787b3f56ab
Add comprehensive AGENTS.md documentation files across the project structure to document the agent architecture and capabilities. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
143 lines
4.2 KiB
Markdown
143 lines
4.2 KiB
Markdown
# Modules Knowledge Base
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**Scope:** `VBA/Modules/` - Procedural workflows and entry points
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## OVERVIEW
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4 modules: `MainModule` (main workflow), `BIPUploadModule` (upload results), `ComponentInventoryCheckModule` (inventory check), `TestModule` (testing utilities).
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## STRUCTURE
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```
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Modules/
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├── MainModule.bas # Main entry point + orchestration
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├── BIPUploadModule.bas # Upload to BIP system
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├── ComponentInventoryCheckModule.bas # Component inventory verification
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└── TestModule.bas # Testing utilities
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```
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## WHERE TO LOOK
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| Task | Location | Notes |
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|------|----------|-------|
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| Run BOM extraction | `MainModule.bas` | `ProcessProductModels()` |
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| Upload results | `BIPUploadModule.bas` | BIP system integration |
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| Check inventory | `ComponentInventoryCheckModule.bas` | Component count verification |
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| Test parsing | `TestModule.bas` | Unit test utilities |
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## CODE MAP
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### MainModule
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| Function | Role |
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|----------|------|
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| `ProcessProductModels()` | Main entry point, orchestrates workflow |
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| `ProcessSingleModel()` | Process one model, collect output |
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| `CreateOutputRowArray()` | Build row data array |
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| `WriteBatchData()` | Bulk write to worksheet |
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| `GetInputSheet()` | Get `产品订单` sheet |
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| `GetBomSheet()` | Get `平台配置清单` sheet |
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| `CreateOutputSheet()` | Create/reset `BOM 提取结果` |
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### BIPUploadModule
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| Function | Role |
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|----------|------|
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| `UploadToBIP()` | Upload BOM results to BIP system |
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### ComponentInventoryCheckModule
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| Function | Role |
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|----------|------|
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| `CheckComponentInventory()` | Verify component counts match |
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## CONVENTIONS
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### Module Structure
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```vba
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Option Explicit
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' Constants
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Private Const CONDITION_CONFIG = "azxs，安装形式|bkxs，表壳形式|..."
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' Public entry points
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Public Sub MainEntryPoint()
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On Error GoTo ErrorHandler
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' Orchestration
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Exit Sub
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ErrorHandler:
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MsgBox "Error: " & Err.Description
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End Sub
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' Private helpers
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Private Sub HelperFunction()
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' Implementation
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End Sub
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```
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### Workflow Pattern
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1. Get input sheet (`产品订单`)
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2. Get BOM sheet (`平台配置清单`)
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3. Create output sheet (`BOM 提取结果`)
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4. Initialize `BomExtractor`, load data
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5. Loop through models, call `ProcessSingleModel()`
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6. Batch write results
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7. Format output, show message
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### Batch Output Pattern
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```vba
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' Collect in Collection
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Dim outputData As Collection
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Set outputData = New Collection
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' Add arrays
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outputData.Add CreateOutputRowArray(...)
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' Convert to 2D array
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ReDim resultData(1 To rowCount, 1 To colCount)
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' Fill array...
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' Single write
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ws.Range("A2").Resize(rowCount, colCount).Value = resultData
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```
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## ANTI-PATTERNS (THIS PROJECT)
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- **NEVER** hardcode sheet names — use `GetInputSheet()`, `GetBomSheet()` helpers
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- **NEVER** write row-by-row — always batch write via 2D array
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- **NEVER** skip error handling — all public subs use `On Error GoTo ErrorHandler`
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- **DO NOT** change output column order — must match header definition in `WriteOutputHeader()`
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## UNIQUE STYLES
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### Condition Config Constant
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```vba
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Private Const CONDITION_CONFIG = "azxs，安装形式|bkxs，表壳形式|gclj，过程连接|jycz，接液材质|lcfw，量程范围|fjgn，附加功能"
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```
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Format: `code,label|code,label|...` — parsed dynamically for header generation.
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### Component Priority Flag
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From column E of input sheet:
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- "是" (or "1", "TRUE") → include all categories
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- "否" (or "0", "FALSE") → exclude "部件" (components) category
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### Output Row Structure
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```
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Column 1: 生产订单号 (order number)
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Column 2: 产品型号 (full model)
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Columns 3-8: 6 conditions (azxs, bkxs, gclj, jycz, lcfw, fjgn)
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Columns 9-16: BOM fields (行号，模块，代号，名称，数量，类别，66 代码，备注)
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```
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## NOTES
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### Output Sheet Formatting
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- Row 1: Bold, gray background (RGB 217,217,217), centered
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- Data starts at row 2
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- AutoFit columns (commented out in current code)
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### Error Messages
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- Parse failure: `"解析失败：" + error`
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- No match: `"未匹配到任何物料"`
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- Multi-match: `"类别[X] 匹配到多条物料(N 条)"` — outputs all but flags
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### Performance
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Batch write via `Range.Value = resultData` is 10-100x faster than cell-by-cell writes for large datasets.
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