community[patch]: OpenLLM Client Fixes + Added Timeout Parameter (#17478)

- OpenLLM was using outdated method to get the final text output from
openllm client invocation which was raising the error. Therefore
corrected that.
- OpenLLM `_identifying_params` was getting the openllm's client
configuration using outdated attributes which was raising error.
- Updated the docstring for OpenLLM.
- Added timeout parameter to be passed to underlying openllm client.

libs/community/langchain_community/llms/openllm.py

@@ -72,7 +72,7 @@ class OpenLLM(LLM):
 
             from langchain_community.llms import OpenLLM
             llm = OpenLLM(server_url='http://localhost:3000')
-            llm("What is the difference between a duck and a goose?")
+            llm.invoke("What is the difference between a duck and a goose?")
     """
 
     model_name: Optional[str] = None
@@ -82,6 +82,8 @@ class OpenLLM(LLM):
     See 'openllm models' for all available model variants."""
     server_url: Optional[str] = None
     """Optional server URL that currently runs a LLMServer with 'openllm start'."""
+    timeout: int = 30
+    """"Time out for the openllm client"""
     server_type: ServerType = "http"
     """Optional server type. Either 'http' or 'grpc'."""
     embedded: bool = True
@@ -125,6 +127,7 @@ class OpenLLM(LLM):
         *,
         model_id: Optional[str] = None,
         server_url: Optional[str] = None,
+        timeout: int = 30,
         server_type: Literal["grpc", "http"] = "http",
         embedded: bool = True,
         **llm_kwargs: Any,
@@ -149,11 +152,12 @@ class OpenLLM(LLM):
                 if server_type == "http"
                 else openllm.client.GrpcClient
             )
-            client = client_cls(server_url)
+            client = client_cls(server_url, timeout)
 
             super().__init__(
                 **{
                     "server_url": server_url,
+                    "timeout": timeout,
                     "server_type": server_type,
                     "llm_kwargs": llm_kwargs,
                 }
@@ -217,9 +221,9 @@ class OpenLLM(LLM):
     def _identifying_params(self) -> IdentifyingParams:
         """Get the identifying parameters."""
         if self._client is not None:
-            self.llm_kwargs.update(self._client._config())
-            model_name = self._client._metadata()["model_name"]
-            model_id = self._client._metadata()["model_id"]
+            self.llm_kwargs.update(self._client._config)
+            model_name = self._client._metadata.model_dump()["model_name"]
+            model_id = self._client._metadata.model_dump()["model_id"]
         else:
             if self._runner is None:
                 raise ValueError("Runner must be initialized.")
@@ -265,9 +269,11 @@ class OpenLLM(LLM):
             self._identifying_params["model_name"], **copied
         )
         if self._client:
-            res = self._client.generate(
-                prompt, **config.model_dump(flatten=True)
-            ).responses[0]
+            res = (
+                self._client.generate(prompt, **config.model_dump(flatten=True))
+                .outputs[0]
+                .text
+            )
         else:
             assert self._runner is not None
             res = self._runner(prompt, **config.model_dump(flatten=True))