- [Docs] Added python-api example (broken link)

docs/blog/posts/python-api-preview.md

@@ -0,0 +1,84 @@
+---
+title: "dstack 0.10.7: An early preview of services"
+date: 2023-09-12
+description: "The 0.10.7 update introduces a new configuration type specifically for serving purposes."
+slug: "python-api-preview.md"
+categories:
+- Releases
+---
+
+# An early preview of Python API
+
+__The 0.10.7 update introduces a new configuration type for serving.__
+
+Until now, `dstack` has supported `dev-environment` and `task` as configuration types. Even though `task` 
+may be used for basic serving use cases, it lacks crucial serving features. With the new update, we introduce
+`service`, a dedicated configuration type for serving.
+
+<!-- more -->
+
+Consider the following example:
+
+<div editor-title="text-generation-inference/serve.dstack.yml">
+
+```yaml
+type: task
+
+image: ghcr.io/huggingface/text-generation-inference:0.9.3
+
+ports: 
+  - 8000
+
+commands: 
+  - text-generation-launcher --hostname 0.0.0.0 --port 8000 --trust-remote-code
+```
+
+</div>
+
+When running it, the `dstack` CLI forwards traffic to `127.0.0.1:8000`.
+This is convenient for development but unsuitable for production.
+
+In production, you need your endpoint available on the external network, preferably behind authentication 
+and a load balancer. 
+
+This is why we introduce the `service` configuration type.
+
+<div editor-title="text-generation-inference/serve.dstack.yml">
+
+```yaml
+type: service
+
+image: ghcr.io/huggingface/text-generation-inference:0.9.3
+
+port: 8000
+
+commands: 
+  - text-generation-launcher --hostname 0.0.0.0 --port 8000 --trust-remote-code
+```
+
+</div>
+
+As you see, there are two differences compared to `task`.
+
+1. The `gateway` property: the address of a special cloud instance that wraps the running service with a public
+   endpoint. Currently, you must specify it manually. In the future, `dstack` will assign it automatically.
+2. The `port` property: A service must always configure one port on which it's running.
+
+When running, `dstack` forwards the traffic to the gateway, providing you with a public endpoint that you can use to
+access the running service.
+
+??? info "Existing limitations"
+    1. Currently, you must create a gateway manually using the `dstack gateway` command 
+    and specify its address via YAML (e.g. using secrets). In the future, `dstack` will assign it automatically.
+    2. Gateways do not support HTTPS yet. When you run a service, its endpoint URL is `<the address of the gateway>:80`. 
+    The port can be overridden via the port property: instead of `8000`, specify `<gateway port>:8000`.
+    3. Gateways do not provide authorization and auto-scaling. In the future, `dstack` will support them as well.
+
+This initial support for services is the first step towards providing multi-cloud and cost-effective inference.
+
+!!! info "Give it a try and share feedback"
+    Even though the current support is limited in many ways, we encourage you to give it a try and share your feedback with us!
+
+    More details on how to use services can be found in a [dedicated guide](../../docs/guides/services.md) in our docs. 
+    Questions and requests for help are
+    very much welcome in our [Slack chat](https://join.slack.com/t/dstackai/shared_invite/zt-xdnsytie-D4qU9BvJP8vkbkHXdi6clQ).

docs/examples/python-api.md

@@ -4,8 +4,8 @@ title: Deploying LLMs with Python API
 
 # Deploying LLMs with Python API
 
-The [Python API](../../docs/docs/reference/api/python/index.md) of `dstack` can be used to run tasks
-and services programmatically.
+The [Python API](../docs/reference/api/python/index.md) of `dstack` can be used to run 
+[tasks](../docs/guides/tasks.md) and [services](../docs/guides/services.md) programmatically.
 
 Below is an example of a Streamlit app that uses `dstack`'s API to deploy a quantized version of Llama 2 to your cloud
 with a simple click of a button.
@@ -18,10 +18,10 @@ with a simple click of a button.
 
     To get started, create an instance of `dstack.Client` and use its methods to submit and manage runs.
 
-    With `dstack.Client`, you can run [tasks](../../docs/guides/tasks.md) and [services](../../docs/guides/services.md). Running a task allows you to programmatically access its ports and
+    With `dstack.Client`, you can run [tasks](../docs/guides/tasks.md) and [services](../docs/guides/services.md). Running a task allows you to programmatically access its ports and
     forward traffic to your local machine. For example, if you run an LLM as a task, you can access it on localhost.
 
-    For more details on the Python API, please refer to its [reference](../../docs/docs/reference/api/python/index.md).
+    For more details on the Python API, please refer to its [reference](../docs/docs/reference/api/python/index.md).
 
 ## Prerequisites