adjustments: transaction parameter extraction

agent_framework_oci/FIX_TRANSACTION_PARAMETER_PRECEDENCE.md

@@ -1,32 +1,102 @@
-# Transaction parameter precedence fix
+# Precedência transacional + extração LLM de parâmetros
 
-Correção para a regressão em que uma resposta curta que preenchia um parâmetro pendente (ex.: `R$ 71,99` para `valor`) era classificada pelo LLM Router como uma nova intent e interrompia a transação.
+Esta correção remove a extração textual hardcoded de parâmetros transacionais e faz a coleta de `policy.requires` por um extrator LLM genérico.
 
-## Regra aplicada
+## Regra de precedência
 
-Durante `COLLECTING_PARAMETERS` a ordem passa a ser:
-
-1. resposta compatível com parâmetro pendente -> mantém a política de estado e continua a transação;
-2. cancelamento explícito -> cancela a transação;
-3. nova intenção clara/pergunta explícita -> interrompe a transação e volta ao roteamento normal;
-4. caso ambíguo -> permanece em clarificação.
-
-Exemplo corrigido:
+Enquanto existir uma transação ativa, o framework trata o turno nesta ordem:
 
 ```text
-não fiz essa contratação TIM CTRL Redes Sociais 8.0
--> informe valor
-R$ 71,99
--> valor=71.99; continua contestar_cobranca; executa pré-validação
+ACTIVE_TRANSACTION
+       |
+       +-- COLLECTING_PARAMETERS
+       |      |
+       |      +-- LLM tenta extrair SOMENTE os parâmetros ainda pendentes
+       |      |
+       |      +-- extraiu >= 1 ?
+       |             |
+       |             +-- SIM -> continua a transação; NÃO avalia intent_shift
+       |             |
+       |             +-- NÃO -> libera EnterpriseRouter para avaliar intent_shift
+       |
+       +-- AWAITING_CONFIRMATION
+              |
+              +-- reconhece confirmação/rejeição explícita
+              |
+              +-- reconheceu ?
+                     |
+                     +-- SIM -> continua/cancela a transação; NÃO avalia intent_shift
+                     |
+                     +-- NÃO -> libera EnterpriseRouter para avaliar intent_shift
 ```
 
-A mensagem `R$ 71,99` não pode mais virar `contas_invoice_explanation` enquanto `valor` estiver pendente.
+## TransactionParameterExtractor
 
-## Testes
+Novo componente:
 
-Foram adicionados testes para:
+`libs/agent_framework/src/agent_framework/runtime/transaction_parameters.py`
 
-- valor monetário com LLM sugerindo outra intent;
-- entidade curta como resposta de parâmetro;
-- pergunta clara durante coleta ainda interrompendo a transação;
-- regressões existentes de intent-shift e transactional tool flow.
+A extração textual dos parâmetros de negócio é feita exclusivamente por LLM. O componente recebe:
+
+- nome da tool/transação ativa;
+- parâmetros atualmente pendentes;
+- argumentos já conhecidos;
+- schema/tipos declarados em `tools.yaml` quando disponíveis;
+- descrição da tool;
+- mensagem atual do usuário.
+
+Ele não conhece nomes de domínio como `order_id`, `reason`, `subject`, `valor`, TIM ou retail. Não há regex de entidades de negócio.
+
+A LLM pode interpretar, por exemplo:
+
+- `PED-1001` quando só há um parâmetro compatível pendente;
+- `o pedido é PED-1001`;
+- `PED-1001, desisti da compra` preenchendo dois parâmetros no mesmo turno;
+- respostas com o nome do parâmetro seguido do valor;
+- respostas apenas com o valor, quando semanticamente inequívocas.
+
+Em caso de dúvida, o prompt manda retornar `null`. Uma nova solicitação não deve ser transformada em valor de parâmetro.
+
+## Separação de responsabilidades
+
+`tool_policies.yaml` continua sendo a fonte de verdade para `requires`.
+
+`tools.yaml` pode fornecer tipos via `args_schema` e descrição da tool para melhorar a interpretação sem introduzir código específico de domínio.
+
+`mcp_parameter_mapping.yaml` continua responsável pelos parâmetros auxiliares/contrato MCP. As strategies do mapper são explicitamente excluídas dos campos presentes em `policy.requires`, para não misturar extração MCP com coleta transacional.
+
+O `EnterpriseRouter` usa o mesmo extrator LLM apenas como *probe* de precedência. Se pelo menos um parâmetro pendente for encontrado, o turno permanece no estado transacional. Os valores extraídos são colocados no metadata da decisão e reutilizados pelo runtime, evitando uma segunda chamada LLM no mesmo turno.
+
+## Profile LLM
+
+Foi adicionado aos templates:
+
+```yaml
+transaction_parameter_extraction:
+  provider: oci_openai
+  model: openai.gpt-4.1-mini
+  temperature: 0
+  max_tokens: 500
+  timeout_seconds: 8
+```
+
+Generation/component:
+
+- `llm.transaction_parameter_extraction`
+- `transaction_parameter_extraction`
+
+## Limpeza de estado
+
+Em `intent_shift`, `transaction_pre_validation` da transação abandonada é removido para não contaminar a nova transação. O resultado de pre-validation continua preservado enquanto pertence à própria transação para auditoria.
+
+## Testes adicionados
+
+`tests/test_transaction_parameter_llm_precedence.py`
+
+Cobertura:
+
+1. dois parâmetros extraídos no mesmo turno;
+2. um parâmetro preenchido ganha precedência sobre keyword que indicaria outra intent;
+3. nenhum parâmetro encontrado libera `intent_shift`;
+4. ausência do antigo `_extract_action_arguments()` hardcoded;
+5. confirmação `sim` ganha precedência sobre intent shift.

agent_framework_oci/Tuning-Performance/Authentication/agent_template_backend_authentication/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/Tuning-Performance/Deterministic_Transactional_Workflow/agent_template_backend/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/Tuning-Performance/Long_Term_Memory/templates/agent_template_backend/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/Tuning-Performance/Normal/templates/agent_template_backend/llm_profiles.yaml

@@ -72,3 +72,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/Tuning-Performance/Route_Stickness/templates/agent_template_backend/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/Tuning-Performance/Route_Stickness/templates/agent_template_backend_day_zero/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/Tuning-Performance/Transaction_Evidence/agent_template_backend/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/Tuning-Performance/Transaction_Pre_Validation/agent_template_backend/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/libs/agent_framework/src/agent_framework/routing/enterprise_router.py

@@ -9,6 +9,7 @@ from typing import Any
 from .config_loader import load_intents, load_router_defaults, load_state_policies
 from .continuity import SemanticRouteContinuity
 from .models import IntentDefinition, RouteDecision, RouterStatePolicy
+from agent_framework.runtime.transaction_parameters import extract_transaction_parameters, parse_transaction_confirmation
 
 logger = logging.getLogger("agent_framework.routing")
 
