代码提交

requirements.txt

@@ -1,6 +1,6 @@
 fastapi==0.115.12
-networkx==3.4.2
-numpy==2.2.5
+#networkx==3.4.2
+#numpy==2.2.5
 pgvector==0.1.8
 pydantic==2.11.1
 Requests==2.31.0
@@ -9,4 +9,4 @@ urllib3==2.3.0
 uvicorn==0.34.0
 psycopg2-binary==2.9.10
 python-dotenv==1.0.0
-hui-tools[all]==0.5.8
+hui-tools[all]==0.5.8

src/knowledge/utils/embed_helper.py

@@ -0,0 +1,11 @@
+#load enviroment variable
+from ..config.site import SiteConfig
+from sentence_transformers import SentenceTransformer
+config = SiteConfig()
+
+class EmbedHelper:
+    def __init__(self):
+        self.embedding_model_name = config.get_config("EMBEDDING_MODEL")
+        self.embedding_model = SentenceTransformer(model_name_or_path=self.embedding_model_name) 
+    def embed_text(self, text):
+        return self.embedding_model.encode(text).tolist()

src/knowledge/utils/license.py

@@ -0,0 +1,39 @@
+from cryptography.hazmat.primitives.asymmetric import padding
+from cryptography.hazmat.primitives import hashes,serialization
+import json
+import time
+import traceback
+
+def validate_license(public_key_pem, license_json, signature):
+    public_key = serialization.load_pem_public_key(public_key_pem)
+
+    try:
+        public_key.verify(
+        signature,
+        license_json,
+        padding.PKCS1v15(),
+        hashes.SHA256()
+        )
+    except:
+        #打印异常信息
+        traceback.print_exc()
+        return False
+
+    license_data=json.loads(license_json.decode())
+    # 检查是否过期
+    if time.time()>license_data["expiration_time"]:
+        return False
+    return True
+
+if __name__ == '__main__':
+    with open("license_issued/public.key","rb") as f:
+        public_key_pem = f.read()
+    with open("license_issued/license_issued.lic","rb") as f:
+        data = json.loads(f.read())
+        license_json = json.dumps(data, sort_keys=True).encode()
+    with open("license_issued/license_issued.key","rb") as f:
+        signature = f.read()
+    if validate_license(public_key_pem,license_json, signature):
+        print("许可证有效!")
+    else:
+        print("许可证无效或已过期!")

src/knowledge/utils/vectorizer.py

@@ -1,9 +1,7 @@
 import logging
 from typing import List
-import numpy as np
-import requests
-from requests.adapters import HTTPAdapter
-from urllib3.util.retry import Retry
+from ..utils.embed_helper import EmbedHelper
+
 
 logger = logging.getLogger(__name__)
 
@@ -11,18 +9,10 @@ class Vectorizer:
     _instance = None
     
     def __init__(self):
-        self.api_url = "http://172.16.8.98:11434/api/embeddings"
-        self.model_name = "bge-m3"
-        self.session = requests.Session()
-        retries = Retry(total=3, backoff_factor=1)
-        self.session.mount('http://', HTTPAdapter(max_retries=retries))
-
-    @staticmethod
-    def get_embedding(text: str) -> List[float]:
-        return Vectorizer()._call_ollama_api(text)
+        self.embedHelper = EmbedHelper()
 
-    def _initialize_model(self):
-        logger.info("Initialized Ollama API client for bge-m3 model")
+    def get_embedding(self, text: str) -> List[float]:
+       return self.embedHelper.embed_text(text)
 
     @classmethod
     def get_instance(cls):
@@ -35,51 +25,10 @@ class Vectorizer:
         return [self.tokenizer.convert_tokens_to_string(tokens[i:i+chunk_size]) 
                for i in range(0, len(tokens), chunk_size)]
 
-    def encode(self, text: str, batch_size: int = 32) -> List[float]:
-        if not text:
-            return [0.0] * 1024  # 调整为1024维以匹配数据库
-        return self._call_ollama_api(text)
 
-    def batch_encode(self, texts: List[str], batch_size: int = 64) -> List[List[float]]:
-        return [self._call_ollama_api(text) for text in texts]
+if __name__ == '__main__':
 
-    def _call_ollama_api(self, text: str) -> List[float]:
-        try:
-            response = self.session.post(
-                self.api_url,
-                json={
-                    "model": self.model_name,
-                    "prompt": text,
-                    "options": {"embedding_only": True}
-                },
-                timeout=30
-            )
-            response.raise_for_status()
-            embedding_array = np.array(response.json()["embedding"])
-            l2_norm = np.linalg.norm(embedding_array)
-            if l2_norm > 0:
-                embedding_array = embedding_array / l2_norm
-            return embedding_array.tolist()
-        except Exception as e:
-            logger.error(f"API请求失败: {str(e)}")
-            raise
+    text = '你好'
+    print(text)
 
-    if __name__ == '__main__':
-        text ='''姓名：李XX  
-            性别：女  
-            年龄：55岁  
-            住院号：NJZY20231102  
-            主诉：突发胸痛伴呼吸困难2小时  
-            现病史：患者于下午3时许突发胸痛，位于心前区，呈压榨性疼痛，伴呼吸困难，持续不缓解，无恶心呕吐及二便失禁。急诊测血压150/90mmHg，心率100次/分。心电图示II、III、aVF导联ST段弓背向上抬高0.3-0.5mV。发病前2周曾诉间断性胸闷，每次持续数分钟自行缓解。  
-            既往史：高血压8年（间断服用降压药），无糖尿病史，无手术史。长期吸烟（20包/年），饮酒史5年（红酒约150g/日）。  
-            体格检查：BP 155/92mmHg，心率102次/分。神志清楚，痛苦面容，双肺呼吸音清，未闻及干湿性啰音。心界不大，心率102次/分，律齐，心尖区可闻及2/6级收缩期杂音。  
-            辅助检查：心电图示II、III、aVF导联ST段弓背向上抬高0.3-0.5mV；心肌酶谱：肌酸激酶同工酶（CK-MB）100U/L，肌钙蛋白T（cTnT）0.4ng/ml；心脏超声示左室下壁运动减弱。  
-            诊断：急性下壁心肌梗死  
-            治疗计划：  
-            1. 抗血小板治疗：阿司匹林300mg嚼服，氯吡格雷300mg负荷剂量后75mg qd。  
-            2. 抗凝治疗：低分子量肝素4000U皮下注射，每12小时1次。  
-            3. 冠状动脉介入治疗（PCI）：急诊行冠状动脉造影，必要时行支架植入术。  
-            4. 调脂治疗：阿托伐他汀20mg qn。  
-            5. 血管扩张剂：硝酸甘油静脉泵入。'''
-        embedding = get_embedding(text)
-        print(f'生成的embedding向量:\n{embedding}')
+    embedding2 = Vectorizer.get_instance().get_embedding(text)