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 c551f7f6..831e7f6a 100644 Binary files a/dsLightRag/Config/__pycache__/Config.cpython-310.pyc and b/dsLightRag/Config/__pycache__/Config.cpython-310.pyc differ 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 717962af..48f183de 100644 Binary files a/dsLightRag/Util/__pycache__/LightRagUtil.cpython-310.pyc and b/dsLightRag/Util/__pycache__/LightRagUtil.cpython-310.pyc differ