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docs/flyte_agents/deploying_agents_to_the_flyte_sandbox.md
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| --- | ||
| jupytext: | ||
| formats: md:myst | ||
| text_representation: | ||
| extension: .md | ||
| format_name: myst | ||
| --- | ||
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| (deploying_agents_to_the_flyte_sandbox)= | ||
| # Deploying agents to the Flyte sandbox | ||
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| After you have finished {ref}`testing an agent locally <testing_agents_locally>`, you can deploy your agent to the Flyte sandbox. | ||
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| Here's a step by step guide to deploying your agent image to the Flyte sandbox. | ||
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| 1. Start the Flyte sandbox: | ||
| ```bash | ||
| flytectl demo start | ||
| ``` | ||
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| 2. Build an agent image: | ||
| You can go to [here](https://github.com/flyteorg/flytekit/blob/master/Dockerfile.agent) to see the Dockerfile we use in flytekit python. | ||
| Take Databricks agent as an example: | ||
| ```Dockerfile | ||
| FROM python:3.9-slim-bookworm | ||
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| RUN apt-get update && apt-get install build-essential git -y | ||
| RUN pip install prometheus-client grpcio-health-checking | ||
| RUN pip install --no-cache-dir -U flytekit \ | ||
| git+https://github.com/flyteorg/flytekit.git@<gitsha>#subdirectory=plugins/flytekit-spark \ | ||
| && apt-get clean autoclean \ | ||
| && apt-get autoremove --yes \ | ||
| && rm -rf /var/lib/{apt,dpkg,cache,log}/ \ | ||
| && : | ||
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| CMD pyflyte serve agent --port 8000 | ||
| ``` | ||
| ```bash | ||
| docker buildx build -t localhost:30000/flyteagent:example -f Dockerfile.agent . --load | ||
| docker push localhost:30000/flyteagent:example | ||
| ``` | ||
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| 2. Deploy your agent image to the Kubernetes cluster: | ||
| ```bash | ||
| kubectl edit deployment flyteagent -n flyte | ||
| ``` | ||
| Search for the `image` key and change its value to your agent image: | ||
| ```yaml | ||
| image: localhost:30000/flyteagent:example | ||
| ``` | ||
| 3. Set up your secrets: | ||
| Let's take Databricks agent as an example: | ||
| ```bash | ||
| kubectl edit secret flyteagent -n flyte | ||
| ``` | ||
| Get your `BASE64_ENCODED_DATABRICKS_TOKEN`: | ||
| ```bash | ||
| echo -n "<DATABRICKS_TOKEN>" | base64 | ||
| ``` | ||
| Add your token to the `data` field: | ||
| ```yaml | ||
| apiVersion: v1 | ||
| data: | ||
| flyte_databricks_access_token: <BASE64_ENCODED_DATABRICKS_TOKEN> | ||
| kind: Secret | ||
| metadata: | ||
| annotations: | ||
| meta.helm.sh/release-name: flyteagent | ||
| meta.helm.sh/release-namespace: flyte | ||
| creationTimestamp: "2023-10-04T04:09:03Z" | ||
| labels: | ||
| app.kubernetes.io/managed-by: Helm | ||
| name: flyteagent | ||
| namespace: flyte | ||
| resourceVersion: "753" | ||
| uid: 5ac1e1b6-2a4c-4e26-9001-d4ba72c39e54 | ||
| type: Opaque | ||
| ``` | ||
| :::{note} | ||
| Please ensure two things: | ||
| 1. The secret name consists only of lowercase English letters. | ||
| 2. The secret value is encoded in Base64. | ||
| ::: | ||
| 4. Restart development: | ||
| ```bash | ||
| kubectl rollout restart deployment flyte-sandbox -n flyte | ||
| ``` | ||
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| 5. Test your agent remotely in the Flyte sandbox: | ||
| ```bash | ||
| pyflyte run --remote agent_workflow.py agent_task | ||
| ``` | ||
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| :::{note} | ||
| You must build an image that includes the plugin for the task and specify its config with the [`--image` flag](https://docs.flyte.org/en/latest/api/flytekit/pyflyte.html#cmdoption-pyflyte-run-i) when running `pyflyte run` or in an {ref}`ImageSpec <imagespec>` definition in your workflow file. | ||
| ::: |
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