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# LLM function calling 示例
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## 功能介绍
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## 安装
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1. clone 本项目
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```shell
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git clone http://1.14.96.249:3000/old-tom/llmFunctionCallDemo.git
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```
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2. 创建虚拟环境
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+ 这里使用的是pipenv,可以换成uv或者conda
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+ python 版本为 3.10或以上稳定版即可
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```shell
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cd llmFunctionCallDemo （clone的代码目录）
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```
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```shell
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pipenv install --python 3.10
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```
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3. 安装依赖
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```shell
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pip install -r requirements.txt
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```
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4. 向量库部署和初始化 (docker)
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```shell
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docker run --name marqo -it --privileged -p 8882:8882 --add-host host.docker.internal:host-gateway marqoai/marqo:latest
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```
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初始化：执行[vector_db.py](vector_db.py) create_and_set_index()方法
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测试：执行[vector_db.py](vector_db.py) query_vector_db() 方法,参数为任意字符串
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5. 配置文件
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[env.toml](env.toml)
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```toml
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[base]
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# 多轮对话历史存储类型（memory：内存）
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history_chat_store = 'memory'
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# 相似度阈值
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similarity_threshold = 0.93
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# dev
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dev = true
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####### 模型配置 #######
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[siliconflow]
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# 硅基流动
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# 密钥
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api_key = ''
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# 模型名称
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model = ''
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# API地址
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base_url = ''
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# 最大token数
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max_tokens = 4096
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# 温度系数
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temperature = 0.6
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# 是否流式返回
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streaming = true
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```
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## TestCase
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## TODO
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