feat：接入mcp，为模型提供图表信息

2026-10-01 06:33:44 -07:00
parent 618290d852
commit f1b2a70ad1
44 changed files with 6531 additions and 207 deletions
@@ -2,6 +2,10 @@

 import json

+from langchain.agents.structured_output import (
+    StructuredOutputError,
+    StructuredOutputValidationError,
+)
 from langchain_core.exceptions import OutputParserException
 from langchain_core.messages import HumanMessage, SystemMessage
 from pydantic import ValidationError
@@ -9,13 +13,18 @@ from pydantic import ValidationError
 from app.actions.plan import assemble_plan_actions, plan_block_reason, plan_materials
 from app.clients.llm import get_llm
 from app.processor.base import BaseNode
+from app.processor.material_agent import field_group_directory, invoke_with_field_tools
 from app.processor.state import QueryState
-from app.prompt.action import build_action_prompt
-from app.resources.material_fields import editable_fields
+from app.prompt.action import build_action_prompt, uses_material_fields
 from app.schemas.action_validation import ActionValidationError, schema_errors
 from app.schemas.actions import ActionBatch, AddAction
 from app.schemas.operations import is_direct_operation

+GENERATION_ERROR = ActionValidationError(
+    code="generation_error",
+    message="模型输出无法解析为 ActionBatch，请按协议重新生成",
+)
+

 def can_generate_actions(state: QueryState) -> bool:
    # 没有阻塞原因时才允许生成动作，路由和节点入口复用同一套能力检查
@@ -59,28 +68,6 @@ def action_block_reason(state: QueryState) -> str | None:
    return None


-def update_fields(state: QueryState) -> dict[str, list[dict]]:
-    """按组件 ID 汇总可能被属性更新的已有组件的可编辑字段，没有字段的组件省略"""
-    plan = state.get("screen_plan")
-    if plan is None:
-        target_ids = [
-            target
-            for change in state["requirement"].changes
-            if change.target_scope == "nodes"
-            for target in change.target_ids
-        ]
-    else:
-        target_ids = [
-            item.target_id for item in plan.components if item.disposition == "modify"
-        ]
-    nodes = {node.id: node for node in state["input_context"].screen.nodes}
-    result = {}
-    for target in dict.fromkeys(target_ids):
-        if target in nodes and (fields := editable_fields(nodes[target].type)):
-            result[target] = fields
-    return result
-
-
 class ActionNode(BaseNode):
    name = "action_node"

@@ -115,10 +102,6 @@ class ActionNode(BaseNode):
            payload["screen_plan"] = state["screen_plan"].model_dump(mode="json")
            payload["component_materials"] = plan_materials(state)

-        # 提供待修改组件的属性面板字段，让模型把用户说的“标题”“颜色”等对应到真实路径
-        if fields := update_fields(state):
-            payload["editable_fields"] = fields
-
        # 如果本轮是动作修正，提供修正建议、上一轮动作和校验错误供模型参考
        if state.get("repair_plan") is not None:
            payload.update(
@@ -133,7 +116,17 @@ class ActionNode(BaseNode):
                ],
            )

-        llm_client = get_llm(ActionBatch)
+        system_prompt = build_action_prompt(
+            state["requirement"],
+            state.get("screen_plan"),
+            repairing=state.get("repair_plan") is not None,
+        )
+        # 需要写组件属性时提供相关组件的字段分组，模型再按需查询字段定义
+        with_fields = uses_material_fields(state["requirement"], state.get("screen_plan"))
+        if with_fields:
+            payload["field_groups"] = field_group_directory(state)
+        # 将本次具体资料放入用户消息，保留中文以便阅读和排查
+        content = json.dumps(payload, ensure_ascii=False)

