add sglang engine demo for /v1/chat/completions

python/ray/llm/_internal/serve/engines/sglang/sglang_engine.py

@@ -0,0 +1,51 @@
+import ray
+import requests
+from fastapi import FastAPI
+from ray import serve
+from ray.serve.handle import DeploymentHandle
+
+app = FastAPI()
+
+@serve.deployment
+@serve.ingress(app)
+class MyFastAPIDeployment:
+    def __init__(self, engine_handle: DeploymentHandle):
+        self._engine_handle = engine_handle
+
+    @app.get("/v1/chat/completions/{in_prompt}") # serve as OPENAI /v1/chat/completions endpoint 
+    async def root(self, in_prompt: str):                 # make endpoint async
+        # Asynchronous call to a method of that deployment (executes remotely) used remote
+        res = await self._engine_handle.chat.remote(in_prompt) 
+        return "useing Llama-3.1-8B-Instruct for your !", in_prompt, res
+
+@serve.deployment
+class SGLangServer:
+    def __init__(self):
+
+        self.engine_kwargs = dict(
+            model_path = "/scratch2/huggingface/hub/meta-llama/Llama-3.1-8B-Instruct/",
+            mem_fraction_static = 0.8,
+            tp_size = 8,
+        )
+
+        try:
+            import sglang
+        except ImportError as e:
+            raise ImportError(
+                "SGLang is not installed or failed to import. Please run "
+                "`pip install sglang[all]` to install required dependencies."
+            ) from e
+        self.engine = sglang.Engine(**self.engine_kwargs)
+
+    async def chat(self, message: str):
+        print('In SGLangServer CHAT with message', message)
+        res = await self.engine.async_generate(
+            prompt = message,
+            stream = False
+        )
+        return {"echo": res}
+
+sglangServer = SGLangServer.bind()
+my_App = MyFastAPIDeployment.bind(sglangServer)
+handle: DeploymentHandle = serve.run(my_App, blocking = True)
+