'commit'

dsRag/Config/Config.py

@@ -28,5 +28,5 @@ DEEPSEEK_URL = 'https://api.deepseek.com'
 
 # 阿里云中用来调用 deepseek v3 的密钥【驿来特】
 MODEL_API_KEY = "sk-f6da0c787eff4b0389e4ad03a35a911f"
-#MODEL_NAME = "qwen-plus"
-MODEL_NAME = "deepseek-v3"
+MODEL_NAME = "qwen-plus"
+#MODEL_NAME = "deepseek-v3"

dsRag/Start.py

@@ -1,4 +1,5 @@
 import os
+import subprocess
 import tempfile
 import urllib.parse
 import uuid
@@ -9,27 +10,18 @@ from typing import List
 
 import jieba  # 导入 jieba 分词库
 import uvicorn
-from docx import Document
 from fastapi import FastAPI, Request, HTTPException
 from fastapi.staticfiles import StaticFiles
 from gensim.models import KeyedVectors
-from openai import OpenAI
 from pydantic import BaseModel, Field, ValidationError
 from starlette.responses import StreamingResponse
 
-from Config import Config
 from Config.Config import MS_MODEL_PATH, MS_MODEL_LIMIT, MS_HOST, MS_PORT, MS_MAX_CONNECTIONS, MS_NPROBE, \
     MS_COLLECTION_NAME
 from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
 from Milvus.Utils.MilvusConnectionPool import *
 from Milvus.Utils.MilvusConnectionPool import MilvusConnectionPool
-import subprocess
-
-
-# 将HTML文件转换为Word文件
-def html_to_word_pandoc(html_file, output_file):
-    subprocess.run(['pandoc', html_file, '-o', output_file])
-
+from Util.ALiYunUtil import ALiYunUtil
 
 # 初始化日志
 logger = logging.getLogger(__name__)
@@ -42,6 +34,10 @@ logger.addHandler(handler)
 model = KeyedVectors.load_word2vec_format(MS_MODEL_PATH, binary=False, limit=MS_MODEL_LIMIT)
 logger.info(f"模型加载成功，词向量维度: {model.vector_size}")
 
+# 将HTML文件转换为Word文件
+def html_to_word_pandoc(html_file, output_file):
+    subprocess.run(['pandoc', html_file, '-o', output_file])
+
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
@@ -52,13 +48,10 @@ async def lifespan(app: FastAPI):
     app.state.collection_manager = MilvusCollectionManager(MS_COLLECTION_NAME)
     app.state.collection_manager.load_collection()
 
-    # 初始化DeepSeek客户端
-    app.state.deepseek_client = OpenAI(
-        api_key=Config.DEEPSEEK_API_KEY,
-        base_url=Config.DEEPSEEK_URL
-    )
-    yield
+    # 初始化阿里云大模型工具
+    app.state.aliyun_util = ALiYunUtil()
 
+    yield
     # 关闭Milvus连接池
     app.state.milvus_pool.close()
 
@@ -154,17 +147,9 @@ async def generate_stream(client, milvus_pool, collection_manager, query, docume
 5. 确保内容结构清晰，便于前端展示
 """
 
-        response = client.chat.completions.create(
-            model="deepseek-chat",
-            messages=[
-                {"role": "system", "content": "你是一个专业的文档整理助手"},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.3,
-            stream=False
-        )
-        # 将返回的html代码保存成文件
-        yield {"data": response.choices[0].message.content}
+        # 调用阿里云大模型
+        html_content = client.chat(prompt)
+        yield {"data": html_content}
     except Exception as e:
         yield {"data": f"生成报告时出错: {str(e)}"}
     finally:
@@ -255,9 +240,9 @@ async def rag_stream(request: Request):
     except Exception as e:
         logger.error(f"请求解析失败: {str(e)}")
         raise HTTPException(status_code=400, detail="无效的请求格式")
-    """RAG+DeepSeek接口"""
+    """RAG+ALiYun接口"""
     async for chunk in generate_stream(
-            request.app.state.deepseek_client,
+            request.app.state.aliyun_util,
             request.app.state.milvus_pool,
             request.app.state.collection_manager,
             query_request.query,