feat: 接入起卦后端流程并完善积分扣减链路

2026-04-03 19:04:46 +08:00
parent a136e42290
commit d87b2e1e3a
56 changed files with 3310 additions and 809 deletions
@@ -17,36 +17,38 @@ from schemas.agent.ui_hints import UiHintsPayload
 if TYPE_CHECKING:
    pass

-_INTERNAL_TO_AGUI: dict[str, EventType] = {
-    "run.started": EventType.RUN_STARTED,
-    "run.finished": EventType.RUN_FINISHED,
-    "run.error": EventType.RUN_ERROR,
-    "step.start": EventType.STEP_STARTED,
-    "step.finish": EventType.STEP_FINISHED,
-    "text.end": EventType.TEXT_MESSAGE_END,
-    "tool.start": EventType.TOOL_CALL_START,
-    "tool.args": EventType.TOOL_CALL_ARGS,
-    "tool.end": EventType.TOOL_CALL_END,
-    "tool.result": EventType.TOOL_CALL_RESULT,
-    "state.snapshot": EventType.STATE_SNAPSHOT,
-    "messages.snapshot": EventType.MESSAGES_SNAPSHOT,
+_INTERNAL_TO_AGUI: dict[str, str] = {
+    "run.started": EventType.RUN_STARTED.value,
+    "run.finished": EventType.RUN_FINISHED.value,
+    "run.error": EventType.RUN_ERROR.value,
+    "step.start": EventType.STEP_STARTED.value,
+    "step.finish": EventType.STEP_FINISHED.value,
+    "text.end": EventType.TEXT_MESSAGE_END.value,
+    "tool.start": EventType.TOOL_CALL_START.value,
+    "tool.args": EventType.TOOL_CALL_ARGS.value,
+    "tool.end": EventType.TOOL_CALL_END.value,
+    "tool.result": EventType.TOOL_CALL_RESULT.value,
+    "state.snapshot": EventType.STATE_SNAPSHOT.value,
+    "messages.snapshot": EventType.MESSAGES_SNAPSHOT.value,
 }

+_ALLOWED_WIRE_TYPES: set[str] = {event_type.value for event_type in EventType}
+_ALLOWED_WIRE_TYPES.add("DIVINATION_DERIVED")

-def _convert_to_agui_type(internal_type: str) -> EventType:
+
+def _convert_to_agui_type(internal_type: str) -> str:
    mapped = _INTERNAL_TO_AGUI.get(internal_type)
    if mapped is not None:
        return mapped
-    return EventType(internal_type.upper().replace(".", "_"))
+    candidate = internal_type.upper().replace(".", "_")
+    if candidate in _ALLOWED_WIRE_TYPES:
+        return candidate
+    raise ValueError(f"unsupported ag-ui event type: {internal_type}")


 def _is_agui_event(event: dict[str, Any]) -> bool:
-    event_type = event.get("type", "")
-    try:
-        EventType(event_type)
-        return True
-    except ValueError:
-        return False
+    event_type = str(event.get("type", "")).strip().upper()
+    return event_type in _ALLOWED_WIRE_TYPES


 def _sanitize_agui_event(event: dict[str, Any]) -> dict[str, Any]:
@@ -153,7 +155,7 @@ def to_agui_wire_event(event: dict[str, Any] | BaseEvent) -> dict[str, Any]:

    if internal_type == "text.end" and isinstance(data, dict):
        text_end_payload: dict[str, Any] = {
-            "type": _convert_to_agui_type(internal_type).value,
+            "type": _convert_to_agui_type(internal_type),
        }
        if isinstance(thread_id, str) and thread_id:
            text_end_payload["threadId"] = thread_id
@@ -174,7 +176,7 @@ def to_agui_wire_event(event: dict[str, Any] | BaseEvent) -> dict[str, Any]:

    if internal_type == "tool.result" and isinstance(data, dict):
        tool_result_payload: dict[str, Any] = {
-            "type": _convert_to_agui_type(internal_type).value,
+            "type": _convert_to_agui_type(internal_type),
        }
        if isinstance(thread_id, str) and thread_id:
            tool_result_payload["threadId"] = thread_id
@@ -203,7 +205,7 @@ def to_agui_wire_event(event: dict[str, Any] | BaseEvent) -> dict[str, Any]:
    wire_type = _convert_to_agui_type(internal_type)

