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Test the hypothesis-lab environment running locally on Docker (port 8000).
Uses the standard OpenEnv interface: env.reset() and env.step(action).
"""
import asyncio
import sys
sys.path.insert(0, "/Users/sbhimraj/Documents/Openenv/lab-experiment")
from client import HypothesisLabEnv
from models import HypLabAction, ActionType, ExperimentType
async def main():
print("=== Testing local hypothesis-lab environment ===\n")
async with HypothesisLabEnv(base_url="http://localhost:8000") as env:
# Reset episode
result = await env.reset(noise_level="low")
obs = result.observation
variables = obs.available_variables
print(f"[reset]")
print(f" variables: {variables}")
print(f" budget: {obs.budget_remaining}")
print(f" message: {obs.system_message[:120]}\n")
v1, v2 = variables[0], variables[1]
# Step 1 — intervention experiment
action = HypLabAction(
action_type=ActionType.EXPERIMENT,
experiment_type=ExperimentType.INTERVENTION,
control_variable=v1,
control_value=2.5,
target_variable=v2,
)
result = await env.step(action)
obs = result.observation
print(f"[step 1: intervention]")
print(f" {v1}=2.5 → {v2} = {obs.result_value}")
print(f" info_gain: {obs.info_gain_reward}")
print(f" budget left: {obs.budget_remaining}")
print(f" done: {result.done}\n")
# Step 2 — correlation experiment
action = HypLabAction(
action_type=ActionType.EXPERIMENT,
experiment_type=ExperimentType.CORRELATION,
control_variable=v1,
control_range=[0.0, 1.0, 2.0, 3.0, 4.0],
target_variable=v2,
)
result = await env.step(action)
obs = result.observation
print(f"[step 2: correlation]")
print(f" {v1} swept → {v2} = {obs.result_value}")
print(f" info_gain: {obs.info_gain_reward}")
print(f" budget left: {obs.budget_remaining}")
print(f" done: {result.done}\n")
# Step 3 — submit hypothesis
action = HypLabAction(
action_type=ActionType.SUBMIT,
hypothesis_text=f"{v2} increases linearly with {v1} by approximately 2.5 units",
confidence=0.7,
)
result = await env.step(action)
obs = result.observation
print(f"[step 3: submit]")
print(f" reward: {result.reward}")
print(f" accuracy_score: {obs.accuracy_score}")
print(f" precision_bonus: {obs.precision_bonus}")
print(f" calibration_score: {obs.calibration_score}")
print(f" efficiency_bonus: {obs.efficiency_bonus}")
print(f" done: {result.done}")
if obs.ground_truth_revealed:
print(f" ground_truth: {obs.ground_truth_revealed[:300]}")
print("\n=== Done — environment is working correctly ===")
asyncio.run(main())
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