19 changed files with 991 additions and 161 deletions
@ -1,42 +1,263 @@ |
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# 全局 client（可复用） |
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import base64 |
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import io |
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import json |
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import os |
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import re |
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import tempfile |
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import traceback |
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|
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from docx import Document |
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import httpx |
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from robyn import jsonify, Response |
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from multipart import FormParser |
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from robyn import jsonify, Response, Request |
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from app import app |
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from controller.client import client |
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from util.neo4j_utils import neo4j_client |
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|
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# 中文类型到英文标签的映射字典 |
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CHINESE_TO_ENGLISH_LABEL = { |
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"疾病": "Disease", |
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"症状": "Symptom", |
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"检查项目": "AuxiliaryExamination", |
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"药物": "Drug", |
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"手术": "Operation", |
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"解剖部位": "CheckSubject", # 或 AnatomicalSite，根据你的图谱设计 |
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"并发症": "Complication", |
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"诊断": "Diagnosis", |
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"治疗": "Treatment", |
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"辅助治疗": "AdjuvantTherapy", |
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"不良反应": "AdverseReactions", |
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"检查": "Check", |
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"部门": "Department", |
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"疾病部位": "DiseaseSite", |
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"相关疾病": "RelatedDisease", |
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"相关症状": "RelatedSymptom", |
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"传播途径": "SpreadWay", |
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"阶段": "Stage", |
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"主题/主体": "Subject", |
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"症状与体征": "SymptomAndSign", |
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"治疗方案": "TreatmentPrograms", |
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"类型": "Type", |
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"原因": "Cause", |
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"属性": "Attribute", |
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"指示/适应症": "Indications", |
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"成分": "Ingredients", |
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"病原学": "Pathogenesis", |
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"病理类型": "PathologicalType", |
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"发病机制": "Pathophysiology", |
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"注意事项": "Precautions", |
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"预后": "Prognosis", |
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"预后生存时间": "PrognosticSurvivalTime", |
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"疾病比率": "DiseaseRatio", |
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"药物治疗": "DrugTherapy", |
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"感染性": "Infectious", |
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"实体": "Entity", |
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# 可根据实际需要补充更多 |
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} |
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@app.post("/api/analyze") |
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async def analyze(request): |
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def json_response(data: dict, status_code: int = 200): |
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body = json.dumps(data, ensure_ascii=False, separators=(',', ':')) |
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headers = {"Content-Type": "application/json; charset=utf-8"} |
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return Response( |
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status_code=status_code, |
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description=body, # ✅ 关键：字段名是 response |
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headers=headers # ✅ 必须是 dict |
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) |
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|
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@app.post("/api/builder/analyze") |
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async def analyze(request: Request): |
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try: |
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# 1. 解析 JSON 请求体 |
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body = request.json() |
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input_text = body.get("text", "").strip() |
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if not input_text: |
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return jsonify({"error": "缺少 text 字段"}), 400 |
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input_text = body.get("text", "").strip() or "" |
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file_b64 = body.get("file_base64") |
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filename = body.get("filename", "unknown.docx") |
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|
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# 2. 如果既无 text 也无文件，报错 |
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if not input_text and not file_b64: |
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return json_response({"error": "必须提供 text 或 file"}, status_code=400) |
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|
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# 3. 从 .docx 提取文本（如果有文件） |
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file_text = "" |
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if file_b64: |
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try: |
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# 直接转发到大模型服务（假设它返回 { "task_id": "xxx" }） |
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file_data = base64.b64decode(file_b64) |
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doc = Document(io.BytesIO(file_data)) |
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file_text = "\n".join([para.text for para in doc.paragraphs]).strip() |
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except Exception as e: |
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return json_response({"error": f"解析 .docx 文件失败: {str(e)}"}, status_code=400) |
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# 4. 合并文本：优先用文件内容，或拼接两者（按你需求调整） |
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# 方案 A：只用文件内容（如果提供了文件） |
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# final_text = file_text if file_text else input_text |
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# 方案 B：拼接（推荐，更灵活） |
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final_text = (input_text + "\n\n" + file_text).strip() |
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if not final_text: |
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return json_response({"error": "合并后文本为空"}, status_code=400) |
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print(f"📄 最终提交文本（前200字符）:\n{final_text[:200]}...") |
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# 5. 转发给大模型服务 |
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resp = await client.post( |
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"/extract_entities_and_relations", |
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json={"text": input_text}, |
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json={"text": final_text}, |
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timeout=1800.0 # 30分钟 |
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) |
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print(resp) |
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if resp.status_code == 202 or resp.status_code == 200: |
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return Response( |
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status_code=200, |
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description=jsonify(resp.json()), |
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headers={"Content-Type": "text/plain; charset=utf-8"} |
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) |
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# 6. 返回结果 |
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if resp.status_code in (200, 202): |
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try: |
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result = resp.json() |
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except: |
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result = {"raw_response": resp.text} |
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return json_response(result, status_code=resp.status_code) |
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else: |
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return jsonify({ |
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"error": "提交失败", |
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"detail": resp.text |
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}), resp.status_code |
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return json_response({ |
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"error": "大模型服务调用失败", |
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"detail": resp.text, |
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"status_code": resp.status_code |
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}, status_code=resp.status_code) |
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except Exception as e: |
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error_trace = traceback.format_exc() |
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print("❌ 发生异常:") |
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print("❌ 后端异常:") |
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print(error_trace) |
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return json_response({ |
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"error": str(e), |
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"traceback": error_trace |
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}, status_code=500) |
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# @app.post("/api/builder/analyze") |
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# async def analyze(request: Request): |
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# ct = (request.headers.get("content-type") or "").lower() |
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# # === 关键：打印 body 前 100 字节的原始内容（作为字符串，忽略编码错误）=== |
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# preview = request.body[:100].decode('utf-8', errors='replace') |
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# print("📦 Body preview (first 100 chars):", repr(preview)) |
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# print("🔍 Content-Type:", repr(ct)) |
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# print("📦 Body length:", len(request.body)) |
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# if "multipart/form-data" not in ct: |
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# return json_response({"error": "仅支持 multipart/form-data"}, 400) |
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# |
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# try: |
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# form_data = parse_multipart(request.body, request.headers.get("content-type")) |
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# except Exception as e: |
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# return json_response({"error": f"表单解析失败: {str(e)}"}, 400) |
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# |
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# # 获取字段 |
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# text_input = form_data.get("text", "") |
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# uploaded_file = form_data.get("file") # 是 dict，含 filename/file/content_type |
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# |
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# if not uploaded_file or not isinstance(uploaded_file, dict): |
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# return json_response({"error": "未提供有效文件"}, 400) |
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# |
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# file_content = uploaded_file["file"] # bytes |
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# filename = uploaded_file["filename"] |
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# |
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# # 后续处理 .docx 等逻辑保持不变... |
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# @app.post("/api/builder/analyze") |
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# async def analyze(request): |
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# body = request.json() |
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# input_text = body.get("text", "").strip() |
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# if not input_text: |
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# return jsonify({"error": "缺少 text 字段"}), 400 |
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# try: |
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# # 直接转发到大模型服务（假设它返回 { "task_id": "xxx" }） |
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# resp = await client.post( |
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# "/extract_entities_and_relations", |
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# json={"text": input_text}, |
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# timeout=1800.0 # 30分钟 |
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# ) |
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# print(resp) |
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# |
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# if resp.status_code == 202 or resp.status_code == 200: |
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# return Response( |
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# status_code=200, |
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# description=jsonify(resp.json()), |
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# headers={"Content-Type": "text/plain; charset=utf-8"} |
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# ) |
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# else: |
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# return jsonify({ |
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# "error": "提交失败", |
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# "detail": resp.text |
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# }), resp.status_code |
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# except Exception as e: |
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# error_trace = traceback.format_exc() |
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# print("❌ 发生异常:") |
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# print(error_trace) |
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# |
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# return jsonify({"error": str(e), "traceback": error_trace}), 500 |
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@app.post("/api/builder/build") |
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async def build(request): |
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body = request.json() |
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entities = body.get("entities", "[]") |
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relations=body.get("relations", "[]") |
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try: |
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# 确保是字符串后再 loads |
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if isinstance(entities, str): |
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entities = json.loads(entities) |
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else: |
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entities = entities # 已经是 list（理想情况） |
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return jsonify({"error": str(e), "traceback": error_trace}), 500 |
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if isinstance(relations, str): |
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relations = json.loads(relations) |
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else: |
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relations = relations |
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except Exception as e: |
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print("JSON decode error:", e) |
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return Response(status_code=400, description=f"Invalid JSON in entities or relations: {e}") |
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name_to_label = {} |
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for ent in entities: |
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name = ent.get("n") |
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typ = ent.get("t") |
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print(f"Entity: {name}, Type: {typ}") |
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# 将中文类型转为英文标签 |
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label = CHINESE_TO_ENGLISH_LABEL.get(typ) |
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if label is None: |
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print(f"⚠️ Warning: Unknown entity type '{typ}' for entity '{name}'. Skipping or using generic label.") |
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label = typ # 默认回退标签 |
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name_to_label[name] = label |
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# 查询 Neo4j（假设函数按属性查） |
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print(label) |
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node = neo4j_client.find_nodes_with_element_id(label=label,properties={"name": name}) |
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if not node: |
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print("1111111") |
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if label is None: |
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print("sssss") |
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node_id = neo4j_client.insert_node(label=None, properties={"name":name}) |
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else: |
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print("2222222") |
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node_id = neo4j_client.insert_node(label=label, properties={"name": name}) |
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print("Found node:", node) |
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for rel in relations: |
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e1 = rel.get("e1") |
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r = rel.get("r") |
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e2 = rel.get("e2") |
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src_label = name_to_label.get(e1) |
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tgt_label = name_to_label.get(e2) |
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relationships = neo4j_client.find_relationships_by_condition( |
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source_label=src_label, |
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source_props={"name": e1}, |
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target_label=tgt_label, |
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target_props={"name": e2}, |
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rel_type=r, |
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rel_properties={"label": r} |
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) |
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if not relationships: |
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neo4j_client.create_relationship( |
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source_label=src_label, |
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source_props={"name": e1}, |
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target_label=tgt_label, |
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target_props={"name": e2}, |
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rel_type=r, |
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rel_properties={"label": r} |
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) |
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# nodes=neo4j_client.find_nodes_with_element_id(properties={"name": "糖尿病"}) |
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print(body) |
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After Width: | Height: | Size: 3.2 KiB |
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After Width: | Height: | Size: 4.5 KiB |
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After Width: | Height: | Size: 1.1 KiB |
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After Width: | Height: | Size: 949 B |
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After Width: | Height: | Size: 1.0 MiB |
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After Width: | Height: | Size: 47 KiB |
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After Width: | Height: | Size: 2.8 KiB |
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After Width: | Height: | Size: 14 KiB |
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After Width: | Height: | Size: 3.2 KiB |
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After Width: | Height: | Size: 4.5 KiB |
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After Width: | Height: | Size: 3.9 KiB |
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