deploying agents in the sandbox

Signed-off-by: Future-Outlier <[email protected]>

docs/flyte_agents/deploying_agents_to_flyte_sandbox.md

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+---
+jupytext:
+  formats: md:myst
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+    extension: .md
+    format_name: myst
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+(deploying_agents_to_the_flyte_sandbox)=
+# Deploying agents to the Flyte Sandbox
+
+After you have finished {ref}`testing an agent locally <testing_agents_locally>` and {ref}`testing agents in the development environment <testing_agents_in_the_development_environment>`,you can deploy your agent to the flyte sandbox.
+
+Here's a step by step guide to deploy your agent image to the flyte sandbox.
+
+1. Start the flyte sandbox.
+```bash
+flytectl demo start
+```
+
+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
+
+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}/ \
+    && :
+
+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
+```
+
+2. Deploy your agent image to the kubernetes cluster
+```bash
+kubectl edit deployment flyteagent -n flyte
+```
+Search the `image` key, and replace its value to your agent image.
+```yaml
+image: localhost:30000/flyteagent:example
+```
+
+3. Set up your secrets
+Let's take databricks agent as the 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 2 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
+```
+
+5. Test your agent remotely in flyte sandbox
+```bash
+pyflyte run --remote agent_workflow.py agent_task
+```
+
+:::{note}
+Please ensure you've built an image and specified it by `--image` flag or use ImageSpec to include the plugin for the task.
+:::

docs/flyte_agents/index.md

@@ -37,6 +37,8 @@ For a list of agents you can use in your tasks and example usage for each, see t
   - Whether using an existing agent or developing a new one, you can test the agent locally without needing to configure your Flyte deployment.
 * - {doc}`Enabling agents in your Flyte deployment <enabling_agents_in_your_flyte_deployment>`
   - Once you have tested an agent locally and want to use it in production, you must configure your Flyte deployment for the agent.
+* - {doc}`Deploying agents to the Flyte Sandbox <deploying_agents_to_the_flyte_sandbox>`
+  - Once you have tested an agent locally and want to use it in production, you must want to test it in sandbox.
 ```
 
 ```{toctree}
@@ -46,4 +48,5 @@ For a list of agents you can use in your tasks and example usage for each, see t
 developing_agents
 testing_agents_locally
 enabling_agents_in_your_flyte_deployment
+deploying_agents_to_the_flyte_sandbox
 ```