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import importlib
from flatmate_rl.models import FlatmateRlAction
from flatmate_rl.server.flatmate_rl_environment import FlatmateRlEnvironment
from flatmate_rl.server.heuristic_policy import autopolicy_next_request, expected_policy_action
from flatmate_rl.server.scenarios import POSTS, SCENARIOS
def _tool(env: FlatmateRlEnvironment, name: str, **kwargs):
scenario_id = env.state.scenario_id or getattr(getattr(env, "_episode", None), "_scenario", {}).get("task_id", "")
if not kwargs and name == "store_user_details":
kwargs = dict(SCENARIOS[scenario_id]["scenario_creation_config"]["expected_answers"])
if not kwargs and name == "store_seller_details":
kwargs = dict(SCENARIOS[scenario_id]["scenario_creation_config"]["followup_seller_expected_answers"])
return env.step(
FlatmateRlAction(
action_type="tool_call",
tool_name=name,
tool_arguments=kwargs,
)
)
def _msg(env: FlatmateRlEnvironment, text: str):
return env.step(
FlatmateRlAction(
action_type="assistant_message",
assistant_message=text,
)
)
def test_scenarios_are_self_consistent() -> None:
for scenario_id, scenario in SCENARIOS.items():
assert scenario["task_id"] == scenario_id
assert scenario["label"]
assert scenario["difficulty"] in {"medium", "hard"}
assert scenario["initial_user_message"]
assert scenario["task_post_ids"]
assert len(scenario["task_post_ids"]) == len(set(scenario["task_post_ids"]))
assert all(post_id in POSTS for post_id in scenario["task_post_ids"])
ground_truth = scenario["ground_truth"]
expected_answers = scenario["scenario_creation_config"]["expected_answers"]
assert ground_truth["required_bookings"] >= 1
assert ground_truth["required_tool_calls"]
assert ground_truth["required_info"]
assert ground_truth["optimal_posts"]
assert set(ground_truth["optimal_posts"]).issubset(set(scenario["task_post_ids"]) | {"post_dynamic_followup_1"})
assert set(ground_truth["acceptable_posts"]).issubset(set(scenario["task_post_ids"]))
assert set(ground_truth["dealbreaker_posts"]).issubset(set(scenario["task_post_ids"]))
assert expected_answers["user_type"] == "buyer"
assert expected_answers["user_sub_type"] == "flat"
assert expected_answers["budget_max"] == scenario["buyer_profile"]["budget_max"]
assert expected_answers["dietary"] == scenario["buyer_profile"]["dietary"]
assert expected_answers["areas"] == scenario["buyer_profile"]["areas"]
assert expected_answers["occupation"] == scenario["buyer_profile"]["occupation"]
assert expected_answers["visit_availability"] == scenario["buyer_profile"]["visit_availability"]
if scenario_id == "task_visit_single_seller_followup":
assert scenario["seller_profile"] is not None
assert (
scenario["scenario_creation_config"]["followup_seller_expected_answers"]["calendar_slots"]
== scenario["seller_profile"]["calendar_slots"]
)
assert scenario["scenario_creation_config"]["followup_seller_expected_answers"]["area"] == scenario["seller_profile"]["area"]
else:
assert scenario["seller_profile"] is None
def test_reset_exposes_initial_buyer_message() -> None:
env = FlatmateRlEnvironment()
observation = env.reset(scenario_id="task_visit_single")
assert observation.status == "ready"
assert observation.scenario_id == "task_visit_single"
assert observation.phase == "buyer"
assert "budget is up to Rs. 20,000" in observation.last_user_message
assert observation.remaining_required_fields == ["diet", "visit_availability"]
def test_seeded_reset_varies_values_without_changing_episode_flow() -> None:
default_env = FlatmateRlEnvironment()
default_obs = default_env.reset(scenario_id="task_visit_single")
seeded_env = FlatmateRlEnvironment()
seeded_obs = seeded_env.reset(scenario_id="task_visit_single", seed=123)
seeded_episode = seeded_env._episode # type: ignore[attr-defined]
assert seeded_obs.scenario_id == default_obs.scenario_id
assert seeded_obs.remaining_required_fields == default_obs.remaining_required_fields
assert seeded_episode._scenario["task_post_ids"] == SCENARIOS["task_visit_single"]["task_post_ids"]
assert seeded_episode._scenario["ground_truth"] == SCENARIOS["task_visit_single"]["ground_truth"]
assert seeded_episode._scenario["buyer_profile"]["budget_max"] != SCENARIOS["task_visit_single"]["buyer_profile"]["budget_max"]
assert (
seeded_episode._scenario["scenario_creation_config"]["expected_answers"]["budget_max"]
== seeded_episode._scenario["buyer_profile"]["budget_max"]
)
def test_search_before_store_user_details_fails() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single")
result = _tool(env, "search_posts")
assert result.last_tool_result["success"] is False
assert "store_user_details must be called before search_posts" in result.last_tool_result["message"]
def test_store_user_details_does_not_return_expected_answers_payload() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single")
_msg(env, "Please share your dietary preference and visit availability.")
result = _tool(env, "store_user_details")
assert result.last_tool_result == {
"tool": "store_user_details",
"success": True,
"message": "Buyer profile stored.",
}
def test_observation_surfaces_prerequisites_and_recent_tool_calls() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single")
_msg(env, "Please share your dietary preference and visit availability.")
stored = _tool(env, "store_user_details")
assert stored.prerequisites_satisfied["details_stored"] is True
assert stored.prerequisites_satisfied["posts_searched"] is False
assert stored.recent_tool_calls[-1] == {
"tool_name": "store_user_details",
"tool_arguments_summary": SCENARIOS["task_visit_single"]["scenario_creation_config"]["expected_answers"],
"success": True,
}
searched = _tool(env, "search_posts")
assert searched.prerequisites_satisfied["posts_searched"] is True
assert searched.recent_tool_calls[-1]["tool_name"] == "search_posts"
assert searched.recent_tool_calls[-1]["success"] is True
def test_strict_eval_mode_hides_scenario_metadata_and_reward(monkeypatch) -> None:
monkeypatch.setenv("STRICT_EVAL_MODE", "1")
environment_module = importlib.import_module("flatmate_rl.server.flatmate_rl_environment")
environment_module = importlib.reload(environment_module)
env = environment_module.FlatmateRlEnvironment()
observation = env.reset(scenario_id="task_visit_single")
assert observation.scenario_id == ""
assert observation.scenario_label == ""
assert observation.difficulty == ""
assert observation.gathered_fields == []
assert observation.remaining_required_fields == []
assert observation.violations == []
assert observation.tool_trace == []
assert observation.total_reward == 0.0
assert "diet" in observation.feedback_summary
assert "visit_availability" in observation.feedback_summary
_msg(env, "Please share your dietary preference and visit availability.")
result = _tool(env, "store_user_details")
assert result.last_tool_result == {
"tool": "store_user_details",
"success": True,
"message": "Buyer profile stored.",
}
assert result.total_reward == 0.0
assert result.tool_trace == []
monkeypatch.delenv("STRICT_EVAL_MODE", raising=False)
importlib.reload(environment_module)
def test_single_visit_scenario_books_one_visit() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single")
_msg(env, "Please share your dietary preference and visit availability.")
_tool(env, "store_user_details")
_tool(env, "search_posts")
_tool(env, "match_location_preference", post_ids=["post_023", "post_031"])
_tool(env, "get_commute_time", post_ids=["post_023", "post_031"])
_tool(env, "check_calendar_slots", post_ids=["post_023"])
_msg(env, "post_023 is available Saturday 11am. Please confirm Saturday 11am if that works.")
_tool(env, "contact_poster", post_id="post_023", time_text="Saturday 11am")
final_obs = _tool(env, "book_viewing", post_id="post_023", time_text="Saturday 11am")
assert final_obs.done is True
assert final_obs.booked_visits == [{"post_id": "post_023", "time": "Saturday 11am"}]
assert len(final_obs.seller_conversation_history) >= 2
assert final_obs.seller_conversation_history[0]["role"] == "assistant"
assert final_obs.seller_conversation_history[1]["role"] == "user"
assert "buyer profile" in final_obs.seller_conversation_history[0]["content"]
assert "budget up to Rs. 20000" in final_obs.seller_conversation_history[0]["content"]
assert "Can you confirm the buyer profile is acceptable" in final_obs.seller_conversation_history[0]["content"]
assert "Saturday 11am" in final_obs.seller_conversation_history[0]["content"]
assert "buyer profile is acceptable" in final_obs.seller_conversation_history[1]["content"]
assert "Saturday 11am works for the visit" in final_obs.seller_conversation_history[1]["content"]
contact_result = next(result for result in final_obs.tool_results if result["tool"] == "contact_poster")
assert contact_result["buyer_profile_shared"] is True
assert contact_result["seller_profile_fit_confirmed"] is True
def test_buyer_answers_diet_and_availability_when_broker_asks_for_both() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single")
obs = _msg(env, "Please share your dietary preference and visit availability.")
assert "non-vegetarian" in obs.last_user_message
assert "visit availability" in obs.last_user_message
assert "diet" in obs.gathered_fields
assert "visit_availability" in obs.gathered_fields
assert obs.remaining_required_fields == []
def test_heuristic_policy_progresses_after_confirmation_in_single_visit() -> None:
env = FlatmateRlEnvironment()
obs = env.reset(scenario_id="task_visit_single")
for _ in range(12):
payload = expected_policy_action("task_visit_single", obs.model_dump())
assert payload is not None
obs = env.step(FlatmateRlAction.model_validate(payload))
if obs.done:
break
assert obs.done is True
assert obs.booked_visits == [{"post_id": "post_023", "time": "Saturday 11am"}]
def test_redundant_successful_tool_call_gets_small_penalty_without_termination() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single")
_msg(env, "Please share your dietary preference and visit availability.")
_tool(env, "store_user_details")
_tool(env, "search_posts")
redundant_step = _tool(env, "search_posts")
assert redundant_step.done is False
assert redundant_step.status == "tool_result"
assert redundant_step.step_reward == -0.05
assert "redundant_tool_call" in redundant_step.message
assert "redundant_tool_call" in redundant_step.violations
def test_seller_followup_non_canonical_tool_order_gets_small_penalty_without_termination() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single_seller_followup")
_msg(env, "Please share your dietary preference.")
_tool(env, "store_user_details")
_tool(env, "search_posts")
wrong_transition = _tool(env, "match_location_preference", post_ids=["post_131"])
assert wrong_transition.done is False
assert wrong_transition.status == "tool_result"
assert wrong_transition.step_reward == -0.1
assert "non_canonical_order: expected close_buyer_conversation, got match_location_preference" in wrong_transition.message
assert "non_canonical_order" in wrong_transition.violations
def test_legal_non_canonical_tool_after_store_can_continue() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single")
_msg(env, "Please share your dietary preference and visit availability.")
_tool(env, "store_user_details")
obs = _tool(env, "match_location_preference", post_ids=["post_023"])
assert obs.done is False
assert obs.step_reward == -0.1
assert "non_canonical_order" in obs.violations
def test_schema_valid_non_canonical_action_never_uses_legacy_flow_failure() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single")
_msg(env, "Please share your dietary preference and visit availability.")
_tool(env, "store_user_details")
obs = env.step(
FlatmateRlAction(
action_type="tool_call",
tool_name="match_location_preference",
tool_arguments={"post_ids": ["post_023", "post_031"]},
)
)
assert obs.done is False
assert obs.status == "tool_result"
assert obs.step_reward == -0.1
assert "expected_flow_violation" not in obs.violations
assert "Expected flow violation" not in obs.message
assert "non_canonical_order" in obs.violations
assert "non_canonical_order: expected search_posts, got match_location_preference" in obs.message
def test_seller_followup_search_returns_no_visit_compatible_current_posts() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single_seller_followup")
_msg(env, "Please share your dietary preference.")
_tool(env, "store_user_details")
obs = _tool(env, "search_posts")
assert obs.last_tool_result["post_ids"] == []
assert obs.last_tool_result["rejected_for_slot_mismatch"] == ["post_131", "post_132"]
assert "search_posts returned 0 results" in obs.feedback_summary
def test_seller_followup_accepts_paraphrased_assistant_message() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single_seller_followup")
obs = _msg(
env,
"Could you please let me know about your dietary preferences? This will help me find the best match for you.",
)
assert obs.status == "user_response"
assert obs.done is False
assert obs.violations == []
assert "diet" in obs.gathered_fields
def test_seller_followup_accepts_expected_tool_with_different_arguments() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single_seller_followup")
_msg(
env,
"Could you please let me know about your dietary preferences? This will help me find the best match for you.",
)
obs = _tool(env, "store_user_details", diet="non-vegetarian")
assert obs.status == "tool_result"
assert obs.done is False
assert obs.violations == []
assert obs.last_tool_result["success"] is True
def test_seller_followup_match_tools_infer_dynamic_post_when_args_are_loose() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single_seller_followup")
_msg(env, "Please share your dietary preference.")
_tool(env, "store_user_details")
_tool(env, "search_posts")
_tool(env, "close_buyer_conversation")
_msg(env, "Please share the household dietary setup, who the flat is for, and available time slots.")
_tool(env, "store_seller_details", dietary="non-vegetarian", occupation_requirement="working professionals")
match_obs = _tool(env, "match_location_preference", area="Jogeshwari", rent=19500)
assert match_obs.last_tool_result["matches"] == {"post_dynamic_followup_1": {"match": True}}
slot_obs = _tool(env, "check_table_slot_matches", post_ids=["post_dynamic_followup_1"])
assert slot_obs.last_tool_result["slot_matches"] == {
"post_dynamic_followup_1": ["Saturday 4pm", "Sunday 5pm"]
}
confirm_obs = _tool(
env,
"confirm_seller_match",
post_id="post_dynamic_followup_1",
time_text="Sunday 5pm",
)
assert confirm_obs.last_tool_result["success"] is True
assert confirm_obs.last_tool_result["time_text"] == "Sunday 5pm"
offer_obs = _tool(env, "offer_matched_listing_to_buyer", post_id="post_dynamic_followup_1", time_text="Sunday 5pm")
assert offer_obs.last_tool_result["success"] is True
final_obs = _tool(env, "schedule_table_visit", post_id="post_dynamic_followup_1", time_text="Sunday 5pm")
assert final_obs.done is True
assert final_obs.booked_visits == [{"post_id": "post_dynamic_followup_1", "time": "Sunday 5pm"}]
def test_heuristic_policy_recovers_from_strict_eval_feedback() -> None:
sanitized_observation = {
"done": False,
"phase": "buyer",
"buyer_profile_stored": False,
"seller_profile_stored": False,
"remaining_required_fields": [],
"feedback_summary": "Ask the buyer for these missing fields before storing details: diet, visit_availability.",
"message": "Missing buyer fields: diet, visit_availability.",
"last_tool_result": {
"tool": "store_user_details",
"success": False,
"message": "Missing buyer fields: diet, visit_availability.",
},
"booked_visits": [],
"selected_posts": [],
"tool_trace": [],
"buyer_conversation_history": [
{
"role": "user",
"content": "Hi, I'm looking for a flatmate-share near Goregaon East.",
}
],
"status": "tool_result",
}
action = autopolicy_next_request("task_visit_single", sanitized_observation)
assert action == {
"action_type": "assistant_message",
"assistant_message": "Please share your dietary preference and visit availability.",
}
def test_hidden_flex_requires_alternative_slot_to_unlock_backup_availability() -> None:
env = FlatmateRlEnvironment()
obs = env.reset(scenario_id="task_visit_single_hidden_flex")
assert "Tuesday after 6pm" in obs.last_user_message
obs = _msg(env, "Please share your dietary preference.")
assert obs.last_user_message == "I’m non-vegetarian."
_tool(env, "store_user_details")
_tool(env, "search_posts")
_tool(env, "match_location_preference", post_ids=["post_023", "post_052"])
_tool(env, "get_commute_time", post_ids=["post_023", "post_052"])
_tool(env, "check_calendar_slots", post_ids=["post_023", "post_052"])
obs = _msg(env, "No Tuesday slot matches. I can offer Saturday 1pm or Sunday 5pm instead.")
assert "confirm" in obs.last_user_message.lower()
assert "Sunday 5pm" in obs.last_user_message or "Saturday 1pm" in obs.last_user_message
_tool(env, "contact_poster", post_id="post_023", time_text="Sunday 5pm")
obs = _tool(env, "book_viewing", post_id="post_023", time_text="Sunday 5pm")
assert obs.done is True
assert obs.booked_visits == [{"post_id": "post_023", "time": "Sunday 5pm"}]
def test_multi_visit_scenario_books_two_visits() -> None:
env = FlatmateRlEnvironment()
obs = env.reset(scenario_id="task_visit_multi")
for _ in range(20):
payload = expected_policy_action("task_visit_multi", obs.model_dump())
assert payload is not None
obs = env.step(FlatmateRlAction.model_validate(payload))
if obs.done:
break
assert obs.done is True
assert len(obs.booked_visits) == 2
def test_seller_followup_scenario_schedules_dynamic_visit() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_single_seller_followup")
_msg(env, "Please share your dietary preference.")
_tool(env, "store_user_details")
_tool(env, "search_posts")
transition = _tool(env, "close_buyer_conversation")
assert transition.phase == "seller"
assert "I will follow up if a suitable listing comes in" in transition.buyer_conversation_history[-1]["content"]
assert "listing a new flatmate-share opening" in transition.seller_conversation_history[-1]["content"]
_msg(env, "Please share the household dietary setup, who the flat is for, and available time slots.")
_tool(env, "store_seller_details")
_tool(env, "match_location_preference", post_ids=["post_dynamic_followup_1"])
_tool(env, "check_table_slot_matches", post_ids=["post_dynamic_followup_1"])
_tool(env, "confirm_seller_match", post_id="post_dynamic_followup_1", time_text="Sunday 5pm")
_tool(env, "offer_matched_listing_to_buyer", post_id="post_dynamic_followup_1", time_text="Sunday 5pm")
final_obs = _tool(env, "schedule_table_visit", post_id="post_dynamic_followup_1", time_text="Sunday 5pm")
assert final_obs.done is True
assert final_obs.booked_visits == [{"post_id": "post_dynamic_followup_1", "time": "Sunday 5pm"}]
def test_conflict_check_calendar_slots_exposes_pre_booked_and_available() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_conflict_check")
_msg(env, "Please share your dietary preference and visit availability.")
_tool(env, "store_user_details")
_tool(env, "search_posts")
_tool(env, "match_location_preference", post_ids=["post_142"])
_tool(env, "get_commute_time", post_ids=["post_142"])
obs = _tool(env, "check_calendar_slots", post_ids=["post_142"])
assert obs.last_tool_result["success"] is True
assert obs.last_tool_result["calendar_slots"]["post_142"] == ["Sunday 5pm"]
assert obs.last_tool_result["pre_booked_slots"]["post_142"] == ["Saturday 11am", "Saturday 4pm"]
assert "already booked" in obs.last_tool_result["message"]
def test_conflict_check_cannot_book_pre_booked_slot() -> None:
env = FlatmateRlEnvironment()
env.reset(scenario_id="task_visit_conflict_check")
_msg(env, "Please share your dietary preference and visit availability.")
_tool(env, "store_user_details")
_tool(env, "search_posts")
_tool(env, "match_location_preference", post_ids=["post_142"])
_tool(env, "get_commute_time", post_ids=["post_142"])
_tool(env, "check_calendar_slots", post_ids=["post_142"])
obs = _tool(env, "contact_poster", post_id="post_142", time_text="Saturday 11am")
assert obs.last_tool_result["success"] is False
assert obs.done is False
def test_conflict_check_heuristic_books_only_available_slot() -> None:
env = FlatmateRlEnvironment()
obs = env.reset(scenario_id="task_visit_conflict_check")
for _ in range(14):
payload = expected_policy_action("task_visit_conflict_check", obs.model_dump())
assert payload is not None
obs = env.step(FlatmateRlAction.model_validate(payload))
if obs.done:
break
assert obs.done is True
assert obs.booked_visits == [{"post_id": "post_142", "time": "Sunday 5pm"}]
def test_negotiation_heuristic_confirms_deal_with_agreed_rent() -> None:
env = FlatmateRlEnvironment()
obs = env.reset(scenario_id="task_negotiation_hidden_budget")
for _ in range(14):
payload = expected_policy_action("task_negotiation_hidden_budget", obs.model_dump())
assert payload is not None
obs = env.step(FlatmateRlAction.model_validate(payload))
if obs.done:
break
assert obs.done is True
assert obs.status == "completed"
assert obs.booked_visits == [{"post_id": "post_155", "time": "negotiated_deal", "agreed_rent": 21000}]
assert obs.last_tool_result["tool"] == "confirm_negotiated_deal"
assert any("Would you accept Rs. 21000" in item["content"] for item in obs.seller_conversation_history)
assert any("I can accept Rs. 21000" in item["content"] for item in obs.seller_conversation_history)
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