    payload: dict[str, Any] = {
-        "type": wire_type.value,
+        "type": wire_type,
    }
    if isinstance(thread_id, str) and thread_id:
        payload["threadId"] = thread_id
@@ -0,0 +1,18 @@
+from __future__ import annotations
+
+from schemas.domain.divination import DerivedDivinationData
+
+
+def build_divination_user_prompt(*, derived: DerivedDivinationData) -> str:
+    structured_json = derived.model_dump_json(
+        by_alias=True,
+        exclude_none=True,
+        ensure_ascii=False,
+    )
+    return (
+        f"用户问题：{derived.question}\n"
+        f"问题类型：{derived.question_type}\n"
+        "以下是后端推导后的六爻结构化数据（JSON）：\n"
+        f"{structured_json}\n"
+        "请仅基于以上六爻数据做专业解读。"
+    )
@@ -13,11 +13,14 @@ from agentscope.message import Msg
 from agentscope.tool import Toolkit
 from agentscope.model import OpenAIChatModel
 from core.agentscope.prompts.system_prompt import build_system_prompt
+from core.agentscope.prompts.user_prompt import build_divination_user_prompt
 from core.agentscope.schemas.agui_input import extract_latest_user_payload
+from core.divination import derive_divination
 from core.agentscope.runtime.json_react_agent import JsonReActAgent
 from core.agentscope.runtime.model_tracking import TrackingChatModel
 from core.agentscope.runtime.stage_emitter import PipelineStageEmitter
 from core.agentscope.utils import patch_agentscope_json_repair_compat
+from core.agentscope.utils.json_finalize import finalize_json_response
 from core.config.settings import config
 from core.db.session import AsyncSessionLocal
 from models.llm import Llm
@@ -26,9 +29,11 @@ from models.system_agents import SystemAgents
 from schemas.agent.forwarded_props import (
    ClientTimeContext,
    RuntimeMode,
+    parse_forwarded_props_divination_payload,
    parse_forwarded_props_client_time,
    parse_forwarded_props_runtime_mode,
 )
+from schemas.domain.divination import DerivedDivinationData
 from schemas.agent.runtime_models import (
    WorkerAgentOutputLite,
    resolve_worker_output_model,
@@ -97,6 +102,21 @@ class AgentScopeRunner:
                worker_toolkit = self._build_toolkit()
                if cancel_checker is not None and await cancel_checker():
                    raise asyncio.CancelledError("run canceled by user")
+                derived_divination = self._resolve_derived_divination(
+                    run_input=run_input
+                )
+                await self._emit_step_event(
+                    pipeline=pipeline,
+                    run_input=run_input,
+                    step_name="divination",
+                    event_type="DIVINATION_DERIVED",
+                    runtime_mode=runtime_mode,
+                    extra_event={
+                        "divination": derived_divination.model_dump(
+                            mode="json", by_alias=True, exclude_none=True
+                        )
+                    },
+                )
                worker_output = await self._execute_worker_step(
                    pipeline=pipeline,
                    run_input=run_input,
@@ -106,6 +126,7 @@ class AgentScopeRunner:
                    stage_config=worker_config,
                    runtime_client_time=runtime_client_time,
                    runtime_mode=runtime_mode,
+                    derived_divination=derived_divination,
                )
                return {
                    "worker": worker_output.model_dump(mode="json", exclude_none=True),
@@ -187,6 +208,7 @@ class AgentScopeRunner:
        stage_config: SystemAgentRuntimeConfig,
        runtime_client_time: ClientTimeContext | None,
        runtime_mode: RuntimeMode,
+        derived_divination: DerivedDivinationData,
    ) -> WorkerAgentOutputLite:
        worker_output_model = resolve_worker_output_model()
        await self._emit_step_event(
@@ -201,6 +223,7 @@ class AgentScopeRunner:
            input_messages=self._build_worker_input_messages(
                context_messages=context_messages,
                run_input=run_input,
+                derived_divination=derived_divination,
            ),
            toolkit=toolkit,
            run_input=run_input,
@@ -234,6 +257,7 @@ class AgentScopeRunner:
        runtime_mode: RuntimeMode,
    ) -> StageExecutionResult:
        tracking_model = self._build_model(stage_config=stage_config)
+        formatter = OpenAIChatFormatter()
        emitter = PipelineStageEmitter(
            pipeline=pipeline,
            session_id=run_input.thread_id,
@@ -243,32 +267,24 @@ class AgentScopeRunner:
            emit_text_events=True,
            emit_tool_events=False,
        )
-        agent = self._build_agent(
-            agent_name=stage_config.agent_type.value,
-            system_prompt=build_system_prompt(
-                agent_type=stage_config.agent_type,
-                llm_config=stage_config.llm_config,
-                user_context=user_context,
-                now_utc=datetime.now(timezone.utc),
-                runtime_client_time=runtime_client_time,
-                extra_context=stage_config.extra_context,
-                tools=None,
-            ),
-            toolkit=toolkit,
-            model=tracking_model,
-            emitter=emitter,
+        system_prompt = build_system_prompt(
+            agent_type=stage_config.agent_type,
+            llm_config=stage_config.llm_config,
+            user_context=user_context,
+            now_utc=datetime.now(timezone.utc),
+            runtime_client_time=runtime_client_time,
+            extra_context=stage_config.extra_context,
+            tools=None,
        )
-        async with self._active_agent_lock:
-            self._active_agent = agent
-        try:
-            response_msg = await agent.reply_json(
-                input_messages, output_model=worker_output_model
-            )
-        finally:
-            async with self._active_agent_lock:
-                if self._active_agent is agent:
-                    self._active_agent = None
-        worker_payload = worker_output_model.model_validate(response_msg.metadata or {})
+
+        _, worker_payload_raw = await finalize_json_response(
+            model=tracking_model,
+            formatter=formatter,
+            base_messages=[Msg("system", system_prompt, "system"), *input_messages],
+            output_model=worker_output_model,
+            retries=2,
+        )
+        worker_payload = worker_output_model.model_validate(worker_payload_raw)
        response_metadata = self._llm_pricing_service.build_usage_metadata(
            model=stage_config.model_code,
            usage_summary=tracking_model.usage_summary(),
@@ -278,7 +294,12 @@ class AgentScopeRunner:
            response_metadata=response_metadata,
        )
        return StageExecutionResult(
-            message=response_msg,
+            message=Msg(
+                name=stage_config.agent_type.value,
+                role="assistant",
+                content=worker_payload.answer,
+                metadata=worker_payload.model_dump(mode="json", exclude_none=True),
+            ),
            payload=worker_payload.model_dump(mode="json", exclude_none=True),
            response_metadata=response_metadata,
        )
@@ -288,13 +309,16 @@ class AgentScopeRunner:
        *,
        context_messages: list[Msg],
        run_input: RunAgentInput,
+        derived_divination: DerivedDivinationData,
    ) -> list[Msg]:
        if context_messages:
            last = context_messages[-1]
            if last.role == "user":
                return context_messages

-        user_text, user_blocks = extract_latest_user_payload(run_input)
+        _, _ = extract_latest_user_payload(run_input)
+        user_text = build_divination_user_prompt(derived=derived_divination)
+        user_blocks = [{"type": "text", "text": user_text}]
        if (
            user_blocks
            and isinstance(user_blocks[0], dict)
@@ -307,6 +331,17 @@ class AgentScopeRunner:
        user_msg = Msg(name="user", role="user", content=content)
        return [*context_messages, user_msg]

+    @staticmethod
+    def _resolve_derived_divination(
+        *, run_input: RunAgentInput
+    ) -> DerivedDivinationData:
+        payload = parse_forwarded_props_divination_payload(
+            getattr(run_input, "forwarded_props", None)
+        )
+        if payload is None:
+            raise ValueError("forwardedProps.divinationPayload is required")
+        return derive_divination(payload)
+
    def _build_model(
        self, *, stage_config: SystemAgentRuntimeConfig
    ) -> TrackingChatModel: