最小化启动依赖

src/config/__init__.py

@@ -49,7 +49,7 @@ class Config(SimpleConfig):
         # 模型配置
         ## 注意这里是模型名，而不是具体的模型路径，默认使用 HuggingFace 的路径
         ## 如果需要自定义路径，则在 config/base.yaml 中配置 model_local_paths
-        self.add_item("model_provider", default="qianfan", des="模型提供商", choices=["qianfan", "vllm", "zhipu", "deepseek", "dashscope"])
+        self.add_item("model_provider", default="zhipu", des="模型提供商", choices=["qianfan", "vllm", "zhipu", "deepseek", "dashscope"])
         self.add_item("model_name", default=None, des="模型名称")
         self.add_item("embed_model", default="bge-large-zh-v1.5", des="Embedding 模型", choices=["bge-large-zh-v1.5", "zhipu"])
         self.add_item("reranker", default="bge-reranker-v2-m3", des="Re-Ranker 模型", choices=["bge-reranker-v2-m3"])

src/core/database.py

@@ -2,10 +2,7 @@ import os
 import json
 import time
 from src.utils import hashstr, setup_logger, is_text_pdf
-from src.plugins import pdf2txt
-from src.core.knowledgebase import KnowledgeBase
 from src.core.filereader import pdfreader, plainreader
-from src.core.graphbase import GraphDatabase
 from src.models.embedding import get_embedding_model
 
 logger = setup_logger("DataBaseManager")
@@ -57,6 +54,8 @@ class DataBaseManager:
         self.embed_model = get_embedding_model(config)
 
         if self.config.enable_knowledge_base:
+            from src.core.knowledgebase import KnowledgeBase
+            from src.core.graphbase import GraphDatabase
             self.knowledge_base = KnowledgeBase(config, self.embed_model)
             self.graph_base = GraphDatabase(self.config, self.embed_model)
             self.graph_base.start()
@@ -180,6 +179,7 @@ class DataBaseManager:
             if is_text_pdf(file):
                 return pdfreader(file)
             else:
+                from src.plugins import pdf2txt
                 return pdf2txt(file, return_text=True)
 
         elif file.endswith(".txt") or file.endswith(".md"):

src/core/filereader.py

@@ -1,14 +1,13 @@
 import os
 
 from pathlib import Path
-from llama_index.readers.file import PDFReader
-
 
 def pdfreader(file_path):
     """读取PDF文件并返回text文本"""
     assert os.path.exists(file_path), "File not found"
     assert file_path.endswith(".pdf"), "File format not supported"
 
+    from llama_index.readers.file import PDFReader
     doc = PDFReader().load_data(file=Path(file_path))
 
     # 简单的拼接起来之后返回纯文本

src/core/knowledgebase.py

@@ -14,6 +14,7 @@ class KnowledgeBase:
 
         assert embed_model, "embed_model=None"
         self.embed_model = embed_model
+
         self.client = MilvusClient(self.milvus_path)
 
     def _init_config(self, config):

src/models/chat_model.py

@@ -64,7 +64,6 @@ class VLLM(OpenAIBase):
         super().__init__(api_key=api_key, base_url=base_url, model_name=model_name)
 
 
-import qianfan
 
 
 class GeneralResponse:
@@ -76,6 +75,7 @@ class GeneralResponse:
 class Qianfan:
 
     def __init__(self, model_name="ernie_speed") -> None:
+        import qianfan
         self.model_name = model_name
         access_key = os.getenv("QIANFAN_ACCESS_KEY")
         secret_key = os.getenv("QIANFAN_SECRET_KEY")

src/requirements.txt

@@ -1,9 +1,6 @@
 FlagEmbedding==1.2.10
 Flask==3.0.3
 Flask_Cors==4.0.1
-llama_index==0.10.53
 openai==1.35.10
-pymilvus==2.4.4
 python-dotenv==1.0.1
 PyYAML==6.0.1
-qianfan==0.4.0.1