update

Author: erikchwang

src/agentlab/agents/vl_agent/main.py

@@ -0,0 +1,33 @@
+from agentlab.agents.vl_agent.config import VL_AGENT_ARGS_DICT
+from agentlab.experiments.study import Study
+import logging
+import os
+
+
+logging.getLogger().setLevel(logging.INFO)
+
+vl_agent_args_list = [VL_AGENT_ARGS_DICT["ui_agent"]]
+benchmark = "miniwob"
+os.environ["MINIWOB_URL"] = "file:///mnt/home/miniwob-plusplus/miniwob/html/miniwob/"
+reproducibility_mode = False
+relaunch = False
+n_jobs = 1
+
+
+if __name__ == "__main__":
+    if reproducibility_mode:
+        for vl_agent_args in vl_agent_args_list:
+            vl_agent_args.set_reproducibility_mode()
+    if relaunch:
+        study = Study.load_most_recent(contains=None)
+        study.find_incomplete(include_errors=True)
+    else:
+        study = Study(vl_agent_args_list, benchmark=benchmark, logging_level_stdout=logging.WARNING)
+    study.run(
+        n_jobs=n_jobs,
+        parallel_backend="sequential",
+        strict_reproducibility=reproducibility_mode,
+        n_relaunch=3,
+    )
+    if reproducibility_mode:
+        study.append_to_journal(strict_reproducibility=True)

src/agentlab/agents/vl_agent/vl_model/base.py

@@ -1,9 +1,8 @@
 from abc import ABC, abstractmethod
 from agentlab.llm.llm_utils import AIMessage, Discussion
-from torch.nn import Module
 
 
-class VLModel(ABC, Module):
+class VLModel(ABC):
     @abstractmethod
     def __call__(self, messages: Discussion) -> AIMessage:
         raise NotImplementedError

src/agentlab/agents/vl_agent/vl_model/openrouter_api_model.py

@@ -1,8 +1,7 @@
 from agentlab.llm.llm_utils import AIMessage, Discussion
 from dataclasses import dataclass
-from openai import AsyncOpenAI, RateLimitError
+from openai import OpenAI, RateLimitError
 from .base import VLModel, VLModelArgs
-import asyncio
 import backoff
 import os
 
@@ -15,15 +14,15 @@ def __init__(
         max_tokens: int,
         reproducibility_config: dict,
     ):
-        self.client = AsyncOpenAI(base_url=base_url, api_key=os.getenv("OPENROUTER_API_KEY"))
+        self.client = OpenAI(base_url=base_url, api_key=os.getenv("OPENROUTER_API_KEY"))
         self.model_id = model_id
         self.max_tokens = max_tokens
         self.reproducibility_config = reproducibility_config
 
     def __call__(self, messages: Discussion) -> AIMessage:
         @backoff.on_exception(backoff.expo, RateLimitError)
-        async def get_response(messages, max_tokens, **kwargs):
-            completion = await self.client.chat.completions.create(
+        def get_response(messages, max_tokens, **kwargs):
+            completion = self.client.chat.completions.create(
                 model=self.model_id, messages=messages, max_tokens=max_tokens, **kwargs
             )
             try:
@@ -32,9 +31,7 @@ async def get_response(messages, max_tokens, **kwargs):
                 response = ""
             return response
 
-        response = asyncio.run(
-            get_response(messages, self.max_tokens, **self.reproducibility_config)
-        )
+        response = get_response(messages, self.max_tokens, **self.reproducibility_config)
         return AIMessage([{"type": "text", "text": response}])
 
     def get_stats(self) -> dict: