Add model_path to auxiliary_models.

pyproject.toml

@@ -23,7 +23,7 @@ requires-python = ">=3.10"
 dependencies = [
     "verl==0.3.0.post1",
     "ray[default]>=2.45.0",
-    "vllm>=0.8.5",
+    "vllm==0.8.5.post1",
     "tensordict==0.6.2",
     "wandb",
     "omegaconf",

tests/explorer/runner_pool_test.py

@@ -2,7 +2,7 @@
 import os
 import time
 import unittest
-from typing import List
+from typing import List, Tuple
 
 import ray
 import torch
@@ -87,8 +87,8 @@ def init_process_group(
     def has_api_server(self) -> bool:
         return True
 
-    def api_server_ready(self) -> str:
-        return "http://localhosts:12345"
+    def api_server_ready(self) -> Tuple[str, str]:
+        return "http://localhosts:12345", "placeholder"
 
 
 class RunnerPoolTest(unittest.TestCase):

trinity/common/models/model.py

@@ -103,16 +103,21 @@ def get_ckp_version(self) -> int:
         return ray.get(self.model.get_ckp_version.remote())
 
     def get_openai_client(self) -> openai.OpenAI:
+        """Get the openai client.
+
+        Returns:
+            openai.OpenAI: The openai client. And `model_path` is added to the client which refers to the model path.
+        """
         if self.openai_client is not None:
             return self.openai_client
         if not ray.get(self.model.has_api_server.remote()):
             raise ValueError(
                 "OpenAI API server is not running on current model."
                 "Please set `enable_openai_api` to `True`."
             )
-        api_address = None
+        api_address, model_path = None, None
         while True:
-            api_address = ray.get(self.model.api_server_ready.remote())
+            api_address, model_path = ray.get(self.model.api_server_ready.remote())
             if api_address is not None:
                 break
             else:
@@ -127,4 +132,5 @@ def get_openai_client(self) -> openai.OpenAI:
             base_url=api_address,
             api_key="EMPTY",
         )
+        setattr(self.openai_client, "model_path", model_path)  # TODO: may be removed
         return self.openai_client

trinity/common/models/vllm_async_model.py

@@ -5,7 +5,7 @@
 
 import os
 import re
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Tuple, Union
 
 import aiohttp
 import torch
@@ -319,26 +319,30 @@ async def run_api_server(self):
     async def has_api_server(self) -> bool:
         return self.config.enable_openai_api
 
-    async def api_server_ready(self) -> Optional[str]:
+    async def api_server_ready(self) -> Tuple[Union[str, None], Union[str, None]]:
         """Check if the OpenAI API server is ready.
 
         Returns:
-            str: The URL of the OpenAI API server.
+            api_url (str): The URL of the OpenAI API server.
+            model_path (str): The path of the model.
         """
         if not await self.has_api_server():
-            return None
+            return None, None
         try:
             async with aiohttp.ClientSession() as session:
                 async with session.get(
                     f"http://{self.api_server_host}:{self.api_server_port}/health"
                 ) as response:
                     if response.status == 200:
-                        return f"http://{self.api_server_host}:{self.api_server_port}/v1"
+                        return (
+                            f"http://{self.api_server_host}:{self.api_server_port}/v1",
+                            self.config.model_path,
+                        )
                     else:
-                        return None
+                        return None, None
         except Exception as e:
             self.logger.error(e)
-            return None
+            return None, None
 
     async def reset_prefix_cache(self) -> None:
         await self.async_llm.reset_prefix_cache()

trinity/common/workflows/workflow.py

@@ -41,6 +41,10 @@ def to_workflow(
 
         Args:
             model (ModelWrapper): The rollout model for the workflow.
+            auxiliary_models (List[openai.OpenAI]): The auxiliary models for the workflow.
+
+        Note:
+            `model_path` attribute is added to the `auxiliary_models` for use within the workflow.
 
         Returns:
             Workflow: The generated workflow object.