choco builder

ChocoBuilder (aka Chocolate Factory)

Read the docs →

What is ChocoBuilder?

ChocoBuilder (origin Chocolate Factory) 是一款開源的LLM 應用開發框架，旨在幫助您輕鬆打造強大的軟件開發SDLC + LLM 生成助手。

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

QuickStart

方式1：集成到JVM 項目中

模塊列表：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
}

更多示例見：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:

• https://github.com/unit-mesh/auto-dev - The AI-powered coding wizard with multilingual support , auto code generation , and a helpful bug-slaying assistant
• https://github.com/phodal/shire - AI Coding Agent Language

Server:

• https://github.com/unit-mesh/devops-genius/

Android:

• https://github.com/unit-mesh/android-semantic-search-kit

Development

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

Design Philosophy: Domain Driven Problem-Solving

The key concepts of ChocoBuilder are:

(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

• Online Demo: https://framework.unitmesh.cc/ (TODO)
• Video Demo: https://www.bilibili.com/video/BV1T14y1C7p2
• Gif Demo:

Example 1: Frontend Screenshot

• 步驟1：ProblemClarifier：使用響應式佈局，編寫一個聊天頁面
  • 步驟1.1：ProblemClarifier：左邊是一個導航，中間是聊天區，聊天區的下方是一個輸入按鈕。
• 步驟2：SolutionDesigner：請確認以下的設計是否符合您的要求。如果符合，請回复"YES"，如果不符合，請提出你的要求。
• 步驟3：SolutionExecutor：生成一個聊天頁面

Example 2: 語義化代碼搜索

• 步驟1：ProblemAnalyzer 分析用戶的需求，轉為成多個語義化的查詢
  • 中文、英文、HyDE 模式
• 步驟2：SolutionExecutor：根據用戶的需求，從數據庫中檢索出最相關的代碼片段，由ChatGPT 做總結

示例輸入：Semantic Workflow 是如何實現的？

最終輸出：

Example 3: Testcase Generator

• 步驟1：ProblemAnalyzer 分析用戶的需求，確認是否是一個測試用例生成的需求
  • 多Temperature 模式：TemperatureMode.Default, TemperatureMode.Creative
• 步驟2：SolutionDesigner 設計測試用例生成的方案
• 步驟3：SolutionReviewer 確認方案是否符合用戶的需求

示例輸入：用戶發表文章

最終輸出：

Examples 4: Code Interpreter

• 步驟1：SolutionExecutor

示例1：編寫乘法表

輸出示例：

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：根據需求生成圖表（TODO）

生成一個2023 年上半年電費圖，信息如下：###1~6 月：201.2,222,234.3,120.2,90,90.4###

過程代碼：

 %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")

最終輸出：

License

RAG relevant modules were inspired by

• LangChain4j
• LangChain
• LlamaIndex
• Spring AI

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.