Wenda: A Platform for Building Private Knowledge Bases in Enterprises Based on Large Models
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Intelligent customer service, Personal Care Assistant and enterprise "digital separation" based on enterprise private knowledge baseConstruction and other application scenarios have become popular applications based on the LLM large model. Today, we recommend a project through which we can innovate our own private knowledge base products
Intelligent customer service, Personal Care Assistant and enterprise "digital separation" based on enterprise private knowledge baseConstruction and other application scenarios have become popular applications based on the LLM large model. Today, we recommend a project through which we can innovate our own private knowledge base products. No nonsense, go to the link.

address
https://github.com/wenda-LLM/wenda#rtst%E6%A8%A1%E5%BC%8F
brief introduction

The design goal of this project is to achieve efficient content generation for specific environments, while consideringLimitations of computing resources for individuals and small and medium-sized enterprises, as well as knowledge security and privacy issues. To achieve the goal, the platform integrates the following capabilities:
- knowledge base: SupportedDocking with local offline vector library, local search engines, online search engines, etc.
twoMultiple Large Language ModelsCurrently, offline deployment models are supportedChatGLM-6BchatGLM2-6B, chatRWKV, llama series (not recommended for Chinese users), moss (not recommended), baichuan (needs to be used with lora, otherwise the effect is poor), Aquila-7B, InternLMOnline API accessOpenaiAPI and chatGLM-130bapi.
threeAuto Script:By developing JavaScript scripts in the form of pluginsAPILoRA.
:Dialogue history management, intranet deployment, and simultaneous use by multiple users.

Supported Model Categories

knowledge base
knowledge base:searchknowledge base.RTST modeCalculate semantics and match in local databases;Fess modesearchbingsearchsearch.
knowledge baseAuto.
knowledge baseknowledge base.

:
- RTST modesentence_transformers+faiss.
- Bing mode, cn. bing search, only available in China
- Bingsite mode, cn. bing website search, only available in China
- Fess modefesssearch
RTST mode
sentence_transformers+faiss.txtpdf.
cudaconfig.yml(example.config.yml)rtstdevice(embedding)12GCPU.
Windows:
plugins/buils_rtst_default_index.bat.
Linux directly uses the Wenda environment to execute Python plugins/gen_ Data_ St.py
modeltxttxt.
:
- GanymedeNil/text2vec-large-chinese is no longer recommended, does not support English and has high graphics memory usage
- Recommendations for moka ai/m3e base
Fess mode
fess.config.yml(example.config.yml)fess_host127.0.0.1:8080.
FESS:
https://github.com/wenda-LLM/wenda/blob/main/install_fess.md
knowledge base

Text matching

search
Secondary development based on this project
wenda-webuiaddress:
https://github.com/AlanLee1996/wenda-webui

Word plugin
address:
https://qun.qq.com/qqweb/qunpro/share?_wv=3& _ Wwv=128& AppChannel=share& InviteCode=20s7Vs0iZMx& ContentID=1mlnYv& BusinessType=2& From=181174& ShareSource=5& Biz=ka
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