonition from "@theme/Admonition";
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# Async API
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## Introduction
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<Admonition type="info" caption="In development">
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This implementation is still in development. Contributions are welcome!
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</Admonition>
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The Async API is an implementation of the Langflow API that uses [Celery](https://docs.celeryproject.org/en/stable/)
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to run the tasks asynchronously, using a message broker to send and receive messages, a result backend to store the results and a cache to store the task states and session data.
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### Configuration
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The folder _`./deploy`_ in the [Github repository](https://github.com/logspace-ai/langflow) contains a _`.env.example`_ file that can be used to configure a Langflow deployment.
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The file contains the variables required to configure a Celery worker queue, Redis cache and result backend and a RabbitMQ message broker.
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To set it up locally you can copy the file to _`.env`_ and run the following command:
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```bash
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docker compose up -d
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```
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This will set up the following containers:
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- Langflow API
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- Celery worker
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- RabbitMQ message broker
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- Redis cache
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- PostgreSQL database
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- PGAdmin
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- Flower
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- Traefik
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- Grafana
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- Prometheus
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### Testing
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To run the tests for the Async API, you can run the following command:
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```bash
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docker compose -f docker-compose.with_tests.yml up --exit-code-from tests tests result_backend broker celeryworker db --build
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```
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@ -27,12 +27,7 @@ module.exports = {
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type: "category",
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type: "category",
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label: " Step-by-Step Guides",
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label: " Step-by-Step Guides",
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collapsed: false,
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collapsed: false,
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items: [
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items: ["guides/langfuse_integration"],
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"guides/async-tasks",
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"guides/loading_document",
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"guides/chatprompttemplate_guide",
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"guides/langfuse_integration",
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],
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},
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},
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{
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{
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type: "category",
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type: "category",
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