new

Author: Your Name

.gitignore

@@ -1,4 +1,3 @@
-<<<<<<< HEAD
 *.csv
 **/*.pt
 **/checkpoints
@@ -166,9 +165,8 @@ pass32_uitars_0928
 viz/
 loss_dump/
 pass32_uitars_0928
-rollouter/
-=======
-dist/
+rollouter/dist/
 .DS_Store
 node_modules/
->>>>>>> 9521ee430f6f63fd2827701d44139186350b2b94
+.vscode/
+tests/osworld/

LICENSE

@@ -1,4 +1,3 @@
-<<<<<<< HEAD
 
                                  Apache License
                            Version 2.0, January 2004
@@ -201,26 +200,3 @@
    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    See the License for the specific language governing permissions and
    limitations under the License.
-=======
-MIT License
-
-Copyright (c) 2025  Computer Use Agents
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
->>>>>>> 9521ee430f6f63fd2827701d44139186350b2b94

loss_dump/minibs32_adv_mean.txt

@@ -2884,3 +2884,9 @@
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tests/osworld/test_batch_level_sampling.py

@@ -101,7 +101,8 @@ def test_agent():
         messages = list(np.repeat(batch["messages"], rollout_n, axis=0))
         print("task_configs", len(task_configs), type(task_configs[0]))
         runners = [TrajectoryRunner.remote(task_config) for task_config in task_configs]
-        reflection_agent = create_reflection_agent("openai", base_url="https://dashscope.aliyuncs.com/compatible-mode/v1", model="qwen2.5-32b-instruct", api_key="sk-075466341a4d4bf584ccb233c85cb6c1")
+        api_key = os.getenv("DASHSCOPE_API_KEY", "")
+        reflection_agent = create_reflection_agent("openai", base_url="https://dashscope.aliyuncs.com/compatible-mode/v1", model="qwen2.5-32b-instruct", api_key=api_key)
 
         try:
             run_agent_loop(llm, 

tests/osworld/test_reward_auto.py

@@ -12,7 +12,9 @@ def setup_env_vars(monkeypatch):
     # Set environment variables for reward server
     monkeypatch.setenv("REWARD_SERVER_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1")
     monkeypatch.setenv("REWARD_MODEL", "qwen2.5-32b-instruct")
-    monkeypatch.setenv("REWARD_SERVER_API_KEY", "sk-075466341a4d4bf584ccb233c85cb6c1")
+    # API key should be set via environment variable, not hardcoded
+    reward_api_key = os.getenv("REWARD_SERVER_API_KEY", os.getenv("DASHSCOPE_API_KEY", ""))
+    monkeypatch.setenv("REWARD_SERVER_API_KEY", reward_api_key)
     monkeypatch.setenv("WINDOW_SIZE", "5")
     monkeypatch.setenv("STRIDE_SIZE", "5")
     monkeypatch.setenv("N_COMPLETIONS", "4")