reduce logs

Add workflow upload func.
add unilabos/workflow and entrypoint
2025-12-14 13:14:39 +00:00 · 2025-12-08 19:23:53 +08:00 · 2025-12-08 19:12:05 +08:00 · 2025-12-07 17:50:27 +08:00
37 changed files with 1628 additions and 622 deletions
--- a/scripts/workflow.py
+++ b/scripts/workflow.py
@@ -2,7 +2,6 @@ import json
 import logging
 import traceback
 import uuid
-import xml.etree.ElementTree as ET
 from typing import Any, Dict, List

 import networkx as nx
@@ -25,7 +24,15 @@ class SimpleGraph:

    def add_edge(self, source, target, **attrs):
        """添加边"""
-        edge = {"source": source, "target": target, **attrs}
+        # edge = {"source": source, "target": target, **attrs}
+        edge = {
+            "source": source, "target": target,
+            "source_node_uuid": source,
+            "target_node_uuid": target,
+            "source_handle_io": "source",
+            "target_handle_io": "target",
+            **attrs
+        }
        self.edges.append(edge)

    def to_dict(self):
@@ -42,6 +49,7 @@ class SimpleGraph:
            "multigraph": False,
            "graph": {},
            "nodes": nodes_list,
+            "edges": self.edges,
            "links": self.edges,
        }

@@ -58,495 +66,8 @@ def extract_json_from_markdown(text: str) -> str:
    return text


-def convert_to_type(val: str) -> Any:
-    """将字符串值转换为适当的数据类型"""
-    if val == "True":
-        return True
-    if val == "False":
-        return False
-    if val == "?":
-        return None
-    if val.endswith(" g"):
-        return float(val.split(" ")[0])
-    if val.endswith("mg"):
-        return float(val.split("mg")[0])
-    elif val.endswith("mmol"):
-        return float(val.split("mmol")[0]) / 1000
-    elif val.endswith("mol"):
-        return float(val.split("mol")[0])
-    elif val.endswith("ml"):
-        return float(val.split("ml")[0])
-    elif val.endswith("RPM"):
-        return float(val.split("RPM")[0])
-    elif val.endswith(" °C"):
-        return float(val.split(" ")[0])
-    elif val.endswith(" %"):
-        return float(val.split(" ")[0])
-    return val


-def refactor_data(data: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
-    """统一的数据重构函数，根据操作类型自动选择模板"""
-    refactored_data = []
-
-    # 定义操作映射，包含生物实验和有机化学的所有操作
-    OPERATION_MAPPING = {
-        # 生物实验操作
-        "transfer_liquid": "SynBioFactory-liquid_handler.prcxi-transfer_liquid",
-        "transfer": "SynBioFactory-liquid_handler.biomek-transfer",
-        "incubation": "SynBioFactory-liquid_handler.biomek-incubation",
-        "move_labware": "SynBioFactory-liquid_handler.biomek-move_labware",
-        "oscillation": "SynBioFactory-liquid_handler.biomek-oscillation",
-        # 有机化学操作
-        "HeatChillToTemp": "SynBioFactory-workstation-HeatChillProtocol",
-        "StopHeatChill": "SynBioFactory-workstation-HeatChillStopProtocol",
-        "StartHeatChill": "SynBioFactory-workstation-HeatChillStartProtocol",
-        "HeatChill": "SynBioFactory-workstation-HeatChillProtocol",
-        "Dissolve": "SynBioFactory-workstation-DissolveProtocol",
-        "Transfer": "SynBioFactory-workstation-TransferProtocol",
-        "Evaporate": "SynBioFactory-workstation-EvaporateProtocol",
-        "Recrystallize": "SynBioFactory-workstation-RecrystallizeProtocol",
-        "Filter": "SynBioFactory-workstation-FilterProtocol",
-        "Dry": "SynBioFactory-workstation-DryProtocol",
-        "Add": "SynBioFactory-workstation-AddProtocol",
-    }
-
-    UNSUPPORTED_OPERATIONS = ["Purge", "Wait", "Stir", "ResetHandling"]
-
-    for step in data:
-        operation = step.get("action")
-        if not operation or operation in UNSUPPORTED_OPERATIONS:
-            continue
-
-        # 处理重复操作
-        if operation == "Repeat":
-            times = step.get("times", step.get("parameters", {}).get("times", 1))
-            sub_steps = step.get("steps", step.get("parameters", {}).get("steps", []))
-            for i in range(int(times)):
-                sub_data = refactor_data(sub_steps)
-                refactored_data.extend(sub_data)
-            continue
-
-        # 获取模板名称
-        template = OPERATION_MAPPING.get(operation)
-        if not template:
-            # 自动推断模板类型
-            if operation.lower() in ["transfer", "incubation", "move_labware", "oscillation"]:
-                template = f"SynBioFactory-liquid_handler.biomek-{operation}"
-            else:
-                template = f"SynBioFactory-workstation-{operation}Protocol"
-
-        # 创建步骤数据
-        step_data = {
-            "template": template,
-            "description": step.get("description", step.get("purpose", f"{operation} operation")),
-            "lab_node_type": "Device",
-            "parameters": step.get("parameters", step.get("action_args", {})),
-        }
-        refactored_data.append(step_data)
-
-    return refactored_data
-
-
-def build_protocol_graph(
-    labware_info: List[Dict[str, Any]], protocol_steps: List[Dict[str, Any]], workstation_name: str
-) -> SimpleGraph:
-    """统一的协议图构建函数，根据设备类型自动选择构建逻辑"""
-    G = SimpleGraph()
-    resource_last_writer = {}
-    LAB_NAME = "SynBioFactory"
-
-    protocol_steps = refactor_data(protocol_steps)
-
-    # 检查协议步骤中的模板来判断协议类型
-    has_biomek_template = any(
-        ("biomek" in step.get("template", "")) or ("prcxi" in step.get("template", ""))
-        for step in protocol_steps
-    )
-
-    if has_biomek_template:
-        # 生物实验协议图构建
-        for labware_id, labware in labware_info.items():
-            node_id = str(uuid.uuid4())
-
-            labware_attrs = labware.copy()
-            labware_id = labware_attrs.pop("id", labware_attrs.get("name", f"labware_{uuid.uuid4()}"))
-            labware_attrs["description"] = labware_id
-            labware_attrs["lab_node_type"] = (
-                "Reagent" if "Plate" in str(labware_id) else "Labware" if "Rack" in str(labware_id) else "Sample"
-            )
-            labware_attrs["device_id"] = workstation_name
-
-            G.add_node(node_id, template=f"{LAB_NAME}-host_node-create_resource", **labware_attrs)
-            resource_last_writer[labware_id] = f"{node_id}:labware"
-
-        # 处理协议步骤
-        prev_node = None
-        for i, step in enumerate(protocol_steps):
-            node_id = str(uuid.uuid4())
-            G.add_node(node_id, **step)
-
-            # 添加控制流边
-            if prev_node is not None:
-                G.add_edge(prev_node, node_id, source_port="ready", target_port="ready")
-            prev_node = node_id
-
-            # 处理物料流
-            params = step.get("parameters", {})
-            if "sources" in params and params["sources"] in resource_last_writer:
-                source_node, source_port = resource_last_writer[params["sources"]].split(":")
-                G.add_edge(source_node, node_id, source_port=source_port, target_port="labware")
-
-            if "targets" in params:
-                resource_last_writer[params["targets"]] = f"{node_id}:labware"
-
-        # 添加协议结束节点
-        end_id = str(uuid.uuid4())
-        G.add_node(end_id, template=f"{LAB_NAME}-liquid_handler.biomek-run_protocol")
-        if prev_node is not None:
-            G.add_edge(prev_node, end_id, source_port="ready", target_port="ready")
-
-    else:
-        # 有机化学协议图构建
-        WORKSTATION_ID = workstation_name
-
-        # 为所有labware创建资源节点
-        for item_id, item in labware_info.items():
-            # item_id = item.get("id") or item.get("name", f"item_{uuid.uuid4()}")
-            node_id = str(uuid.uuid4())
-
-            # 判断节点类型
-            if item.get("type") == "hardware" or "reactor" in str(item_id).lower():
-                if "reactor" not in str(item_id).lower():
-                    continue
-                lab_node_type = "Sample"
-                description = f"Prepare Reactor: {item_id}"
-                liquid_type = []
-                liquid_volume = []
-            else:
-                lab_node_type = "Reagent"
-                description = f"Add Reagent to Flask: {item_id}"
-                liquid_type = [item_id]
-                liquid_volume = [1e5]
-
-            G.add_node(
-                node_id,
-                template=f"{LAB_NAME}-host_node-create_resource",
-                description=description,
-                lab_node_type=lab_node_type,
-                res_id=item_id,
-                device_id=WORKSTATION_ID,
-                class_name="container",
-                parent=WORKSTATION_ID,
-                bind_locations={"x": 0.0, "y": 0.0, "z": 0.0},
-                liquid_input_slot=[-1],
-                liquid_type=liquid_type,
-                liquid_volume=liquid_volume,
-                slot_on_deck="",
-                role=item.get("role", ""),
-            )
-            resource_last_writer[item_id] = f"{node_id}:labware"
-
-        last_control_node_id = None
-
-        # 处理协议步骤
-        for step in protocol_steps:
-            node_id = str(uuid.uuid4())
-            G.add_node(node_id, **step)
-
-            # 控制流
-            if last_control_node_id is not None:
-                G.add_edge(last_control_node_id, node_id, source_port="ready", target_port="ready")
-            last_control_node_id = node_id
-
-            # 物料流
-            params = step.get("parameters", {})
-            input_resources = {
-                "Vessel": params.get("vessel"),
-                "ToVessel": params.get("to_vessel"),
-                "FromVessel": params.get("from_vessel"),
-                "reagent": params.get("reagent"),
-                "solvent": params.get("solvent"),
-                "compound": params.get("compound"),
-                "sources": params.get("sources"),
-                "targets": params.get("targets"),
-            }
-
-            for target_port, resource_name in input_resources.items():
-                if resource_name and resource_name in resource_last_writer:
-                    source_node, source_port = resource_last_writer[resource_name].split(":")
-                    G.add_edge(source_node, node_id, source_port=source_port, target_port=target_port)
-
-            output_resources = {
-                "VesselOut": params.get("vessel"),
-                "FromVesselOut": params.get("from_vessel"),
-                "ToVesselOut": params.get("to_vessel"),
-                "FiltrateOut": params.get("filtrate_vessel"),
-                "reagent": params.get("reagent"),
-                "solvent": params.get("solvent"),
-                "compound": params.get("compound"),
-                "sources_out": params.get("sources"),
-                "targets_out": params.get("targets"),
-            }
-
-            for source_port, resource_name in output_resources.items():
-                if resource_name:
-                    resource_last_writer[resource_name] = f"{node_id}:{source_port}"
-
-    return G
-
-
-def draw_protocol_graph(protocol_graph: SimpleGraph, output_path: str):
-    """
-    (辅助功能) 使用 networkx 和 matplotlib 绘制协议工作流图，用于可视化。
-    """
-    if not protocol_graph:
-        print("Cannot draw graph: Graph object is empty.")
-        return
-
-    G = nx.DiGraph()
-
-    for node_id, attrs in protocol_graph.nodes.items():
-        label = attrs.get("description", attrs.get("template", node_id[:8]))
-        G.add_node(node_id, label=label, **attrs)
-
-    for edge in protocol_graph.edges:
-        G.add_edge(edge["source"], edge["target"])
-
-    plt.figure(figsize=(20, 15))
-    try:
-        pos = nx.nx_agraph.graphviz_layout(G, prog="dot")
-    except Exception:
-        pos = nx.shell_layout(G)  # Fallback layout
-
-    node_labels = {node: data["label"] for node, data in G.nodes(data=True)}
-    nx.draw(
-        G,
-        pos,
-        with_labels=False,
-        node_size=2500,
-        node_color="skyblue",
-        node_shape="o",
-        edge_color="gray",
-        width=1.5,
-        arrowsize=15,
-    )
-    nx.draw_networkx_labels(G, pos, labels=node_labels, font_size=8, font_weight="bold")
-
-    plt.title("Chemical Protocol Workflow Graph", size=15)
-    plt.savefig(output_path, dpi=300, bbox_inches="tight")
-    plt.close()
-    print(f"  - Visualization saved to '{output_path}'")
-
-
-from networkx.drawing.nx_agraph import to_agraph
-import re
-
-COMPASS = {"n","e","s","w","ne","nw","se","sw","c"}
-
-def _is_compass(port: str) -> bool:
-    return isinstance(port, str) and port.lower() in COMPASS
-
-def draw_protocol_graph_with_ports(protocol_graph, output_path: str, rankdir: str = "LR"):
-    """
-    使用 Graphviz 端口语法绘制协议工作流图。
-    - 若边上的 source_port/target_port 是 compass（n/e/s/w/...），直接用 compass。
-    - 否则自动为节点创建 record 形状并定义命名端口 <portname>。
-    最终由 PyGraphviz 渲染并输出到 output_path（后缀决定格式，如 .png/.svg/.pdf）。
-    """
-    if not protocol_graph:
-        print("Cannot draw graph: Graph object is empty.")
-        return
-
-    # 1) 先用 networkx 搭建有向图，保留端口属性
-    G = nx.DiGraph()
-    for node_id, attrs in protocol_graph.nodes.items():
-        label = attrs.get("description", attrs.get("template", node_id[:8]))
-        # 保留一个干净的“中心标签”，用于放在 record 的中间槽
-        G.add_node(node_id, _core_label=str(label), **{k:v for k,v in attrs.items() if k not in ("label",)})
-
-    edges_data = []
-    in_ports_by_node  = {}  # 收集命名输入端口
-    out_ports_by_node = {}  # 收集命名输出端口
-
-    for edge in protocol_graph.edges:
-        u = edge["source"]
-        v = edge["target"]
-        sp = edge.get("source_port")
-        tp = edge.get("target_port")
-
-        # 记录到图里（保留原始端口信息）
-        G.add_edge(u, v, source_port=sp, target_port=tp)
-        edges_data.append((u, v, sp, tp))
-
-        # 如果不是 compass，就按“命名端口”先归类，等会儿给节点造 record
-        if sp and not _is_compass(sp):
-            out_ports_by_node.setdefault(u, set()).add(str(sp))
-        if tp and not _is_compass(tp):
-            in_ports_by_node.setdefault(v, set()).add(str(tp))
-
-    # 2) 转为 AGraph，使用 Graphviz 渲染
-    A = to_agraph(G)
-    A.graph_attr.update(rankdir=rankdir, splines="true", concentrate="false", fontsize="10")
-    A.node_attr.update(shape="box", style="rounded,filled", fillcolor="lightyellow", color="#999999", fontname="Helvetica")
-    A.edge_attr.update(arrowsize="0.8", color="#666666")
-
-    # 3) 为需要命名端口的节点设置 record 形状与 label
-    #    左列 = 输入端口；中间 = 核心标签；右列 = 输出端口
-    for n in A.nodes():
-        node = A.get_node(n)
-        core = G.nodes[n].get("_core_label", n)
-
-        in_ports  = sorted(in_ports_by_node.get(n, []))
-        out_ports = sorted(out_ports_by_node.get(n, []))
-
-        # 如果该节点涉及命名端口，则用 record；否则保留原 box
-        if in_ports or out_ports:
-            def port_fields(ports):
-                if not ports:
-                    return " "  # 必须留一个空槽占位
-                # 每个端口一个小格子，<p> name
-                return "|".join(f"<{re.sub(r'[^A-Za-z0-9_:.|-]', '_', p)}> {p}" for p in ports)
-
-            left  = port_fields(in_ports)
-            right = port_fields(out_ports)
-
-            # 三栏：左(入) | 中(节点名) | 右(出)
-            record_label = f"{{ {left} | {core} | {right} }}"
-            node.attr.update(shape="record", label=record_label)
-        else:
-            # 没有命名端口：普通盒子，显示核心标签
-            node.attr.update(label=str(core))
-
-    # 4) 给边设置 headport / tailport
-    #    - 若端口为 compass：直接用 compass（e.g., headport="e"）
-    #    - 若端口为命名端口：使用在 record 中定义的 <port> 名（同名即可）
-    for (u, v, sp, tp) in edges_data:
-        e = A.get_edge(u, v)
-
-        # Graphviz 属性：tail 是源，head 是目标
-        if sp:
-            if _is_compass(sp):
-                e.attr["tailport"] = sp.lower()
-            else:
-                # 与 record label 中 <port> 名一致；特殊字符已在 label 中做了清洗
-                e.attr["tailport"] = re.sub(r'[^A-Za-z0-9_:.|-]', '_', str(sp))
-
-        if tp:
-            if _is_compass(tp):
-                e.attr["headport"] = tp.lower()
-            else:
-                e.attr["headport"] = re.sub(r'[^A-Za-z0-9_:.|-]', '_', str(tp))
-
-        # 可选：若想让边更贴边缘，可设置 constraint/spline 等
-        # e.attr["arrowhead"] = "vee"
-
-    # 5) 输出
-    A.draw(output_path, prog="dot")
-    print(f"  - Port-aware workflow rendered to '{output_path}'")
-
-
-def flatten_xdl_procedure(procedure_elem: ET.Element) -> List[ET.Element]:
-    """展平嵌套的XDL程序结构"""
-    flattened_operations = []
-    TEMP_UNSUPPORTED_PROTOCOL = ["Purge", "Wait", "Stir", "ResetHandling"]
-
-    def extract_operations(element: ET.Element):
-        if element.tag not in ["Prep", "Reaction", "Workup", "Purification", "Procedure"]:
-            if element.tag not in TEMP_UNSUPPORTED_PROTOCOL:
-                flattened_operations.append(element)
-
-        for child in element:
-            extract_operations(child)
-
-    for child in procedure_elem:
-        extract_operations(child)
-
-    return flattened_operations
-
-
-def parse_xdl_content(xdl_content: str) -> tuple:
-    """解析XDL内容"""
-    try:
-        xdl_content_cleaned = "".join(c for c in xdl_content if c.isprintable())
-        root = ET.fromstring(xdl_content_cleaned)
-
-        synthesis_elem = root.find("Synthesis")
-        if synthesis_elem is None:
-            return None, None, None
-
-        # 解析硬件组件
-        hardware_elem = synthesis_elem.find("Hardware")
-        hardware = []
-        if hardware_elem is not None:
-            hardware = [{"id": c.get("id"), "type": c.get("type")} for c in hardware_elem.findall("Component")]
-
-        # 解析试剂
-        reagents_elem = synthesis_elem.find("Reagents")
-        reagents = []
-        if reagents_elem is not None:
-            reagents = [{"name": r.get("name"), "role": r.get("role", "")} for r in reagents_elem.findall("Reagent")]
-
-        # 解析程序
-        procedure_elem = synthesis_elem.find("Procedure")
-        if procedure_elem is None:
-            return None, None, None
-
-        flattened_operations = flatten_xdl_procedure(procedure_elem)
-        return hardware, reagents, flattened_operations
-
-    except ET.ParseError as e:
-        raise ValueError(f"Invalid XDL format: {e}")
-
-
-def convert_xdl_to_dict(xdl_content: str) -> Dict[str, Any]:
-    """
-    将XDL XML格式转换为标准的字典格式
-
-    Args:
-        xdl_content: XDL XML内容
-
-    Returns:
-        转换结果，包含步骤和器材信息
-    """
-    try:
-        hardware, reagents, flattened_operations = parse_xdl_content(xdl_content)
-        if hardware is None:
-            return {"error": "Failed to parse XDL content", "success": False}
-
-        # 将XDL元素转换为字典格式
-        steps_data = []
-        for elem in flattened_operations:
-            # 转换参数类型
-            parameters = {}
-            for key, val in elem.attrib.items():
-                converted_val = convert_to_type(val)
-                if converted_val is not None:
-                    parameters[key] = converted_val
-
-            step_dict = {
-                "operation": elem.tag,
-                "parameters": parameters,
-                "description": elem.get("purpose", f"Operation: {elem.tag}"),
-            }
-            steps_data.append(step_dict)
-
-        # 合并硬件和试剂为统一的labware_info格式
-        labware_data = []
-        labware_data.extend({"id": hw["id"], "type": "hardware", **hw} for hw in hardware)
-        labware_data.extend({"name": reagent["name"], "type": "reagent", **reagent} for reagent in reagents)
-
-        return {
-            "success": True,
-            "steps": steps_data,
-            "labware": labware_data,
-            "message": f"Successfully converted XDL to dict format. Found {len(steps_data)} steps and {len(labware_data)} labware items.",
-        }
-
-    except Exception as e:
-        error_msg = f"XDL conversion failed: {str(e)}"
-        logger.error(error_msg)
-        return {"error": error_msg, "success": False}


