--wip--

docs/architecture/distributed_runtime.md

@@ -34,7 +34,7 @@ For example, the deployment configuration `examples/llm/configs/disagg.yaml` hav
 - `Processor`: When a new request arrives, `Processor` applies the chat template and perform the tokenization. Then, it route the request to the `VllmWorker`.
 - `VllmWorker` and `PrefillWorker`: Perform the actual decode and prefill computation.
 
-Since the four workers are deployed in different processes, each of them have their own `DistributedRuntime`. Within their own `DistributedRuntime`, they all have their own `Namespace`s named `dynamo`. Then, under their own `dynamo` namespace, they have their own `Component`s named `Frontend/Processor/VllmWorker/PrefillWorker`. Lastly, for the `Endpoint`, `Frontend` has no `Endpoints`, `Processor` and `VllmWorker` each has a `generate` endpoint, and `PrefillWorker` has a placeholder `mock` endpoint. Their `DistributedRuntime`s and `Namespace`s are set in the `@service` decorators in `examples/llm/components/<frontend/processor/worker/prefill_worker>.py`. Their `Component`s are set by their name in `/deploy/dynamo/sdk/src/dynamo/sdk/cli/serve_dynamo.py`. Their `Endpoint`s are set by the `@endpoint` decorators in `examples/llm/components/<frontend/processor/worker/prefill_worker>.py`.
+Since the four workers are deployed in different processes, each of them have their own `DistributedRuntime`. Within their own `DistributedRuntime`, they all have their own `Namespace`s named `dynamo`. Then, under their own `dynamo` namespace, they have their own `Component`s named `Frontend/Processor/VllmWorker/PrefillWorker`. Lastly, for the `Endpoint`, `Frontend` has no `Endpoints`, `Processor` and `VllmWorker` each has a `generate` endpoint, and `PrefillWorker` has a placeholder `mock` endpoint.
 
 ## Initialization
 

docs/dynamo_glossary.md

@@ -24,8 +24,6 @@
 **Dynamo Cloud** - A Kubernetes platform providing managed deployment experience for Dynamo inference graphs.
 
 ## E
-**@endpoint** - A Python decorator used to define service endpoints within a Dynamo component.
-
 **Endpoint** - A specific network-accessible API within a Dynamo component, such as `generate` or `load_metrics`.
 
 ## F
@@ -70,8 +68,6 @@
 **RDMA (Remote Direct Memory Access)** - Technology that allows direct memory access between distributed systems, used for efficient KV cache transfers.
 
 ## S
-**@service** - Python decorator used to define a Dynamo service class.
-
 **SGLang** - Fast LLM inference framework with native embedding support and RadixAttention.
 
 ## T