mirror of
https://github.com/dptech-corp/Uni-Lab-OS.git
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217 lines
7.4 KiB
Python
217 lines
7.4 KiB
Python
import json
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import logging
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import traceback
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import uuid
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from typing import Any, Dict, List
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import networkx as nx
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import matplotlib.pyplot as plt
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import requests
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logger = logging.getLogger(__name__)
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class SimpleGraph:
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"""简单的有向图实现，用于构建工作流图"""
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def __init__(self):
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self.nodes = {}
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self.edges = []
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def add_node(self, node_id, **attrs):
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"""添加节点"""
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self.nodes[node_id] = attrs
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def add_edge(self, source, target, **attrs):
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"""添加边"""
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# edge = {"source": source, "target": target, **attrs}
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edge = {
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"source": source, "target": target,
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"source_node_uuid": source,
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"target_node_uuid": target,
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"source_handle_io": "source",
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"target_handle_io": "target",
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**attrs
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}
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self.edges.append(edge)
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def to_dict(self):
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"""转换为工作流图格式"""
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nodes_list = []
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for node_id, attrs in self.nodes.items():
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node_attrs = attrs.copy()
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params = node_attrs.pop("parameters", {}) or {}
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node_attrs.update(params)
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nodes_list.append({"id": node_id, **node_attrs})
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return {
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"directed": True,
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"multigraph": False,
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"graph": {},
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"nodes": nodes_list,
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"edges": self.edges,
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"links": self.edges,
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}
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def extract_json_from_markdown(text: str) -> str:
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"""从markdown代码块中提取JSON"""
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text = text.strip()
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if text.startswith("```json\n"):
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text = text[8:]
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if text.startswith("```\n"):
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text = text[4:]
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if text.endswith("\n```"):
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text = text[:-4]
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return text
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def create_workflow(
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steps_info: str,
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labware_info: str,
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workflow_name: str = "Generated Workflow",
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workstation_name: str = "workstation",
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workflow_description: str = "Auto-generated workflow from protocol",
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) -> Dict[str, Any]:
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"""
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创建工作流，输入数据已经是统一的字典格式
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Args:
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steps_info: 步骤信息 (JSON字符串，已经是list of dict格式)
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labware_info: 实验器材和试剂信息 (JSON字符串，已经是list of dict格式)
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workflow_name: 工作流名称
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workflow_description: 工作流描述
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Returns:
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创建结果，包含工作流UUID和详细信息
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"""
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try:
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# 直接解析JSON数据
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steps_info_clean = extract_json_from_markdown(steps_info)
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labware_info_clean = extract_json_from_markdown(labware_info)
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steps_data = json.loads(steps_info_clean)
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labware_data = json.loads(labware_info_clean)
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# 统一处理所有数据
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protocol_graph = build_protocol_graph(labware_data, steps_data, workstation_name=workstation_name)
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# 检测协议类型（用于标签）
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protocol_type = "bio" if any("biomek" in step.get("template", "") for step in refactored_steps) else "organic"
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# 转换为工作流格式
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data = protocol_graph.to_dict()
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# 转换节点格式
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for i, node in enumerate(data["nodes"]):
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description = node.get("description", "")
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onode = {
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"template": node.pop("template"),
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"id": node["id"],
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"lab_node_type": node.get("lab_node_type", "Device"),
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"name": description or f"Node {i + 1}",
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"params": {"default": node},
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"handles": {},
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}
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# 处理边连接
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for edge in data["links"]:
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if edge["source"] == node["id"]:
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source_port = edge.get("source_port", "output")
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if source_port not in onode["handles"]:
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onode["handles"][source_port] = {"type": "source"}
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if edge["target"] == node["id"]:
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target_port = edge.get("target_port", "input")
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if target_port not in onode["handles"]:
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onode["handles"][target_port] = {"type": "target"}
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data["nodes"][i] = onode
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# 发送到API创建工作流
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api_secret = configs.Lab.Key
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if not api_secret:
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return {"error": "API SecretKey is not configured", "success": False}
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# Step 1: 创建工作流
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workflow_url = f"{configs.Lab.Api}/api/v1/workflow/"
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headers = {
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"Content-Type": "application/json",
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}
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params = {"secret_key": api_secret}
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graph_data = {"name": workflow_name, **data}
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logger.info(f"Creating workflow: {workflow_name}")
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response = requests.post(
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workflow_url, params=params, json=graph_data, headers=headers, timeout=configs.Lab.Timeout
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)
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response.raise_for_status()
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workflow_info = response.json()
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if workflow_info.get("code") != 0:
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error_msg = f"API returned an error: {workflow_info.get('msg', 'Unknown Error')}"
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logger.error(error_msg)
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return {"error": error_msg, "success": False}
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workflow_uuid = workflow_info.get("data", {}).get("uuid")
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if not workflow_uuid:
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return {"error": "Failed to get workflow UUID from response", "success": False}
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# Step 2: 添加到模板库（可选）
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try:
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library_url = f"{configs.Lab.Api}/api/flociety/vs/workflows/library/"
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lib_payload = {
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"workflow_uuid": workflow_uuid,
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"title": workflow_name,
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"description": workflow_description,
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"labels": [protocol_type.title(), "Auto-generated"],
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}
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library_response = requests.post(
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library_url, params=params, json=lib_payload, headers=headers, timeout=configs.Lab.Timeout
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)
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library_response.raise_for_status()
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library_info = library_response.json()
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logger.info(f"Workflow added to library: {library_info}")
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return {
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"success": True,
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"workflow_uuid": workflow_uuid,
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"workflow_info": workflow_info.get("data"),
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"library_info": library_info.get("data"),
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"protocol_type": protocol_type,
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"message": f"Workflow '{workflow_name}' created successfully",
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}
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except Exception as e:
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# 即使添加到库失败，工作流创建仍然成功
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logger.warning(f"Failed to add workflow to library: {str(e)}")
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return {
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"success": True,
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"workflow_uuid": workflow_uuid,
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"workflow_info": workflow_info.get("data"),
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"protocol_type": protocol_type,
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"message": f"Workflow '{workflow_name}' created successfully (library addition failed)",
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}
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except requests.exceptions.RequestException as e:
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error_msg = f"Network error when calling API: {str(e)}"
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logger.error(error_msg)
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return {"error": error_msg, "success": False}
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except json.JSONDecodeError as e:
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error_msg = f"JSON parsing error: {str(e)}"
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logger.error(error_msg)
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return {"error": error_msg, "success": False}
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except Exception as e:
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error_msg = f"An unexpected error occurred: {str(e)}"
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logger.error(error_msg)
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logger.error(traceback.format_exc())
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return {"error": error_msg, "success": False}
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