 def create_workflow(
--- a/unilabos/test/resources/init.py
+++ b/unilabos/test/resources/init.py
--- a/unilabos/test/resources/bioyond_materials_liquidhandling_1.json
+++ b/unilabos/test/resources/bioyond_materials_liquidhandling_1.json
--- a/unilabos/test/resources/bioyond_materials_liquidhandling_2.json
+++ b/unilabos/test/resources/bioyond_materials_liquidhandling_2.json
--- a/unilabos/test/resources/bioyond_materials_reaction.json
+++ b/unilabos/test/resources/bioyond_materials_reaction.json
--- a/unilabos/test/resources/test_bottle_carrier.py
+++ b/unilabos/test/resources/test_bottle_carrier.py
--- a/unilabos/test/resources/test_converter_bioyond.py
+++ b/unilabos/test/resources/test_converter_bioyond.py
--- a/unilabos/test/resources/test_itemized_carrier.py
+++ b/unilabos/test/resources/test_itemized_carrier.py
--- a/unilabos/test/resources/test_resourcetreeset.py
+++ b/unilabos/test/resources/test_resourcetreeset.py
--- a/unilabos/test/ros/init.py
+++ b/unilabos/test/ros/init.py
--- a/unilabos/test/ros/msgs/init.py
+++ b/unilabos/test/ros/msgs/init.py
--- a/unilabos/test/ros/msgs/test_basic.py
+++ b/unilabos/test/ros/msgs/test_basic.py
--- a/unilabos/test/ros/msgs/test_conversion.py
+++ b/unilabos/test/ros/msgs/test_conversion.py
--- a/unilabos/test/ros/msgs/test_mapping.py
+++ b/unilabos/test/ros/msgs/test_mapping.py
--- a/unilabos/test/ros/msgs/test_runner.py
+++ b/unilabos/test/ros/msgs/test_runner.py
--- a/unilabos/test/workflow/init.py
+++ b/unilabos/test/workflow/init.py
--- a/unilabos/test/workflow/example_bio.json
+++ b/unilabos/test/workflow/example_bio.json
--- a/unilabos/test/workflow/example_bio_graph.png
+++ b/unilabos/test/workflow/example_bio_graph.png
--- a/unilabos/test/workflow/example_prcxi.json
+++ b/unilabos/test/workflow/example_prcxi.json
--- a/unilabos/test/workflow/example_prcxi_graph.png
+++ b/unilabos/test/workflow/example_prcxi_graph.png
--- a/unilabos/test/workflow/example_prcxi_graph_20251022_1359.png
+++ b/unilabos/test/workflow/example_prcxi_graph_20251022_1359.png
--- a/test/workflow/merge_workflow.py
+++ b/test/workflow/merge_workflow.py
@@ -0,0 +1,35 @@
+import sys
+from datetime import datetime
+from pathlib import Path
+
+ROOT_DIR = Path(__file__).resolve().parents[2]
+if str(ROOT_DIR) not in sys.path:
+    sys.path.insert(0, str(ROOT_DIR))
+
+import pytest
+
+from unilabos.workflow.convert_from_json import (
+    convert_from_json,
+    normalize_steps as _normalize_steps,
+    normalize_labware as _normalize_labware,
+)
+from unilabos.workflow.common import draw_protocol_graph_with_ports
+
+
+@pytest.mark.parametrize(
+    "protocol_name",
+    [
+        "example_bio",
+        # "bioyond_materials_liquidhandling_1",
+        "example_prcxi",
+    ],
+)
+def test_build_protocol_graph(protocol_name):
+    data_path = Path(__file__).with_name(f"{protocol_name}.json")
+
+    graph = convert_from_json(data_path, workstation_name="PRCXi")
+
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M")
+    output_path = data_path.with_name(f"{protocol_name}_graph_{timestamp}.png")
+    draw_protocol_graph_with_ports(graph, str(output_path))
+    print(graph)
--- a/unilabos/app/main.py
+++ b/unilabos/app/main.py
@@ -20,6 +20,7 @@ if unilabos_dir not in sys.path:
 from unilabos.utils.banner_print import print_status, print_unilab_banner
 from unilabos.config.config import load_config, BasicConfig, HTTPConfig

+
 def load_config_from_file(config_path):
    if config_path is None:
        config_path = os.environ.get("UNILABOS_BASICCONFIG_CONFIG_PATH", None)
@@ -41,7 +42,7 @@ def convert_argv_dashes_to_underscores(args: argparse.ArgumentParser):
    for i, arg in enumerate(sys.argv):
        for option_string in option_strings:
            if arg.startswith(option_string):
-                new_arg = arg[:2] + arg[2:len(option_string)].replace("-", "_") + arg[len(option_string):]
+                new_arg = arg[:2] + arg[2 : len(option_string)].replace("-", "_") + arg[len(option_string) :]
                sys.argv[i] = new_arg
                break

@@ -49,6 +50,8 @@ def convert_argv_dashes_to_underscores(args: argparse.ArgumentParser):
 def parse_args():
    """解析命令行参数"""
    parser = argparse.ArgumentParser(description="Start Uni-Lab Edge server.")
+    subparsers = parser.add_subparsers(title="Valid subcommands", dest="command")
+
    parser.add_argument("-g", "--graph", help="Physical setup graph file path.")
    parser.add_argument("-c", "--controllers", default=None, help="Controllers config file path.")
    parser.add_argument(
@@ -153,6 +156,39 @@ def parse_args():
        default=False,
        help="Complete registry information",
    )
+    # workflow upload subcommand
+    workflow_parser = subparsers.add_parser(
+        "workflow_upload",
+        aliases=["wf"],
+        help="Upload workflow from xdl/json/python files",
+    )
+    workflow_parser.add_argument(
+        "-f",
+        "--workflow_file",
+        type=str,
+        required=True,
+        help="Path to the workflow file (JSON format)",
+    )
+    workflow_parser.add_argument(
+        "-n",
+        "--workflow_name",
+        type=str,
+        default=None,
+        help="Workflow name, if not provided will use the name from file or filename",
+    )
+    workflow_parser.add_argument(
+        "--tags",
+        type=str,
+        nargs="*",
+        default=[],
+        help="Tags for the workflow (space-separated)",
+    )
+    workflow_parser.add_argument(
+        "--published",
+        action="store_true",
+        default=False,
+        help="Whether to publish the workflow (default: False)",
+    )
    return parser


@@ -167,7 +203,6 @@ def main():
    if not args_dict.get("skip_env_check", False):
        from unilabos.utils.environment_check import check_environment

-        print_status("正在进行环境依赖检查...", "info")
        if not check_environment(auto_install=True):
            print_status("环境检查失败，程序退出", "error")
            os._exit(1)
@@ -239,9 +274,12 @@ def main():
    if args_dict.get("sk", ""):
        BasicConfig.sk = args_dict.get("sk", "")
        print_status("传入了sk参数，优先采用传入参数！", "info")
+    BasicConfig.working_dir = working_dir
+
+    workflow_upload = args_dict.get("command") in ("workflow_upload", "wf")

    # 使用远程资源启动
-    if args_dict["use_remote_resource"]:
+    if not workflow_upload and args_dict["use_remote_resource"]:
        print_status("使用远程资源启动", "info")
        from unilabos.app.web import http_client

@@ -254,7 +292,6 @@ def main():

    BasicConfig.port = args_dict["port"] if args_dict["port"] else BasicConfig.port
    BasicConfig.disable_browser = args_dict["disable_browser"] or BasicConfig.disable_browser
-    BasicConfig.working_dir = working_dir
    BasicConfig.is_host_mode = not args_dict.get("is_slave", False)
    BasicConfig.slave_no_host = args_dict.get("slave_no_host", False)
    BasicConfig.upload_registry = args_dict.get("upload_registry", False)
@@ -283,9 +320,31 @@ def main():

    # 注册表
    lab_registry = build_registry(
-        args_dict["registry_path"], args_dict.get("complete_registry", False), args_dict["upload_registry"]
+        args_dict["registry_path"], args_dict.get("complete_registry", False), BasicConfig.upload_registry
    )

+    if BasicConfig.upload_registry:
+        # 设备注册到服务端 - 需要 ak 和 sk
+        if BasicConfig.ak and BasicConfig.sk:
+            print_status("开始注册设备到服务端...", "info")
+            try:
+                register_devices_and_resources(lab_registry)
+                print_status("设备注册完成", "info")
+            except Exception as e:
+                print_status(f"设备注册失败: {e}", "error")
+        else:
+            print_status("未提供 ak 和 sk，跳过设备注册", "info")
+    else:
+        print_status("本次启动注册表不报送云端，如果您需要联网调试，请在启动命令增加--upload_registry", "warning")
+
+    # 处理 workflow_upload 子命令
+    if workflow_upload:
+        from unilabos.workflow.wf_utils import handle_workflow_upload_command
+
+        handle_workflow_upload_command(args_dict)
+        print_status("工作流上传完成，程序退出", "info")
+        os._exit(0)
+
    if not BasicConfig.ak or not BasicConfig.sk:
        print_status("后续运行必须拥有一个实验室，请前往 https://uni-lab.bohrium.com 注册实验室！", "warning")
        os._exit(1)
@@ -362,20 +421,6 @@ def main():
    args_dict["devices_config"] = resource_tree_set
    args_dict["graph"] = graph_res.physical_setup_graph

-    if BasicConfig.upload_registry:
-        # 设备注册到服务端 - 需要 ak 和 sk
-        if BasicConfig.ak and BasicConfig.sk:
-            print_status("开始注册设备到服务端...", "info")
-            try:
-                register_devices_and_resources(lab_registry)
-                print_status("设备注册完成", "info")
-            except Exception as e:
-                print_status(f"设备注册失败: {e}", "error")
-        else:
-            print_status("未提供 ak 和 sk，跳过设备注册", "info")
-    else:
-        print_status("本次启动注册表不报送云端，如果您需要联网调试，请在启动命令增加--upload_registry", "warning")
-
    if args_dict["controllers"] is not None:
        args_dict["controllers_config"] = yaml.safe_load(open(args_dict["controllers"], encoding="utf-8"))
    else:
@@ -390,6 +435,7 @@ def main():
        comm_client = get_communication_client()
        if "websocket" in args_dict["app_bridges"]:
            args_dict["bridges"].append(comm_client)
+
            def _exit(signum, frame):
                comm_client.stop()
                sys.exit(0)
@@ -431,16 +477,13 @@ def main():
                resource_visualization.start()
            except OSError as e:
                if "AMENT_PREFIX_PATH" in str(e):
-                    print_status(
-                        f"ROS 2环境未正确设置，跳过3D可视化启动。错误详情: {e}",
-                        "warning"
-                    )
+                    print_status(f"ROS 2环境未正确设置，跳过3D可视化启动。错误详情: {e}", "warning")
                    print_status(
                        "建议解决方案：\n"
                        "1. 激活Conda环境: conda activate unilab\n"
                        "2. 或使用 --backend simple 参数\n"
                        "3. 或使用 --visual disable 参数禁用可视化",
-                        "info"
+                        "info",
                    )
                else:
                    raise
--- a/unilabos/app/web/client.py
+++ b/unilabos/app/web/client.py
@@ -76,7 +76,8 @@ class HTTPClient:
            Dict[str, str]: 旧UUID到新UUID的映射关系 {old_uuid: new_uuid}
        """
        with open(os.path.join(BasicConfig.working_dir, "req_resource_tree_add.json"), "w", encoding="utf-8") as f:
-            f.write(json.dumps({"nodes": [x for xs in resources.dump() for x in xs], "mount_uuid": mount_uuid}, indent=4))
+            payload = {"nodes": [x for xs in resources.dump() for x in xs], "mount_uuid": mount_uuid}
+            f.write(json.dumps(payload, indent=4))
        # 从序列化数据中提取所有节点的UUID（保存旧UUID）
        old_uuids = {n.res_content.uuid: n for n in resources.all_nodes}
        if not self.initialized or first_add:
@@ -331,6 +332,67 @@ class HTTPClient:
                logger.error(f"响应内容: {response.text}")
        return None

+    def workflow_import(
+        self,
+        name: str,
+        workflow_uuid: str,
+        workflow_name: str,
+        nodes: List[Dict[str, Any]],
+        edges: List[Dict[str, Any]],
+        tags: Optional[List[str]] = None,
+        published: bool = False,
+    ) -> Dict[str, Any]:
+        """
+        导入工作流到服务器
+
+        Args:
+            name: 工作流名称（顶层）
+            workflow_uuid: 工作流UUID
+            workflow_name: 工作流名称（data内部）
+            nodes: 工作流节点列表
+            edges: 工作流边列表
+            tags: 工作流标签列表，默认为空列表
+            published: 是否发布工作流，默认为False
+
+        Returns:
+            Dict: API响应数据，包含 code 和 data (uuid, name)
+        """
+        # target_lab_uuid 暂时使用默认值，后续由后端根据 ak/sk 获取
+        payload = {
+            "target_lab_uuid": "28c38bb0-63f6-4352-b0d8-b5b8eb1766d5",
+            "name": name,
+            "data": {
+                "workflow_uuid": workflow_uuid,
+                "workflow_name": workflow_name,
+                "nodes": nodes,
+                "edges": edges,
+                "tags": tags if tags is not None else [],
+                "published": published,
+            },
+        }
+        # 保存请求到文件
+        with open(os.path.join(BasicConfig.working_dir, "req_workflow_upload.json"), "w", encoding="utf-8") as f:
+            f.write(json.dumps(payload, indent=4, ensure_ascii=False))
+
+        response = requests.post(
+            f"{self.remote_addr}/lab/workflow/owner/import",
+            json=payload,
+            headers={"Authorization": f"Lab {self.auth}"},
+            timeout=60,
+        )
+        # 保存响应到文件
+        with open(os.path.join(BasicConfig.working_dir, "res_workflow_upload.json"), "w", encoding="utf-8") as f:
+            f.write(f"{response.status_code}" + "\n" + response.text)
+
+        if response.status_code == 200:
+            res = response.json()
+            if "code" in res and res["code"] != 0:
+                logger.error(f"导入工作流失败: {response.text}")
+            return res
+        else:
+            logger.error(f"导入工作流失败: {response.status_code}, {response.text}")
+            return {"code": response.status_code, "message": response.text}
+

 # 创建默认客户端实例
 http_client = HTTPClient()
--- a/unilabos/app/ws_client.py
+++ b/unilabos/app/ws_client.py
@@ -438,7 +438,7 @@ class MessageProcessor:
                    self.connected = True
                    self.reconnect_count = 0

-                    logger.info(f"[MessageProcessor] Connected to {self.websocket_url}")
+                    logger.trace(f"[MessageProcessor] Connected to {self.websocket_url}")

                    # 启动发送协程
                    send_task = asyncio.create_task(self._send_handler())
@@ -503,7 +503,7 @@ class MessageProcessor:

    async def _send_handler(self):
        """处理发送队列中的消息"""
-        logger.debug("[MessageProcessor] Send handler started")
+        logger.trace("[MessageProcessor] Send handler started")

        try:
            while self.connected and self.websocket:
@@ -965,7 +965,7 @@ class QueueProcessor:

    def _run(self):
        """运行队列处理主循环"""
-        logger.debug("[QueueProcessor] Queue processor started")
+        logger.trace("[QueueProcessor] Queue processor started")

        while self.is_running:
            try:
@@ -1175,7 +1175,6 @@ class WebSocketClient(BaseCommunicationClient):
        else:
            url = f"{scheme}://{parsed.netloc}/api/v1/ws/schedule"

-        logger.debug(f"[WebSocketClient] URL: {url}")
        return url

    def start(self) -> None:
@@ -1188,13 +1187,11 @@ class WebSocketClient(BaseCommunicationClient):
            logger.error("[WebSocketClient] WebSocket URL not configured")
            return

-        logger.info(f"[WebSocketClient] Starting connection to {self.websocket_url}")
-
        # 启动两个核心线程
        self.message_processor.start()
        self.queue_processor.start()

-        logger.info("[WebSocketClient] All threads started")
+        logger.trace("[WebSocketClient] All threads started")

    def stop(self) -> None:
        """停止WebSocket客户端"""
--- a/unilabos/config/config.py
+++ b/unilabos/config/config.py
@@ -21,7 +21,8 @@ class BasicConfig:
    startup_json_path = None  # 填写绝对路径
    disable_browser = False  # 禁止浏览器自动打开
    port = 8002  # 本地HTTP服务
-    log_level: Literal['TRACE', 'DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'] = "DEBUG"  # 'TRACE', 'DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'
+    # 'TRACE', 'DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'
+    log_level: Literal["TRACE", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"] = "DEBUG"

    @classmethod
    def auth_secret(cls):
@@ -65,13 +66,14 @@ def _update_config_from_module(module):
                    if not attr.startswith("_"):
                        setattr(obj, attr, getattr(getattr(module, name), attr))

+
 def _update_config_from_env():
    prefix = "UNILABOS_"
    for env_key, env_value in os.environ.items():
        if not env_key.startswith(prefix):
            continue
        try:
-            key_path = env_key[len(prefix):]  # Remove UNILAB_ prefix
+            key_path = env_key[len(prefix) :]  # Remove UNILAB_ prefix
            class_field = key_path.upper().split("_", 1)
            if len(class_field) != 2:
                logger.warning(f"[ENV] 环境变量格式不正确：{env_key}")
--- a/unilabos/registry/devices/liquid_handler.yaml
+++ b/unilabos/registry/devices/liquid_handler.yaml
@@ -9333,7 +9333,34 @@ liquid_handler.prcxi:
          touch_tip: false
          use_channels:
          - 0
-        handles: {}
+        handles:
+          input:
+          - data_key: liquid
+            data_source: handle
+            data_type: resource
+            handler_key: sources
+            label: sources
+          - data_key: liquid
+            data_source: executor
+            data_type: resource
+            handler_key: targets
+            label: targets
+          - data_key: liquid
+            data_source: executor
+            data_type: resource
+            handler_key: tip_rack
+            label: tip_rack
+          output:
+          - data_key: liquid
+            data_source: handle
+            data_type: resource
+            handler_key: sources_out
+            label: sources
+          - data_key: liquid
+            data_source: executor
+            data_type: resource
+            handler_key: targets_out
+            label: targets
        placeholder_keys:
          sources: unilabos_resources
          targets: unilabos_resources
--- a/unilabos/registry/registry.py
+++ b/unilabos/registry/registry.py
@@ -222,7 +222,7 @@ class Registry:
        abs_path = Path(path).absolute()
        resource_path = abs_path / "resources"
        files = list(resource_path.glob("*/*.yaml"))
-        logger.debug(f"[UniLab Registry] resources: {resource_path.exists()}, total: {len(files)}")
+        logger.trace(f"[UniLab Registry] load resources? {resource_path.exists()}, total: {len(files)}")
        current_resource_number = len(self.resource_type_registry) + 1
        for i, file in enumerate(files):
            with open(file, encoding="utf-8", mode="r") as f:
--- a/unilabos/resources/graphio.py
+++ b/unilabos/resources/graphio.py
@@ -42,7 +42,7 @@ def canonicalize_nodes_data(
    Returns:
        ResourceTreeSet: 标准化后的资源树集合
    """
-    print_status(f"{len(nodes)} Resources loaded:", "info")
+    print_status(f"{len(nodes)} Resources loaded", "info")

    # 第一步：基本预处理（处理graphml的label字段）
    outer_host_node_id = None
--- a/unilabos/ros/nodes/resource_tracker.py
+++ b/unilabos/ros/nodes/resource_tracker.py
@@ -66,8 +66,8 @@ class ResourceDict(BaseModel):
    klass: str = Field(alias="class", description="Resource class name")
    pose: ResourceDictPosition = Field(description="Resource position", default_factory=ResourceDictPosition)
    config: Dict[str, Any] = Field(description="Resource configuration")
-    data: Dict[str, Any] = Field(description="Resource data")
-    extra: Dict[str, Any] = Field(description="Extra data")
+    data: Dict[str, Any] = Field(description="Resource data, eg: container liquid data")
+    extra: Dict[str, Any] = Field(description="Extra data, eg: slot index")

    @field_serializer("parent_uuid")
    def _serialize_parent(self, parent_uuid: Optional["ResourceDict"]):
--- a/unilabos/test/workflow/merge_workflow.py
+++ b/unilabos/test/workflow/merge_workflow.py
@@ -1,94 +0,0 @@
-import json
-import sys
-from datetime import datetime
-from pathlib import Path
-
-ROOT_DIR = Path(__file__).resolve().parents[2]
-if str(ROOT_DIR) not in sys.path:
-    sys.path.insert(0, str(ROOT_DIR))
-
-import pytest
-
-from scripts.workflow import build_protocol_graph, draw_protocol_graph, draw_protocol_graph_with_ports
-
-
-ROOT_DIR = Path(__file__).resolve().parents[2]
-if str(ROOT_DIR) not in sys.path:
-    sys.path.insert(0, str(ROOT_DIR))
-
-
-def _normalize_steps(data):
-    normalized = []
-    for step in data:
-        action = step.get("action") or step.get("operation")
-        if not action:
-            continue
-        raw_params = step.get("parameters") or step.get("action_args") or {}
-        params = dict(raw_params)
-
-        if "source" in raw_params and "sources" not in raw_params:
-            params["sources"] = raw_params["source"]
-        if "target" in raw_params and "targets" not in raw_params:
-            params["targets"] = raw_params["target"]
-
-        description = step.get("description") or step.get("purpose")
-        step_dict = {"action": action, "parameters": params}
-        if description:
-            step_dict["description"] = description
-        normalized.append(step_dict)
-    return normalized
-
-
-def _normalize_labware(data):
-    labware = {}
-    for item in data:
-        reagent_name = item.get("reagent_name")
-        key = reagent_name or item.get("material_name") or item.get("name")
-        if not key:
-            continue
-        key = str(key)
-        idx = 1
-        original_key = key
-        while key in labware:
-            idx += 1
-            key = f"{original_key}_{idx}"
-
-        labware[key] = {
-            "slot": item.get("positions") or item.get("slot"),
-            "labware": item.get("material_name") or item.get("labware"),
-            "well": item.get("well", []),
-            "type": item.get("type", "reagent"),
-            "role": item.get("role", ""),
-            "name": key,
-        }
-    return labware
-
-
-@pytest.mark.parametrize("protocol_name", [
-    "example_bio",
-    # "bioyond_materials_liquidhandling_1",
-    "example_prcxi",
-])
-def test_build_protocol_graph(protocol_name):
-    data_path = Path(__file__).with_name(f"{protocol_name}.json")
-    with data_path.open("r", encoding="utf-8") as fp:
-        d = json.load(fp)
-
-    if "workflow" in d and "reagent" in d:
-        protocol_steps = d["workflow"]
-        labware_info = d["reagent"]
-    elif "steps_info" in d and "labware_info" in d:
-        protocol_steps = _normalize_steps(d["steps_info"])
-        labware_info = _normalize_labware(d["labware_info"])
-    else:
-        raise ValueError("Unsupported protocol format")
-
-    graph = build_protocol_graph(
-        labware_info=labware_info,
-        protocol_steps=protocol_steps,
-        workstation_name="PRCXi",
-    )
-    timestamp = datetime.now().strftime("%Y%m%d_%H%M")
-    output_path = data_path.with_name(f"{protocol_name}_graph_{timestamp}.png")
-    draw_protocol_graph_with_ports(graph, str(output_path))
-    print(graph)
--- a/unilabos/workflow/init.py
+++ b/unilabos/workflow/init.py
--- a/unilabos/workflow/common.py
+++ b/unilabos/workflow/common.py
@@ -0,0 +1,547 @@
+import re
+import uuid
+
+import networkx as nx
+from networkx.drawing.nx_agraph import to_agraph
+import matplotlib.pyplot as plt
+from typing import Dict, List, Any, Tuple, Optional
+
+Json = Dict[str, Any]
+
+# ---------------- Graph ----------------
+
+
+class WorkflowGraph:
+    """简单的有向图实现：使用 params 单层参数；inputs 内含连线；支持 node-link 导出"""
+
+    def __init__(self):
+        self.nodes: Dict[str, Dict[str, Any]] = {}
+        self.edges: List[Dict[str, Any]] = []
+
+    def add_node(self, node_id: str, **attrs):
+        self.nodes[node_id] = attrs
+
+    def add_edge(self, source: str, target: str, **attrs):
+        # 将 source_port/target_port 映射为服务端期望的 source_handle_key/target_handle_key
+        source_handle_key = attrs.pop("source_port", "") or attrs.pop("source_handle_key", "")
+        target_handle_key = attrs.pop("target_port", "") or attrs.pop("target_handle_key", "")
+
+        edge = {
+            "source": source,
+            "target": target,
+            "source_node_uuid": source,
+            "target_node_uuid": target,
+            "source_handle_key": source_handle_key,
+            "source_handle_io": attrs.pop("source_handle_io", "source"),
+            "target_handle_key": target_handle_key,
+            "target_handle_io": attrs.pop("target_handle_io", "target"),
+            **attrs,
+        }
+        self.edges.append(edge)
+
+    def _materialize_wiring_into_inputs(
+        self,
+        obj: Any,
+        inputs: Dict[str, Any],
+        variable_sources: Dict[str, Dict[str, Any]],
+        target_node_id: str,
+        base_path: List[str],
+    ):
+        has_var = False
+
+        def walk(node: Any, path: List[str]):
+            nonlocal has_var
+            if isinstance(node, dict):
+                if "__var__" in node:
+                    has_var = True
+                    varname = node["__var__"]
+                    placeholder = f"${{{varname}}}"
+                    src = variable_sources.get(varname)
+                    if src:
+                        key = ".".join(path)  # e.g. "params.foo.bar.0"
+                        inputs[key] = {"node": src["node_id"], "output": src.get("output_name", "result")}
+                        self.add_edge(
+                            str(src["node_id"]),
+                            target_node_id,
+                            source_handle_io=src.get("output_name", "result"),
+                            target_handle_io=key,
+                        )
+                    return placeholder
+                return {k: walk(v, path + [k]) for k, v in node.items()}
+            if isinstance(node, list):
+                return [walk(v, path + [str(i)]) for i, v in enumerate(node)]
+            return node
+
+        replaced = walk(obj, base_path[:])
+        return replaced, has_var
+
+    def add_workflow_node(
+        self,
+        node_id: int,
+        *,
+        device_key: Optional[str] = None,  # 实例名，如 "ser"
+        resource_name: Optional[str] = None,  # registry key（原 device_class）
+        module: Optional[str] = None,
+        template_name: Optional[str] = None,  # 动作/模板名（原 action_key）
+        params: Dict[str, Any],
+        variable_sources: Dict[str, Dict[str, Any]],
+        add_ready_if_no_vars: bool = True,
+        prev_node_id: Optional[int] = None,
+        **extra_attrs,
+    ) -> None:
+        """添加工作流节点：params 单层；自动变量连线与 ready 串联；支持附加属性"""
+        node_id_str = str(node_id)
+        inputs: Dict[str, Any] = {}
+
+        params, has_var = self._materialize_wiring_into_inputs(
+            params, inputs, variable_sources, node_id_str, base_path=["params"]
+        )
+
+        if add_ready_if_no_vars and not has_var:
+            last_id = str(prev_node_id) if prev_node_id is not None else "-1"
+            inputs["ready"] = {"node": int(last_id), "output": "ready"}
+            self.add_edge(last_id, node_id_str, source_handle_io="ready", target_handle_io="ready")
+
+        node_obj = {
+            "device_key": device_key,
+            "resource_name": resource_name,  # ✅ 新名字
+            "module": module,
+            "template_name": template_name,  # ✅ 新名字
+            "params": params,
+            "inputs": inputs,
+        }
+        node_obj.update(extra_attrs or {})
+        self.add_node(node_id_str, parameters=node_obj)
+
+    # 顺序工作流导出（连线在 inputs，不返回 edges）
+    def to_dict(self) -> List[Dict[str, Any]]:
+        result = []
+        for node_id, attrs in self.nodes.items():
+            node = {"uuid": node_id}
+            params = dict(attrs.get("parameters", {}) or {})
+            flat = {k: v for k, v in attrs.items() if k != "parameters"}
+            flat.update(params)
+            node.update(flat)
+            result.append(node)
+        return sorted(result, key=lambda n: int(n["uuid"]) if str(n["uuid"]).isdigit() else n["uuid"])
+
+    # node-link 导出（含 edges）
+    def to_node_link_dict(self) -> Dict[str, Any]:
+        nodes_list = []
+        for node_id, attrs in self.nodes.items():
+            node_attrs = attrs.copy()
+            params = node_attrs.pop("parameters", {}) or {}
+            node_attrs.update(params)
+            nodes_list.append({"uuid": node_id, **node_attrs})
+        return {
+            "directed": True,
+            "multigraph": False,
+            "graph": {},
+            "nodes": nodes_list,
+            "edges": self.edges,
+            "links": self.edges,
+        }
+
+
+def refactor_data(
+    data: List[Dict[str, Any]],
+    action_resource_mapping: Optional[Dict[str, str]] = None,
+) -> List[Dict[str, Any]]:
+    """统一的数据重构函数，根据操作类型自动选择模板
+
+    Args:
+        data: 原始步骤数据列表
+        action_resource_mapping: action 到 resource_name 的映射字典，可选
+    """
+    refactored_data = []
+
+    # 定义操作映射，包含生物实验和有机化学的所有操作
+    OPERATION_MAPPING = {
+        # 生物实验操作
+        "transfer_liquid": "transfer_liquid",
+        "transfer": "transfer",
+        "incubation": "incubation",
+        "move_labware": "move_labware",
+        "oscillation": "oscillation",
+        # 有机化学操作
+        "HeatChillToTemp": "HeatChillProtocol",
+        "StopHeatChill": "HeatChillStopProtocol",
+        "StartHeatChill": "HeatChillStartProtocol",
+        "HeatChill": "HeatChillProtocol",
+        "Dissolve": "DissolveProtocol",
+        "Transfer": "TransferProtocol",
+        "Evaporate": "EvaporateProtocol",
+        "Recrystallize": "RecrystallizeProtocol",
+        "Filter": "FilterProtocol",
+        "Dry": "DryProtocol",
+        "Add": "AddProtocol",
+    }
+
+    UNSUPPORTED_OPERATIONS = ["Purge", "Wait", "Stir", "ResetHandling"]
+
+    for step in data:
+        operation = step.get("action")
+        if not operation or operation in UNSUPPORTED_OPERATIONS:
+            continue
+
+        # 处理重复操作
+        if operation == "Repeat":
+            times = step.get("times", step.get("parameters", {}).get("times", 1))
+            sub_steps = step.get("steps", step.get("parameters", {}).get("steps", []))
+            for i in range(int(times)):
+                sub_data = refactor_data(sub_steps, action_resource_mapping)
+                refactored_data.extend(sub_data)
+            continue
+
+        # 获取模板名称
+        template_name = OPERATION_MAPPING.get(operation)
+        if not template_name:
+            # 自动推断模板类型
+            if operation.lower() in ["transfer", "incubation", "move_labware", "oscillation"]:
+                template_name = f"biomek-{operation}"
+            else:
+                template_name = f"{operation}Protocol"
+
+        # 获取 resource_name
+        resource_name = f"device.{operation.lower()}"
+        if action_resource_mapping:
+            resource_name = action_resource_mapping.get(operation, resource_name)
+
+        # 获取步骤编号，生成 name 字段
+        step_number = step.get("step_number")
+        name = f"Step {step_number}" if step_number is not None else None
+
+        # 创建步骤数据
+        step_data = {
+            "template_name": template_name,
+            "resource_name": resource_name,
+            "description": step.get("description", step.get("purpose", f"{operation} operation")),
+            "lab_node_type": "Device",
+            "param": step.get("parameters", step.get("action_args", {})),
+            "footer": f"{template_name}-{resource_name}",
+        }
+        if name:
+            step_data["name"] = name
+        refactored_data.append(step_data)
+
+    return refactored_data
+
+
+def build_protocol_graph(
+    labware_info: List[Dict[str, Any]],
+    protocol_steps: List[Dict[str, Any]],
+    workstation_name: str,
+    action_resource_mapping: Optional[Dict[str, str]] = None,
+) -> WorkflowGraph:
+    """统一的协议图构建函数，根据设备类型自动选择构建逻辑
+
+    Args:
+        labware_info: labware 信息字典
+        protocol_steps: 协议步骤列表
+        workstation_name: 工作站名称
+        action_resource_mapping: action 到 resource_name 的映射字典，可选
+    """
+    G = WorkflowGraph()
+    resource_last_writer = {}
+
+    protocol_steps = refactor_data(protocol_steps, action_resource_mapping)
+    # 有机化学&移液站协议图构建
+    WORKSTATION_ID = workstation_name
+
+    # 为所有labware创建资源节点
+    res_index = 0
+    for labware_id, item in labware_info.items():
+        # item_id = item.get("id") or item.get("name", f"item_{uuid.uuid4()}")
+        node_id = str(uuid.uuid4())
+
+        # 判断节点类型
+        if "Rack" in str(labware_id) or "Tip" in str(labware_id):
+            lab_node_type = "Labware"
+            description = f"Prepare Labware: {labware_id}"
+            liquid_type = []
+            liquid_volume = []
+        elif item.get("type") == "hardware" or "reactor" in str(labware_id).lower():
+            if "reactor" not in str(labware_id).lower():
+                continue
+            lab_node_type = "Sample"
+            description = f"Prepare Reactor: {labware_id}"
+            liquid_type = []
+            liquid_volume = []
+        else:
+            lab_node_type = "Reagent"
+            description = f"Add Reagent to Flask: {labware_id}"
+            liquid_type = [labware_id]
+            liquid_volume = [1e5]
+
+        res_index += 1
+        G.add_node(
+            node_id,
+            template_name="create_resource",
+            resource_name="host_node",
+            name=f"Res {res_index}",
+            description=description,
+            lab_node_type=lab_node_type,
+            footer="create_resource-host_node",
+            param={
+                "res_id": labware_id,
+                "device_id": WORKSTATION_ID,
+                "class_name": "container",
+                "parent": WORKSTATION_ID,
+                "bind_locations": {"x": 0.0, "y": 0.0, "z": 0.0},
+                "liquid_input_slot": [-1],
+                "liquid_type": liquid_type,
+                "liquid_volume": liquid_volume,
+                "slot_on_deck": "",
+            },
+        )
+        resource_last_writer[labware_id] = f"{node_id}:labware"
+
+    last_control_node_id = None
+
+    # 处理协议步骤
+    for step in protocol_steps:
+        node_id = str(uuid.uuid4())
+        G.add_node(node_id, **step)
+
+        # 控制流
+        if last_control_node_id is not None:
+            G.add_edge(last_control_node_id, node_id, source_port="ready", target_port="ready")
+        last_control_node_id = node_id
+
+        # 物料流
+        params = step.get("param", {})
+        input_resources_possible_names = [
+            "vessel",
+            "to_vessel",
+            "from_vessel",
+            "reagent",
+            "solvent",
+            "compound",
+            "sources",
+            "targets",
+        ]
+
+        for target_port in input_resources_possible_names:
+            resource_name = params.get(target_port)
+            if resource_name and resource_name in resource_last_writer:
+                source_node, source_port = resource_last_writer[resource_name].split(":")
+                G.add_edge(source_node, node_id, source_port=source_port, target_port=target_port)
+
+        output_resources = {
+            "vessel_out": params.get("vessel"),
+            "from_vessel_out": params.get("from_vessel"),
+            "to_vessel_out": params.get("to_vessel"),
+            "filtrate_out": params.get("filtrate_vessel"),
+            "reagent": params.get("reagent"),
+            "solvent": params.get("solvent"),
+            "compound": params.get("compound"),
+            "sources_out": params.get("sources"),
+            "targets_out": params.get("targets"),
+        }
+
+        for source_port, resource_name in output_resources.items():
+            if resource_name:
+                resource_last_writer[resource_name] = f"{node_id}:{source_port}"
+
+    return G
+
+
+def draw_protocol_graph(protocol_graph: WorkflowGraph, output_path: str):
+    """
+    (辅助功能) 使用 networkx 和 matplotlib 绘制协议工作流图，用于可视化。
+    """
+    if not protocol_graph:
+        print("Cannot draw graph: Graph object is empty.")
+        return
+
+    G = nx.DiGraph()
+
+    for node_id, attrs in protocol_graph.nodes.items():
+        label = attrs.get("description", attrs.get("template_name", node_id[:8]))
+        G.add_node(node_id, label=label, **attrs)
+
+    for edge in protocol_graph.edges:
+        G.add_edge(edge["source"], edge["target"])
+
+    plt.figure(figsize=(20, 15))
+    try:
+        pos = nx.nx_agraph.graphviz_layout(G, prog="dot")
+    except Exception:
+        pos = nx.shell_layout(G)  # Fallback layout
+
+    node_labels = {node: data["label"] for node, data in G.nodes(data=True)}
+    nx.draw(
+        G,
+        pos,
+        with_labels=False,
+        node_size=2500,
+        node_color="skyblue",
+        node_shape="o",
+        edge_color="gray",
+        width=1.5,
+        arrowsize=15,
+    )
+    nx.draw_networkx_labels(G, pos, labels=node_labels, font_size=8, font_weight="bold")
+
+    plt.title("Chemical Protocol Workflow Graph", size=15)
+    plt.savefig(output_path, dpi=300, bbox_inches="tight")
+    plt.close()
+    print(f"  - Visualization saved to '{output_path}'")
+
+
+COMPASS = {"n", "e", "s", "w", "ne", "nw", "se", "sw", "c"}
+
+
+def _is_compass(port: str) -> bool:
+    return isinstance(port, str) and port.lower() in COMPASS
+
+
+def draw_protocol_graph_with_ports(protocol_graph, output_path: str, rankdir: str = "LR"):
+    """
+    使用 Graphviz 端口语法绘制协议工作流图。
+    - 若边上的 source_port/target_port 是 compass（n/e/s/w/...），直接用 compass。
+    - 否则自动为节点创建 record 形状并定义命名端口 <portname>。
+    最终由 PyGraphviz 渲染并输出到 output_path（后缀决定格式，如 .png/.svg/.pdf）。
+    """
+    if not protocol_graph:
+        print("Cannot draw graph: Graph object is empty.")
+        return
+
+    # 1) 先用 networkx 搭建有向图，保留端口属性
+    G = nx.DiGraph()
+    for node_id, attrs in protocol_graph.nodes.items():
+        label = attrs.get("description", attrs.get("template_name", node_id[:8]))
+        # 保留一个干净的“中心标签”，用于放在 record 的中间槽
+        G.add_node(node_id, _core_label=str(label), **{k: v for k, v in attrs.items() if k not in ("label",)})
+
+    edges_data = []
+    in_ports_by_node = {}  # 收集命名输入端口
+    out_ports_by_node = {}  # 收集命名输出端口
+
+    for edge in protocol_graph.edges:
+        u = edge["source"]
+        v = edge["target"]
+        sp = edge.get("source_handle_key") or edge.get("source_port")
+        tp = edge.get("target_handle_key") or edge.get("target_port")
+
+        # 记录到图里（保留原始端口信息）
+        G.add_edge(u, v, source_handle_key=sp, target_handle_key=tp)
+        edges_data.append((u, v, sp, tp))
+
+        # 如果不是 compass，就按“命名端口”先归类，等会儿给节点造 record
+        if sp and not _is_compass(sp):
+            out_ports_by_node.setdefault(u, set()).add(str(sp))
+        if tp and not _is_compass(tp):
+            in_ports_by_node.setdefault(v, set()).add(str(tp))
+
+    # 2) 转为 AGraph，使用 Graphviz 渲染
+    A = to_agraph(G)
+    A.graph_attr.update(rankdir=rankdir, splines="true", concentrate="false", fontsize="10")
+    A.node_attr.update(
+        shape="box", style="rounded,filled", fillcolor="lightyellow", color="#999999", fontname="Helvetica"
+    )
+    A.edge_attr.update(arrowsize="0.8", color="#666666")
+
+    # 3) 为需要命名端口的节点设置 record 形状与 label
+    #    左列 = 输入端口；中间 = 核心标签；右列 = 输出端口
+    for n in A.nodes():
+        node = A.get_node(n)
+        core = G.nodes[n].get("_core_label", n)
+
+        in_ports = sorted(in_ports_by_node.get(n, []))
+        out_ports = sorted(out_ports_by_node.get(n, []))
+
+        # 如果该节点涉及命名端口，则用 record；否则保留原 box
+        if in_ports or out_ports:
+
+            def port_fields(ports):
+                if not ports:
+                    return " "  # 必须留一个空槽占位
+                # 每个端口一个小格子，<p> name
+                return "|".join(f"<{re.sub(r'[^A-Za-z0-9_:.|-]', '_', p)}> {p}" for p in ports)
+
+            left = port_fields(in_ports)
+            right = port_fields(out_ports)
+
+            # 三栏：左(入) | 中(节点名) | 右(出)
+            record_label = f"{{ {left} | {core} | {right} }}"
+            node.attr.update(shape="record", label=record_label)
+        else:
+            # 没有命名端口：普通盒子，显示核心标签
+            node.attr.update(label=str(core))
+
+    # 4) 给边设置 headport / tailport
+    #    - 若端口为 compass：直接用 compass（e.g., headport="e"）
+    #    - 若端口为命名端口：使用在 record 中定义的 <port> 名（同名即可）
+    for u, v, sp, tp in edges_data:
+        e = A.get_edge(u, v)
+
+        # Graphviz 属性：tail 是源，head 是目标
+        if sp:
+            if _is_compass(sp):
+                e.attr["tailport"] = sp.lower()
+            else:
+                # 与 record label 中 <port> 名一致；特殊字符已在 label 中做了清洗
+                e.attr["tailport"] = re.sub(r"[^A-Za-z0-9_:.|-]", "_", str(sp))
+
+        if tp:
+            if _is_compass(tp):
+                e.attr["headport"] = tp.lower()
+            else:
+                e.attr["headport"] = re.sub(r"[^A-Za-z0-9_:.|-]", "_", str(tp))
+
+        # 可选：若想让边更贴边缘，可设置 constraint/spline 等
+        # e.attr["arrowhead"] = "vee"
+
+    # 5) 输出
+    A.draw(output_path, prog="dot")
+    print(f"  - Port-aware workflow rendered to '{output_path}'")
+
+
+# ---------------- Registry Adapter ----------------
+
+
+class RegistryAdapter:
+    """根据 module 的类名（冒号右侧）反查 registry 的 resource_name（原 device_class），并抽取参数顺序"""
+
+    def __init__(self, device_registry: Dict[str, Any]):
+        self.device_registry = device_registry or {}
+        self.module_class_to_resource = self._build_module_class_index()
+
+    def _build_module_class_index(self) -> Dict[str, str]:
+        idx = {}
+        for resource_name, info in self.device_registry.items():
+            module = info.get("module")
+            if isinstance(module, str) and ":" in module:
+                cls = module.split(":")[-1]
+                idx[cls] = resource_name
+                idx[cls.lower()] = resource_name
+        return idx
+
+    def resolve_resource_by_classname(self, class_name: str) -> Optional[str]:
+        if not class_name:
+            return None
+        return self.module_class_to_resource.get(class_name) or self.module_class_to_resource.get(class_name.lower())
+
+    def get_device_module(self, resource_name: Optional[str]) -> Optional[str]:
+        if not resource_name:
+            return None
+        return self.device_registry.get(resource_name, {}).get("module")
+
+    def get_actions(self, resource_name: Optional[str]) -> Dict[str, Any]:
+        if not resource_name:
+            return {}
+        return (self.device_registry.get(resource_name, {}).get("class", {}).get("action_value_mappings", {})) or {}
+
+    def get_action_schema(self, resource_name: Optional[str], template_name: str) -> Optional[Json]:
+        return (self.get_actions(resource_name).get(template_name) or {}).get("schema")
+
+    def get_action_goal_default(self, resource_name: Optional[str], template_name: str) -> Json:
+        return (self.get_actions(resource_name).get(template_name) or {}).get("goal_default", {}) or {}
+
+    def get_action_input_keys(self, resource_name: Optional[str], template_name: str) -> List[str]:
+        schema = self.get_action_schema(resource_name, template_name) or {}
+        goal = (schema.get("properties") or {}).get("goal") or {}
+        props = goal.get("properties") or {}
+        required = goal.get("required") or []
+        return list(dict.fromkeys(required + list(props.keys())))
--- a/unilabos/workflow/convert_from_json.py
+++ b/unilabos/workflow/convert_from_json.py
@@ -0,0 +1,356 @@
+"""
+JSON 工作流转换模块
+
+提供从多种 JSON 格式转换为统一工作流格式的功能。
+支持的格式：
+1. workflow/reagent 格式
+2. steps_info/labware_info 格式
+"""
+
+import json
+from os import PathLike
+from pathlib import Path
+from typing import Any, Dict, List, Optional, Set, Tuple, Union
+
+from unilabos.workflow.common import WorkflowGraph, build_protocol_graph
+from unilabos.registry.registry import lab_registry
+
+
+def get_action_handles(resource_name: str, template_name: str) -> Dict[str, List[str]]:
+    """
+    从 registry 获取指定设备和动作的 handles 配置
+
+    Args:
+        resource_name: 设备资源名称，如 "liquid_handler.prcxi"
+        template_name: 动作模板名称，如 "transfer_liquid"
+
+    Returns:
+        包含 source 和 target handler_keys 的字典:
+        {"source": ["sources_out", "targets_out", ...], "target": ["sources", "targets", ...]}
+    """
+    result = {"source": [], "target": []}
+
+    device_info = lab_registry.device_type_registry.get(resource_name, {})
+    if not device_info:
+        return result
+
+    action_mappings = device_info.get("class", {}).get("action_value_mappings", {})
+    action_config = action_mappings.get(template_name, {})
+    handles = action_config.get("handles", {})
+
+    if isinstance(handles, dict):
+        # 处理 input handles (作为 target)
+        for handle in handles.get("input", []):
+            handler_key = handle.get("handler_key", "")
+            if handler_key:
+                result["source"].append(handler_key)
+        # 处理 output handles (作为 source)
+        for handle in handles.get("output", []):
+            handler_key = handle.get("handler_key", "")
+            if handler_key:
+                result["target"].append(handler_key)
+
+    return result
+
+
+def validate_workflow_handles(graph: WorkflowGraph) -> Tuple[bool, List[str]]:
+    """
+    校验工作流图中所有边的句柄配置是否正确
+
+    Args:
+        graph: 工作流图对象
+
+    Returns:
+        (is_valid, errors): 是否有效，错误信息列表
+    """
+    errors = []
+    nodes = graph.nodes
+
+    for edge in graph.edges:
+        left_uuid = edge.get("source")
+        right_uuid = edge.get("target")
+        # target_handle_key是target, right的输入节点（入节点）
+        # source_handle_key是source, left的输出节点（出节点）
+        right_source_conn_key = edge.get("target_handle_key", "")
+        left_target_conn_key = edge.get("source_handle_key", "")
+
+        # 获取源节点和目标节点信息
+        left_node = nodes.get(left_uuid, {})
+        right_node = nodes.get(right_uuid, {})
+
+        left_res_name = left_node.get("resource_name", "")
+        left_template_name = left_node.get("template_name", "")
+        right_res_name = right_node.get("resource_name", "")
+        right_template_name = right_node.get("template_name", "")
+
+        # 获取源节点的 output handles
+        left_node_handles = get_action_handles(left_res_name, left_template_name)
+        target_valid_keys = left_node_handles.get("target", [])
+        target_valid_keys.append("ready")
+
+        # 获取目标节点的 input handles
+        right_node_handles = get_action_handles(right_res_name, right_template_name)
+        source_valid_keys = right_node_handles.get("source", [])
+        source_valid_keys.append("ready")
+
+        # 如果节点配置了 output handles，则 source_port 必须有效
+        if not right_source_conn_key:
+            node_name = left_node.get("name", left_uuid[:8])
+            errors.append(f"源节点 '{node_name}' 的 source_handle_key 为空，" f"应设置为: {source_valid_keys}")
+        elif right_source_conn_key not in source_valid_keys:
+            node_name = left_node.get("name", left_uuid[:8])
+            errors.append(
+                f"源节点 '{node_name}' 的 source 端点 '{right_source_conn_key}' 不存在，" f"支持的端点: {source_valid_keys}"
+            )
+
+        # 如果节点配置了 input handles，则 target_port 必须有效
+        if not left_target_conn_key:
+            node_name = right_node.get("name", right_uuid[:8])
+            errors.append(f"目标节点 '{node_name}' 的 target_handle_key 为空，" f"应设置为: {target_valid_keys}")
+        elif left_target_conn_key not in target_valid_keys:
+            node_name = right_node.get("name", right_uuid[:8])
+            errors.append(
+                f"目标节点 '{node_name}' 的 target 端点 '{left_target_conn_key}' 不存在，"
+                f"支持的端点: {target_valid_keys}"
+            )
+
+    return len(errors) == 0, errors
+
+
+# action 到 resource_name 的映射
+ACTION_RESOURCE_MAPPING: Dict[str, str] = {
+    # 生物实验操作
+    "transfer_liquid": "liquid_handler.prcxi",
+    "transfer": "liquid_handler.prcxi",
+    "incubation": "incubator.prcxi",
+    "move_labware": "labware_mover.prcxi",
+    "oscillation": "shaker.prcxi",
+    # 有机化学操作
+    "HeatChillToTemp": "heatchill.chemputer",
+    "StopHeatChill": "heatchill.chemputer",
+    "StartHeatChill": "heatchill.chemputer",
+    "HeatChill": "heatchill.chemputer",
+    "Dissolve": "stirrer.chemputer",
+    "Transfer": "liquid_handler.chemputer",
+    "Evaporate": "rotavap.chemputer",
+    "Recrystallize": "reactor.chemputer",
+    "Filter": "filter.chemputer",
+    "Dry": "dryer.chemputer",
+    "Add": "liquid_handler.chemputer",
+}
+
+
+def normalize_steps(data: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+    """
+    将不同格式的步骤数据规范化为统一格式
+
+    支持的输入格式：
+    - action + parameters
+    - action + action_args
+    - operation + parameters
+
+    Args:
+        data: 原始步骤数据列表
+
+    Returns:
+        规范化后的步骤列表，格式为 [{"action": str, "parameters": dict, "description": str?, "step_number": int?}, ...]
+    """
+    normalized = []
+    for idx, step in enumerate(data):
+        # 获取动作名称（支持 action 或 operation 字段）
+        action = step.get("action") or step.get("operation")
+        if not action:
+            continue
+
+        # 获取参数（支持 parameters 或 action_args 字段）
+        raw_params = step.get("parameters") or step.get("action_args") or {}
+        params = dict(raw_params)
+
+        # 规范化 source/target -> sources/targets
+        if "source" in raw_params and "sources" not in raw_params:
+            params["sources"] = raw_params["source"]
+        if "target" in raw_params and "targets" not in raw_params:
+            params["targets"] = raw_params["target"]
+
+        # 获取描述（支持 description 或 purpose 字段）
+        description = step.get("description") or step.get("purpose")
+
+        # 获取步骤编号（优先使用原始数据中的 step_number，否则使用索引+1）
+        step_number = step.get("step_number", idx + 1)
+
+        step_dict = {"action": action, "parameters": params, "step_number": step_number}
+        if description:
+            step_dict["description"] = description
+
+        normalized.append(step_dict)
+
+    return normalized
+
+
+def normalize_labware(data: List[Dict[str, Any]]) -> Dict[str, Dict[str, Any]]:
+    """
+    将不同格式的 labware 数据规范化为统一的字典格式
+
+    支持的输入格式：
+    - reagent_name + material_name + positions
+    - name + labware + slot
+
+    Args:
+        data: 原始 labware 数据列表
+
+    Returns:
+        规范化后的 labware 字典，格式为 {name: {"slot": int, "labware": str, "well": list, "type": str, "role": str, "name": str}, ...}
+    """
+    labware = {}
+    for item in data:
+        # 获取 key 名称（优先使用 reagent_name，其次是 material_name 或 name）
+        reagent_name = item.get("reagent_name")
+        key = reagent_name or item.get("material_name") or item.get("name")
+        if not key:
+            continue
+
+        key = str(key)
+
+        # 处理重复 key，自动添加后缀
+        idx = 1
+        original_key = key
+        while key in labware:
+            idx += 1
+            key = f"{original_key}_{idx}"
+
+        labware[key] = {
+            "slot": item.get("positions") or item.get("slot"),
+            "labware": item.get("material_name") or item.get("labware"),
+            "well": item.get("well", []),
+            "type": item.get("type", "reagent"),
+            "role": item.get("role", ""),
+            "name": key,
+        }
+
+    return labware
+
+
+def convert_from_json(
+    data: Union[str, PathLike, Dict[str, Any]],
+    workstation_name: str = "PRCXi",
+    validate: bool = True,
+) -> WorkflowGraph:
+    """
+    从 JSON 数据或文件转换为 WorkflowGraph
+
+    支持的 JSON 格式：
+    1. {"workflow": [...], "reagent": {...}} - 直接格式
+    2. {"steps_info": [...], "labware_info": [...]} - 需要规范化的格式
+
+    Args:
+        data: JSON 文件路径、字典数据、或 JSON 字符串
+        workstation_name: 工作站名称，默认 "PRCXi"
+        validate: 是否校验句柄配置，默认 True
+
+    Returns:
+        WorkflowGraph: 构建好的工作流图
+
+    Raises:
+        ValueError: 不支持的 JSON 格式 或 句柄校验失败
+        FileNotFoundError: 文件不存在
+        json.JSONDecodeError: JSON 解析失败
+    """
+    # 处理输入数据
+    if isinstance(data, (str, PathLike)):
+        path = Path(data)
+        if path.exists():
+            with path.open("r", encoding="utf-8") as fp:
+                json_data = json.load(fp)
+        elif isinstance(data, str):
+            # 尝试作为 JSON 字符串解析
+            json_data = json.loads(data)
+        else:
+            raise FileNotFoundError(f"文件不存在: {data}")
+    elif isinstance(data, dict):
+        json_data = data
+    else:
+        raise TypeError(f"不支持的数据类型: {type(data)}")
+
+    # 根据格式解析数据
+    if "workflow" in json_data and "reagent" in json_data:
+        # 格式1: workflow/reagent（已经是规范格式）
+        protocol_steps = json_data["workflow"]
+        labware_info = json_data["reagent"]
+    elif "steps_info" in json_data and "labware_info" in json_data:
+        # 格式2: steps_info/labware_info（需要规范化）
+        protocol_steps = normalize_steps(json_data["steps_info"])
+        labware_info = normalize_labware(json_data["labware_info"])
+    elif "steps" in json_data and "labware" in json_data:
+        # 格式3: steps/labware（另一种常见格式）
+        protocol_steps = normalize_steps(json_data["steps"])
+        if isinstance(json_data["labware"], list):
+            labware_info = normalize_labware(json_data["labware"])
+        else:
+            labware_info = json_data["labware"]
+    else:
+        raise ValueError(
+            "不支持的 JSON 格式。支持的格式：\n"
+            "1. {'workflow': [...], 'reagent': {...}}\n"
+            "2. {'steps_info': [...], 'labware_info': [...]}\n"
+            "3. {'steps': [...], 'labware': [...]}"
+        )
+
+    # 构建工作流图
+    graph = build_protocol_graph(
+        labware_info=labware_info,
+        protocol_steps=protocol_steps,
+        workstation_name=workstation_name,
+        action_resource_mapping=ACTION_RESOURCE_MAPPING,
+    )
+
+    # 校验句柄配置
+    if validate:
+        is_valid, errors = validate_workflow_handles(graph)
+        if not is_valid:
+            import warnings
+
+            for error in errors:
+                warnings.warn(f"句柄校验警告: {error}")
+
+    return graph
+
+
+def convert_json_to_node_link(
+    data: Union[str, PathLike, Dict[str, Any]],
+    workstation_name: str = "PRCXi",
+) -> Dict[str, Any]:
+    """
+    将 JSON 数据转换为 node-link 格式的字典
+
+    Args:
+        data: JSON 文件路径、字典数据、或 JSON 字符串
+        workstation_name: 工作站名称，默认 "PRCXi"
+
+    Returns:
+        Dict: node-link 格式的工作流数据
+    """
+    graph = convert_from_json(data, workstation_name)
+    return graph.to_node_link_dict()
+
+
+def convert_json_to_workflow_list(
+    data: Union[str, PathLike, Dict[str, Any]],
+    workstation_name: str = "PRCXi",
+) -> List[Dict[str, Any]]:
+    """
+    将 JSON 数据转换为工作流列表格式
+
+    Args:
+        data: JSON 文件路径、字典数据、或 JSON 字符串
+        workstation_name: 工作站名称，默认 "PRCXi"
+
+    Returns:
+        List: 工作流节点列表
+    """
+    graph = convert_from_json(data, workstation_name)
+    return graph.to_dict()
+
+
+# 为了向后兼容，保留下划线前缀的别名
+_normalize_steps = normalize_steps
+_normalize_labware = normalize_labware
--- a/unilabos/workflow/from_python_script.py
+++ b/unilabos/workflow/from_python_script.py
@@ -0,0 +1,241 @@
+import ast
+import json
+from typing import Dict, List, Any, Tuple, Optional
+
+from .common import WorkflowGraph, RegistryAdapter
+
+Json = Dict[str, Any]
+
+# ---------------- Converter ----------------
+
+class DeviceMethodConverter:
+    """
+    - 字段统一：resource_name（原 device_class）、template_name（原 action_key）
+    - params 单层；inputs 使用 'params.' 前缀
+    - SimpleGraph.add_workflow_node 负责变量连线与边
+    """
+    def __init__(self, device_registry: Optional[Dict[str, Any]] = None):
+        self.graph = WorkflowGraph()
+        self.variable_sources: Dict[str, Dict[str, Any]] = {}        # var -> {node_id, output_name}
+        self.instance_to_resource: Dict[str, Optional[str]] = {}     # 实例名 -> resource_name
+        self.node_id_counter: int = 0
+        self.registry = RegistryAdapter(device_registry or {})
+
+    # ---- helpers ----
+    def _new_node_id(self) -> int:
+        nid = self.node_id_counter
+        self.node_id_counter += 1
+        return nid
+
+    def _assign_targets(self, targets) -> List[str]:
+        names: List[str] = []
+        import ast
+        if isinstance(targets, ast.Tuple):
+            for elt in targets.elts:
+                if isinstance(elt, ast.Name):
+                    names.append(elt.id)
+        elif isinstance(targets, ast.Name):
+            names.append(targets.id)
+        return names
+
+    def _extract_device_instantiation(self, node) -> Optional[Tuple[str, str]]:
+        import ast
+        if not isinstance(node.value, ast.Call):
+            return None
+        callee = node.value.func
+        if isinstance(callee, ast.Name):
+            class_name = callee.id
+        elif isinstance(callee, ast.Attribute) and isinstance(callee.value, ast.Name):
+            class_name = callee.attr
+        else:
+            return None
+        if isinstance(node.targets[0], ast.Name):
+            instance = node.targets[0].id
+            return instance, class_name
+        return None
+
+    def _extract_call(self, call) -> Tuple[str, str, Dict[str, Any], str]:
+        import ast
+        owner_name, method_name, call_kind = "", "", "func"
+        if isinstance(call.func, ast.Attribute):
+            method_name = call.func.attr
+            if isinstance(call.func.value, ast.Name):
+                owner_name = call.func.value.id
+                call_kind = "instance" if owner_name in self.instance_to_resource else "class_or_module"
+            elif isinstance(call.func.value, ast.Attribute) and isinstance(call.func.value.value, ast.Name):
+                owner_name = call.func.value.attr
+                call_kind = "class_or_module"
+        elif isinstance(call.func, ast.Name):
+            method_name = call.func.id
+            call_kind = "func"
+
+        def pack(node):
+            if isinstance(node, ast.Name):
+                return {"type": "variable", "value": node.id}
+            if isinstance(node, ast.Constant):
+                return {"type": "constant", "value": node.value}
+            if isinstance(node, ast.Dict):
+                return {"type": "dict", "value": self._parse_dict(node)}
+            if isinstance(node, ast.List):
+                return {"type": "list", "value": self._parse_list(node)}
+            return {"type": "raw", "value": ast.unparse(node) if hasattr(ast, "unparse") else str(node)}
+
+        args: Dict[str, Any] = {}
+        pos: List[Any] = []
+        for a in call.args:
+            pos.append(pack(a))
+        for kw in call.keywords:
+            args[kw.arg] = pack(kw.value)
+        if pos:
+            args["_positional"] = pos
+        return owner_name, method_name, args, call_kind
+
+    def _parse_dict(self, node) -> Dict[str, Any]:
+        import ast
+        out: Dict[str, Any] = {}
+        for k, v in zip(node.keys, node.values):
+            if isinstance(k, ast.Constant):
+                key = str(k.value)
+                if isinstance(v, ast.Name):
+                    out[key] = f"var:{v.id}"
+                elif isinstance(v, ast.Constant):
+                    out[key] = v.value
+                elif isinstance(v, ast.Dict):
+                    out[key] = self._parse_dict(v)
+                elif isinstance(v, ast.List):
+                    out[key] = self._parse_list(v)
+        return out
+
+    def _parse_list(self, node) -> List[Any]:
+        import ast
+        out: List[Any] = []
+        for elt in node.elts:
+            if isinstance(elt, ast.Name):
+                out.append(f"var:{elt.id}")
+            elif isinstance(elt, ast.Constant):
+                out.append(elt.value)
+            elif isinstance(elt, ast.Dict):
+                out.append(self._parse_dict(elt))
+            elif isinstance(elt, ast.List):
+                out.append(self._parse_list(elt))
+        return out
+
+    def _normalize_var_tokens(self, x: Any) -> Any:
+        if isinstance(x, str) and x.startswith("var:"):
+            return {"__var__": x[4:]}
+        if isinstance(x, list):
+            return [self._normalize_var_tokens(i) for i in x]
+        if isinstance(x, dict):
+            return {k: self._normalize_var_tokens(v) for k, v in x.items()}
+        return x
+
+    def _make_params_payload(self, resource_name: Optional[str], template_name: str, call_args: Dict[str, Any]) -> Dict[str, Any]:
+        input_keys = self.registry.get_action_input_keys(resource_name, template_name) if resource_name else []
+        defaults = self.registry.get_action_goal_default(resource_name, template_name) if resource_name else {}
+        params: Dict[str, Any] = dict(defaults)
+
+        def unpack(p):
+            t, v = p.get("type"), p.get("value")
+            if t == "variable":
+                return {"__var__": v}
+            if t == "dict":
+                return self._normalize_var_tokens(v)
+            if t == "list":
+                return self._normalize_var_tokens(v)
+            return v
+
+        for k, p in call_args.items():
+            if k == "_positional":
+                continue
+            params[k] = unpack(p)
+
+        pos = call_args.get("_positional", [])
+        if pos:
+            if input_keys:
+                for i, p in enumerate(pos):
+                    if i >= len(input_keys):
+                        break
+                    name = input_keys[i]
+                    if name in params:
+                        continue
+                    params[name] = unpack(p)
+            else:
+                for i, p in enumerate(pos):
+                    params[f"arg_{i}"] = unpack(p)
+        return params
+
+    # ---- handlers ----
+    def _on_assign(self, stmt):
+        import ast
+        inst = self._extract_device_instantiation(stmt)
+        if inst:
+            instance, code_class = inst
+            resource_name = self.registry.resolve_resource_by_classname(code_class)
+            self.instance_to_resource[instance] = resource_name
+            return
+
+        if isinstance(stmt.value, ast.Call):
+            owner, method, call_args, kind = self._extract_call(stmt.value)
+            if kind == "instance":
+                device_key = owner
+                resource_name = self.instance_to_resource.get(owner)
+            else:
+                device_key = owner
+                resource_name = self.registry.resolve_resource_by_classname(owner)
+
+            module = self.registry.get_device_module(resource_name)
+            params = self._make_params_payload(resource_name, method, call_args)
+
+            nid = self._new_node_id()
+            self.graph.add_workflow_node(
+                nid,
+                device_key=device_key,
+                resource_name=resource_name,      # ✅
+                module=module,
+                template_name=method,             # ✅
+                params=params,
+                variable_sources=self.variable_sources,
+                add_ready_if_no_vars=True,
+                prev_node_id=(nid - 1) if nid > 0 else None,
+            )
+
+            out_vars = self._assign_targets(stmt.targets[0])
+            for var in out_vars:
+                self.variable_sources[var] = {"node_id": nid, "output_name": "result"}
+
+    def _on_expr(self, stmt):
+        import ast
+        if not isinstance(stmt.value, ast.Call):
+            return
+        owner, method, call_args, kind = self._extract_call(stmt.value)
+        if kind == "instance":
+            device_key = owner
+            resource_name = self.instance_to_resource.get(owner)
+        else:
+            device_key = owner
+            resource_name = self.registry.resolve_resource_by_classname(owner)
+
+        module = self.registry.get_device_module(resource_name)
+        params = self._make_params_payload(resource_name, method, call_args)
+
+        nid = self._new_node_id()
+        self.graph.add_workflow_node(
+            nid,
+            device_key=device_key,
+            resource_name=resource_name,      # ✅
+            module=module,
+            template_name=method,             # ✅
+            params=params,
+            variable_sources=self.variable_sources,
+            add_ready_if_no_vars=True,
+            prev_node_id=(nid - 1) if nid > 0 else None,
+        )
+
+    def convert(self, python_code: str):
+        tree = ast.parse(python_code)
+        for stmt in tree.body:
+            if isinstance(stmt, ast.Assign):
+                self._on_assign(stmt)
+            elif isinstance(stmt, ast.Expr):
+                self._on_expr(stmt)
+        return self
--- a/unilabos/workflow/from_xdl.py
+++ b/unilabos/workflow/from_xdl.py
@@ -0,0 +1,131 @@
+from typing import List, Any, Dict
+import xml.etree.ElementTree as ET
+
+
+def convert_to_type(val: str) -> Any:
+    """将字符串值转换为适当的数据类型"""
+    if val == "True":
+        return True
+    if val == "False":
+        return False
+    if val == "?":
+        return None
+    if val.endswith(" g"):
+        return float(val.split(" ")[0])
+    if val.endswith("mg"):
+        return float(val.split("mg")[0])
+    elif val.endswith("mmol"):
+        return float(val.split("mmol")[0]) / 1000
+    elif val.endswith("mol"):
+        return float(val.split("mol")[0])
+    elif val.endswith("ml"):
+        return float(val.split("ml")[0])
+    elif val.endswith("RPM"):
+        return float(val.split("RPM")[0])
+    elif val.endswith(" °C"):
+        return float(val.split(" ")[0])
+    elif val.endswith(" %"):
+        return float(val.split(" ")[0])
+    return val
+
+
+def flatten_xdl_procedure(procedure_elem: ET.Element) -> List[ET.Element]:
+    """展平嵌套的XDL程序结构"""
+    flattened_operations = []
+    TEMP_UNSUPPORTED_PROTOCOL = ["Purge", "Wait", "Stir", "ResetHandling"]
+
+    def extract_operations(element: ET.Element):
+        if element.tag not in ["Prep", "Reaction", "Workup", "Purification", "Procedure"]:
+            if element.tag not in TEMP_UNSUPPORTED_PROTOCOL:
+                flattened_operations.append(element)
+
+        for child in element:
+            extract_operations(child)
+
+    for child in procedure_elem:
+        extract_operations(child)
+
+    return flattened_operations
+
+
+def parse_xdl_content(xdl_content: str) -> tuple:
+    """解析XDL内容"""
+    try:
+        xdl_content_cleaned = "".join(c for c in xdl_content if c.isprintable())
+        root = ET.fromstring(xdl_content_cleaned)
+
+        synthesis_elem = root.find("Synthesis")
+        if synthesis_elem is None:
+            return None, None, None
+
+        # 解析硬件组件
+        hardware_elem = synthesis_elem.find("Hardware")
+        hardware = []
+        if hardware_elem is not None:
+            hardware = [{"id": c.get("id"), "type": c.get("type")} for c in hardware_elem.findall("Component")]
+
+        # 解析试剂
+        reagents_elem = synthesis_elem.find("Reagents")
+        reagents = []
+        if reagents_elem is not None:
+            reagents = [{"name": r.get("name"), "role": r.get("role", "")} for r in reagents_elem.findall("Reagent")]
+
+        # 解析程序
+        procedure_elem = synthesis_elem.find("Procedure")
+        if procedure_elem is None:
+            return None, None, None
+
+        flattened_operations = flatten_xdl_procedure(procedure_elem)
+        return hardware, reagents, flattened_operations
+
+    except ET.ParseError as e:
+        raise ValueError(f"Invalid XDL format: {e}")
+
+
+def convert_xdl_to_dict(xdl_content: str) -> Dict[str, Any]:
+    """
+    将XDL XML格式转换为标准的字典格式
+
+    Args:
+        xdl_content: XDL XML内容
+
+    Returns:
+        转换结果，包含步骤和器材信息
+    """
+    try:
+        hardware, reagents, flattened_operations = parse_xdl_content(xdl_content)
+        if hardware is None:
+            return {"error": "Failed to parse XDL content", "success": False}
+
+        # 将XDL元素转换为字典格式
+        steps_data = []
+        for elem in flattened_operations:
+            # 转换参数类型
+            parameters = {}
+            for key, val in elem.attrib.items():
+                converted_val = convert_to_type(val)
+                if converted_val is not None:
+                    parameters[key] = converted_val
+
+            step_dict = {
+                "operation": elem.tag,
+                "parameters": parameters,
+                "description": elem.get("purpose", f"Operation: {elem.tag}"),
+            }
+            steps_data.append(step_dict)
+
+        # 合并硬件和试剂为统一的labware_info格式
+        labware_data = []
+        labware_data.extend({"id": hw["id"], "type": "hardware", **hw} for hw in hardware)
+        labware_data.extend({"name": reagent["name"], "type": "reagent", **reagent} for reagent in reagents)
+
+        return {
+            "success": True,
+            "steps": steps_data,
+            "labware": labware_data,
+            "message": f"Successfully converted XDL to dict format. Found {len(steps_data)} steps and {len(labware_data)} labware items.",
+        }
+
+    except Exception as e:
+        error_msg = f"XDL conversion failed: {str(e)}"
+        return {"error": error_msg, "success": False}
--- a/unilabos/workflow/wf_utils.py
+++ b/unilabos/workflow/wf_utils.py
@@ -0,0 +1,138 @@
+"""
+工作流工具模块
+
+提供工作流上传等功能
+"""
+
+import json
+import os
+import uuid
+from typing import Any, Dict, List, Optional
+
+from unilabos.utils.banner_print import print_status
+
+
+def _is_node_link_format(data: Dict[str, Any]) -> bool:
+    """检查数据是否为 node-link 格式"""
+    return "nodes" in data and "edges" in data
+
+
+def _convert_to_node_link(workflow_file: str, workflow_data: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    将非 node-link 格式的工作流数据转换为 node-link 格式
+
+    Args:
+        workflow_file: 工作流文件路径（用于日志）
+        workflow_data: 原始工作流数据
+
+    Returns:
+        node-link 格式的工作流数据
+    """
+    from unilabos.workflow.convert_from_json import convert_json_to_node_link
+
+    print_status(f"检测到非 node-link 格式，正在转换...", "info")
+    node_link_data = convert_json_to_node_link(workflow_data)
+    print_status(f"转换完成", "success")
+    return node_link_data
+
+
+def upload_workflow(
+    workflow_file: str,
+    workflow_name: Optional[str] = None,
+    tags: Optional[List[str]] = None,
+    published: bool = False,
+) -> Dict[str, Any]:
+    """
+    上传工作流到服务器
+
+    支持的输入格式：
+    1. node-link 格式: {"nodes": [...], "edges": [...]}
+    2. workflow/reagent 格式: {"workflow": [...], "reagent": {...}}
+    3. steps_info/labware_info 格式: {"steps_info": [...], "labware_info": [...]}
+    4. steps/labware 格式: {"steps": [...], "labware": [...]}
+
+    Args:
+        workflow_file: 工作流文件路径（JSON格式）
+        workflow_name: 工作流名称，如果不提供则从文件中读取或使用文件名
+        tags: 工作流标签列表，默认为空列表
+        published: 是否发布工作流，默认为False
+
+    Returns:
+        Dict: API响应数据
+    """
+    # 延迟导入，避免在配置文件加载之前初始化 http_client
+    from unilabos.app.web import http_client
+
+    if not os.path.exists(workflow_file):
+        print_status(f"工作流文件不存在: {workflow_file}", "error")
+        return {"code": -1, "message": f"文件不存在: {workflow_file}"}
+
+    # 读取工作流文件
+    try:
+        with open(workflow_file, "r", encoding="utf-8") as f:
+            workflow_data = json.load(f)
+    except json.JSONDecodeError as e:
+        print_status(f"工作流文件JSON解析失败: {e}", "error")
+        return {"code": -1, "message": f"JSON解析失败: {e}"}
+
+    # 自动检测并转换格式
+    if not _is_node_link_format(workflow_data):
+        try:
+            workflow_data = _convert_to_node_link(workflow_file, workflow_data)
+        except Exception as e:
+            print_status(f"工作流格式转换失败: {e}", "error")
+            return {"code": -1, "message": f"格式转换失败: {e}"}
+
+    # 提取工作流数据
+    nodes = workflow_data.get("nodes", [])
+    edges = workflow_data.get("edges", [])
+    workflow_uuid_val = workflow_data.get("workflow_uuid", str(uuid.uuid4()))
+    wf_name_from_file = workflow_data.get("workflow_name", os.path.basename(workflow_file).replace(".json", ""))
+
+    # 确定工作流名称
+    final_name = workflow_name or wf_name_from_file
+
+    print_status(f"正在上传工作流: {final_name}", "info")
+    print_status(f"  - 节点数量: {len(nodes)}", "info")
+    print_status(f"  - 边数量: {len(edges)}", "info")
+    print_status(f"  - 标签: {tags or []}", "info")
+    print_status(f"  - 发布状态: {published}", "info")
+
+    # 调用 http_client 上传
+    result = http_client.workflow_import(
+        name=final_name,
+        workflow_uuid=workflow_uuid_val,
+        workflow_name=final_name,
+        nodes=nodes,
+        edges=edges,
+        tags=tags,
+        published=published,
+    )
+
+    if result.get("code") == 0:
+        data = result.get("data", {})
+        print_status("工作流上传成功！", "success")
+        print_status(f"  - UUID: {data.get('uuid', 'N/A')}", "info")
+        print_status(f"  - 名称: {data.get('name', 'N/A')}", "info")
+    else:
+        print_status(f"工作流上传失败: {result.get('message', '未知错误')}", "error")
+
+    return result
+
+
+def handle_workflow_upload_command(args_dict: Dict[str, Any]) -> None:
+    """
+    处理 workflow_upload 子命令
+
+    Args:
+        args_dict: 命令行参数字典
+    """
+    workflow_file = args_dict.get("workflow_file")
+    workflow_name = args_dict.get("workflow_name")
+    tags = args_dict.get("tags", [])
+    published = args_dict.get("published", False)
+
+    if workflow_file:
+        upload_workflow(workflow_file, workflow_name, tags, published)
+    else:
+        print_status("未指定工作流文件路径，请使用 -f/--workflow_file 参数", "error")
Author	SHA1	Message	Date
Xuwznln	ed56c1eba2	reduce logs	2025-12-08 19:23:53 +08:00
Xuwznln	16ee3de086	Add workflow upload func.	2025-12-08 19:12:05 +08:00
Junhan Chang	ced961050d	add unilabos/workflow and entrypoint	2025-12-07 17:50:27 +08:00