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53 lines
1.7 KiB
Markdown
53 lines
1.7 KiB
Markdown
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<img src="https://github.com/InternLM/HuixiangDou/releases/download/v0.1.0rc1/huixiangdou.jpg" width="64" height="auto" />
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# [HuixiangDou](https://github.com/InternLM/HuixiangDou)
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"HuixiangDou" is a domain knowledge assistant based on LLM. Features:
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1. Handles complex scenarios such as group chat and handle answer user questions without flooding messages.
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2. Proposes a solution for technical issues through an algorithm pipeline.
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3. Low cost, see [arxiv2401.08772](https://arxiv.org/abs/2401.08772)
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# Demonstration
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HuixiangDou is a **assistant**
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* Says it doesn't know in response to halluciations
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* Personal Wechat supported
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* Feishu supported
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<img src="https://github.com/InternLM/HuixiangDou/releases/download/v0.1.0rc1/demo0.jpg" width="400">
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HuixiangDou is a **group** assistant
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* Ignores idle talk
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* Only interacts with those who need help
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<img src="https://github.com/InternLM/HuixiangDou/releases/download/v0.1.0rc1/inside-mmpose.jpg" width="400">
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HuixiangDou is a **domain knowledge** group assistant
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* Relies on an algorithm pipeline + LLM instead of training
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* Has faced thousands of users, and has been "teased" over 20,000 times in half a year
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<img src="https://github.com/InternLM/HuixiangDou/releases/download/v0.1.0rc1/inside-middleware.png" width="400">
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# Configuring deepseek API
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**STEP1.** Apply for a token at deepseek open platform
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**STEP2.** Follow the HuixiangDou Advanced Configuration and fill in the config.ini with your token
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```ini
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# config.ini
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[llm]
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enable_local = 0
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enable_remote = 1
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..
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[llm.server]
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..
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remote_type = "deepseek"
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remote_api_key = "YOUR-API-KEY"
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remote_llm_max_text_length = 16000
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remote_llm_model = "deepseek-chat"
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```
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**STEP3.** Run
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```shell
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python3 -m huixiangdou.main --standalone
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```
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