@@ -78,6 +79,12 @@ class EnterpriseRouter:
         # pendente antes de executar a nova intent.
         state_decision = self._route_by_state(current_state)
         if state_decision:
+            consumed = await self._transaction_parameter_precedence(
+                state, text=str(text), state_decision=state_decision
+            )
+            if consumed is not None:
+                await self._emit(consumed, state)
+                return consumed
             interruption = await self._transaction_state_interruption_candidate(
                 state, text=str(text), state_decision=state_decision
             )
@@ -109,6 +116,17 @@ class EnterpriseRouter:
                 method="state",
                 next_state=tx_status,
             )
+            consumed = await self._transaction_parameter_precedence(
+                state, text=str(text), state_decision=synthetic
+            )
+            if consumed is not None:
+                consumed.metadata = {
+                    **(consumed.metadata or {}),
+                    "transaction_state_recovered": True,
+                }
+                await self._emit(consumed, state)
+                return consumed
+
             interruption = await self._transaction_state_interruption_candidate(
                 state, text=str(text), state_decision=synthetic
             )
@@ -186,6 +204,63 @@ class EnterpriseRouter:
         return decision
 
 
+    async def _transaction_parameter_precedence(
+        self,
+        state: dict[str, Any],
+        *,
+        text: str,
+        state_decision: RouteDecision,
+    ) -> RouteDecision | None:
+        """Consume a turn as transaction parameters before evaluating intent shift.
+
+        Only COLLECTING_PARAMETERS participates. The LLM extracts values for the
+        currently missing parameters; if at least one value is found, the state
+        route wins deterministically and intent-shift classification is skipped.
+        """
+        tx_status = str(state.get("transaction_status") or "").strip().upper()
+        if tx_status == "AWAITING_CONFIRMATION":
+            confirmation = parse_transaction_confirmation(text)
+            if confirmation is None:
+                return None
+            state_decision.metadata = {
+                **(state_decision.metadata or {}),
+                "transaction_turn_consumed": True,
+                "transaction_confirmation_decision": confirmation,
+                "transaction_confirmation_source": "deterministic",
+            }
+            return state_decision
+        if tx_status != "COLLECTING_PARAMETERS":
+            return None
+        missing = [str(name) for name in (state.get("missing_parameters") or []) if str(name).strip()]
+        if not missing:
+            return None
+        active = state.get("active_transaction") if isinstance(state.get("active_transaction"), dict) else {}
+        tool_name = str(active.get("tool_name") or ((state.get("selected_tool_call") or {}).get("tool_name") if isinstance(state.get("selected_tool_call"), dict) else "") or "").strip()
+        if not tool_name:
+            return None
+        known = dict(active.get("arguments") or {})
+        schema = active.get("parameter_schema") if isinstance(active.get("parameter_schema"), dict) else {}
+        description = str(active.get("tool_description") or "")
+        values = await extract_transaction_parameters(
+            self.llm,
+            text=text,
+            tool_name=tool_name,
+            missing_parameters=missing,
+            known_arguments=known,
+            parameter_schema=schema,
+            tool_description=description,
+        )
+        if not values:
+            return None
+        state_decision.metadata = {
+            **(state_decision.metadata or {}),
+            "transaction_turn_consumed": True,
+            "transaction_parameter_values": values,
+            "transaction_parameter_source": "llm",
+            "transaction_parameter_missing_before": missing,
+        }
+        return state_decision
+
     async def _transaction_state_interruption_candidate(
         self,
         state: dict[str, Any],
@@ -213,52 +288,15 @@ class EnterpriseRouter:
                 or (previous_intent and not previous_intent.startswith("state:") and candidate.intent != previous_intent)
             )
             if different:
-                tx_status = str(state.get("transaction_status") or "").strip().upper()
-                missing = list(state.get("missing_parameters") or [])
-                same_agent = candidate.agent == state_decision.agent
-                matched_keyword = str((candidate.metadata or {}).get("matched_keyword") or "").strip()
-                informative_tokens = [
-                    token
-                    for token in self._keyword_tokens(matched_keyword)
-                    if len(token) > 1
-                ]
-
-                # Durante coleta de parâmetros, uma keyword genérica de uma única
-                # palavra do MESMO agente não pode preemptar a transação. Ex.:
-                # ``o pedido é o PED-1001`` enquanto ``order_id`` está pendente.
-                # Nesse caso ``pedido`` pode casar com ``retail_order_tracking``,
-                # mas a mensagem é perfeitamente compatível com a resposta ao
-                # parâmetro solicitado. Keywords mais específicas (duas ou mais
-                # palavras informativas) continuam aptas a representar mudança
-                # explícita de intenção. Se o roteador LLM estiver habilitado,
-                # deixamos a decisão semântica abaixo desempatar o caso fraco.
-                weak_same_agent_keyword_during_collection = (
-                    tx_status == "COLLECTING_PARAMETERS"
-                    and bool(missing)
-                    and same_agent
-                    and len(informative_tokens) <= 1
-                )
-
-                if not weak_same_agent_keyword_during_collection:
-                    candidate.metadata = {
-                        **(candidate.metadata or {}),
-                        "transaction_interruption": "intent_shift",
-                        "interrupted_state": state_decision.next_state,
-                        "interrupted_agent": state_decision.agent,
-                        "interrupted_intent": started_intent or previous_intent,
-                        "interruption_source": "configured_routing",
-                    }
-                    return candidate
-
-                logger.debug(
-                    "Keyword transacional fraca não preemptou coleta de parâmetro: "
-                    "keyword=%r intent=%s missing=%s",
-                    matched_keyword,
-                    candidate.intent,
-                    missing,
-                )
-                # Não retorne aqui: se houver LLM router, ele pode confirmar uma
-                # mudança semântica real; sem LLM, a transação permanece ativa.
+                candidate.metadata = {
+                    **(candidate.metadata or {}),
+                    "transaction_interruption": "intent_shift",
+                    "interrupted_state": state_decision.next_state,
+                    "interrupted_agent": state_decision.agent,
+                    "interrupted_intent": started_intent or previous_intent,
+                    "interruption_source": "configured_routing",
+                }
+                return candidate
             else:
                 return None
 

agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/agent_runtime.py

@@ -10,6 +10,7 @@ from typing import Any, Iterable, Mapping
 
 
 from agent_framework.memory.summary_memory import MemoryContext, render_recent_messages
+from agent_framework.runtime.transaction_parameters import extract_transaction_parameters, parse_transaction_confirmation
 
 
 logger = logging.getLogger(__name__)
@@ -571,6 +572,7 @@ class AgentRuntimeMixin:
         state: dict[str, Any],
         *,
         overwrite_from_message: bool = False,
+        exclude_fields: Iterable[str] = (),
     ) -> dict[str, Any]:
         """Executa regras ``extract`` declaradas para a tool escolhida.
 
@@ -586,11 +588,14 @@ class AgentRuntimeMixin:
             return dict(arguments or {})
 
         resolved = dict(arguments or {})
+        excluded = {str(name) for name in (exclude_fields or ())}
         runtime = self.get_runtime_context(state)
         message = runtime.sanitized_input or runtime.original_text or runtime.user_text
         llm = getattr(self, "llm", None)
 
         for field_name, rule in rules.items():
+            if str(field_name) in excluded:
+                continue
             from_message = str(rule.get("from") or "message").lower() == "message"
             if not from_message:
                 continue
@@ -1233,46 +1238,59 @@ class AgentRuntimeMixin:
 
     @staticmethod
     def _confirmation_decision(text: str) -> str | None:
-        normalized = " ".join((text or "").strip().lower().split())
-        normalized = re.sub(r"[.!?]+$", "", normalized).strip()
-        if normalized in {"sim", "confirmo", "sim, confirmo", "pode fazer", "pode prosseguir", "sim, desejo", "sim, desejo trocar", "sim, confirmo a devolução", "sim, confirmo a troca"}:
-            return "confirm"
-        if normalized in {"não", "nao", "cancelar", "cancele", "não confirmo", "nao confirmo"}:
-            return "reject"
-        return None
+        return parse_transaction_confirmation(text)
 
-    @staticmethod
-    def _extract_action_arguments(text: str) -> dict[str, Any]:
-        """Extrai apenas entidades explicitamente informadas na mensagem.
+    def _transaction_parameter_schema(self, tool_name: str, policy: dict[str, Any] | None = None) -> dict[str, Any]:
+        """Return generic schema metadata for transactional required parameters."""
+        cfg = self._tool_config(tool_name)
+        raw_schema = dict(getattr(cfg, "args_schema", {}) or {}) if cfg is not None else {}
+        required = [str(name) for name in ((policy or {}).get("requires") or getattr(cfg, "requires", []) or [])]
+        if not required:
+            return raw_schema
+        return {name: raw_schema.get(name, "string") for name in required}
 
-        Não usa a mensagem inteira como ``reason``: frases como "quero devolver
-        uma compra" expressam a ação, mas não necessariamente o motivo. Defaults
-        declarados no mapper continuam sendo aplicados por ``build_tool_arguments``.
+    def _transaction_tool_description(self, tool_name: str) -> str:
+        cfg = self._tool_config(tool_name)
+        return str(getattr(cfg, "description", "") or "") if cfg is not None else ""
+
+    async def _extract_transaction_parameters(
+        self,
+        state: dict[str, Any],
+        *,
+        tool_name: str,
+        missing_parameters: list[str],
+        known_arguments: dict[str, Any] | None = None,
+    ) -> dict[str, Any]:
+        """Use the dedicated LLM extractor for pending transaction parameters.
+
+        A route decision may already contain the extraction performed by the
+        router solely to enforce parameter-before-intent-shift precedence.  Reuse
+        it to avoid a second LLM call in the same turn.
         """
-        raw = text or ""
-        args: dict[str, Any] = {}
-        match = re.search(
-            r"(?:pedido|ordem)\s*(?:n[ºo°.]?\s*)?(?:é\s*(?:o\s*)?|[:#=-]\s*)?([A-Za-z0-9_-]+)",
-            raw,
-            flags=re.IGNORECASE,
-        )
-        if match:
-            args["order_id"] = match.group(1)
+        route_meta = ((state.get("route_decision") or {}).get("metadata") or {}) if isinstance(state.get("route_decision"), dict) else {}
+        cached = route_meta.get("transaction_parameter_values")
+        if isinstance(cached, dict):
+            allowed = set(str(x) for x in missing_parameters)
+            reused = {str(k): v for k, v in cached.items() if str(k) in allowed and v not in _EMPTY_VALUES}
+            if reused:
+                return reused
 
-        reason_match = re.search(
-            r"(?:porque|pois|motivo\s*[:=-]?|por\s+(?:arrependimento|defeito|erro|atraso)|me\s+arrependi(?:\s+da\s+compra)?|arrependimento)\s*(.*)",
-            raw,
-            flags=re.IGNORECASE,
+        active = self._active_transaction(state) or {}
+        schema = active.get("parameter_schema") if isinstance(active.get("parameter_schema"), dict) else None
+        if not schema:
+            policy = self._resolve_tool_execution_policy(tool_name, known_arguments or {})
+            schema = self._transaction_parameter_schema(tool_name, policy)
+        description = str(active.get("tool_description") or self._transaction_tool_description(tool_name) or "")
+        text = state.get("sanitized_input") or state.get("user_text") or ""
+        return await extract_transaction_parameters(
+            getattr(self, "llm", None),
+            text=str(text),
+            tool_name=tool_name,
+            missing_parameters=list(missing_parameters or []),
+            known_arguments=known_arguments or {},
+            parameter_schema=schema,
+            tool_description=description,
         )
-        if reason_match:
-            reason = reason_match.group(1).strip(" .,:;-")
-            if not reason:
-                matched_phrase = reason_match.group(0).strip(" .,:;-")
-                if re.search(r"me\s+arrependi|arrependimento", matched_phrase, flags=re.IGNORECASE):
-                    reason = "Arrependimento da compra"
-            if reason:
-                args["reason"] = reason
-        return args
 
     def _transactional_action_match(self, text: str, tools: list[str] | None = None) -> str | None:
         """Detecta solicitação transacional usando metadados de tools.yaml.
@@ -1515,12 +1533,19 @@ class AgentRuntimeMixin:
     ) -> dict[str, Any]:
         current = state.get("active_transaction") if isinstance(state.get("active_transaction"), dict) else {}
         txid = transaction_id or current.get("transaction_id") or str(uuid.uuid4())
+        if str(current.get("tool_name") or "") != str(tool_name):
+            state["transaction_pre_validation"] = None
+        cfg = self._tool_config(tool_name)
+        policy = self._resolve_tool_execution_policy(tool_name, arguments or {})
         tx = {
             "transaction_id": txid,
             "tool_name": tool_name,
             "arguments": dict(arguments or {}),
             "status": status,
             "started_from_intent": current.get("started_from_intent") or state.get("intent"),
+            "requires": list(policy.get("requires") or getattr(cfg, "requires", []) or []),
+            "parameter_schema": self._transaction_parameter_schema(tool_name, policy),
+            "tool_description": self._transaction_tool_description(tool_name),
         }
         state["active_transaction"] = tx
         return tx
@@ -2057,6 +2082,7 @@ class AgentRuntimeMixin:
         if active_before_interruption and interruption == "intent_shift":
             interrupted_tool = active_before_interruption.get("tool_name")
             self._finish_active_transaction(state, "CANCELLED")
+            state["transaction_pre_validation"] = None
             state["tool_policy_result"] = {
                 "action": "cancelled_by_intent_shift",
                 "tool_name": interrupted_tool,
@@ -2080,28 +2106,40 @@ class AgentRuntimeMixin:
             tool_name = selected.get("tool_name")
             if tool_name:
                 previous_args = dict(selected.get("arguments") or {})
-                new_args = self.build_tool_arguments(
+                policy = self._resolve_tool_execution_policy(tool_name, previous_args)
+                missing_before = self._missing_required_arguments(policy, previous_args)
+
+                # Parâmetros TRANSACIONAIS são interpretados exclusivamente pelo
+                # extrator LLM genérico. Não existem regexes/nome de entidade
+                # hardcoded no framework. O extrator recebe apenas os parâmetros
+                # ainda pendentes da policy e pode consumir um ou vários no turno.
+                extracted = await self._extract_transaction_parameters(
                     state,
                     tool_name=tool_name,
-                    intent=state.get("intent"),
-                    aliases=aliases,
-                    extra_args=self._extract_action_arguments(text),
+                    missing_parameters=missing_before,
+                    known_arguments=previous_args,
                 )
-                # Durante coleta incremental, valores de contexto podem ainda conter
-                # parâmetros de uma operação anterior. O que já foi coletado para a
-                # transação pendente prevalece; o turno atual só preenche lacunas.
-                non_empty_new = {k: v for k, v in new_args.items() if v not in (None, "", [], {})}
-                arguments = {**non_empty_new, **previous_args}
+                arguments = {**previous_args, **extracted}
 
-                # Campos de envelope pertencem ao turno corrente e devem permanecer
-                # atualizados, mesmo quando os parâmetros de negócio ficam congelados.
-                for per_turn_key in ("query", "operator_instructions", "interaction_key"):
-                    if non_empty_new.get(per_turn_key) not in (None, "", [], {}):
-                        arguments[per_turn_key] = non_empty_new[per_turn_key]
-
-                # Reutiliza o contrato declarativo para preencher somente os campos
-                # ainda faltantes; campos previamente coletados não são sobrescritos.
-                arguments = await self._extract_mcp_parameters(tool_name, arguments, state)
+                # Argumentos estruturados já presentes no contexto são aceitos de
+                # forma genérica (não são parsing textual). Para required fields,
+                # só completam lacunas que a fala atual/LLM não preencheu; valores
+                # previamente coletados nunca são sobrescritos.
+                contextual = self.build_tool_arguments(
+                    state, tool_name=tool_name, intent=state.get("intent"), aliases=aliases
+                )
+                required_set = set(str(name) for name in (policy.get("requires") or []))
+                for key, value in contextual.items():
+                    if value in _EMPTY_VALUES:
+                        continue
+                    if key in required_set:
+                        if arguments.get(key) in _EMPTY_VALUES:
+                            arguments[key] = value
+                    else:
+                        arguments[key] = value
+                arguments = await self._extract_mcp_parameters(
+                    tool_name, arguments, state, exclude_fields=policy.get("requires") or []
+                )
                 policy = self._resolve_tool_execution_policy(tool_name, arguments)
                 missing = self._missing_required_arguments(policy, arguments)
                 if missing:
@@ -2250,23 +2288,46 @@ class AgentRuntimeMixin:
         if not selected_action:
             return results
 
-        explicit_action_args = self._extract_action_arguments(text)
         action_args = self.build_tool_arguments(
             state,
             tool_name=selected_action,
             intent=state.get("intent"),
             aliases=aliases,
-            extra_args=explicit_action_args,
         )
-        # Nova transação: parâmetros declarados ``from: message`` não podem ser
-        # herdados de context.tool_arguments de uma operação anterior.
+        # Campos que o contrato MCP declara como vindos da mensagem corrente não
+        # podem herdar valores textuais de uma transação anterior. Isto é apenas
+        # uma regra de freshness do envelope MCP; a extração de policy.requires
+        # continua exclusivamente no TransactionParameterExtractor LLM abaixo.
         action_args = self._drop_stale_message_extracted_arguments(
-            selected_action, action_args, explicit_fields=explicit_action_args.keys()
+            selected_action, action_args, explicit_fields=()
         )
-        # A mensagem atual é a fonte de verdade para esses campos no primeiro
-        # turno transacional.
+        policy = self._resolve_tool_execution_policy(selected_action, action_args)
+        required = [str(name) for name in (policy.get("requires") or [])]
+
+        # Valores já estruturados no contexto podem satisfazer requirements sem
+        # parsing textual. Para qualquer required field ainda ausente, a fala do
+        # usuário é interpretada exclusivamente pelo extrator LLM transacional.
+        missing_initial = self._missing_required_arguments(policy, action_args)
+        # No primeiro turno, a fala atual pode fornecer/corrigir qualquer required
+        # field, inclusive um valor que exista no contexto estruturado mas pertença
+        # a uma transação anterior. O extrator continua restrito ao contrato
+        # ``requires`` e só sobrescreve quando a LLM realmente extrai um valor.
+        extracted_initial = await self._extract_transaction_parameters(
+            state,
+            tool_name=selected_action,
+            missing_parameters=required,
+            known_arguments={k: v for k, v in action_args.items() if k not in set(required)},
+        )
+        action_args.update(extracted_initial)
+
+        # O mapper MCP continua responsável somente por parâmetros auxiliares que
+        # não pertencem ao contrato transacional.
         action_args = await self._extract_mcp_parameters(
-            selected_action, action_args, state, overwrite_from_message=True
+            selected_action,
+            action_args,
+            state,
+            overwrite_from_message=True,
+            exclude_fields=required,
         )
         policy = self._resolve_tool_execution_policy(selected_action, action_args)
         selected = {"tool_name": selected_action, "arguments": action_args}

agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/transaction_input.py

@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+import re
+from typing import Any
+
+
+def confirmation_decision(text: str) -> str | None:
+    """Classifica respostas explícitas ao estado AWAITING_CONFIRMATION.
+
+    Esta função é compartilhada pelo router (precedência antes de intent_shift)
+    e pelo runtime (execução/cancelamento efetivo), garantindo que ambos
+    reconheçam exatamente o mesmo conjunto de respostas.
+    """
+    normalized = " ".join((text or "").strip().lower().split())
+    normalized = re.sub(r"[.!?]+$", "", normalized).strip()
+    if normalized in {
+        "sim",
+        "confirmo",
+        "sim, confirmo",
+        "pode fazer",
+        "pode prosseguir",
+        "sim, desejo",
+        "sim, desejo trocar",
+        "sim, confirmo a devolução",
+        "sim, confirmo a troca",
+    }:
+        return "confirm"
+    if normalized in {"não", "nao", "cancelar", "cancele", "não confirmo", "nao confirmo"}:
+        return "reject"
+    return None
+
+
+def extract_action_arguments(text: str) -> dict[str, Any]:
+    """Extrai entidades explicitamente informadas em ações transacionais.
+
+    É usada tanto pelo runtime quanto pelo probe de precedência do router. Não
+    transforma a mensagem inteira em motivo: só captura valores explicitamente
+    identificáveis no turno atual.
+    """
+    raw = text or ""
+    args: dict[str, Any] = {}
+    match = re.search(
+        r"(?:pedido|ordem)\s*(?:n[ºo°.]?\s*)?(?:é\s*(?:o\s*)?|[:#=-]\s*)?([A-Za-z0-9_-]+)",
+        raw,
+        flags=re.IGNORECASE,
+    )
+    if match:
+        args["order_id"] = match.group(1)
+
+    reason_match = re.search(
+        r"(?:porque|pois|motivo\s*[:=-]?|por\s+(?:arrependimento|defeito|erro|atraso)|me\s+arrependi(?:\s+da\s+compra)?|arrependimento)\s*(.*)",
+        raw,
+        flags=re.IGNORECASE,
+    )
+    if reason_match:
+        reason = reason_match.group(1).strip(" .,:;-")
+        if not reason:
+            matched_phrase = reason_match.group(0).strip(" .,:;-")
+            if re.search(r"me\s+arrependi|arrependimento", matched_phrase, flags=re.IGNORECASE):
+                reason = "Arrependimento da compra"
+        if reason:
+            args["reason"] = reason
+    return args

agent_framework_oci/libs/agent_framework/src/agent_framework/runtime/transaction_parameters.py

@@ -0,0 +1,181 @@
+from __future__ import annotations
+
+import json
+import logging
+import re
+from typing import Any, Mapping
+
+logger = logging.getLogger(__name__)
+
+_EMPTY_VALUES = (None, "", {}, [])
+
+
+def _response_text(response: Any) -> str:
+    if response is None:
+        return ""
+    if isinstance(response, str):
+        return response
+    if isinstance(response, dict):
+        return str(response.get("content") or response.get("text") or response.get("answer") or "")
+    return str(getattr(response, "content", None) or getattr(response, "text", None) or response)
+
+
+def _coerce(value: Any, declared_type: Any) -> Any:
+    if value in _EMPTY_VALUES:
+        return None
+    type_name = str(declared_type or "string").strip().lower()
+    try:
+        if type_name in {"integer", "int"}:
+            return int(value)
+        if type_name in {"number", "float", "double"}:
+            return float(value)
+        if type_name in {"boolean", "bool"}:
+            if isinstance(value, bool):
+                return value
+            normalized = str(value).strip().lower()
+            if normalized in {"true", "1", "yes", "sim"}:
+                return True
+            if normalized in {"false", "0", "no", "não", "nao"}:
+                return False
+            return None
+        if type_name in {"array", "list"}:
+            return value if isinstance(value, list) else [value]
+        if type_name in {"object", "dict", "map"}:
+            return value if isinstance(value, dict) else None
+        return str(value).strip()
+    except (TypeError, ValueError):
+        return None
+
+
+def parse_transaction_confirmation(text: str) -> str | None:
+    """Recognize an explicit confirmation/rejection before intent-shift routing.
+
+    This is intentionally small and domain-neutral. Parameter interpretation is
+    LLM-only; confirmation remains a deterministic control token so an explicit
+    yes/no cannot be reclassified as a new intent.
+    """
+    normalized = " ".join(str(text or "").strip().lower().split())
+    normalized = re.sub(r"[.!?]+$", "", normalized).strip()
+    if normalized in {
+        "sim", "confirmo", "sim, confirmo", "pode fazer", "pode prosseguir",
+        "sim, desejo", "sim, desejo trocar", "sim, confirmo a devolução",
+        "sim, confirmo a troca",
+    }:
+        return "confirm"
+    if normalized in {"não", "nao", "cancelar", "cancele", "não confirmo", "nao confirmo"}:
+        return "reject"
+    return None
+
+
+async def extract_transaction_parameters(
+    llm: Any,
+    *,
+    text: str,
+    tool_name: str,
+    missing_parameters: list[str],
+    known_arguments: Mapping[str, Any] | None = None,
+    parameter_schema: Mapping[str, Any] | None = None,
+    tool_description: str | None = None,
+) -> dict[str, Any]:
+    """Extract values for pending transactional parameters using the LLM only.
+
+    This component intentionally contains no domain/entity regexes and no
+    knowledge of parameter names such as ``order_id`` or ``reason``.  The
+    transaction runtime supplies the pending parameter names and optional schema;
+    the LLM only interprets the current user turn.  State/control-flow decisions
+    remain deterministic outside this function.
+    """
+    pending = [str(name) for name in (missing_parameters or []) if str(name).strip()]
+    message = str(text or "").strip()
+    if not pending or not message or llm is None:
+        return {}
+
+    schema = dict(parameter_schema or {})
+    known = {
+        str(key): value
+        for key, value in dict(known_arguments or {}).items()
+        if value not in _EMPTY_VALUES and str(key) not in pending
+    }
+    field_spec = {
+        name: {
+            "type": schema.get(name, "string") if not isinstance(schema.get(name), dict) else schema.get(name, {}).get("type", "string"),
+            "description": None if not isinstance(schema.get(name), dict) else schema.get(name, {}).get("description"),
+        }
+        for name in pending
+    }
+    output_shape = {name: None for name in pending}
+    prompt = (
+        "Você extrai parâmetros PENDENTES de uma transação ativa. "
+        "Sua única tarefa é interpretar a mensagem atual e devolver valores para os parâmetros pendentes. "
+        "Não decida roteamento, intenção, confirmação ou execução da transação.\n\n"
+        "REGRAS OBRIGATÓRIAS:\n"
+        "1. Extraia SOMENTE parâmetros listados em pending_parameters.\n"
+        "2. Não invente valores e não transforme uma nova solicitação/intenção do usuário em valor de parâmetro.\n"
+        "3. Se nenhum parâmetro pendente foi realmente informado, devolva null para todos.\n"
+        "4. Se houver apenas um parâmetro pendente, uma resposta contendo apenas um valor pode ser associada a ele quando isso for semanticamente inequívoco.\n"
+        "5. Se houver vários parâmetros pendentes, extraia todos os que estiverem presentes no mesmo turno.\n"
+        "6. O nome do parâmetro não precisa aparecer literalmente na fala; use a semântica, o nome da transação e o schema para associar valores.\n"
+        "7. Em caso de dúvida, prefira null.\n"
+        "8. Responda SOMENTE JSON válido, sem markdown, sem explicação e sem chaves extras.\n\n"
+        f"transaction_tool: {tool_name}\n"
+        f"transaction_description: {tool_description or ''}\n"
+        f"pending_parameters: {json.dumps(pending, ensure_ascii=False)}\n"
+        f"parameter_schema: {json.dumps(field_spec, ensure_ascii=False, default=str)}\n"
+        f"known_arguments: {json.dumps(known, ensure_ascii=False, default=str)}\n"
+        f"user_message: {message}\n"
+        f"Formato obrigatório: {json.dumps(output_shape, ensure_ascii=False)}"
+    )
+
+    try:
+        response = await llm.ainvoke(
+            [{"role": "user", "content": prompt}],
+            profile_name="transaction_parameter_extraction",
+            component_name="transaction_parameter_extraction",
+            generation_name="llm.transaction_parameter_extraction",
+            temperature=0.0,
+            max_tokens=max(120, min(500, 80 + 60 * len(pending))),
+        )
+    except TypeError:
+        # Compatibilidade com doubles/testes e providers mínimos que aceitam
+        # apenas messages.
+        response = await llm.ainvoke([{"role": "user", "content": prompt}])
+    except Exception as exc:
+        logger.warning(
+            "transaction.parameter.llm_extract_failed tool=%s pending=%s error=%s",
+            tool_name,
+            pending,
+            exc,
+        )
+        return {}
+
+    raw = _response_text(response).strip()
+    if raw.startswith("```"):
+        raw = re.sub(r"^```(?:json)?\s*|\s*```$", "", raw, flags=re.IGNORECASE | re.DOTALL).strip()
+    try:
+        payload = json.loads(raw)
+    except (TypeError, ValueError, json.JSONDecodeError):
+        logger.warning(
+            "transaction.parameter.llm_invalid_json tool=%s pending=%s raw=%r",
+            tool_name,
+            pending,
+            raw[:240],
+        )
+        return {}
+    if not isinstance(payload, dict):
+        return {}
+
+    extracted: dict[str, Any] = {}
+    for name in pending:
+        value = payload.get(name)
+        declared = field_spec.get(name, {}).get("type", "string")
+        coerced = _coerce(value, declared)
+        if coerced not in _EMPTY_VALUES:
+            extracted[name] = coerced
+
+    logger.info(
+        "transaction.parameter.llm_extracted tool=%s pending=%s consumed=%s",
+        tool_name,
+        pending,
+        sorted(extracted),
+    )
+    return extracted

agent_framework_oci/templates/agent_template_backend/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/templates/agent_template_backend_day_zero/llm_profiles.yaml

@@ -78,3 +78,10 @@ profiles:
     temperature: 0
     max_tokens: 80
     timeout_seconds: 5
+
+  transaction_parameter_extraction:
+    provider: oci_openai
+    model: openai.gpt-4.1-mini
+    temperature: 0
+    max_tokens: 500
+    timeout_seconds: 8

agent_framework_oci/tests/test_transaction_parameter_llm_precedence.py

@@ -0,0 +1,293 @@
+from __future__ import annotations
+
+import json
+from types import SimpleNamespace
+
+import pytest
+
+from agent_framework.routing.enterprise_router import EnterpriseRouter
+from agent_framework.runtime.agent_runtime import AgentRuntimeMixin
+
+
+class _SemanticLLM:
+    """Test double: parameter extraction + intent-shift classification."""
+
+    async def ainvoke(self, messages, **kwargs):
+        prompt = messages[-1]["content"] if isinstance(messages[-1], dict) else str(messages[-1])
+        profile = kwargs.get("profile_name")
+        if profile == "transaction_parameter_extraction" or "pending_parameters:" in prompt:
+            marker = "user_message: "
+            user = prompt.split(marker, 1)[1].split("\nFormato obrigatório:", 1)[0].strip() if marker in prompt else ""
+            pending_raw = prompt.split("pending_parameters: ", 1)[1].split("\n", 1)[0]
+            pending = json.loads(pending_raw)
+            values = {name: None for name in pending}
+            low = user.lower()
+            if "ped-1001" in low and "order_id" in values:
+                values["order_id"] = "PED-1001"
+            if "desisti" in low and "reason" in values:
+                values["reason"] = "desisti da compra"
+            if low.strip() == "71,99" and "valor" in values:
+                values["valor"] = 71.99
+            if low.strip() == "tim music" and "subject" in values:
+                values["subject"] = "TIM Music"
+            return json.dumps(values, ensure_ascii=False)
+
+        # Router LLM fallback: treat fatura as a real intent shift.
+        if "fatura" in prompt.lower():
+            return json.dumps({
+                "decision": "SHIFT",
+                "intent": "billing_invoice_explanation",
+                "agent": "billing_agent",
+                "confidence": 0.98,
+                "reason": "nova intenção de fatura",
+            })
+        return json.dumps({
+            "decision": "CONTINUE",
+            "intent": None,
+            "agent": None,
+            "confidence": 0.95,
+            "reason": "continua transação",
+        })
+
+
+class _Router:
+    def __init__(self):
+        self.registry = SimpleNamespace(
+            tools={},
+            get_tool=self.get_tool,
+        )
+
+    def get_tool(self, name):
+        data = {
+            "solicitar_devolucao": SimpleNamespace(
+                name="solicitar_devolucao",
+                description="Abre uma solicitação de devolução de pedido.",
+                selection_keywords=["devolver pedido", "devolução", "devolver"],
+                args_schema={"order_id": "string", "reason": "string"},
+                requires=["order_id", "reason"],
+                confirmation_required=True,
+                tool_type="action",
+            ),
+            "cancelar_pedido": SimpleNamespace(
+                name="cancelar_pedido",
+                description="Cancela um pedido.",
+                selection_keywords=["cancelar pedido", "cancelar compra"],
+                args_schema={"order_id": "string"},
+                requires=["order_id"],
+                confirmation_required=True,
+                tool_type="action",
+            ),
+        }
+        return data.get(name)
+
+    def resolve_execution_policy(self, tool_name, arguments=None):
+        cfg = self.get_tool(tool_name)
+        if not cfg:
+            return {"operation_type": "read_only", "require_confirmation": False, "requires": []}
+        return {
+            "operation_type": "transactional",
+            "require_confirmation": True,
+            "requires": list(cfg.requires),
+            "policy_source": "test",
+        }
+
+    def parameter_extract_rules(self, tool_name):
+        # Deliberately has MCP mappings for the same fields: transactional fields
+        # must be excluded from this mechanism by the runtime.
+        return {
+            "order_id": {"from": "message", "strategy": "regex", "pattern": r"pedido\\s+(\\w+)"},
+            "reason": {"from": "message", "strategy": "regex", "pattern": r"motivo\\s+(.+)"},
+        }
+
+    def validate_execution_policy(self, tool_name, arguments=None):
+        return True, None, self.resolve_execution_policy(tool_name, arguments)
+
+
+class _Runtime(AgentRuntimeMixin):
+    def __init__(self):
+        self.tool_router = _Router()
+        self.llm = _SemanticLLM()
+        self.calls = []
+
+    async def _call_mcp_tool(self, tool_name, arguments, state):
+        self.calls.append((tool_name, dict(arguments)))
+        return {"ok": True, "tool_name": tool_name, "result": {"status": "OK"}}
+
+
+@pytest.mark.asyncio
+async def test_transaction_extractor_handles_multiple_parameters_without_hardcoded_regex():
+    runtime = _Runtime()
+    state = {
+        "user_text": "quero devolver pedido PED-1001 porque desisti da compra",
+        "sanitized_input": "quero devolver pedido PED-1001 porque desisti da compra",
+        "mcp_tools": ["solicitar_devolucao"],
+        "route": "support_agent",
+        "intent": "retail_support_exchange_return",
+    }
+    result = await runtime.execute_tools_for_intent(state)
+    assert result[-1]["awaiting_confirmation"] is True
+    assert state["transaction_status"] == "AWAITING_CONFIRMATION"
+    args = state["pending_tool_call"]["arguments"]
+    assert args["order_id"] == "PED-1001"
+    assert args["reason"] == "desisti da compra"
+
+
+@pytest.mark.asyncio
+async def test_collecting_one_parameter_consumes_turn_before_intent_shift(tmp_path):
+    routing = tmp_path / "routing.yaml"
+    routing.write_text(
+        """
+router:
+  fallback_agent: support_agent
+  confidence_threshold: 0.70
+state_policies:
+  - state: COLLECTING_SUPPORT_PARAMETERS
+    agent: support_agent
+intents:
+  - name: retail_order_tracking
+    agent: orders_agent
+    priority: 20
+    keywords: [pedido]
+  - name: retail_support_exchange_return
+    agent: support_agent
+    priority: 30
+    keywords: [devolver pedido]
+  - name: billing_invoice_explanation
+    agent: billing_agent
+    priority: 40
+    keywords: [fatura]
+""",
+        encoding="utf-8",
+    )
+    settings = SimpleNamespace(
+        ROUTING_CONFIG_PATH=str(routing),
+        ENABLE_LLM_ROUTER=True,
+        ENABLE_ROUTE_STICKINESS=False,
+    )
+    router = EnterpriseRouter(settings, llm=_SemanticLLM())
+    state = {
+        "user_text": "o numero do pedido é PED-1001",
+        "sanitized_input": "o numero do pedido é PED-1001",
+        "next_state": "COLLECTING_SUPPORT_PARAMETERS",
+        "transaction_status": "COLLECTING_PARAMETERS",
+        "missing_parameters": ["order_id", "reason"],
+        "active_agent": "support_agent",
+        "intent": "state:COLLECTING_SUPPORT_PARAMETERS",
+        "active_transaction": {
+            "tool_name": "solicitar_devolucao",
+            "arguments": {},
+            "status": "COLLECTING_PARAMETERS",
+            "started_from_intent": "retail_support_exchange_return",
+            "parameter_schema": {"order_id": "string", "reason": "string"},
+            "tool_description": "Abre uma solicitação de devolução de pedido.",
+        },
+    }
+    decision = await router.route(state)
+    assert decision.agent == "support_agent"
+    assert decision.intent == "state:COLLECTING_SUPPORT_PARAMETERS"
+    assert decision.metadata["transaction_turn_consumed"] is True
+    assert decision.metadata["transaction_parameter_values"] == {"order_id": "PED-1001"}
+    assert "transaction_interruption" not in decision.metadata
+
+
+@pytest.mark.asyncio
+async def test_no_parameter_found_allows_intent_shift(tmp_path):
+    routing = tmp_path / "routing.yaml"
+    routing.write_text(
+        """
+router:
+  fallback_agent: support_agent
+  confidence_threshold: 0.70
+state_policies:
+  - state: COLLECTING_SUPPORT_PARAMETERS
+    agent: support_agent
+intents:
+  - name: retail_support_exchange_return
+    agent: support_agent
+    priority: 20
+    keywords: [devolver pedido]
+  - name: billing_invoice_explanation
+    agent: billing_agent
+    priority: 40
+    keywords: [fatura]
+""",
+        encoding="utf-8",
+    )
+    settings = SimpleNamespace(
+        ROUTING_CONFIG_PATH=str(routing),
+        ENABLE_LLM_ROUTER=True,
+        ENABLE_ROUTE_STICKINESS=False,
+    )
+    router = EnterpriseRouter(settings, llm=_SemanticLLM())
+    state = {
+        "user_text": "esquece isso, quero ver minha fatura",
+        "sanitized_input": "esquece isso, quero ver minha fatura",
+        "next_state": "COLLECTING_SUPPORT_PARAMETERS",
+        "transaction_status": "COLLECTING_PARAMETERS",
+        "missing_parameters": ["order_id", "reason"],
+        "active_agent": "support_agent",
+        "intent": "state:COLLECTING_SUPPORT_PARAMETERS",
+        "active_transaction": {
+            "tool_name": "solicitar_devolucao",
+            "arguments": {},
+            "status": "COLLECTING_PARAMETERS",
+            "started_from_intent": "retail_support_exchange_return",
+            "parameter_schema": {"order_id": "string", "reason": "string"},
+        },
+    }
+    decision = await router.route(state)
+    assert decision.intent == "billing_invoice_explanation"
+    assert decision.agent == "billing_agent"
+    assert decision.metadata["transaction_interruption"] == "intent_shift"
+
+
+def test_hardcoded_action_argument_extractor_removed():
+    from pathlib import Path
+    source = Path("libs/agent_framework/src/agent_framework/runtime/agent_runtime.py").read_text(encoding="utf-8")
+    assert "def _extract_action_arguments" not in source
+    assert "pedido|ordem" not in source
+    assert "reason_match" not in source
+
+@pytest.mark.asyncio
+async def test_confirmation_is_consumed_before_intent_shift(tmp_path):
+    routing = tmp_path / "routing.yaml"
+    routing.write_text(
+        """
+router:
+  fallback_agent: support_agent
+  confidence_threshold: 0.70
+state_policies:
+  - state: WAITING_SUPPORT_CONFIRMATION
+    agent: support_agent
+intents:
+  - name: generic_yes_intent
+    agent: other_agent
+    priority: 50
+    keywords: [sim]
+""",
+        encoding="utf-8",
+    )
+    settings = SimpleNamespace(
+        ROUTING_CONFIG_PATH=str(routing),
+        ENABLE_LLM_ROUTER=True,
+        ENABLE_ROUTE_STICKINESS=False,
+    )
+    router = EnterpriseRouter(settings, llm=_SemanticLLM())
+    state = {
+        "user_text": "sim",
+        "sanitized_input": "sim",
+        "next_state": "WAITING_SUPPORT_CONFIRMATION",
+        "transaction_status": "AWAITING_CONFIRMATION",
+        "active_agent": "support_agent",
+        "active_transaction": {
+            "tool_name": "solicitar_devolucao",
+            "arguments": {"order_id": "PED-1001", "reason": "desisti"},
+            "status": "AWAITING_CONFIRMATION",
+            "started_from_intent": "retail_support_exchange_return",
+        },
+    }
+    decision = await router.route(state)
+    assert decision.agent == "support_agent"
+    assert decision.metadata["transaction_turn_consumed"] is True
+    assert decision.metadata["transaction_confirmation_decision"] == "confirm"
+    assert "transaction_interruption" not in decision.metadata

agent_framework_oci/tests/test_transaction_state_regression_matrix.py

@@ -34,6 +34,20 @@ intents:
 """
 
 
+class _ParameterLLM:
+    async def ainvoke(self, messages, **kwargs):
+        import json
+        prompt = messages[-1]["content"]
+        if kwargs.get("profile_name") == "transaction_parameter_extraction":
+            pending = json.loads(prompt.split("pending_parameters: ", 1)[1].split("\n", 1)[0])
+            user = prompt.split("user_message: ", 1)[1].split("\nFormato obrigatório:", 1)[0].strip()
+            out = {name: None for name in pending}
+            if len(pending) == 1 and user not in {"quero rastrear pedido", "quero ver minha fatura"}:
+                out[pending[0]] = user
+            return json.dumps(out, ensure_ascii=False)
+        return '{}'
+
+
 def _router(tmp_path, *, stickiness=True):
     routing = tmp_path / "routing.yaml"
     routing.write_text(ROUTING_YAML, encoding="utf-8")
@@ -42,7 +56,7 @@ def _router(tmp_path, *, stickiness=True):
         ENABLE_LLM_ROUTER=False,
         ENABLE_ROUTE_STICKINESS=stickiness,
     )
-    return EnterpriseRouter(settings)
+    return EnterpriseRouter(settings, llm=_ParameterLLM())
 
 
 def _active_tx(status="COLLECTING_PARAMETERS", arguments=None):

agent_framework_oci/tests/test_transactional_tool_flow.py

@@ -30,20 +30,45 @@ import pytest
 from agent_framework.runtime.agent_runtime import AgentRuntimeMixin
 
 
+class _TransactionTestLLM:
+    async def ainvoke(self, messages, **kwargs):
+        import json
+        prompt = messages[-1]["content"]
+        if kwargs.get("profile_name") == "transaction_parameter_extraction" or "pending_parameters:" in prompt:
+            pending = json.loads(prompt.split("pending_parameters: ", 1)[1].split("\n", 1)[0])
+            user = prompt.split("user_message: ", 1)[1].split("\nFormato obrigatório:", 1)[0].strip()
+            out = {name: None for name in pending}
+            low = user.lower()
+            if "order_id" in out:
+                import re
+                m = re.search(r"\b(?:ped[- ]?)?(\d+)\b", low, re.I)
+                if m:
+                    out["order_id"] = ("PED-" + m.group(1)) if "ped" in m.group(0).lower() else m.group(1)
+            if "reason" in out and ("arrepend" in low or "desisti" in low):
+                out["reason"] = "Arrependimento da compra" if "arrepend" in low else "desisti da compra"
+            return {"content": json.dumps(out, ensure_ascii=False)}
+        return {"content": "{}"}
+
+
 class _PolicyRouter:
     def __init__(self):
         from types import SimpleNamespace
         self.registry = SimpleNamespace(
             tools={"consultar_pedido": object(), "solicitar_devolucao": object()},
             get_tool=lambda name: {
-                "consultar_pedido": SimpleNamespace(selection_keywords=["consultar pedido", "pedido"]),
-                "solicitar_devolucao": SimpleNamespace(selection_keywords=["devolver pedido", "devolver", "devolução", "arrependimento"]),
+                "consultar_pedido": SimpleNamespace(selection_keywords=["consultar pedido", "pedido"], args_schema={}, requires=[]),
+                "solicitar_devolucao": SimpleNamespace(
+                    selection_keywords=["devolver pedido", "devolver", "devolução", "arrependimento"],
+                    args_schema={"order_id": "string", "reason": "string"},
+                    requires=["order_id", "reason"],
+                    description="Solicita devolução de pedido",
+                ),
             }.get(name),
         )
 
     def resolve_execution_policy(self, tool_name, arguments=None):
         if tool_name == "solicitar_devolucao":
-            return {"operation_type": "transactional", "require_confirmation": True, "policy_source": "test"}
+            return {"operation_type": "transactional", "require_confirmation": True, "requires": ["order_id", "reason"], "policy_source": "test"}
         return {"operation_type": "read_only", "require_confirmation": False, "policy_source": "test"}
 
     def validate_execution_policy(self, tool_name, arguments=None):
@@ -56,6 +81,7 @@ class _PolicyRouter:
 class _Runtime(AgentRuntimeMixin):
     def __init__(self):
         self.tool_router = _PolicyRouter()
+        self.llm = _TransactionTestLLM()
         self.calls = []
 
     async def _call_mcp_tool(self, tool_name, arguments, state):
@@ -163,14 +189,20 @@ async def test_collecting_parameters_does_not_replace_collected_subject_with_sta
 
 class _InitialContestLLM:
     async def ainvoke(self, messages, **kwargs):
-        prompt = messages[0]["content"]
-        if "Campo: subject" in prompt:
-            return {"content": '{"subject": "TIM CTRL Redes Sociais 8.0"}'}
-        if "Campo: valor" in prompt:
-            return {"content": '{"valor": null}'}
-        if "Campo: motivo" in prompt:
-            return {"content": '{"motivo": "não contratei"}'}
-        return {"content": '{}'}
+        import json
+        prompt = messages[-1]["content"]
+        if kwargs.get("profile_name") == "transaction_parameter_extraction":
+            pending = json.loads(prompt.split("pending_parameters: ", 1)[1].split("\n", 1)[0])
+            out = {name: None for name in pending}
+            if "subject" in out:
+                out["subject"] = "TIM CTRL Redes Sociais 8.0"
+            return {"content": json.dumps(out, ensure_ascii=False)}
+        if kwargs.get("profile_name") == "mcp_parameter_extraction":
+            if "Campo: motivo" in prompt:
+                return {"content": '{"motivo": "não contratei"}'}
+            if "Campo: valor" in prompt:
+                return {"content": '{"valor": null}'}
+        return {"content": "{}"}
 
 
 class _InitialContestRouter(_ContestPolicyRouter):