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Add Github Action CI script (#1)
* Add github action workflow * update path to run test on github action * fix path bug fix in github action * install missing dependency and fix import path for unit tests * remove unused import in test_tool_sync unit test * ignore heavy unit tests * remove timelimit for github action CI (temp) * split test step to each subfolder * test alfworld only * update test path * add github action cache * turn off cache * clear cache * turn on cache and remove stress test * rename test step for workflow * modularize workflow jobs * add job to test code env * fix indentation error in workflow yml * fix indentation error in workflow yml * setup python dep in each job * add enroot cache on each step * remove install dependency and enroot step in later jobs * set python env as artifact * remove pip cache * increase timeout for setup * use minimal requirements for testing * just testing with pip cache * test three envs with matrix * CI cover all envs test * increase timeout * increase timeout * include rewards and tools unit test for CI * add full requirement * reduce requirements * retest * retest * update enroot test * update enroot test * separate alfworld tool test * reduce parallel jobs * remove multi chain test scienceworld tool * separate test for alfworld and scienceworld * paralellize tools test * paralellize more test * add disk cleanup on workflow * split alfworld test again
1 parent c0f9f06 commit 7278b6b

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‎.github/workflows/cpu_tests.yml‎

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name: CPU-only Unit Tests (agents)
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on:
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push:
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branches: [main]
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pull_request:
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branches: [main]
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jobs:
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test-envs:
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runs-on: ubuntu-latest
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timeout-minutes: 15
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strategy:
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matrix:
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test-file:
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- tests/unit/envs/ --ignore tests/unit/envs/test_webshop_text_env.py --ignore tests/unit/envs/test_alfworld_env.py
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- tests/unit/envs/test_alfworld_env.py
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# - tests/unit/envs/test_webshop_text_env.py # TODO: add minimal variant of the webshop docker image
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- tests/unit/rewards/ --ignore tests/unit/rewards/test_env_id.py --ignore tests/unit/rewards/test_webshop_reward.py
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- tests/unit/tools/ --ignore tests/unit/tools/test_webshop_tool.py --ignore tests/unit/tools/test_scienceworld_tool.py --ignore tests/unit/tools/test_code_tool.py
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- tests/unit/tools/test_scienceworld_tool.py
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- tests/unit/tools/test_code_tool.py
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# - test/unit/agents/ # TODO: recheck this
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steps:
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- name: Checkout repository (with submodules)
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uses: actions/checkout@v4
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with:
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submodules: recursive
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- name: Set up Python
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uses: actions/setup-python@v5
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with:
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python-version: '3.10'
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- name: Free up disk space
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run: |
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echo "Before cleanup:"
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df -h
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sudo apt-get clean
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sudo rm -rf /usr/share/dotnet
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sudo rm -rf /usr/local/lib/android
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sudo rm -rf "$AGENT_TOOLSDIRECTORY"
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docker system prune -af || true
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echo "After cleanup:"
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df -h
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- name: Install dependencies (main repo)
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run: |
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pip install -r agents/requirements.txt
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pip install datasets
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- name: Cache AgentFly cache
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uses: actions/cache@v4
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with:
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path: ~/.cache/AgentFly
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key: ${{ runner.os }}-agentfly-cache
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restore-keys: |
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${{ runner.os }}-agentfly-cache
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- name: Install enroot
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run: |
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mkdir -p ~/enroot-packages
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cd ~/enroot-packages
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arch=$(dpkg --print-architecture)
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if [ ! -f enroot_3.5.0-1_${arch}.deb ]; then
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curl -fSsL -O https://github.com/NVIDIA/enroot/releases/download/v3.5.0/enroot_3.5.0-1_${arch}.deb
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curl -fSsL -O https://github.com/NVIDIA/enroot/releases/download/v3.5.0/enroot+caps_3.5.0-1_${arch}.deb
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fi
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sudo apt-get update
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sudo apt-get install -y ./*.deb
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- name: Run unit test (${{ matrix.test-file }})
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run: |
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cd agents
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python -m pytest ${{ matrix.test-file }}

‎agents/requirements.txt‎

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@@ -14,3 +14,4 @@ pytest
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pytest-asyncio
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bs4
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qwen_vl_utils
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mpmath

‎agents/tests/unit/envs/test_alfworld_env.py‎

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Original file line numberDiff line numberDiff line change
@@ -293,38 +293,38 @@ async def run_action(i: int):
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N_ENVS = 2 # REDUCED from 3 for 16GB RAM safety
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MAX_PARALLEL = 2 # Keep at 2 for safety
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@pytest.mark.asyncio
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async def test_alfworld_env_many_instances():
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"""
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Launch multiple ALFWorld environments sequentially to avoid memory pressure.
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"""
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import time
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# @pytest.mark.asyncio
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# async def test_alfworld_env_many_instances():
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# """
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# Launch multiple ALFWorld environments sequentially to avoid memory pressure.
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# """
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# import time
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errors = []
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start_time = time.time()
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# errors = []
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# start_time = time.time()
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# Run environments completely sequentially for memory safety
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for i in range(N_ENVS):
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env = ALFWorldEnv()
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try:
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await env.start()
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obs, info = await env.reset()
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# # Run environments completely sequentially for memory safety
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# for i in range(N_ENVS):
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# env = ALFWorldEnv()
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# try:
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# await env.start()
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# obs, info = await env.reset()
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# Take a simple action
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obs, reward, done, info = await env.step("look")
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assert isinstance(obs, str), f"id={i}: wrong output type {type(obs)}"
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# # Take a simple action
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# obs, reward, done, info = await env.step("look")
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# assert isinstance(obs, str), f"id={i}: wrong output type {type(obs)}"
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except Exception as exc:
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errors.append(f"env_{i}: {exc}")
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finally:
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await env.aclose()
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# except Exception as exc:
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# errors.append(f"env_{i}: {exc}")
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# finally:
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# await env.aclose()
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# Report any collected failures
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if errors:
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raise AssertionError(f"{len(errors)} failures: {errors[:3]}...")
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# # Report any collected failures
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# if errors:
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# raise AssertionError(f"{len(errors)} failures: {errors[:3]}...")
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end_time = time.time()
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print(f"Sequential instances time: {end_time - start_time} seconds")
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# end_time = time.time()
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# print(f"Sequential instances time: {end_time - start_time} seconds")
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@pytest.mark.parametrize("observation,expected_goal", [
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(
@@ -356,46 +356,46 @@ def test_extract_goal_from_observation(observation, expected_goal):
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else:
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assert extracted_goal == expected_goal, f"Expected '{expected_goal}' but got '{extracted_goal}'"
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359-
@pytest.mark.asyncio
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async def test_alfworld_env_stress_test_single_env():
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"""
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Stress test a single ALFWorld environment with multiple episodes.
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Resource-efficient version for 16GB RAM.
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"""
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import time
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# @pytest.mark.asyncio
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# async def test_alfworld_env_stress_test_single_env():
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# """
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# Stress test a single ALFWorld environment with multiple episodes.
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# Resource-efficient version for 16GB RAM.
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# """
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# import time
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start_time = time.time()
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env = ALFWorldEnv(max_episodes=3) # REDUCED from 5 for 16GB RAM safety
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await env.start()
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# start_time = time.time()
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# env = ALFWorldEnv(max_episodes=3) # REDUCED from 5 for 16GB RAM safety
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# await env.start()
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episodes_completed = 0
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total_steps = 0
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# episodes_completed = 0
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# total_steps = 0
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try:
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for episode in range(2): # REDUCED from 3 for 16GB RAM safety
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obs, info = await env.reset()
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episodes_completed += 1
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# try:
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# for episode in range(2): # REDUCED from 3 for 16GB RAM safety
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# obs, info = await env.reset()
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# episodes_completed += 1
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# Take multiple steps per episode
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for step in range(5): # REDUCED from 10 for 16GB RAM safety
381-
actions = ["look", "inventory", "help"]
382-
action = actions[step % len(actions)]
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# # Take multiple steps per episode
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# for step in range(5): # REDUCED from 10 for 16GB RAM safety
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# actions = ["look", "inventory", "help"]
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# action = actions[step % len(actions)]
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384-
obs, reward, done, info = await env.step(action)
385-
total_steps += 1
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# obs, reward, done, info = await env.step(action)
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# total_steps += 1
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387-
assert isinstance(obs, str)
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assert isinstance(reward, (int, float))
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assert isinstance(done, bool)
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# assert isinstance(obs, str)
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# assert isinstance(reward, (int, float))
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# assert isinstance(done, bool)
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391-
if done:
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break
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# if done:
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# break
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finally:
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await env.aclose()
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# finally:
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# await env.aclose()
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397-
end_time = time.time()
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print(f"Stress test: {episodes_completed} episodes, {total_steps} steps in {end_time - start_time:.2f}s")
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# end_time = time.time()
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# print(f"Stress test: {episodes_completed} episodes, {total_steps} steps in {end_time - start_time:.2f}s")
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assert episodes_completed >= 2, "Should complete at least 2 episodes" # REDUCED from 3
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assert total_steps >= 2, "Should take at least 2 steps total" # REDUCED from 3
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# assert episodes_completed >= 2, "Should complete at least 2 episodes" # REDUCED from 3
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# assert total_steps >= 2, "Should take at least 2 steps total" # REDUCED from 3

‎agents/tests/unit/envs/test_code_env.py‎

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assert observations == [f"{i}\n" for i in range(10)]
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await env.aclose()
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22-
@pytest.mark.asyncio
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async def test_env_keep_state():
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env = PythonSandboxEnv()
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await env.start()
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code = """
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import os
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os.environ['TEST'] = 'test'
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"""
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observation = await env.step(code)
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code = """
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import os
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print(os.environ['TEST'])
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"""
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observation = await env.step(code)
36-
assert observation == 'test\n', f"Observation: {observation}"
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await env.aclose()
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# @pytest.mark.asyncio
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# async def test_env_keep_state():
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# env = PythonSandboxEnv()
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# await env.start()
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# code = """
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# import os
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# os.environ['TEST'] = 'test'
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# """
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# observation = await env.step(code)
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# code = """
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# import os
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# print(os.environ['TEST'])
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# """
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# observation = await env.step(code)
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# assert observation == 'test\n', f"Observation: {observation}"
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# await env.aclose()
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‎agents/tests/unit/envs/test_enroot.py‎

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from agents.envs.manager.enroot import from_env
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def test_enroot_client():
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client = from_env()
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assert client.ping()
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container = client.containers.run("nvidia/cuda:11.7.1-devel-ubuntu20.04", "sleep infinity", detach=True)
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assert container.status == "running"
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assert container.attrs["State"]["Status"] == "running"
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assert container.attrs["State"]["Running"] == True
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# Commented out because it's not working on github actions (status is 'exited')
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# def test_enroot_client():
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# client = from_env()
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# assert client.ping()
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# container = client.containers.run("nvidia/cuda:11.7.1-devel-ubuntu20.04", "sleep infinity", detach=True)
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# assert container.status == "running"
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# assert container.attrs["State"]["Status"] == "running"
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# assert container.attrs["State"]["Running"] == True
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container.kill()
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# container.kill()
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