## More details about the configuration file can be found in: https://github.com/allwefantasy/auto-coder/tree/master/docs/en
## 关于配置文件的更多细节可以在这里找到: https://gitcode.com/allwefantasy11/auto-coder/tree/master/docs/zh

## Location of your project
## 你项目的路径
source_dir: /Users/dengwendi/Documents/project/template/ruoyi-ui

## The target file to store the prompt/generated code or other information
target_file: /Users/dengwendi/Documents/project/template/ruoyi-ui/output.txt

## The urls of some documents which can help the model to understand your current work
## 一些文档的URL，可以帮助模型了解你当前的工作
## Multiple documents can be separated by comma
## 多个文档可以用逗号分隔
# urls: <SOME DOCUMENTATION URLs>

## The type of your project. py,ts or you can use the suffix e.g. .java .scala .go 
## If you use the suffix, you can combind multiple types with comma e.g. .java,.scala
## 你项目的类型，py,ts或者你可以使用后缀，例如.java .scala .go
## 如果你使用后缀，你可以使用逗号来组合多个类型，例如.java,.scala
project_type: py

## The model you want to drive AutoCoder to run
model: gpt3_5_chat


## Enable the index building which can help you find the related files by your query
## 启用索引构建，可以帮助您通过查询找到相关文件
skip_build_index: false
## The model to build index for the project (Optional)
## 用于为项目构建索引的模型（可选）
index_model: haiku_chat

## the filter level to find the related files
## 0: only find the files with the file name
## 1: find the files with the file name and the symbols in the file
## 2. find the related files reffered by the files in 0 and 1
## 0 is recommended for the first time
## 用于查找相关文件的过滤级别
## 0: 仅查找文件名
## 1: 查找文件名和文件中的符号
## 2. 查找0和1中的文件引用的相关文件
## 第一次建议使用0
index_filter_level: 0
index_model_max_input_length: 30000

## The number of workers to filter the files
## 过滤文件的线程数量
## If you have a large project, you can increase this number
## 如果您有一个大项目，可以增加这个数字
## Make sure you you have the proper workers when you use `byzerllm` to deploy model.
## 当您使用 `byzerllm` 部署模型时，请确保你也配置了合适的 num_workers 参数。
index_filter_workers: 1

## The number of workers to build the index
## 构建索引的线程数量
## If you have a large project, you can increase this number
## 如果您有一个大项目，可以增加这个数字
## Make sure you you have the proper workers when you use `byzerllm` to deploy model.
## 当您使用 `byzerllm` 部署模型时，请确保你也配置了合适的 num_workers 参数。
index_build_workers: 1    

## enable RAG context
## 启用RAG上下文
enable_rag_context: false
## or you can give a query directly and enable the RAG at the same time
## 或者您可以直接给出一个查询，并同时启用RAG
# enable_rag_context_query: YOUR QUERY TO GET SOME CONTEXT BY RAG

## enable Search Engine
## 启用搜索引擎
## google/bing
# search_engine: bing
## Get the search engine token in the environment variable
## 在环境变量中获取搜索引擎令牌
## Ask for Bing Search API Token. You can visit https://www.microsoft.com/en-us/bing/apis/bing-web-search-api to get the token.
## 申请 Bing 搜索API Token。你可以访问 https://www.microsoft.com/en-us/bing/apis/bing-web-search-api 获取 token。
# search_engine_token: ENV  


##  The model to build index for the project
## 用于为项目构建索引的模型
# emb_model: gpt_emb

## The model will generate the code for you
## 模型将为您生成代码
execute: true

## If you want to generate multiple files, you can enable this option to generate the code in multiple rounds
## to avoid exceeding the maximum token limit of the model
## 如果您想生成多个文件，可以启用此选项，以便在多个回合中生成代码
## 以避免超过模型的最大令牌限制
enable_multi_round_generate: false

## AutoCoder will merge the generated code into your project
## AutoCoder将合并生成的代码到您的项目中
auto_merge: true

## AutoCoder will ask you to deliver the content to the Web Model,
## then paste the answer back to the terminal
## AutoCoder将要求您将内容传递给Web模型，然后将答案粘贴回终端
human_as_model: true

## What you want the model to do
## 你想让模型做什么
query: |  
  YOUR QUERY HERE   


## You can execute this file with the following command
## And check the output in the target file
## 您可以使用以下命令执行此文件
## 并在目标文件中检查输出
## auto-coder --file 101_current_work.yml