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