feat(studio): 新增 Studio 工作流编辑/运行页，优化顶部三栏对齐

- 后端：项目/运行 API、上下文服务与数据模型
- 前端：Studio 列表、编辑页（R1/R2 布局）、运行页与节点图
- 编辑页顶部：CSS Grid 统一标签行与控件行对齐，项目按钮独立第三行
- Docker 开发配置与文档脚本

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/services/studio_context_service.py

@@ -0,0 +1,188 @@
+"""
+Assemble Studio run prompt context from pipeline snapshot, workflow variables,
+and node outputs (R2). Does not include full chat history.
+"""
+from __future__ import annotations
+
+import json
+import re
+from typing import Any, Dict, List, Optional
+
+from models.studio_models import (
+    PipelineDefinition,
+    PromptBlock,
+    StudioNode,
+    StudioNodeRunState,
+    StudioRun,
+)
+
+_NODE_OUTPUT_REF = re.compile(r"^([^.]+)\.output$")
+
+AUTO_BLOCK_SPECS = (
+    ("currentProduct", "目前产物", "auto"),
+    ("thinkingFlow", "思考流程", "auto"),
+    ("coreGoal", "核心目的", "auto"),
+    ("scoringCriteria", "评价标准与优化建议", "auto"),
+)
+
+
+def _find_node(pipeline: PipelineDefinition, node_id: str) -> Optional[StudioNode]:
+    for node in pipeline.nodes:
+        if node.id == node_id:
+            return node
+    return None
+
+
+def _state_map(run: StudioRun) -> Dict[str, StudioNodeRunState]:
+    return {s.nodeId: s for s in run.nodeStates}
+
+
+def _format_draft(draft: Optional[Dict[str, Any]]) -> str:
+    if not draft:
+        return "（暂无内容）"
+    for key in ("entryContent", "content", "text", "body"):
+        value = draft.get(key)
+        if isinstance(value, str) and value.strip():
+            return value.strip()
+    return json.dumps(draft, ensure_ascii=False, indent=2)
+
+
+def _format_scoring(config: Dict[str, Any]) -> str:
+    scoring = config.get("scoring") or {}
+    if not scoring.get("enabled", True):
+        return "（本步骤未启用评价）"
+    dimensions = scoring.get("dimensions") or []
+    if not dimensions:
+        rubric = scoring.get("rubric")
+        if rubric:
+            return str(rubric).strip()
+        return "（未配置评价维度）"
+    lines: List[str] = []
+    for dim in dimensions:
+        name = dim.get("name") or dim.get("id") or "维度"
+        criteria = (dim.get("criteria") or "").strip()
+        lines.append(f"- {name}：{criteria}" if criteria else f"- {name}")
+    return "\n".join(lines)
+
+
+def _resolve_workflow_ref(ref: str, workflow_variables: Dict[str, Any]) -> str:
+    value = workflow_variables.get(ref)
+    if value is None:
+        return "（尚未可用）"
+    if isinstance(value, str):
+        return value.strip() or "（空）"
+    return json.dumps(value, ensure_ascii=False, indent=2)
+
+
+def _resolve_node_output_ref(
+    ref: str,
+    pipeline: PipelineDefinition,
+    state_by_id: Dict[str, StudioNodeRunState],
+) -> str:
+    match = _NODE_OUTPUT_REF.match(ref)
+    if not match:
+        return f"（无法解析引用：{ref}）"
+    node_id = match.group(1)
+    source_node = _find_node(pipeline, node_id)
+    source_state = state_by_id.get(node_id)
+    label = source_node.displayName if source_node else node_id
+    if not source_state or source_state.status != "completed":
+        return f"（前序步骤「{label}」尚未完成）"
+    return _format_draft(source_state.lastDraft)
+
+
+def _auto_block_content(
+    block_id: str,
+    node: StudioNode,
+    node_state: Optional[StudioNodeRunState],
+) -> str:
+    config = node.config or {}
+    if block_id == "currentProduct":
+        return _format_draft(node_state.lastDraft if node_state else None)
+    if block_id == "thinkingFlow":
+        return (config.get("thinkingPrompt") or "").strip() or "（未配置思考流程）"
+    if block_id == "coreGoal":
+        return (config.get("stepGoal") or "").strip() or "（未配置步骤目标）"
+    if block_id == "scoringCriteria":
+        return _format_scoring(config)
+    return ""
+
+
+def assemble_prompt_blocks(run: StudioRun, node_id: str) -> List[PromptBlock]:
+    """
+    Build ordered prompt blocks for a worldbook step from inputs[].ref,
+    workflow variables, node outputs, and auto-injected context items.
+    """
+    pipeline = run.pipelineSnapshot
+    node = _find_node(pipeline, node_id)
+    if not node:
+        return []
+
+    if node.skillId != "studio.worldbook_entry":
+        return []
+
+    state_by_id = _state_map(run)
+    node_state = state_by_id.get(node_id)
+    workflow_variables = dict(run.workflowVariables or {})
+    blocks: List[PromptBlock] = []
+    seen_ids: set[str] = set()
+
+    def append_block(
+        block_id: str,
+        label: str,
+        content: str,
+        source: str,
+    ) -> None:
+        if block_id in seen_ids:
+            return
+        seen_ids.add(block_id)
+        blocks.append(
+            PromptBlock(
+                id=block_id,
+                label=label,
+                content=content,
+                source=source,
+            )
+        )
+
+    for inp in node.inputs or []:
+        ref = (inp.ref or "").strip()
+        if not ref:
+            continue
+        label = (inp.label or ref).strip()
+        block_id = f"ref:{ref}"
+
+        if ref.startswith("workflow."):
+            content = _resolve_workflow_ref(ref, workflow_variables)
+            if inp.optional and content in ("（尚未可用）", "（空）"):
+                continue
+            append_block(block_id, label, content, "workflow")
+            continue
+
+        if _NODE_OUTPUT_REF.match(ref):
+            content = _resolve_node_output_ref(ref, pipeline, state_by_id)
+            if inp.optional and content.startswith("（前序步骤"):
+                continue
+            append_block(block_id, label, content, "manual")
+            continue
+
+        append_block(block_id, label, f"（未知引用类型：{ref}）", "manual")
+
+    for block_id, label, source in AUTO_BLOCK_SPECS:
+        content = _auto_block_content(block_id, node, node_state)
+        append_block(block_id, label, content, source)
+
+    return blocks
+
+
+def store_context_on_run(run: StudioRun, node_id: Optional[str]) -> StudioRun:
+    """Attach assembled prompt blocks to run for debug / frontend display."""
+    if not node_id:
+        return run.model_copy(update={"lastPromptBlocks": []})
+
+    node = _find_node(run.pipelineSnapshot, node_id)
+    if not node or node.skillId != "studio.worldbook_entry":
+        return run.model_copy(update={"lastPromptBlocks": []})
+
+    blocks = assemble_prompt_blocks(run, node_id)
+    return run.model_copy(update={"lastPromptBlocks": blocks})