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ChocoBuilder (Chocolate Factory) is a cutting-edge LLM toolkit designed to empower you in creating your very own AI assistant.Chocolate Factory 是一款开源的 LLM 应用开发框架,旨在帮助您轻松打造强大的软件开发 SDLC + LLM 生成助手。无论您是需要生成前端页面、后端 API、SQL 图表,还是测试用例数据,Chocolate Factory 都能满足您的需求。

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ChocoBuilder (aka Chocolate Factory)

stars CI Docker Image Version (latest semver) Maven

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What is ChocoBuilder?

ChocoBuilder (origin Chocolate Factory) 是一款开源的 LLM 应用开发框架,旨在帮助您轻松打造强大的软件开发 SDLC + LLM 生成助手。

For native (Android/iOS/Embedded device) SDK: see in https://github.com/unit-mesh/edge-infer

Architecture

QuickStart

方式 1:集成到 JVM 项目中

模块列表:https://central.sonatype.com/namespace/cc.unitmesh

dependencies {
    // 核心模块
    implementation 'cc.unitmesh:cocoa-core:1.0.0'
    // Pinecone
    implementation 'cc.unitmesh:store-pinecone:1.0.0'
    // ElasticSearch
    implementation 'cc.unitmesh:store-elasticsearch:1.0.0'
    //...其它模块
}

更多示例见:examples/

方式 2:使用 RAGScript

@file:DependsOn("cc.unitmesh:rag-script:1.0.0")

import cc.unitmesh.rag.*

rag {
    indexing {
        val chunks = document("README.md").split()
        store.indexing(chunks)
    }

    querying {
        store.findRelevant("workflow dsl design ")
            .lowInMiddle()
            .also {
                println(it)
            }
    }
}

方式 3:本地部署示例

git clone https://github.com/unit-mesh/chocolate-factory
# modify OPENAI_API_KEY and OPENAI_HOST in docker-compose.yml
docker-compose up

Use Cases

Desktop/IDE:

Server:

Android:

Development

See in https://framework.unitmesh.cc/ or see in documents

Design Philosophy: Domain Driven Problem-Solving

The key concepts of ChocoBuilder are:

ChocoBuilder Concepts

(PS: Origin made by Michael Plöd at Aligning organization and architecture with strategic DDD)

A user's problem is processed by the following steps:

  1. ProblemClarifier.kt
  2. ProblemAnalyzer.kt
  3. SolutionDesigner.kt
  4. SolutionReviewer.kt
  5. SolutionExecutor.kt

Example 1: Frontend Screenshot

  • 步骤 1:ProblemClarifier:使用响应式布局,编写一个聊天页面
    • 步骤 1.1:ProblemClarifier:左边是一个导航,中间是聊天区,聊天区的下方是一个输入按钮。
  • 步骤 2:SolutionDesigner:请确认以下的设计是否符合您的要求。如果符合,请回复"YES",如果不符合,请提出你的要求。
  • 步骤 3:SolutionExecutor:生成一个聊天页面

Frontend

Example 2: 语义化代码搜索

  • 步骤 1:ProblemAnalyzer 分析用户的需求,转为成多个语义化的查询
    • 中文、英文、HyDE 模式
  • 步骤 2:SolutionExecutor:根据用户的需求,从数据库中检索出最相关的代码片段,由 ChatGPT 做总结

示例输入:Semantic Workflow 是如何实现的?

最终输出:

Semantic

Example 3: Testcase Generator

  • 步骤 1:ProblemAnalyzer 分析用户的需求,确认是否是一个测试用例生成的需求
    • 多 Temperature 模式:TemperatureMode.Default, TemperatureMode.Creative
  • 步骤 2:SolutionDesigner 设计测试用例生成的方案
  • 步骤 3:SolutionReviewer 确认方案是否符合用户的需求

示例输入:用户发表文章

最终输出:

Testcases

Examples 4: Code Interpreter

  • 步骤 1:SolutionExecutor

示例 1:编写乘法表

输出示例:

1    2    3    4    5    6    7    8    9
2    4    6    8    10    12    14    16    18
3    6    9    12    15    18    21    24    27
4    8    12    16    20    24    28    32    36
5    10    15    20    25    30    35    40    45
6    12    18    24    30    36    42    48    54
7    14    21    28    35    42    49    56    63
8    16    24    32    40    48    56    64    72
9    18    27    36    45    54    63    72    81    

示例 2:根据需求生成图表 (TODO)

生成一个 2023 年上半年电费图,信息如下:###1~6 月:201.2,222,234.3,120.2,90,90.4###

过程代码:

%use lets-plot

import kotlin.math.PI
import kotlin.random.Random


val incomeData = mapOf(
    "x" to listOf("一月", "二月", "三月", "四月", "五月", "六月"),
    "y" to listOf(201.2, 222, 234.3, 120.2, 90, 94.4)
)
letsPlot(incomeData) { x = "x"; y = "y" } +
        geomBar(stat = Stat.identity) +
        geomText(labelFormat = "\${.2f}") { label = "y"; } +
        ggtitle("2023 年上半年电费")

最终输出:

Frontend

License

RAG relevant modules were inspired by

Some RAG modules based on LangChain4j and Spring AI which is licensed under the Apache License 2.0.

This code is distributed under the MPL 2.0 license. See LICENSE in this directory.

About

ChocoBuilder (Chocolate Factory) is a cutting-edge LLM toolkit designed to empower you in creating your very own AI assistant.Chocolate Factory 是一款开源的 LLM 应用开发框架,旨在帮助您轻松打造强大的软件开发 SDLC + LLM 生成助手。无论您是需要生成前端页面、后端 API、SQL 图表,还是测试用例数据,Chocolate Factory 都能满足您的需求。

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