feat: service inventory, ERP reports, sqlite-vec integration, visualize tool
- Add SERVICE_INVENTORY_V1.0.0.md (25 source-verified tools, 3.7GB) - Add ERP_SELECTION_REPORT.md (Odoo CE vs ERPNext comparison) - Add SFTPGO_ODOO_REPLACEMENT.md (SFTPGo migration plan) - Add SERVICE_GO_GITEA_BUILD.md (Go compiler + Gitea build report) - Add release visualize command (face trace heatmap + identity filter) - Add sqlite-vec integration (160MB SQLite with vec0 vector tables) - Add export_identities.py, export_sqlite.py, render_face_heatmap.py - Add Go, Gitea, Rust/Cargo, Swift, yt-dlp, SQLite, sqlite-vec to service CLI - Fix package to include identities and identity_bindings in data.sql - Update release list to show all deployed video stats - Add V1.0.0 YAML frontmatter to all docs (DOCS_STANDARD compliant)
This commit is contained in:
Accusys
@@ -128,6 +128,14 @@ path = "src/bin/test_bm25_simple.rs"
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name = "integrated_player"
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path = "src/bin/integrated_player.rs"
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[[bin]]
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name = "release"
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path = "src/bin/release.rs"
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[[bin]]
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name = "service"
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path = "src/bin/service.rs"
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[build-dependencies]
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chrono = "0.4"
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167
docs_v1.0/M4_workspace/REPORTS/ERP_COMPARISON_TABLE.md
Normal file
167
docs_v1.0/M4_workspace/REPORTS/ERP_COMPARISON_TABLE.md
Normal file
@@ -0,0 +1,167 @@
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---
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document_type: "reference_doc"
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service: "MOMENTRY_CORE"
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title: "ERP Comparison Table — Odoo CE vs ERPNext Feature Matrix"
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date: "2026-05-13"
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version: "V1.0"
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status: "active"
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owner: "M5"
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created_by: "OpenCode"
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tags:
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- "erp"
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- "odoo"
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- "erpnext"
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- "comparison"
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- "bom"
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- "manufacturing"
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- "billing"
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- "electronics"
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ai_query_hints:
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- "Odoo CE vs ERPNext 功能對比表"
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- "ERPNext 替代料功能是否比 Odoo CE 強"
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- "Odoo CE 是否支援 BOM 版控"
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- "Odoo CE vs ERPNext 電子製造業適合哪個"
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- "ERP feature comparison table for Odoo and ERPNext"
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related_documents:
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- "M5_workspace/RESEARCH/ERP_SELECTION_REPORT.md"
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- "M5_workspace/RESEARCH/SFTPGO_ODOO_REPLACEMENT.md"
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---
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# ERP Function Comparison Table — Odoo CE vs ERPNext
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| 項目 | 內容 |
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|------|------|
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| 調查者 | M5 Team |
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| 文件版本 | V1.0 |
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| 建立日期 | 2026-05-13 |
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---
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## 版本歷史
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| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
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|------|------|------|--------|-----------|
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| V1.0 | 2026-05-13 | 建立 ERP 功能對比表 | OpenCode | deepseek-v4-pro |
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---
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> Source verified via actual source code: Odoo CE `addons/mrp/models/`, ERPNext `erpnext/manufacturing/doctype/`
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> 標記：✅ CE/Free 支援 | ❌ 不支援 | ⚠️ 需 custom/有限 | (EE) Odoo Enterprise only
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## 一、Billing / 開票帳務
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| 功能 | Odoo CE | ERPNext |
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|------|:--:|:--:|
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| 客戶發票 | ✅ | ✅ |
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| 供應商帳單 | ✅ | ✅ |
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| 付款追蹤 | ✅ | ✅ |
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| 線上付款 | ✅ 25+ | ✅ |
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| 定期訂閱 | ❌ (EE) | ✅ |
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| 多幣別 | ✅ | ✅ |
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| 稅務在地化 | ✅ 50+ 國 | ✅ |
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| 銀行對帳 | ✅ | ✅ |
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| P&L / BS 報表 | ✅ | ✅ |
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| 退款/折讓 | ✅ | ✅ |
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## 二、Membership / 會員系統
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| 功能 | Odoo CE | ERPNext |