        # 旧动作及错误已放入模型输入，现在清空输出状态，避免本轮失败后残留旧结果
        updated_state["actions"] = None
@@ -146,19 +139,12 @@ class ActionNode(BaseNode):
        # 捕获输出结构和解析错误，转换成统一校验结果供后续修正流程使用
        try:
            # 异步调用模型，根据需求、规划及是否正在修正选择对应的系统规则
-            result = await llm_client.ainvoke(
-                [
-                    SystemMessage(
-                        content=build_action_prompt(
-                            state["requirement"],
-                            state.get("screen_plan"),
-                            repairing=state.get("repair_plan") is not None,
-                        )
-                    ),
-                    # 将本次具体资料放入用户消息，保留中文以便阅读和排查
-                    HumanMessage(content=json.dumps(payload, ensure_ascii=False)),
-                ]
-            )
+            if with_fields:
+                result = await invoke_with_field_tools(ActionBatch, system_prompt, content)
+            else:
+                result = await get_llm(ActionBatch).ainvoke(
+                    [SystemMessage(content=system_prompt), HumanMessage(content=content)]
+                )

            # 响应中没有工具调用时解析器会返回 None
            if result is None:
@@ -184,15 +170,19 @@ class ActionNode(BaseNode):
            updated_state["validation_passed"] = False
            updated_state["validation_errors"] = schema_errors(error)
            return updated_state
-        except OutputParserException:
+        except StructuredOutputValidationError as error:
+            # 查询字段后的输出不符合结构，与直接输出时的处理一致
+            updated_state["validation_passed"] = False
+            updated_state["validation_errors"] = (
+                schema_errors(error.source)
+                if isinstance(error.source, ValidationError)
+                else [GENERATION_ERROR]
+            )
+            return updated_state
+        except (OutputParserException, StructuredOutputError):
            # 如果模型输出无法解析，记录生成错误，提示后续按 ActionBatch 协议重新生成
            updated_state["validation_passed"] = False
-            updated_state["validation_errors"] = [
-                ActionValidationError(
-                    code="generation_error",
-                    message="模型输出无法解析为 ActionBatch，请按协议重新生成",
-                )
-            ]
+            updated_state["validation_errors"] = [GENERATION_ERROR]
            return updated_state

        # 保存生成的动作，实际目标、规划一致性及模拟执行结果仍由后续校验节点检查
@@ -2,6 +2,7 @@

 import json

+from langchain.agents.structured_output import StructuredOutputError
 from langchain_core.exceptions import OutputParserException
 from langchain_core.messages import HumanMessage, SystemMessage
 from pydantic import ValidationError
@@ -9,7 +10,9 @@ from pydantic import ValidationError
 from app.actions.plan import plan_materials
 from app.clients.llm import get_llm
 from app.processor.base import BaseNode
+from app.processor.material_agent import field_group_directory, invoke_with_field_tools
 from app.processor.state import QueryState
+from app.prompt.action import FIELD_QUERY_PROMPT, uses_material_fields
 from app.schemas.capabilities import USER_FAILURE_MESSAGE
 from app.prompt.reflection import REFLECTION_SYSTEM_PROMPT
 from app.schemas.action_repair import ActionRepairPlan
@@ -22,7 +25,6 @@ class ReflectionNode(BaseNode):
        # 浅拷贝状态
        updated_state: QueryState = state.copy()

-        llm_client = get_llm(ActionRepairPlan)
        # 汇总原始上下文、需求和失败信息，让模型基于实际错误提出修正建议
        payload = {
            "input_context": state["input_context"].model_dump(mode="json"),
@@ -46,21 +48,30 @@ class ReflectionNode(BaseNode):
            payload["screen_plan"] = state["screen_plan"].model_dump(mode="json")
            payload["component_materials"] = plan_materials(state)

+        # 涉及组件属性时，修正建议须基于查询到的字段定义，与动作生成使用同一组工具
+        with_fields = uses_material_fields(state["requirement"], state.get("screen_plan"))
+        if with_fields:
+            payload["field_groups"] = field_group_directory(state)
+        # 用户消息承载本轮待分析的具体资料，序列化时保留中文
+        content = json.dumps(payload, ensure_ascii=False)
+
        # 只捕获输出结构和解析错误，配置、网络等异常继续向上抛出
        try:
            # 异步生成修正建议，本节点不直接修改动作
-            plan = await llm_client.ainvoke(
-                [
-                    # 系统消息提供稳定的失败分析和修正规则
-                    SystemMessage(content=REFLECTION_SYSTEM_PROMPT),
-                    # 用户消息承载本轮待分析的具体资料，序列化时保留中文
-                    HumanMessage(content=json.dumps(payload, ensure_ascii=False)),
-                ]
-            )
+            if with_fields:
+                plan = await invoke_with_field_tools(
+                    ActionRepairPlan,
+                    REFLECTION_SYSTEM_PROMPT + "\n" + FIELD_QUERY_PROMPT,
+                    content,
+                )
+            else:
+                plan = await get_llm(ActionRepairPlan).ainvoke(
+                    [SystemMessage(content=REFLECTION_SYSTEM_PROMPT), HumanMessage(content=content)]
+                )
            # 响应中没有工具调用时解析器会返回 None
            if plan is None:
                raise OutputParserException("模型未返回结构化结果")
-        except (ValidationError, OutputParserException):
+        except (ValidationError, OutputParserException, StructuredOutputError):
            # 如果未能得到合法建议，清空旧修正计划，避免再次使用已失效的建议
            updated_state["repair_plan"] = None
            # 记录无法继续修正的原因，交给后续路由和失败处理流程
@@ -4,10 +4,18 @@ from pydantic import ValidationError

 from app.actions.plan import validate_plan_actions, validate_plan_result
 from app.actions.registry import apply_action
+from app.actions.update import fit_existing_path
 from app.processor.base import BaseNode
 from app.processor.state import QueryState
+from app.resources.component import get_catalog_cache
+from app.resources.material_fields import check_update_field
 from app.schemas.action_validation import ActionValidationError, schema_errors
-from app.schemas.actions import ActionBatch, AddAction, UpdateCanvasAction
+from app.schemas.actions import (
+    ActionBatch,
+    AddAction,
+    UpdateAction,
+    UpdateCanvasAction,
+)
 from app.schemas.operations import is_canvas_operation


@@ -121,8 +129,32 @@ class ValidatorNode(BaseNode):
        # 在副本上试执行，不改变用户传入的大屏，也不操作前端画布
        screen = state["input_context"].screen.model_copy(deep=True)

+        catalog = get_catalog_cache()
+        # 保存补齐路径后的动作，前端按它执行
+        actions = list(batch.actions)
+
        # 按动作顺序逐项执行，每一步都使用上一步更新后的大屏副本
-        for index, action in enumerate(batch.actions):
+        for index, action in enumerate(actions):
+            # 属性更新先按物料字段定义检查，目标不存在时交给处理器报错
+            node = (
+                next((item for item in screen.nodes if item.id == action.target_id), None)
+                if isinstance(action, UpdateAction)
+                else None
+            )
+            if node is not None:
+                try:
+                    check_update_field(catalog, node.type, action)
+                except ValueError as error:
+                    updated_state["validation_passed"] = False
+                    updated_state["validation_errors"] = [
+                        ActionValidationError(
+                            action_index=index, code="field_error", message=str(error)
+                        )
+                    ]
+                    updated_state["simulated_screen"] = None
+                    return updated_state
+                # 字段定义允许、但组件中还没有的中间对象，折叠进值里再执行
+                action = actions[index] = fit_existing_path(node, action)
            try:
                # 根据动作类型调用对应处理逻辑，检查目标和参数并返回更新后的大屏
                screen = apply_action(screen, action)
@@ -147,8 +179,8 @@ class ValidatorNode(BaseNode):
                updated_state["simulated_screen"] = None
                return updated_state

-        # 全部检查通过后，保存重新校验过的动作对象，统一后续读取的数据结构
-        updated_state["actions"] = batch.actions
+        # 全部检查通过后，保存重新校验并补齐路径的动作对象，统一后续读取的数据结构
+        updated_state["actions"] = actions
        # 标记整批动作校验通过，并清空之前可能残留的错误
        updated_state["validation_passed"] = True
        updated_state["validation_errors"] = []