add unilabos/workflow and entrypoint

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(

unilabos/app/main.py

@@ -49,6 +49,8 @@ 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 +155,14 @@ def parse_args():
         default=False,
         help="Complete registry information",
     )
+
+    # label
+    workflow_parser = subparsers.add_parser(
+        "workflow_upload",
+        help="Upload workflow from xdl/json/python files",
+    )
+    workflow_parser.add_argument("-t", "--labeltype", default="singlepoint", type=str,
+                              help="QM calculation type, support 'singlepoint', 'optimize' and 'dimer' currently")
     return parser
 
 
@@ -163,6 +173,9 @@ def main():
     convert_argv_dashes_to_underscores(args)
     args_dict = vars(args.parse_args())
 
+    # 显示启动横幅
+    print_unilab_banner(args_dict)
+
     # 环境检查 - 检查并自动安装必需的包 (可选)
     if not args_dict.get("skip_env_check", False):
         from unilabos.utils.environment_check import check_environment
@@ -239,7 +252,18 @@ 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
 
+    # 显示启动横幅
+    print_unilab_banner(args_dict)
+
+    #####################################
+    ######## 启动设备接入端(主入口) ########
+    #####################################
+    launch(args_dict)
+
+
+def launch(args_dict: Dict[str, Any]):
     # 使用远程资源启动
     if args_dict["use_remote_resource"]:
         print_status("使用远程资源启动", "info")
@@ -254,7 +278,6 @@ 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)
@@ -278,9 +301,6 @@ def main():
     from unilabos.resources.graphio import modify_to_backend_format
     from unilabos.ros.nodes.resource_tracker import ResourceTreeSet, ResourceDict
 
-    # 显示启动横幅
-    print_unilab_banner(args_dict)
-
     # 注册表
     lab_registry = build_registry(
         args_dict["registry_path"], args_dict.get("complete_registry", False), args_dict["upload_registry"]

unilabos/test/workflow/merge_workflow.py

@@ -9,7 +9,7 @@ if str(ROOT_DIR) not in sys.path:
 
 import pytest
 
-from scripts.workflow import build_protocol_graph, draw_protocol_graph, draw_protocol_graph_with_ports
+from unilabos.workflow.common import build_protocol_graph, draw_protocol_graph, draw_protocol_graph_with_ports
 
 
 ROOT_DIR = Path(__file__).resolve().parents[2]

unilabos/workflow/common.py

@@ -0,0 +1,484 @@
+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):
+        edge = {
+            "source": source,
+            "target": target,
+            "source_node_uuid": source,
+            "target_node_uuid": target,
+            "source_handle_io": attrs.pop("source_handle_io", "source"),
+            "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 = {"id": 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["id"]) if str(n["id"]).isdigit() else n["id"])
+
+    # 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({"id": 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]]) -> 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": "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)
+                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"biomek-{operation}"
+            else:
+                template = f"{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
+) -> 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"""
+    G = WorkflowGraph()
+    resource_last_writer = {}
+
+    protocol_steps = refactor_data(protocol_steps)
+    # 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
+    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]
+
+        G.add_node(
+            node_id,
+            template_name=f"create_resource",
+            resource_name="host_node",
+            description=description,
+            lab_node_type=lab_node_type,
+            params={
+                "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": "",
+            },
+            role=item.get("role", ""),
+        )
+        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("parameters", {})
+        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", 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", 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}'")
+# ---------------- 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())))

unilabos/workflow/from_labwares_and_steps.py

@@ -0,0 +1,24 @@
+import json
+from os import PathLike
+
+from unilabos.workflow.common import build_protocol_graph
+
+
+def from_labwares_and_steps(data_path: PathLike):
+    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",
+    )

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

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}