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|------|:--:|:--:|
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| 會員註冊 | ✅ website | ✅ |
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| 會員分級 (Gold/Silver/Free) | ✅ Product variants | ✅ |
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| 會籍有效期 | ❌ (EE) | ✅ |
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| 自動續約 | ❌ (EE) | ✅ |
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| eWallet / 點數 | ✅ loyalty | ✅ |
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| 登入整合 (OAuth/API) | ✅ | ✅ |
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## 三、BOM 核心結構
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| 功能 | Odoo CE | ERPNext |
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|------|:--:|:--:|
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| Multi-level BOM | ✅ | ✅ |
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| Component Qty + UOM | ✅ | ✅ |
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| Reference Designator | ⚠️ code 欄位 | ✅ |
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| Phantom / Kit BOM | ✅ | ✅ |
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| By-Products | ✅ | ✅ |
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| Scrap 報廢 | ✅ | ✅ |
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| BOM 成本計算 | ✅ auto | ⚠️ manual |
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| BOM 匯入/匯出 | ✅ Excel | ✅ CSV |
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| Substitute Items | ❌ | ✅ |
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| BOM Version / Revision | ❌ (EE) | ✅ |
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| BOM Comparison Tool | ❌ | ✅ |
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| BOM 圖片/附件 | ✅ | ✅ |
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## 四、產線管理
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| 功能 | Odoo CE | ERPNext |
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|------|:--:|:--:|
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| Work Centers | ✅ | ✅ Workstations |
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| Routing / 工序 | ✅ | ✅ |
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| Work Orders | ✅ | ✅ Job Cards |
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| Shop Floor Tablet UI | ❌ (EE) | ✅ |
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| Unbuild / 拆解 | ✅ | ❌ |
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| Subcontracting | ✅ 3 種 | ❌ |
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| MPS / 主排程 | ❌ (EE) | ✅ |
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| Time Tracking | ❌ (EE) | ✅ |
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## 五、品質管理
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| 功能 | Odoo CE | ERPNext |
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|------|:--:|:--:|
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| Quality Inspection | ❌ (EE) | ✅ |
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| In-process QC | ❌ (EE) | ✅ |
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| Non-conformance | ❌ (EE) | ✅ |
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## 六、PLM / ECO
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| 功能 | Odoo CE | ERPNext |
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|------|:--:|:--:|
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| ECO 工程變更 | ❌ (EE) | ❌ |
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| ECO Type / Stage | ❌ (EE) | ❌ |
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| 版本管控 | ❌ (EE) | ✅ |
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| Approval Workflow | ❌ (EE) | ❌ |
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## 七、物料追蹤
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| 功能 | Odoo CE | ERPNext |
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|------|:--:|:--:|
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| Lot / Serial Number | ✅ | ✅ |
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| Traceability | ✅ | ✅ |
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| Product Expiry | ✅ | ✅ |
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| Reorder / MRP | ✅ | ✅ |
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| AVL (Approved Vendor) | ❌ | ❌ |
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| RoHS / Compliance | ❌ | ❌ |
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## 八、授權與技術
|
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|
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| | Odoo CE | ERPNext |
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||||
|--|:--:|:--:|
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| License | **LGPL-3.0** | GPL-3.0 |
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| Framework License | LGPL-3.0 | **MIT** |
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| Database | **PostgreSQL** | MariaDB |
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| Language | Python + JS | Python + JS |
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| Stars | 50.6k | 33.8k |
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| Forks | 32.4k | 11.2k |
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| Modules | 200+ | 15+ |
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| Custom module license | **任意** | GPL 相容 |
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## 九、電子業 BOM 特別需求
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| 需求 | Odoo CE | ERPNext | 重要度 |
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|------|:--:|:--:|:--:|
|
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| 替代料 (AVL) | ❌ | ✅ | 🔴 必備 |
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| BOM Rev 管控 | ❌ (EE) | ✅ | 🔴 必備 |
|
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| SMT RefDes | ⚠️ | ⚠️ | 🔴 必備 |
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| 委外 SMT | ✅ | ❌ | 🟡 |
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||||
| ECO 工程變更 | ❌ (EE) | ❌ | 🟡 |
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| RoHS / Compliance | ❌ | ❌ | 🟡 |
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## 十、總結
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| 面向 | 推薦 |
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|------|------|
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| Billing + Membership | **Odoo CE** — PG 共用 + custom module 自由 |
|
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| BOM 基礎 + 委外 | **Odoo CE** — subcontracting + unbuild |
|
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| 電子業 BOM (替代料+QC) | **ERPNext** — 原生替代料 + 版控 + QC |
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| 長期授權保障 | **Odoo CE** — LGPL 比 GPL 鬆 |
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| 最小化 infra | **Odoo CE** — PG 與 Momentry 共用 |
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395
docs_v1.0/M4_workspace/REPORTS/ERP_SELECTION_REPORT.md
Normal file
395
docs_v1.0/M4_workspace/REPORTS/ERP_SELECTION_REPORT.md
Normal file
@@ -0,0 +1,395 @@
|
||||
---
|
||||
document_type: "reference_doc"
|
||||
service: "MOMENTRY_CORE"
|
||||
title: "ERP Selection Report — Odoo CE vs ERPNext for Momentry Core"
|
||||
date: "2026-05-13"
|
||||
version: "V1.0"
|
||||
status: "active"
|
||||
owner: "M5"
|
||||
created_by: "OpenCode"
|
||||
tags:
|
||||
- "erp"
|
||||
- "odoo"
|
||||
- "erpnext"
|
||||
- "selection"
|
||||
- "bom"
|
||||
- "manufacturing"
|
||||
- "billing"
|
||||
- "license"
|
||||
ai_query_hints:
|
||||
- "查詢 ERP 選型報告的結論與建議"
|
||||
- "Odoo CE vs ERPNext 授權比較"
|
||||
- "電子製造業 BOM 管理 Odoo vs ERPNext 哪個更適合"
|
||||
- "Odoo Community Edition 可以商用修改嗎"
|
||||
- "ERPNext GPL-3.0 授權對 Momentry 的影響"
|
||||
- "Odoo CE vs ERPNext 會員管理功能對比"
|
||||
- "Odoo CE billing system 能否取代現有系統"
|
||||
- "ERP selection report for Momentry Core"
|
||||
related_documents:
|
||||
- "M5_workspace/RESEARCH/ERP_COMPARISON_TABLE.md"
|
||||
- "M5_workspace/RESEARCH/SFTPGO_ODOO_REPLACEMENT.md"
|
||||
- "M4_M5_COLLABORATION_PROTOCOL.md"
|
||||
---
|
||||
|
||||
# ERP Selection Report — Odoo CE vs ERPNext for Momentry Core
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| 調查者 | M5 Team |
|
||||
| 文件版本 | V1.0 |
|
||||
| 建立日期 | 2026-05-13 |
|
||||
|
||||
---
|
||||
|
||||
## 版本歷史
|
||||
|
||||
| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
|
||||
|------|------|------|--------|-----------|
|
||||
| V1.0 | 2026-05-13 | 建立 Odoo CE vs ERPNext 選型報告 | OpenCode | deepseek-v4-pro |
|
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|
||||
---
|
||||
|
||||
## 關鍵術語定義
|
||||
|
||||
| 術語 | 定義 |
|
||||
|------|------|
|
||||
| CE | Community Edition（社群版，免費開源） |
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||||
| EE | Enterprise Edition（企業版，付費授權） |
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| BOM | Bill of Materials（物料清單） |
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| PLM | Product Lifecycle Management（產品生命週期管理） |
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| ECO | Engineering Change Order（工程變更單） |
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||||
| LGPL-3.0 | GNU Lesser General Public License v3 |
|
||||
| GPL-3.0 | GNU General Public License v3 |
|
||||
| AGPL-3.0 | GNU Affero General Public License v3 |
|
||||
|
||||
---
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## 目錄
|
||||
|
||||
1. [研究範圍與基準](#1-研究範圍與基準)
|
||||
2. [授權分析](#2-授權分析)
|
||||
3. [Billing 模組對比](#3-billing-模組對比)
|
||||
4. [BOM 管理對比](#4-bom-管理對比)
|
||||
5. [電子製造業 BOM 管理（源碼驗證）](#5-電子製造業-bom-管理源碼驗證)
|
||||
6. [雙系統協作可行性](#6-雙系統協作可行性)
|
||||
7. [技術整合架構](#7-技術整合架構)
|
||||
8. [授權風險矩陣](#8-授權風險矩陣)
|
||||
9. [建置成本](#9-建置成本)
|
||||
10. [結論與建議](#10-結論與建議)
|
||||
|
||||
---
|
||||
|
||||
## 1. 研究範圍與基準
|
||||
|
||||
### 研究對象
|
||||
|
||||
| 系統 | 版本 | 授權 | Source 位置 |
|
||||
|------|------|------|-----------|
|
||||
| **Odoo Community Edition** | 19.0 | LGPL-3.0 | `services/src/odoo/` (1.3GB) |
|
||||
| **ERPNext** | v15 | GPL-3.0 | `services/src/erpnext/` (97MB) |
|
||||
| **Frappe Framework** | v15 | MIT | `services/src/frappe/` (101MB) |
|
||||
|
||||
### 比較基準
|
||||
|
||||
- **Odoo CE**: 以 Community Edition 為基準，Enterprise-only 功能標記 `(EE)`
|
||||
- **ERPNext**: 全部免費功能
|
||||
- 所有 Odoo CE 功能已透過檢查 `addons/mrp/models/` 實際原始碼驗證
|
||||
- 所有 ERPNext 功能已透過檢查 `erpnext/manufacturing/doctype/` 實際原始碼驗證
|
||||
|
||||
---
|
||||
|
||||
## 2. 授權分析
|
||||
|
||||
### 核心授權比較
|
||||
|
||||
| | Odoo CE | ERPNext |
|
||||
|--|---------|---------|
|
||||
| ERP 授權 | **LGPL-3.0** | GPL-3.0 |
|
||||
| Framework 授權 | LGPL-3.0 (Odoo) | **MIT** (Frappe) |
|
||||
| 商用修改 | ✅ | ✅ |
|
||||
| SaaS（不散佈 binary）修改不需開源 | ✅ | ✅ (GPL) / ❌ (AGPL) |
|
||||
| 散佈修改需開源 | ⚠️ 修改部分 | ❌ 全部 |
|
||||
| 自訂模組授權 | 任意 | 需 GPL 相容 |
|
||||
| 品牌名稱 | "Odoo" 為註冊商標 | "ERPNext" 為註冊商標 |
|
||||
| 付費方案 | Enterprise (EE) | Hosting + Support |
|
||||
|
||||
### 對 Momentry 的影響
|
||||
|
||||
Momentry Core 使用 Rust（proprietary），與 ERP 透過 REST API 溝通。兩者程式碼不相依賴：
|
||||
|
||||
```
|
||||
✅ 無 LGPL/GPL 傳染風險 — API 橋接不構成 derivative work
|
||||
✅ Odoo custom addon 可用 proprietary license
|
||||
⚠️ ERPNext custom app 需 GPL-3.0 相容授權
|
||||
```
|
||||
|
||||
### ERPNext 的 AGPL 疑慮
|
||||
|
||||
ERPNext GitHub 標示 GPL-3.0，但 Frappe 官網 pricing page 稱 "AGPL-3.0 licensed"。
|
||||
AGPL 會限制 SaaS 修改的閉源性。建議正式使用前向 Frappe 確認授權。
|
||||
|
||||
---
|
||||
|
||||
## 3. Billing 模組對比
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| 客戶發票 (Invoice) | ✅ | ✅ |
|
||||
| 供應商帳單 (Vendor Bill) | ✅ | ✅ |
|
||||
| 付款追蹤 (Payment Follow-up) | ✅ | ✅ |
|
||||
| 線上付款 (Stripe, PayPal) | ✅ 25+ provider | ✅ |
|
||||
| 訂閱/定期計費 (Subscriptions) | ❌ (EE) | ✅ |
|
||||
| 多幣別 | ✅ | ✅ |
|
||||
| 稅務在地化 | ✅ 50+ 國 | ✅ |
|
||||
| 銀行對帳 | ✅ | ✅ |
|
||||
| 報表 (P&L, BS, AR) | ✅ | ✅ |
|
||||
| Credit Notes / 退款 | ✅ | ✅ |
|
||||
| 會員分級 / 方案管理 | ✅ (via Product variants) | ✅ |
|
||||
|
||||
**Odoo 優勢**: 付款 provider 多、50+ 國稅務在地化
|
||||
**ERPNext 優勢**: Subscriptions 內建（Odoo CE 需 EE）
|
||||
|
||||
---
|
||||
|
||||
## 4. BOM 管理對比
|
||||
|
||||
### 基礎 BOM 功能
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Multi-level BOM (sub-assembly) | ✅ | ✅ |
|
||||
| BOM component quantity + UOM | ✅ | ✅ |
|
||||
| Reference Designator (位號) | ⚠️ `code` 欄位 | ✅ |
|
||||
| Phantom / Kit BOM | ✅ (type=phantom) | ✅ |
|
||||
| By-Products / Co-Products | ✅ | ✅ |
|
||||
| Scrap 報廢 | ✅ | ✅ |
|
||||
| BOM 成本自動計算 | ✅ (from Purchase) | ⚠️ |
|
||||
| BOM 導入/匯出 | ✅ Excel | ✅ CSV |
|
||||
|
||||
### 產線管理
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Work Centers / Workstations | ✅ | ✅ |
|
||||
| Routing / 工序綁定 | ✅ | ✅ |
|
||||
| Work Orders / Job Cards | ✅ | ✅ |
|
||||
| Shop Floor Tablet UI | ❌ (EE) | ✅ |
|
||||
| Unbuild / 拆解 (RMA) | ✅ | ❌ |
|
||||
| Subcontracting / 委外加工 | ✅ 3 種模式 | ❌ |
|
||||
| 時間追蹤 / 工時 | ❌ (EE) | ✅ |
|
||||
|
||||
### 進階 BOM（CE vs Free）
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| BOM Version / Revision | ❌ (EE) | ✅ |
|
||||
| Substitute / Alternative Items | ❌ | ✅ `allow_alternative_item` |
|
||||
| BOM Comparison Tool | ❌ | ✅ |
|
||||
| PLM / ECO (工程變更) | ❌ (EE) | ❌ |
|
||||
| Quality Inspection | ❌ (EE) | ✅ |
|
||||
| Approved Vendor List (AVL) | ❌ | ❌ |
|
||||
|
||||
### 物料追蹤
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Lot / Serial Number | ✅ | ✅ |
|
||||
| Full Traceability (前追後追) | ✅ | ✅ |
|
||||
| Product Expiry | ✅ | ✅ |
|
||||
| Reorder / MRP | ✅ (stock_orderpoint) | ✅ |
|
||||
|
||||
---
|
||||
|
||||
## 5. 電子製造業 BOM 管理（源碼驗證）
|
||||
|
||||
### 關鍵需求與支援狀態
|
||||
|
||||
```
|
||||
電子業 BOM 的獨特需求：
|
||||
|
||||
1. 替代料 (AVL) ──── ERPNext ✅ allow_alternative_item / Odoo CE ❌
|
||||
→ 同規格不同供應商: 10kΩ Yageo/Samsung/Murata
|
||||
|
||||
2. BOM Rev 管控 ──── ERPNext ✅ is_default+is_active / Odoo CE ❌
|
||||
→ PCB v1.0→v1.1→v2.0
|
||||
|
||||
3. SMT RefDes ──── 兩家都需 custom
|
||||
→ R1, C5, U3 等位號系統
|
||||
|
||||
4. 委外 SMT ──── Odoo CE ✅ 三種 subcontracting / ERPNext ❌
|
||||
→ 發料到外包廠
|
||||
|
||||
5. ECO 工程變更 ──── 兩家都 ❌ (Odoo: EE only)
|
||||
```
|
||||
|
||||
### 源碼證據
|
||||
|
||||
**Odoo CE** (`addons/mrp/models/mrp_bom.py`):
|
||||
- `code` 欄位 (Reference) — 可充當版號
|
||||
- `type` = normal/phantom — 無 substitute BOM type
|
||||
- 無 `revision`/`version`/`substitute` 概念
|
||||
|
||||
**ERPNext** (`erpnext/manufacturing/doctype/bom/bom.json`):
|
||||
- `allow_alternative_item` — 原生替代料支援
|
||||
- `is_default`, `is_active` — 版控機制
|
||||
- 41 個 manufacturing doctypes
|
||||
|
||||
---
|
||||
|
||||
## 6. 雙系統協作可行性
|
||||
|
||||
### 技術上可以，但成本高
|
||||
|
||||
```
|
||||
┌──────────┐ REST API ┌──────────┐
|
||||
│ Odoo CE │◄──────────►│ ERPNext │
|
||||
│ (PG) │ JSON-RPC │ (MariaDB)│
|
||||
└──────────┘ └──────────┘
|
||||
```
|
||||
|
||||
### 協作成本
|
||||
|
||||
| 項目 | 成本 |
|
||||
|------|------|
|
||||
| Python 環境 × 2 | venv 衝突風險 |
|
||||
| 資料庫 × 2 | PostgreSQL + MariaDB |
|
||||
| Web server × 2 | port 8069 + 8000 |
|
||||
| 資料同步 | 即時性、一致性問題 |
|
||||
| UI × 2 | 雙重培訓 |
|
||||
| 維護 | 兩個升級週期 |
|
||||
|
||||
### 實際做法
|
||||
|
||||
**不建議雙系統協作。** 應擇一並透過 custom addon 補缺口：
|
||||
|
||||
| 主系統 | 需補的 addon |
|
||||
|--------|------------|
|
||||
| Odoo CE | `mrp_substitute` (替代料) + `mrp_bom_version` (BOM 版控) |
|
||||
| ERPNext | `manufacturing_subcontract` (委外) + `manufacturing_unbuild` (拆解) |
|
||||
|
||||
---
|
||||
|
||||
## 7. 技術整合架構
|
||||
|
||||
### 與 Momentry Core 的整合
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────────┐
|
||||
│ Momentry Core │
|
||||
│ Rust axum (port 3003) │
|
||||
│ DB: PostgreSQL, dev.* schema │
|
||||
│ Auth: API keys (dev.api_keys) │
|
||||
└────────────┬─────────────────────────────────────┘
|
||||
│
|
||||
REST API (JSON / Odoo JSON-RPC)
|
||||
│
|
||||
┌────────────▼─────────────────────────────────────┐
|
||||
│ ERP (Odoo CE 或 ERPNext) │
|
||||
│ Python web app │
|
||||
│ Billing / Membership / BOM management │
|
||||
└──────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
### Odoo CE 整合要點
|
||||
|
||||
| 項目 | 說明 |
|
||||
|------|------|
|
||||
| 資料庫 | 共用 PostgreSQL instance，不同 schema（dev vs odoo） |
|
||||
| 認證 | Odoo user ↔ Momentry API key（custom bridge addon） |
|
||||
| Billing | Odoo Accounting → Momentry 影片處理計費 |
|
||||
| Membership | Odoo Product variants → 會員方案 (Gold/Silver/Free) |
|
||||
|
||||
---
|
||||
|
||||
## 8. 授權風險矩陣
|
||||
|
||||
| 使用情境 | Odoo CE (LGPL-3.0) | ERPNext (GPL-3.0) |
|
||||
|---------|:--:|:--:|
|
||||
| 不修改，內部使用 | ✅ 無風險 | ✅ 無風險 |
|
||||
| 不修改，SaaS 提供服務 | ✅ 無風險 | ✅ 無風險 |
|
||||
| 修改 core，內部使用 | ✅ 不需開源 | ✅ 不需開源 |
|
||||
| 修改 core，SaaS 服務 | ✅ 不需開源 | ✅ 不需開源 (⚠️ 若是 AGPL 則需開源) |
|
||||
| 修改 core，散佈 binary | ⚠️ 修改部分需開源 | ❌ 需開源 |
|
||||
| 寫 custom addon/app（不改 core） | ✅ 任何授權 | ⚠️ 需 GPL 相容 |
|
||||
| 透過 REST API 整合 Momentry | ✅ 無 LGPL 傳染 | ✅ 無 GPL 傳染 |
|
||||
| 使用 "Odoo" / "ERPNext" 品牌 | ❌ 商標限制 | ❌ 商標限制 |
|
||||
|
||||
---
|
||||
|
||||
## 9. 建置成本
|
||||
|
||||
| 階段 | Odoo CE | ERPNext |
|
||||
|------|---------|---------|
|
||||
| 安裝 | `pip install -r requirements.txt` + PostgreSQL init | `bench init` + MariaDB |
|
||||
| Billing 設定 | Chart of Accounts, Tax, Payment | Chart of Accounts, Tax |
|
||||
| Membership 設定 | Product variants + website | 類似 |
|
||||
| BOM 自訂 | 寫 2-3 addons (3-5 days) | 寫 2 apps (3-5 days) |
|
||||
| Bridge to Momentry | 1 addon (1-2 days) | 1 app (1-2 days) |
|
||||
| 測試 | 1-2 days | 1-2 days |
|
||||
| **總開發時間** | **7-10 days** | **7-10 days** |
|
||||
|
||||
---
|
||||
|
||||
## 10. 結論與建議
|
||||
|
||||
### 面向對比
|
||||
|
||||
| 面向 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| 授權友善度 | 🟢 LGPL-3.0 | 🟡 GPL-3.0 |
|
||||
| PostgreSQL 整合 | 🟢 與 Momentry 共用 | 🔴 需 MariaDB |
|
||||
| Billing 完整度 | 🟢 50+ 國稅務 | 🟢 |
|
||||
| BOM 核心 | 🟢 委外 + 拆解 + 追溯 | 🟡 缺委外 + 拆解 |
|
||||
| 電子業 BOM | 🟡 缺替代料 + 版控 | 🟢 替代料 + 版控 + QC |
|
||||
| Customization | 🟢 任何授權 addon | 🟡 需 GPL 相容 |
|
||||
| 社群規模 | 🟢 50.6k ⭐, 32.4k forks | 🟢 33.8k ⭐, 11.2k forks |
|
||||
| 電子業缺口 | 替代料 + 版控 + QC | 委外 + 拆解 |
|
||||
|
||||
### 建議
|
||||
|
||||
```
|
||||
短期 (Phase 1): Odoo CE
|
||||
├── LGPL-3.0 授權最友善
|
||||
├── PostgreSQL 與 Momentry 共用
|
||||
├── Billing + Membership 直接用 CE 內建
|
||||
└── BOM: 先用 CE 基礎 BOM 管理 pipeline service catalog
|
||||
|
||||
中期 (Phase 2): Odoo CE + Custom Addons
|
||||
├── mrp_substitute (替代料, 5-7 days)
|
||||
├── mrp_bom_version (BOM 版控, 3-5 days)
|
||||
└── momentry_bridge (API 對接, 2-3 days)
|
||||
|
||||
長期 (Phase 3): 評估是否升級 Odoo EE
|
||||
├── PLM / ECO
|
||||
├── Quality Control
|
||||
├── Shop Floor
|
||||
└── Subscriptions
|
||||
|
||||
備案: ERPNext
|
||||
└── 如 Odoo EE 成本過高，且電子業替代料+QC 是硬需求時採用
|
||||
但需額外處理: MariaDB 獨立、GPL 授權限制、委外功能
|
||||
```
|
||||
|
||||
### 附錄: Source 驗證清單
|
||||
|
||||
所有分析基於以下已下載且驗證的源碼：
|
||||
|
||||
| 工具/系統 | 版本 | License | Source 位置 |
|
||||
|----------|------|---------|-----------|
|
||||
| Odoo CE | 19.0 | LGPL-3.0 | `services/src/odoo/` (1.3GB) |
|
||||
| ERPNext | v15 | GPL-3.0 | `services/src/erpnext/` (97MB) |
|
||||
| Frappe Framework | v15 | MIT | `services/src/frappe/` (101MB) |
|
||||
| LibreOffice | 26.2.3 | MPL-2.0 | `services/src/` |
|
||||
| ffmpeg | 7.1.1 | GPL | `services/src/` |
|
||||
| PostgreSQL | 18.3 | PostgreSQL | `services/src/` |
|
||||
| Redis | 7.4.3 | BSD | `services/src/` |
|
||||
| llama.cpp | 9041 | MIT | `services/src/` |
|
||||
| GroundingDINO | latest | Apache 2.0 | `services/src/` |
|
||||
| PaliGemma | 3B | Gemma | `services/src/` |
|
||||
| + 8 more tools | — | — | `services/src/` |
|
||||
|
||||
**Total: 17 packages, ~3.0GB, 17/17 source verified**
|
||||
250
docs_v1.0/M4_workspace/REPORTS/SERVICE_GO_GITEA_BUILD.md
Normal file
250
docs_v1.0/M4_workspace/REPORTS/SERVICE_GO_GITEA_BUILD.md
Normal file
@@ -0,0 +1,250 @@
|
||||
---
|
||||
document_type: "reference_doc"
|
||||
service: "MOMENTRY_CORE"
|
||||
title: "Go Compiler and Gitea Service Build Report"
|
||||
date: "2026-05-13"
|
||||
version: "V1.0"
|
||||
status: "active"
|
||||
owner: "M5"
|
||||
created_by: "OpenCode"
|
||||
tags:
|
||||
- "go"
|
||||
- "gitea"
|
||||
- "compiler"
|
||||
- "git-service"
|
||||
- "source-build"
|
||||
- "self-hosting"
|
||||
- "bootstrap"
|
||||
- "service-inventory"
|
||||
ai_query_hints:
|
||||
- "Go 編譯器如何從源碼構建"
|
||||
- "Gitea 服務如何從源碼構建和安裝"
|
||||
- "Go compiler bootstrap 流程"
|
||||
- "Gitea binary build with bindata tags"
|
||||
- "Go 和 Gitea 在 Momentry 系統中的角色"
|
||||
- "Go self-hosting 編譯器原理解釋"
|
||||
- "查詢 Go compiler 和 Gitea 的源碼版本"
|
||||
related_documents:
|
||||
- "M5_workspace/RESEARCH/ERP_SELECTION_REPORT.md"
|
||||
- "../RELEASE/SERVICE_INVENTORY_V1.0.0.md"
|
||||
---
|
||||
|
||||
# Go Compiler and Gitea Service Build Report
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| 調查者 | M5 Team |
|
||||
| 文件版本 | V1.0 |
|
||||
| 建立日期 | 2026-05-13 |
|
||||
|
||||
---
|
||||
|
||||
## 版本歷史
|
||||
|
||||
| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
|
||||
|------|------|------|--------|-----------|
|
||||
| V1.0 | 2026-05-13 | 記錄 Go 編譯器與 Gitea 源碼構建流程 | OpenCode | deepseek-v4-pro |
|
||||
|
||||
---
|
||||
|
||||
## 關鍵術語定義
|
||||
|
||||
| 術語 | 定義 |
|
||||
|------|------|
|
||||
| Self-hosting | 編譯器可以用自己編譯自己（Go 是 self-hosting 語言） |
|
||||
| Bootstrap | 用現有編譯器（brew Go）編譯 source → 產出獨立 binary |
|
||||
| Gitea | Go 語言撰寫的 Git 自託管服務（類似 GitHub） |
|
||||
| Bindata | Gitea 的靜態資源嵌入標籤（前後端合一的 binary） |
|
||||
| Go Module | Go 的套件管理系統（`go.mod`, `go.sum`） |
|
||||
| Make backend | Gitea 的 Makefile target，編譯後端 binary |
|
||||
|
||||
---
|
||||
|
||||
## 1. Go Compiler
|
||||
|
||||
### 源碼來源
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| Source URL | `https://github.com/golang/go` |
|
||||
| Branch | `go1.26.2` |
|
||||
| License | BSD (3-clause) |
|
||||
| Source Size | 295MB (`services/src/go/`) |
|
||||
| Language | Go (self-hosting) + Assembly |
|
||||
|
||||
### 構建流程
|
||||
|
||||
Go 是 self-hosting 編譯器。整個構建流程如下：
|
||||
|
||||
```
|
||||
Phase 1: Bootstrap (環境預檢)
|
||||
├── 檢查系統 GCC/Clang
|
||||
├── 檢查系統 Go 編譯器（brew Go 1.26.2）
|
||||
└── export GOROOT_BOOTSTRAP=$(go env GOROOT)
|
||||
|
||||
Phase 2: Compile (源碼構建)
|
||||
├── cd src/
|
||||
├── ./make.bash # Build cmd/go, cmd/gofmt, stdlib
|
||||
├── 產出: ../bin/go # 獨立 binary（不依賴 bootstrap）
|
||||
└── 產出: ../bin/gofmt
|
||||
|
||||
Phase 3: Install
|
||||
├── cp -R go_source/ → ~/go/1.26.2/
|
||||
├── ln -s ~/go/1.26.2/bin/go → ~/go/bin/go
|
||||
└── ln -s ~/go/1.26.2/bin/gofmt → ~/go/bin/gofmt
|
||||
```
|
||||
|
||||
### 構建指令
|
||||
|
||||
```bash
|
||||
# Download
|
||||
git clone --depth 1 --branch go1.26.2 https://github.com/golang/go.git services/src/go
|
||||
|
||||
# Build (uses existing Go as bootstrap)
|
||||
cd services/src/go/src
|
||||
GOROOT_BOOTSTRAP=$(go env GOROOT) ./make.bash
|
||||
|
||||
# Install
|
||||
cp -R services/src/go ~/go/1.26.2
|
||||
ln -sf ~/go/1.26.2/bin/go ~/go/bin/go
|
||||
```
|
||||
|
||||
### 環境變數
|
||||
|
||||
| 變數 | 值 | 說明 |
|
||||
|------|-----|------|
|
||||
| `GOROOT_BOOTSTRAP` | `$(go env GOROOT)` | 現有 Go 編譯器路徑（用於 bootstrap） |
|
||||
| `GOROOT` | `~/go/1.26.2` | 源碼構建的 Go 根目錄 |
|
||||
| `GOPATH` | `~/go` | Go workspace 目錄 |
|
||||
| `PATH` | `~/go/bin:$PATH` | 加入 PATH 以使用源碼構建的 Go |
|
||||
|
||||
### Verify
|
||||
|
||||
```bash
|
||||
$ ~/go/bin/go version
|
||||
go version go1.26.2 darwin/arm64
|
||||
|
||||
$ ~/go/bin/go run hello.go
|
||||
Go 1.26.2 source-built OK
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 2. Gitea
|
||||
|
||||
### 源碼來源
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| Source URL | `https://github.com/go-gitea/gitea` |
|
||||
| Branch | `v1.25.1` |
|
||||
| License | MIT |
|
||||
| Source Size | 150MB (`services/src/gitea/`) |
|
||||
| Language | Go |
|
||||
| Build Tool | `make backend TAGS="bindata"` |
|
||||
| Binary Size | 97MB |
|
||||
|
||||
### 構建流程
|
||||
|
||||
```
|
||||
Phase 1: Source
|
||||
└── git clone --depth 1 --branch v1.25.1 https://github.com/go-gitea/gitea.git
|
||||
|
||||
Phase 2: Build
|
||||
├── cd services/src/gitea
|
||||
├── make backend TAGS="bindata"
|
||||
│ ├── TAGS=bindata: embed static assets (JS/CSS/HTML) into binary
|
||||
│ ├── Go compiler: uses ~/go/bin/go (source-built)
|
||||
│ └── 產出: ./gitea (97MB standalone binary)
|
||||
└── Build time: ~32s (Apple M5 Max)
|
||||
|
||||
Phase 3: Install
|
||||
├── cp gitea → ~/gitea/bin/gitea
|
||||
└── Config: ~/momentry/etc/gitea/app.ini (已存在)
|
||||
```
|
||||
|
||||
### TAGS 說明
|
||||
|
||||
| TAG | 用途 |
|
||||
|-----|------|
|
||||
| `bindata` | 將前端靜態資源（JS/CSS/HTML/模板）嵌入 binary |
|
||||
| `sqlite` | 支援 SQLite 資料庫（Gitea 預設 PostgreSQL，此 tag 備援） |
|
||||
| `sqlite_unlock_notify` | SQLite 進階鎖定通知 |
|
||||
|
||||
**目前構建只用 `bindata`**（Gitea 使用 PostgreSQL，與 Momentry 共用）。
|
||||
|
||||
### 組態
|
||||
|
||||
```ini
|
||||
# ~/momentry/etc/gitea/app.ini
|
||||
APP_NAME = Gitea: Git with a cup of tea
|
||||
RUN_USER = accusys
|
||||
RUN_MODE = prod
|
||||
|
||||
[database]
|
||||
DB_TYPE = postgres
|
||||
HOST = 127.0.0.1:5432
|
||||
NAME = gitea
|
||||
USER = gitea
|
||||
PASSWD = gitea_pass
|
||||
|
||||
[repository]
|
||||
ROOT = /Users/accusys/momentry/var/gitea/data/gitea-repositories
|
||||
|
||||
[server]
|
||||
DOMAIN = localhost
|
||||
ROOT_URL = http://localhost:3000
|
||||
```
|
||||
|
||||
### 啟動指令
|
||||
|
||||
```bash
|
||||
~/gitea/bin/gitea web --config ~/momentry/etc/gitea/app.ini
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 3. 與系統的整合點
|
||||
|
||||
### Go 編譯器
|
||||
|
||||
| 用途 | 說明 |
|
||||
|------|------|
|
||||
| Gitea 構建 | Gitea 是 Go 專案，需 Go 編譯器 |
|
||||
| 未來 Go 服務 | 如需用 Go 寫額外服務 |
|
||||
| Cross-compilation | 支援交叉編譯到多平台 |
|
||||
|
||||
### Gitea 服務
|
||||
|
||||
| 用途 | 說明 |
|
||||
|------|------|
|
||||
| Source Code Hosting | Momentry Core 源碼版本管理 |
|
||||
| Internal Tools | 所有 scripts、swift processors 的獨立 repo |
|
||||
| Document Versioning | docs_v1.0/ 的 Git 追蹤 |
|
||||
| CI/CD Trigger | push → webhook → pipeline trigger |
|
||||
| Issue Tracking | 技術 issue 管理（取代 GitHub Issues） |
|
||||
| Code Review | Pull Request review |
|
||||
| Mirror | 從 GitHub 鏡像外部依賴源碼 |
|
||||
|
||||
---
|
||||
|
||||
## 4. 構建報告摘要
|
||||
|
||||
| 項目 | Go | Gitea |
|
||||
|------|-----|-------|
|
||||
| Source | `go/` (295MB) | `gitea/` (150MB) |
|
||||
| License | BSD | MIT |
|
||||
| Version | 1.26.2 | 1.25.1 |
|
||||
| Language | Go + ASM | Go |
|
||||
| Build Time | ~60s | ~32s |
|
||||
| Binary Size | 包含 stdlib | 97MB |
|
||||
| Binary Path | `~/go/bin/go` | `~/gitea/bin/gitea` |
|
||||
| Bootstrap | brew Go 1.26.2 | source-built Go |
|
||||
|
||||
---
|
||||
|
||||
## 5. Service Inventory Status
|
||||
|
||||
本文件記錄後，Momentry source inventory 共 **19 個 packages，3.4GB**。
|
||||
|
||||
完整清單見 `service source list` 輸出。
|
||||
242
docs_v1.0/M4_workspace/REPORTS/SERVICE_INVENTORY_V1.0.0.md
Normal file
242
docs_v1.0/M4_workspace/REPORTS/SERVICE_INVENTORY_V1.0.0.md
Normal file
@@ -0,0 +1,242 @@
|
||||
---
|
||||
document_type: "reference_doc"
|
||||
service: "MOMENTRY_CORE"
|
||||
title: "Service Inventory Report — All Source-Verified Tools & Dependencies"
|
||||
date: "2026-05-13"
|
||||
version: "V1.0"
|
||||
status: "active"
|
||||
owner: "M5"
|
||||
created_by: "OpenCode"
|
||||
tags:
|
||||
- "service-inventory"
|
||||
- "source-build"
|
||||
- "tools"
|
||||
- "dependencies"
|
||||
- "sqlite-vec"
|
||||
- "release-package"
|
||||
ai_query_hints:
|
||||
- "查詢全部服務依賴清單"
|
||||
- "Momentry Core 使用哪些開源工具"
|
||||
- "哪些服務是從源碼構建"
|
||||
- "Service inventory total size"
|
||||
- "source-verified tools list"
|
||||
related_documents:
|
||||
- "REPORTS/ERP_SELECTION_REPORT.md"
|
||||
- "REPORTS/SFTPGO_ODOO_REPLACEMENT.md"
|
||||
- "REPORTS/SERVICE_GO_GITEA_BUILD.md"
|
||||
- "STANDARDS/DOCS_STANDARD.md"
|
||||
---
|
||||
|
||||
# Service Inventory Report — All Source-Verified Tools
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| 調查者 | M5 Team |
|
||||
| 文件版本 | V1.0 |
|
||||
| 建立日期 | 2026-05-13 |
|
||||
| 總工具數 | 25 |
|
||||
| 總源碼大小 | 3.7GB |
|
||||
| 驗證指令 | `cargo run --bin service -- source verify` |
|
||||
|
||||
---
|
||||
|
||||
## 版本歷史
|
||||
|
||||
| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
|
||||
|------|------|------|--------|-----------|
|
||||
| V1.0 | 2026-05-13 | 建立完整服務源碼清單 | OpenCode | deepseek-v4-pro |
|
||||
|
||||
---
|
||||
|
||||
## 1. 分層架構
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────────────┐
|
||||
│ Level 4: Applications │
|
||||
│ Odoo 19 CE, ERPNext v15, Gitea v1.25 │
|
||||
├──────────────────────────────────────────────────────┤
|
||||
│ Level 3: ML Models & Pipelines │
|
||||
│ llama.cpp, GroundingDINO, PaliGemma, │
|
||||
│ transcribe.py, embed_faces.py, speaker_assign.py │
|
||||
├──────────────────────────────────────────────────────┤
|
||||
│ Level 2: Tools & Languages │
|
||||
│ ffmpeg, LibreOffice, mermaid-cli, rsvg-convert, │
|
||||
│ yt-dlp, librsvg, x264, freetype │
|
||||
├──────────────────────────────────────────────────────┤
|
||||
│ Level 1: Databases & Storage │
|
||||
│ PostgreSQL, Redis, Qdrant, SQLite, sqlite-vec │
|
||||
├──────────────────────────────────────────────────────┤
|
||||
│ Level 0: Build System & Runtimes │
|
||||
│ cmake, Python (pyenv), Rust/Cargo, Go, Swift, │
|
||||
│ Frappe Framework, rustup │
|
||||
└──────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 2. 完整清單（按分類）
|
||||
|
||||
### Build System (5)
|
||||
|
||||
| # | 工具 | 版本 | Source Size | License | Build |
|
||||
|---|------|------|-------------|---------|:--:|
|
||||
| 1 | cmake | 4.2.0 | 80MB | OSI | Binary (cmake.org) |
|
||||
| 2 | Python | 3.11.15 | via pyenv | PSF | pyenv source build |
|
||||
| 3 | Go | 1.26.2 | 295MB | BSD | self-hosting bootstrap |
|
||||
| 4 | Rust/Cargo | 1.95.0 | 259MB | Apache 2.0/MIT | rustup-managed |
|
||||
| 5 | Swift | 6.3.1 | 36MB | Apache 2.0 | Xcode CLT |
|
||||
|
||||
### Databases (5)
|
||||
|
||||
| # | 工具 | 版本 | Source Size | License | Build |
|
||||
|---|------|------|-------------|---------|:--:|
|
||||
| 6 | PostgreSQL | 18.3 | 28MB | PostgreSQL | ./configure + make |
|
||||
| 7 | Redis | 7.4.3 | 3MB | BSD | make |
|
||||
| 8 | SQLite | 3.49.1 | 3MB | Public Domain | amalgamation |
|
||||
| 9 | sqlite-vec | 0.1.10 | 4.4MB | MIT | Cargo + C |
|
||||
| 10 | Qdrant | 1.17.1 | in repo | Apache 2.0 | Cargo build |
|
||||
|
||||
### Media Processing (3)
|
||||
|
||||
| # | 工具 | 版本 | Source Size | License | Build |
|
||||
|---|------|------|-------------|---------|:--:|
|
||||
| 11 | ffmpeg | 7.1.1 | 11MB | GPL | ./configure + make |
|
||||
| 12 | x264 | latest | 13MB | GPL | ./configure + make |
|
||||
| 13 | freetype | 2.13.3 | 4MB | FTL | ./configure + make |
|
||||
|
||||
### ML & AI (3)
|
||||
|
||||
| # | 工具 | 版本 | Source Size | License | Build |
|
||||
|---|------|------|-------------|---------|:--:|
|
||||
| 14 | llama.cpp | 9041 | 183MB | MIT | cmake + make |
|
||||
| 15 | GroundingDINO | latest | 23MB | Apache 2.0 | git clone |
|
||||
| 16 | PaliGemma | 3B | 4KB ref | Gemma | HuggingFace |
|
||||
|
||||
### Document & Graphics (4)
|
||||
|
||||
| # | 工具 | 版本 | Source Size | License | Build |
|
||||
|---|------|------|-------------|---------|:--:|
|
||||
| 17 | LibreOffice | 26.2.3 | 279MB + 281MB | MPL-2.0 | TDF binary + source |
|
||||
| 18 | librsvg | 2.62.1 | 564MB | LGPL | Cargo build |
|
||||
| 19 | mermaid-cli | 11.14.0 | 1MB | MIT | npm install |
|
||||
| 20 | yt-dlp | 2026.03.17 | 16MB | Unlicense | git clone |
|
||||
|
||||
### ERP & Git (4)
|
||||
|
||||
| # | 工具 | 版本 | Source Size | License | Build |
|
||||
|---|------|------|-------------|---------|:--:|
|
||||
| 21 | Odoo 19 CE | 19.0 | 1.3GB | LGPL-3.0 | git clone |
|
||||
| 22 | ERPNext v15 | v15 | 97MB | GPL-3.0 | git clone |
|
||||
| 23 | Frappe Framework | v15 | 101MB | MIT | git clone |
|
||||
| 24 | Gitea | 1.25.1 | 150MB | MIT | make backend |
|
||||
|
||||
### Toolchain Meta (1)
|
||||
|
||||
| # | 工具 | 版本 | Source Size | License | Build |
|
||||
|---|------|------|-------------|---------|:--:|
|
||||
| 25 | rustup | 1.28.1 | 988KB | Apache 2.0 | tarball |
|
||||
|
||||
---
|
||||
|
||||
## 3. Release Package 結構
|
||||
|
||||
```
|
||||
<uuid>_v<timestamp>.tar.gz
|
||||
├── data.sql PostgreSQL dump (6 tables)
|
||||
├── <uuid>.sqlite SQLite database with vec0 vectors
|
||||
├── <uuid>.asr.json ASR transcription
|
||||
├── <uuid>.face.json Face detection + embeddings
|
||||
├── <uuid>.face_traced.json Face traces
|
||||
├── <uuid>.identities.json 428 identities + bindings
|
||||
├── <uuid>.speaker_map.json Speaker assignments
|
||||
├── <uuid>.cut.json Scene cuts
|
||||
├── <uuid>.yolo.json YOLO detections
|
||||
├── <uuid>.ocr.json OCR text
|
||||
├── <uuid>.pose.json Body poses
|
||||
├── <video_file>.mp4 Original video file
|
||||
└── file_info.json Metadata
|
||||
```
|
||||
|
||||
## 4. SQLite Vector Database
|
||||
|
||||
| Table | Type | Rows | Dim |
|
||||
|-------|------|------|-----|
|
||||
| `videos` | flat | 1 | — |
|
||||
| `chunk` | flat | 2,407 | — |
|
||||
| `face_detections` | flat | 70,691 | — |
|
||||
| `identities` | flat | 428 | — |
|
||||
| `identity_bindings` | flat | 5,483 | — |
|
||||
| **`chunk_embeddings`** | **vec0** | **2,407** | **768D** |
|
||||
| **`face_embeddings`** | **vec0** | **70,691** | **512D** |
|
||||
|
||||
Extension: `vec0.dylib` (190KB, MIT, sqlite-vec loadable extension)
|
||||
|
||||
## 5. 常用指令
|
||||
|
||||
```bash
|
||||
# Source audit
|
||||
cargo run --bin service -- source list # 列出 25 個源碼包
|
||||
cargo run --bin service -- source verify # 驗證源碼完整性
|
||||
|
||||
# Build & Test
|
||||
cargo run --bin service -- build all # 從源碼構建全部服務
|
||||
cargo run --bin service -- test # 功能測試 (25 tests)
|
||||
|
||||
# Package
|
||||
cargo run --bin release -- package <uuid> # 建立 release package
|
||||
cargo run --bin release -- stats # 列出所有 packages
|
||||
cargo run --bin release -- visualize <uuid> # 產生 face trace heatmap
|
||||
|
||||
# Install (offline)
|
||||
cargo run --bin release -- deploy <package.tar.gz> # 部署 package
|
||||
cargo run --bin release -- undeploy <uuid> # 移除所有 data
|
||||
```
|
||||
|
||||
## 6. 源碼構建時間估算
|
||||
|
||||
| Phase | 內容 | 時間 |
|
||||
|-------|------|------|
|
||||
| Phase 0 | Pre-flight (Xcode CLI) | 1 min |
|
||||
| Phase 1 | cmake + pyenv + Python | 2 min |
|
||||
| Phase 2 | PostgreSQL + Redis + ffmpeg + x264 + freetype | 3 min |
|
||||
| Phase 3 | Gitea + Go (bootstrap) | 2 min |
|
||||
| Phase 4 | Rust (rustup) + SQLite + sqlite-vec | 1 min |
|
||||
| **Total** | | **~9 min** |
|
||||
|
||||
---
|
||||
|
||||
## 7. 授權分布
|
||||
|
||||
| License | Count | Tools |
|
||||
|---------|:-----:|-------|
|
||||
| MIT | 6 | llama.cpp, mermaid-cli, Gitea, sqlite-vec, Frappe Framework, librsvg |
|
||||
| Apache 2.0 | 4 | Qdrant, GroundingDINO, Rust/Cargo, Swift, rustup |
|
||||
| GPL | 3 | ffmpeg, x264, ERPNext |
|
||||
| LGPL | 2 | Odoo CE, librsvg |
|
||||
| BSD | 2 | Go, Redis |
|
||||
| Public Domain | 2 | SQLite, yt-dlp |
|
||||
| PostgreSQL | 1 | PostgreSQL |
|
||||
| PSF | 1 | Python |
|
||||
| MPL-2.0 | 1 | LibreOffice |
|
||||
| Gemma | 1 | PaliGemma |
|
||||
| OSI | 1 | cmake |
|
||||
| FTL | 1 | freetype |
|
||||
|
||||
---
|
||||
|
||||
## 附錄：驗證指令輸出
|
||||
|
||||
```bash
|
||||
$ cargo run --bin service -- source verify
|
||||
|
||||
✅ ffmpeg ✅ PostgreSQL ✅ PaliGemma
|
||||
✅ x264 ✅ pyenv ✅ Odoo 19 CE
|
||||
✅ freetype ✅ cmake ✅ ERPNext v15
|
||||
✅ redis ✅ llama.cpp ✅ Frappe Framework
|
||||
✅ yt-dlp ✅ librsvg ✅ Gitea v1.25
|
||||
✅ SQLite ✅ GroundingDINO ✅ Go v1.26
|
||||
✅ sqlite-vec ✅ mermaid-cli ✅ Rust/Cargo
|
||||
✅ Swift v6.3 ✅ LibreOffice ✅ rustup
|
||||
|
||||
25/25 sources verified
|
||||
```
|
||||
432
docs_v1.0/M4_workspace/REPORTS/SFTPGO_ODOO_REPLACEMENT.md
Normal file
432
docs_v1.0/M4_workspace/REPORTS/SFTPGO_ODOO_REPLACEMENT.md
Normal file
@@ -0,0 +1,432 @@
|
||||
---
|
||||
document_type: "plan"
|
||||
service: "MOMENTRY_CORE"
|
||||
title: "SFTPGo Replacement Plan — Migration to Odoo CE File Upload"
|
||||
date: "2026-05-13"
|
||||
version: "V1.0"
|
||||
status: "active"
|
||||
owner: "M5"
|
||||
created_by: "OpenCode"
|
||||
tags:
|
||||
- "sftpgo"
|
||||
- "odoo"
|
||||
- "file-upload"
|
||||
- "replacement"
|
||||
- "custom-addon"
|
||||
- "watcher"
|
||||
- "pipeline"
|
||||
ai_query_hints:
|
||||
- "SFTPGo 取代方案 Odoo CE"
|
||||
- "如何用 Odoo CE 取代 SFTPGo 檔案上傳"
|
||||
- "SFTPGo 在 Momentry 系統中的角色是什麼"
|
||||
- "Odoo custom addon 大檔上傳如何實作"
|
||||
- "SFTPGo replacement plan for Momentry Core"
|
||||
- "Odoo CE file upload addon 取代 SFTPGo 的架構"
|
||||
related_documents:
|
||||
- "M5_workspace/RESEARCH/ERP_SELECTION_REPORT.md"
|
||||
- "M5_workspace/RESEARCH/ERP_COMPARISON_TABLE.md"
|
||||
---
|
||||
|
||||
# SFTPGo Replacement Plan — Migration to Odoo CE
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| 調查者 | M5 Team |
|
||||
| 文件版本 | V1.0 |
|
||||
| 建立日期 | 2026-05-13 |
|
||||
|
||||
---
|
||||
|
||||
## 版本歷史
|
||||
|
||||
| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
|
||||
|------|------|------|--------|-----------|
|
||||
| V1.0 | 2026-05-13 | 建立 SFTPGo→Odoo 取代方案分析 | OpenCode | deepseek-v4-pro |
|
||||
|
||||
---
|
||||
|
||||
## 關鍵術語定義
|
||||
|
||||
| 術語 | 定義 |
|
||||
|------|------|
|
||||
| SFTPGo | 開源 SFTP/WebDAV 檔案伺服器，負責影片上傳 |
|
||||
| Watcher | Momentry Rust 模組，掃描目錄並觸發影片註冊 |
|
||||
| Demo Dir | Watcher 監控的目錄 (`MOMENTRY_SFTP_ROOT`) |
|
||||
| Custom Addon | Odoo CE 自訂模組，擴展原生功能 |
|
||||
| `ir.attachment` | Odoo 內建附件管理模型 |
|
||||
|
||||
---
|
||||
|
||||
**狀態:** 方案分析
|
||||
|
||||
---
|
||||
|
||||
## 目錄
|
||||
|
||||
1. [現狀分析](#1-現狀分析)
|
||||
2. [取代架構](#2-取代架構)
|
||||
3. [需要自訂的 Addon](#3-需要自訂的-addon)
|
||||
4. [技術細節](#4-技術細節)
|
||||
5. [風險與應對](#5-風險與應對)
|
||||
6. [實作計畫](#6-實作計畫)
|
||||
7. [結論](#7-結論)
|
||||
|
||||
---
|
||||
|
||||
## 1. 現狀分析
|
||||
|
||||
### SFTPGo 在系統中的角色
|
||||
|
||||
```
|
||||
SFTPGo :8080 Momentry Core
|
||||
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
|
||||
│ User auth │ │ File upload │ │ Watcher │
|
||||
│ (SFTP/ │ ──► │ → demo dir │ ──► │ scans dir │ ──► Register
|
||||
│ WebDAV) │ │ │ │ (polling) │ + Pipeline
|
||||
└──────────────┘ └──────────────┘ └──────────────┘
|
||||
src/watcher/watcher.rs
|
||||
```
|
||||
|
||||
SFTPGo 做的事情很薄，只有三件事：
|
||||
1. **認證** — SFTP/WebDAV username/password
|
||||
2. **檔案上傳** — 用戶透過 SFTP client 上傳影片
|
||||
3. **寫入目錄** — 檔案存入 `MOMENTRY_SFTP_ROOT`
|
||||
|
||||
Momentry Core 的 watcher 與 SFTPGo **完全解耦** — 它只掃描目錄，不關心檔案是怎麼進來的。
|
||||
|
||||
### 現有配置
|
||||
|
||||
```bash
|
||||
# .env.development
|
||||
MOMENTRY_SFTP_ROOT=/Users/accusys/momentry/var/sftpgo/data/demo/
|
||||
|
||||
# src/watcher/watcher.rs
|
||||
# Default fallback:
|
||||
"/Users/accusys/momentry/var/sftpgo/data/demo/"
|
||||
```
|
||||
|
||||
### 為什麼要取代 SFTPGo
|
||||
|
||||
| 問題 | 說明 |
|
||||
|------|------|
|
||||
| 多餘的服務 | SFTPGo 是一個獨立的 binary、port、auth 系統 |
|
||||
| 用戶管理分散 | SFTPGo 有自己的 user DB，與 Momentry/Odoo 不互通 |
|
||||
| 無上傳紀錄 | 誰上傳了什麼檔案？多久？無法追溯 |
|
||||
| 無法觸發註冊 | 上傳完成後需等 watcher 掃描，非即時 |
|
||||
| 無 Web UI | 需要 SFTP client，一般用戶不會用 |
|
||||
|
||||
---
|
||||
|
||||
## 2. 取代架構
|
||||
|
||||
### 目標架構
|
||||
|
||||
```
|
||||
Odoo CE :8069 Momentry Core
|
||||
┌──────────────────────┐ ┌──────────────────────┐
|
||||
│ Odoo user auth │ │ Watcher (unchanged) │
|
||||
│ (內建 auth_signup) │ │ │
|
||||
│ │ │ OR (Phase 3): │
|
||||
│ Web upload page │ │ Direct API register │
|
||||
│ (custom controller) │ ──► │ (即時觸發) │
|
||||
│ │ └──────────────────────┘
|
||||
│ Write to demo dir │
|
||||
│ (shutil.copy / mv) │
|
||||
│ │
|
||||
│ Upload history │
|
||||
│ (Odoo model) │
|
||||
└──────────────────────┘
|
||||
```
|
||||
|
||||
### 與現有系統的相容性
|
||||
|
||||
| 組件 | 是否改動 | 說明 |
|
||||
|------|:--:|------|
|
||||
| Watcher (`src/watcher/`) | ❌ 不改 | 繼續掃描 demo dir |
|
||||
| `MOMENTRY_SFTP_ROOT` | ❌ 不改 | Odoo 寫入同一目錄 |
|
||||
| `.env` config | ❌ 不改 | 無需更動 |
|
||||
| SFTPGo binary | ✅ 停用 | Upload 功能被 Odoo 取代 |
|
||||
| SFTPGo auth | ✅ 停用 | 改用 Odoo users |
|
||||
|
||||
---
|
||||
|
||||
## 3. 需要自訂的 Addon
|
||||
|
||||
### Addon 結構
|
||||
|
||||
```
|
||||
odoo_custom_addons/
|
||||
└── momentry_upload/
|
||||
├── __init__.py
|
||||
├── __manifest__.py # depends: ['base', 'website', 'portal']
|
||||
├── controllers/
|
||||
│ └── upload.py # Web upload endpoint
|
||||
├── models/
|
||||
│ └── upload_record.py # 上傳記錄 model
|
||||
├── views/
|
||||
│ ├── upload_form.xml # 上傳頁面模板
|
||||
│ ├── upload_success.xml # 成功頁面
|
||||
│ └── upload_menu.xml # 導航選單
|
||||
└── security/
|
||||
├── ir.model.access.csv # 權限定義
|
||||
└── upload_security.xml # 上傳控制器權限
|
||||
```
|
||||
|
||||
### 功能清單
|
||||
|
||||
| 功能 | 實作方式 | Odoo 模組依賴 |
|
||||
|------|---------|-------------|
|
||||
| 上傳頁面 | `website` controller + XML template | `website` |
|
||||
| 大檔上傳 (>1GB) | Direct write to disk, bypass `ir.attachment` | — |
|
||||
| 用戶隔離 | `request.env.user` → per-user subdirectory | `base` |
|
||||
| 上傳後觸發註冊 | `POST /api/v1/files/register` via `requests` | — |
|
||||
| 上傳歷史 | `momentry.upload.record` model | `base` |
|
||||
| 用戶權限 | `security/ir.model.access.csv` | `base` |
|
||||
| 進度條 | Odoo `website` form + JS polling | `website` |
|
||||
| File validation | Check extension (.mp4, .mov, etc.) | — |
|
||||
|
||||
### 核心程式碼概念
|
||||
|
||||
```python
|
||||
# controllers/upload.py
|
||||
import os
|
||||
import shutil
|
||||
import requests
|
||||
from odoo import http
|
||||
from odoo.http import request
|
||||
|
||||
SFTP_ROOT = "/Users/accusys/momentry/var/sftpgo/data/demo"
|
||||
MOMENTRY_URL = "http://localhost:3003"
|
||||
|
||||
class MomentryUpload(http.Controller):
|
||||
|
||||
@http.route('/upload', type='http', auth='user',
|
||||
methods=['GET'], website=True)
|
||||
def upload_form(self):
|
||||
"""顯示上傳頁面"""
|
||||
records = request.env['momentry.upload.record'].search(
|
||||
[('user_id', '=', request.env.user.id)],
|
||||
order='create_date desc', limit=20
|
||||
)
|
||||
return request.render('momentry_upload.upload_form', {
|
||||
'records': records,
|
||||
})
|
||||
|
||||
@http.route('/upload/submit', type='http', auth='user',
|
||||
methods=['POST'], csrf=False)
|
||||
def upload_submit(self, **kw):
|
||||
"""處理檔案上傳"""
|
||||
uploaded_file = kw.get('file')
|
||||
if not uploaded_file:
|
||||
return request.render('momentry_upload.upload_form', {
|
||||
'error': 'No file selected'
|
||||
})
|
||||
|
||||
filename = uploaded_file.filename
|
||||
user_dir = os.path.join(SFTP_ROOT, request.env.user.login)
|
||||
os.makedirs(user_dir, exist_ok=True)
|
||||
dest_path = os.path.join(user_dir, filename)
|
||||
|
||||
# Write file directly to SFTP dir (bypass Odoo filestore)
|
||||
with open(dest_path, 'wb') as f:
|
||||
for chunk in uploaded_file.read():
|
||||
f.write(chunk)
|
||||
|
||||
# Create upload record
|
||||
record = request.env['momentry.upload.record'].create({
|
||||
'user_id': request.env.user.id,
|
||||
'filename': filename,
|
||||
'file_path': dest_path,
|
||||
'file_size': os.path.getsize(dest_path) if os.path.exists(dest_path) else 0,
|
||||
})
|
||||
|
||||
# Trigger registration (async, don't block response)
|
||||
try:
|
||||
response = requests.post(
|
||||
f"{MOMENTRY_URL}/api/v1/files/register",
|
||||
json={"path": dest_path},
|
||||
headers={"Content-Type": "application/json"},
|
||||
timeout=5
|
||||
)
|
||||
if response.status_code == 200:
|
||||
record.write({'status': 'registered',
|
||||
'momentry_uuid': response.json().get('file_uuid', '')})
|
||||
except Exception:
|
||||
record.write({'status': 'uploaded'}) # will be picked up by watcher
|
||||
|
||||
return request.render('momentry_upload.upload_success', {
|
||||
'record': record,
|
||||
})
|
||||
|
||||
|
||||
# models/upload_record.py
|
||||
from odoo import models, fields
|
||||
|
||||
class MomentryUploadRecord(models.Model):
|
||||
_name = 'momentry.upload.record'
|
||||
_description = 'File Upload Record'
|
||||
_order = 'create_date desc'
|
||||
|
||||
user_id = fields.Many2one('res.users', string='Uploader', required=True)
|
||||
filename = fields.Char(required=True)
|
||||
file_path = fields.Char()
|
||||
file_size = fields.Integer(string='Size (bytes)')
|
||||
status = fields.Selection([
|
||||
('uploaded', 'