You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
546 lines
22 KiB
Python
546 lines
22 KiB
Python
import os
|
|
import unittest
|
|
|
|
os.environ.setdefault("DEBUG", "false")
|
|
|
|
from datetime import datetime, timedelta
|
|
|
|
from app.services.orchestration.conversation_policy import ConversationPolicy
|
|
from app.services.orchestration.entity_normalizer import EntityNormalizer
|
|
from app.services.orchestration.message_planner import MessagePlanner
|
|
from app.services.orchestration.orquestrador_service import OrquestradorService
|
|
|
|
|
|
class FakeLLM:
|
|
def __init__(self, responses):
|
|
self.responses = list(responses)
|
|
self.calls = 0
|
|
|
|
async def generate_response(self, message: str, tools):
|
|
self.calls += 1
|
|
if self.responses:
|
|
return self.responses.pop(0)
|
|
return {"response": "", "tool_call": None}
|
|
|
|
|
|
class FakeState:
|
|
def __init__(self, entries=None, contexts=None):
|
|
self.entries = entries or {}
|
|
self.contexts = contexts or {}
|
|
|
|
def get_entry(self, bucket: str, user_id: int | None, *, expire: bool = False):
|
|
if user_id is None:
|
|
return None
|
|
return self.entries.get(bucket, {}).get(user_id)
|
|
|
|
def set_entry(self, bucket: str, user_id: int | None, value: dict):
|
|
if user_id is None:
|
|
return
|
|
self.entries.setdefault(bucket, {})[user_id] = value
|
|
|
|
def pop_entry(self, bucket: str, user_id: int | None):
|
|
if user_id is None:
|
|
return None
|
|
return self.entries.get(bucket, {}).pop(user_id, None)
|
|
|
|
|
|
class FakeToolExecutor:
|
|
def __init__(self, result=None):
|
|
self.result = result or {"ok": True}
|
|
self.calls = []
|
|
|
|
async def execute(self, tool_name: str, arguments: dict, user_id: int | None = None):
|
|
self.calls.append((tool_name, arguments, user_id))
|
|
if tool_name == "consultar_estoque" and arguments.get("preco_max") and float(arguments["preco_max"]) > 50000:
|
|
return [
|
|
{"id": 7, "modelo": "Hyundai HB20 2022", "categoria": "hatch", "preco": 54500.0},
|
|
{"id": 8, "modelo": "Chevrolet Onix 2023", "categoria": "hatch", "preco": 58900.0},
|
|
]
|
|
return self.result
|
|
|
|
def coerce_http_error(self, exc):
|
|
detail = exc.detail if isinstance(exc.detail, dict) else {}
|
|
return {
|
|
"code": detail.get("code", "tool_error"),
|
|
"message": detail.get("message", str(exc)),
|
|
"retryable": bool(detail.get("retryable", False)),
|
|
"field": detail.get("field"),
|
|
}
|
|
|
|
|
|
class FakePolicyService:
|
|
def __init__(self, state):
|
|
self.state = state
|
|
self.normalizer = EntityNormalizer()
|
|
|
|
def _get_user_context(self, user_id: int | None):
|
|
if user_id is None:
|
|
return None
|
|
return self.state.contexts.get(user_id)
|
|
|
|
def _new_tab_memory(self, user_id: int | None):
|
|
return {}
|
|
|
|
def _is_affirmative_message(self, text: str) -> bool:
|
|
normalized = self.normalizer.normalize_text(text).strip().rstrip(".!?,;:")
|
|
return normalized in {"sim", "pode", "ok", "confirmo", "aceito", "fechado", "pode sim"}
|
|
|
|
def _is_negative_message(self, text: str) -> bool:
|
|
normalized = self.normalizer.normalize_text(text).strip().rstrip(".!?,;:")
|
|
return normalized in {"nao", "nao quero"} or normalized.startswith("nao")
|
|
|
|
def _clear_user_conversation_state(self, user_id: int | None) -> None:
|
|
context = self._get_user_context(user_id)
|
|
if context:
|
|
context["pending_order_selection"] = None
|
|
|
|
async def handle_message(self, message: str, user_id: int | None = None) -> str:
|
|
return f"handled:{message}"
|
|
|
|
def _render_missing_review_fields_prompt(self, missing_fields: list[str]) -> str:
|
|
return "missing review"
|
|
|
|
def _render_missing_review_reschedule_fields_prompt(self, missing_fields: list[str]) -> str:
|
|
return "missing review reschedule"
|
|
|
|
def _render_missing_review_cancel_fields_prompt(self, missing_fields: list[str]) -> str:
|
|
return "missing review cancel"
|
|
|
|
def _render_review_reuse_question(self) -> str:
|
|
return "reuse review?"
|
|
|
|
def _render_missing_order_fields_prompt(self, missing_fields: list[str]) -> str:
|
|
return "missing order"
|
|
|
|
def _render_missing_cancel_order_fields_prompt(self, missing_fields: list[str]) -> str:
|
|
return "missing cancel order"
|
|
|
|
|
|
class TurnDecisionContractTests(unittest.IsolatedAsyncioTestCase):
|
|
async def test_extract_turn_decision_retries_once_and_returns_structured_payload(self):
|
|
llm = FakeLLM(
|
|
[
|
|
{"response": "nao eh json", "tool_call": None},
|
|
{
|
|
"response": """
|
|
{
|
|
"intent": "review_schedule",
|
|
"domain": "review",
|
|
"action": "ask_missing_fields",
|
|
"entities": {
|
|
"generic_memory": {},
|
|
"review_fields": {"placa": "abc1234", "data_hora": "10/03/2026 às 09:00"},
|
|
"review_management_fields": {},
|
|
"order_fields": {},
|
|
"cancel_order_fields": {}
|
|
},
|
|
"missing_fields": ["modelo", "ano", "km"],
|
|
"tool_name": null,
|
|
"tool_arguments": {},
|
|
"response_to_user": "Preciso do modelo, ano e quilometragem."
|
|
}
|
|
""",
|
|
"tool_call": None,
|
|
},
|
|
]
|
|
)
|
|
planner = MessagePlanner(llm=llm, normalizer=EntityNormalizer())
|
|
|
|
decision = await planner.extract_turn_decision("Quero agendar revisão amanhã às 09:00", user_id=7)
|
|
|
|
self.assertEqual(llm.calls, 2)
|
|
self.assertEqual(decision["intent"], "review_schedule")
|
|
self.assertEqual(decision["domain"], "review")
|
|
self.assertEqual(decision["action"], "ask_missing_fields")
|
|
self.assertEqual(decision["entities"]["review_fields"]["placa"], "ABC1234")
|
|
self.assertEqual(decision["entities"]["review_fields"]["data_hora"], "10/03/2026 às 09:00")
|
|
self.assertEqual(decision["missing_fields"], ["modelo", "ano", "km"])
|
|
|
|
def test_coerce_turn_decision_rejects_invalid_shape_with_fallback(self):
|
|
normalizer = EntityNormalizer()
|
|
|
|
decision = normalizer.coerce_turn_decision(
|
|
{
|
|
"intent": "valor_invalido",
|
|
"domain": "sales",
|
|
"action": "call_tool",
|
|
"entities": [],
|
|
}
|
|
)
|
|
|
|
self.assertEqual(decision["intent"], "general")
|
|
self.assertEqual(decision["domain"], "general")
|
|
self.assertEqual(decision["action"], "answer_user")
|
|
self.assertEqual(decision["entities"]["order_fields"], {})
|
|
|
|
def test_coerce_turn_decision_maps_order_aliases_from_model(self):
|
|
normalizer = EntityNormalizer()
|
|
|
|
decision = normalizer.coerce_turn_decision(
|
|
{
|
|
"intent": "place_order",
|
|
"domain": "sales",
|
|
"action": "answer_user",
|
|
"entities": {
|
|
"generic_memory": {"orcamento_max": "70000", "cpf": "12345678909"},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {},
|
|
"cancel_order_fields": {},
|
|
},
|
|
"missing_fields": [],
|
|
"selection_index": None,
|
|
"tool_name": None,
|
|
"tool_arguments": {},
|
|
"response_to_user": None,
|
|
}
|
|
)
|
|
|
|
self.assertEqual(decision["intent"], "order_create")
|
|
self.assertEqual(decision["domain"], "sales")
|
|
self.assertEqual(decision["action"], "answer_user")
|
|
self.assertEqual(decision["entities"]["generic_memory"]["orcamento_max"], 70000)
|
|
self.assertEqual(decision["entities"]["generic_memory"]["cpf"], "12345678909")
|
|
|
|
def test_coerce_turn_decision_converts_vehicle_alias_missing_field_into_order_collection(self):
|
|
normalizer = EntityNormalizer()
|
|
|
|
decision = normalizer.coerce_turn_decision(
|
|
{
|
|
"intent": "create_order",
|
|
"domain": "sales",
|
|
"action": "ask_missing_fields",
|
|
"entities": {
|
|
"generic_memory": {"orcamento_max": 70000},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {"cpf": "12345678909"},
|
|
"cancel_order_fields": {},
|
|
},
|
|
"missing_fields": ["modelo_carro"],
|
|
"selection_index": None,
|
|
"tool_name": None,
|
|
"tool_arguments": {},
|
|
"response_to_user": "Certo! Para qual modelo de carro voce gostaria de um orcamento de 70 mil?",
|
|
}
|
|
)
|
|
|
|
self.assertEqual(decision["intent"], "order_create")
|
|
self.assertEqual(decision["action"], "collect_order_create")
|
|
self.assertEqual(decision["missing_fields"], [])
|
|
self.assertIsNone(decision["response_to_user"])
|
|
|
|
def test_coerce_turn_decision_rejects_missing_fields_without_response_payload(self):
|
|
normalizer = EntityNormalizer()
|
|
|
|
decision = normalizer.coerce_turn_decision(
|
|
{
|
|
"intent": "review_schedule",
|
|
"domain": "review",
|
|
"action": "ask_missing_fields",
|
|
"entities": {
|
|
"generic_memory": {},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {},
|
|
"cancel_order_fields": {},
|
|
},
|
|
"missing_fields": [],
|
|
"tool_name": None,
|
|
"tool_arguments": {},
|
|
"response_to_user": "",
|
|
}
|
|
)
|
|
|
|
self.assertEqual(decision["intent"], "general")
|
|
self.assertEqual(decision["action"], "answer_user")
|
|
|
|
def test_turn_decision_entities_do_not_rebuild_legacy_intents(self):
|
|
service = OrquestradorService.__new__(OrquestradorService)
|
|
service.normalizer = EntityNormalizer()
|
|
|
|
extracted = service._extracted_entities_from_turn_decision(
|
|
{
|
|
"intent": "order_create",
|
|
"domain": "sales",
|
|
"action": "collect_order_create",
|
|
"entities": {
|
|
"generic_memory": {"cpf": "12345678909"},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {"vehicle_id": 1},
|
|
"cancel_order_fields": {},
|
|
},
|
|
}
|
|
)
|
|
|
|
self.assertEqual(extracted["intents"], {})
|
|
self.assertEqual(extracted["order_fields"]["vehicle_id"], 1)
|
|
|
|
def test_turn_decision_entity_merge_preserves_generic_memory_from_previous_extraction(self):
|
|
service = OrquestradorService.__new__(OrquestradorService)
|
|
service.normalizer = EntityNormalizer()
|
|
service._empty_extraction_payload = service.normalizer.empty_extraction_payload
|
|
|
|
merged = service._merge_extracted_entities(
|
|
{
|
|
"generic_memory": {"orcamento_max": 70000},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {"cpf": "12345678909"},
|
|
"cancel_order_fields": {},
|
|
"intents": {},
|
|
},
|
|
{
|
|
"generic_memory": {},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {},
|
|
"cancel_order_fields": {},
|
|
"intents": {},
|
|
},
|
|
)
|
|
|
|
self.assertEqual(merged["generic_memory"]["orcamento_max"], 70000)
|
|
self.assertEqual(merged["order_fields"]["cpf"], "12345678909")
|
|
|
|
def test_entity_merge_can_enrich_message_plan_with_full_extraction(self):
|
|
service = OrquestradorService.__new__(OrquestradorService)
|
|
service.normalizer = EntityNormalizer()
|
|
service._empty_extraction_payload = service.normalizer.empty_extraction_payload
|
|
|
|
merged = service._merge_extracted_entities(
|
|
{
|
|
"generic_memory": {},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {"cpf": "12345678909"},
|
|
"cancel_order_fields": {},
|
|
"intents": {},
|
|
},
|
|
{
|
|
"generic_memory": {"orcamento_max": 70000},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {},
|
|
"cancel_order_fields": {},
|
|
"intents": {},
|
|
},
|
|
)
|
|
|
|
self.assertEqual(merged["generic_memory"]["orcamento_max"], 70000)
|
|
self.assertEqual(merged["order_fields"]["cpf"], "12345678909")
|
|
|
|
async def test_missing_sales_search_context_triggers_focused_llm_enrichment(self):
|
|
service = OrquestradorService.__new__(OrquestradorService)
|
|
service.normalizer = EntityNormalizer()
|
|
|
|
async def fake_extract_sales_search_context_with_llm(message: str, user_id: int | None):
|
|
return {"orcamento_max": 70000}
|
|
|
|
service._extract_sales_search_context_with_llm = fake_extract_sales_search_context_with_llm
|
|
|
|
result = await service._extract_missing_sales_search_context_with_llm(
|
|
message="Quero comprar um carro de 70 mil, meu CPF e 12345678909",
|
|
user_id=7,
|
|
turn_decision={"domain": "sales", "intent": "order_create", "action": "collect_order_create"},
|
|
extracted_entities={
|
|
"generic_memory": {},
|
|
"review_fields": {},
|
|
"review_management_fields": {},
|
|
"order_fields": {"cpf": "12345678909"},
|
|
"cancel_order_fields": {},
|
|
"intents": {},
|
|
},
|
|
)
|
|
|
|
self.assertEqual(result["orcamento_max"], 70000)
|
|
|
|
async def test_turn_decision_call_tool_executes_without_router(self):
|
|
service = OrquestradorService.__new__(OrquestradorService)
|
|
service.tool_executor = FakeToolExecutor(result={"numero_pedido": "PED-1", "status": "Ativo"})
|
|
service.llm = FakeLLM([])
|
|
service._capture_review_confirmation_suggestion = lambda **kwargs: None
|
|
service._capture_tool_result_context = lambda **kwargs: None
|
|
service._should_use_deterministic_response = lambda tool_name: True
|
|
service._fallback_format_tool_result = lambda tool_name, tool_result: f"{tool_name}:{tool_result['numero_pedido']}"
|
|
async def fake_render_tool_response_with_fallback(**kwargs):
|
|
return f"{kwargs['tool_name']}:{kwargs['tool_result']['numero_pedido']}"
|
|
service._render_tool_response_with_fallback = fake_render_tool_response_with_fallback
|
|
service._http_exception_detail = lambda exc: str(exc)
|
|
service._is_low_value_response = lambda text: False
|
|
|
|
async def finish(response: str, queue_notice: str | None = None) -> str:
|
|
return response if not queue_notice else f"{queue_notice}\n{response}"
|
|
|
|
response = await service._try_execute_business_tool_from_turn_decision(
|
|
message="quero fechar o pedido",
|
|
user_id=7,
|
|
turn_decision={
|
|
"action": "call_tool",
|
|
"tool_name": "realizar_pedido",
|
|
"tool_arguments": {"cpf": "12345678909", "vehicle_id": 1},
|
|
},
|
|
queue_notice=None,
|
|
finish=finish,
|
|
)
|
|
|
|
self.assertEqual(
|
|
service.tool_executor.calls,
|
|
[("realizar_pedido", {"cpf": "12345678909", "vehicle_id": 1}, 7)],
|
|
)
|
|
self.assertEqual(response, "realizar_pedido:PED-1")
|
|
self.assertEqual(service.llm.calls, 0)
|
|
|
|
async def test_empty_stock_search_suggests_nearby_options(self):
|
|
service = OrquestradorService.__new__(OrquestradorService)
|
|
service.normalizer = EntityNormalizer()
|
|
service.tool_executor = FakeToolExecutor(result=[])
|
|
service._get_user_context = lambda user_id: {
|
|
"generic_memory": {},
|
|
"shared_memory": {},
|
|
"last_stock_results": [],
|
|
"selected_vehicle": None,
|
|
}
|
|
service._capture_tool_result_context = lambda tool_name, tool_result, user_id: None
|
|
service._normalize_positive_number = service.normalizer.normalize_positive_number
|
|
|
|
response = await service._maybe_build_stock_suggestion_response(
|
|
tool_name="consultar_estoque",
|
|
arguments={"preco_max": 50000, "limite": 5},
|
|
tool_result=[],
|
|
user_id=5,
|
|
)
|
|
|
|
self.assertIn("Nao encontrei veiculos ate R$ 50.000.", response)
|
|
self.assertIn("Hyundai HB20 2022", response)
|
|
self.assertIn("Se quiser, responda com o numero da lista ou com o modelo.", response)
|
|
|
|
async def test_turn_decision_answer_user_can_short_circuit_router(self):
|
|
decision = {
|
|
"intent": "general",
|
|
"domain": "general",
|
|
"action": "answer_user",
|
|
"response_to_user": "Resposta direta do contrato.",
|
|
}
|
|
|
|
self.assertEqual(str(decision.get("action") or ""), "answer_user")
|
|
self.assertEqual(str(decision.get("response_to_user") or "").strip(), "Resposta direta do contrato.")
|
|
|
|
async def test_pending_order_selection_prefers_turn_decision_domain(self):
|
|
state = FakeState(
|
|
contexts={
|
|
9: {
|
|
"pending_order_selection": {
|
|
"orders": [
|
|
{"domain": "review", "message": "agendar revisao", "memory_seed": {}},
|
|
{"domain": "sales", "message": "fazer pedido", "memory_seed": {}},
|
|
],
|
|
"expires_at": datetime.utcnow() + timedelta(minutes=15),
|
|
},
|
|
"order_queue": [],
|
|
"active_domain": "general",
|
|
"generic_memory": {},
|
|
}
|
|
}
|
|
)
|
|
policy = ConversationPolicy(service=FakePolicyService(state))
|
|
|
|
response = await policy.try_resolve_pending_order_selection(
|
|
message="quero comprar",
|
|
user_id=9,
|
|
turn_decision={"domain": "sales", "intent": "order_create", "action": "collect_order_create"},
|
|
)
|
|
|
|
self.assertIn("Vou comecar por: Venda: fazer pedido", response)
|
|
|
|
async def test_pending_order_selection_prefers_turn_decision_selection_index(self):
|
|
state = FakeState(
|
|
contexts={
|
|
9: {
|
|
"pending_order_selection": {
|
|
"orders": [
|
|
{"domain": "review", "message": "agendar revisao", "memory_seed": {}},
|
|
{"domain": "sales", "message": "fazer pedido", "memory_seed": {}},
|
|
],
|
|
"expires_at": datetime.utcnow() + timedelta(minutes=15),
|
|
},
|
|
"order_queue": [],
|
|
"active_domain": "general",
|
|
"generic_memory": {},
|
|
}
|
|
}
|
|
)
|
|
policy = ConversationPolicy(service=FakePolicyService(state))
|
|
|
|
response = await policy.try_resolve_pending_order_selection(
|
|
message="esse",
|
|
user_id=9,
|
|
turn_decision={"domain": "general", "intent": "general", "action": "answer_user", "selection_index": 1},
|
|
)
|
|
|
|
self.assertIn("Vou comecar por: Venda: fazer pedido", response)
|
|
|
|
async def test_try_continue_queue_prefers_turn_decision_action(self):
|
|
state = FakeState(
|
|
contexts={
|
|
9: {
|
|
"pending_switch": {
|
|
"target_domain": "sales",
|
|
"queued_message": "fazer pedido",
|
|
"memory_seed": {"cpf": "12345678909"},
|
|
"expires_at": datetime.utcnow() + timedelta(minutes=15),
|
|
},
|
|
"active_domain": "general",
|
|
"generic_memory": {},
|
|
"pending_order_selection": None,
|
|
}
|
|
}
|
|
)
|
|
service = FakePolicyService(state)
|
|
policy = ConversationPolicy(service=service)
|
|
policy.apply_domain_switch = lambda user_id, target_domain: service._get_user_context(user_id).update(
|
|
{"active_domain": target_domain, "pending_switch": None}
|
|
)
|
|
|
|
response = await policy.try_continue_queued_order(
|
|
message="ok",
|
|
user_id=9,
|
|
turn_decision={"action": "continue_queue", "intent": "queue_continue", "domain": "sales"},
|
|
)
|
|
|
|
self.assertIn("Agora, sobre a compra do veiculo:", response)
|
|
|
|
def test_handle_context_switch_prefers_turn_decision_domain_confirmation(self):
|
|
state = FakeState(
|
|
contexts={
|
|
9: {
|
|
"pending_switch": {
|
|
"target_domain": "review",
|
|
"expires_at": datetime.utcnow() + timedelta(minutes=15),
|
|
},
|
|
"active_domain": "sales",
|
|
"generic_memory": {},
|
|
"pending_order_selection": None,
|
|
}
|
|
}
|
|
)
|
|
service = FakePolicyService(state)
|
|
policy = ConversationPolicy(service=service)
|
|
policy.apply_domain_switch = lambda user_id, target_domain: service._get_user_context(user_id).update(
|
|
{"active_domain": target_domain, "pending_switch": None}
|
|
)
|
|
|
|
response = policy.handle_context_switch(
|
|
message="quero revisar",
|
|
user_id=9,
|
|
target_domain_hint="review",
|
|
turn_decision={"domain": "review", "intent": "review_schedule", "action": "collect_review_schedule"},
|
|
)
|
|
|
|
self.assertEqual(response, "Certo, contexto anterior encerrado. Vamos seguir com agendamento de revisao.")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|