From f059f9fce40d6b35fa95899bbed11572b299b178 Mon Sep 17 00:00:00 2001
From: HuangHai <10402852@qq.com>
Date: Wed, 16 Jul 2025 22:16:36 +0800
Subject: [PATCH] 'commit'

---
 dsLightRag/Config/Config.py                   |  14 +++++++-------
 .../Config/__pycache__/Config.cpython-310.pyc | Bin 888 -> 911 bytes
 dsLightRag/Start.py                           |   9 +++++----
 dsLightRag/Util/LightRagUtil.py               |   3 +--
 .../__pycache__/LightRagUtil.cpython-310.pyc  | Bin 4496 -> 4496 bytes
 5 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/dsLightRag/Config/Config.py b/dsLightRag/Config/Config.py
index 27d78a80..920f3a4b 100644
--- a/dsLightRag/Config/Config.py
+++ b/dsLightRag/Config/Config.py
@@ -3,15 +3,15 @@ ALY_AK = 'LTAI5tE4tgpGcKWhbZg6C4bh'
 ALY_SK = 'oizcTOZ8izbGUouboC00RcmGE8vBQ1'
 
 # 大模型 【DeepSeek深度求索官方】训练时用这个
-LLM_API_KEY = "sk-44ae895eeb614aa1a9c6460579e322f1"
-LLM_BASE_URL = "https://api.deepseek.com"
-LLM_MODEL_NAME = "deepseek-chat"
+# LLM_API_KEY = "sk-44ae895eeb614aa1a9c6460579e322f1"
+# LLM_BASE_URL = "https://api.deepseek.com"
+# LLM_MODEL_NAME = "deepseek-chat"
 
 # 阿里云提供的大模型服务 【阿里云在处理文字材料时，容易引发绿网拦截，导致数据上报异常】
-#LLM_API_KEY = "sk-f6da0c787eff4b0389e4ad03a35a911f"
-#LLM_BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
-#LLM_MODEL_NAME = "qwen-plus" # 不要使用通义千问，会导致化学方程式不正确！
-#LLM_MODEL_NAME = "deepseek-v3"
+LLM_API_KEY = "sk-f6da0c787eff4b0389e4ad03a35a911f"
+LLM_BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
+# LLM_MODEL_NAME = "qwen-plus" # 不要使用通义千问，会导致化学方程式不正确！
+LLM_MODEL_NAME = "deepseek-v3"
 #LLM_MODEL_NAME = "deepseek-r1"  # 使用更牛B的r1模型
 
 EMBED_MODEL_NAME = "BAAI/bge-m3"
diff --git a/dsLightRag/Config/__pycache__/Config.cpython-310.pyc b/dsLightRag/Config/__pycache__/Config.cpython-310.pyc
index c551f7f6a39e4d9881c562acb9a358f2569fd42f..831e7f6a6edea7247ad01162aee4bba3dc3ef8b4 100644
GIT binary patch
delta 135
zcmeyt*3ZtH&&$ij00g^cm1js!<lU8!W|op@kZf*Yo|=|sl4M|PVVP=@m||d@Xl$Bj
zX=s>MWtdS?Qc!HAub+}woKc*dUy!Pon3GvqnwMOxmz<xg55xtDC7DS%sk*uODXIEp
khE?1tsi_6Usj1nzWyYHY7+smzIanB3m{^!6$1uwP06Ft1UjP6A

delta 136
zcmeBY|G~za&&$ij00bXh$}&VJ^6v69F-c6dury6gO)@hyNlY|Mv`jWLF*7hVw@fuQ
zGD<V7lE^42DJZtm*H0|S)JsWCEhtV+&DKlK&#mHx@pO|j5=%C#GrBS<GqW%PAt#sw
Pv6w(C4n`J;IG7Cp7#SZ^

diff --git a/dsLightRag/Start.py b/dsLightRag/Start.py
index dadd8cbd..6632ceb0 100644
--- a/dsLightRag/Start.py
+++ b/dsLightRag/Start.py
@@ -61,8 +61,9 @@ async def rag(request: fastapi.Request):
     if output_model == "txt":
         user_prompt = "1、如果资料中提供了图片的，一定要严格按照原文提供图片输出，绝对不能省略或不输出！"
         user_prompt = user_prompt + "\n 2、不要提供引用信息！"
-        user_prompt = user_prompt + "\n 3、提供给你的材料中，与问题完全相关的需要完整保留！"
-        user_prompt = user_prompt + "\n 4、提供给你的材料中，与问题不完全相关的一定不要输出！"
+        user_prompt = user_prompt + "\n 3、依据提供的材料，判断是否与问题强相关，强相关的可以适当发挥！"
+        #user_prompt = user_prompt + "\n 3、提供给你的材料中，与问题完全相关的需要完整保留！"
+        #user_prompt = user_prompt + "\n 4、提供给你的材料中，与问题不完全相关的一定不要输出！"
         user_prompt = user_prompt + "\n 5、资料中提供化学反应方程式的，一定要严格按提供的Latex公式输出，绝对不允许对Latex公式进行修改 ！"
         user_prompt = user_prompt + "\n 6、发现输出内容中包含Latex公式的，一定要检查是不是包含了$$或$的包含符号,不能让Latex无包含符号出现！"
     elif output_model == 'html':
@@ -106,7 +107,7 @@ async def rag(request: fastapi.Request):
 
     # 使用PG库后，这个是没有用的,但目前的项目代码要求必传，就写一个吧。
     WORKING_DIR = './output/'
-    async def generate_response_stream(query: str):
+    async def generate_response_stream(query: str, workspace: str):
         try:
             logger.info("workspace=" + workspace)
             # 使用锁确保线程安全
@@ -128,7 +129,7 @@ async def rag(request: fastapi.Request):
                 # 发送流结束标记
                 yield "data: [DONE]\n\n"
 
-    return EventSourceResponse(generate_response_stream(query=query))
+    return EventSourceResponse(generate_response_stream(query=query, workspace=workspace))
 
 
 @app.post("/api/save-word")
diff --git a/dsLightRag/Util/LightRagUtil.py b/dsLightRag/Util/LightRagUtil.py
index b1f78cd2..d3d4640b 100644
--- a/dsLightRag/Util/LightRagUtil.py
+++ b/dsLightRag/Util/LightRagUtil.py
@@ -170,8 +170,7 @@ async def initialize_pg_rag(WORKING_DIR, workspace):
         graph_storage="PGGraphStorage",
         vector_storage="PGVectorStorage",
         auto_manage_storages_states=False,
-        vector_db_storage_cls_kwargs={"workspace": workspace}
-    )
+        vector_db_storage_cls_kwargs={"workspace": workspace})
 
     await rag.initialize_storages()
     await initialize_pipeline_status()
diff --git a/dsLightRag/Util/__pycache__/LightRagUtil.cpython-310.pyc b/dsLightRag/Util/__pycache__/LightRagUtil.cpython-310.pyc
index 717962affaee6574c0508615a2059626760d037f..48f183de899d1f4eef7731b38c3f71bf18ec5bf3 100644
GIT binary patch
delta 29
jcmbQBJVBW^pO=@50SIarlxIBO$SW$qD7;x&AeRvUY<>qd

delta 29
jcmbQBJVBW^pO=@50SGQ7lxMu%$SW$qD6&~uAeRvUZd?aZ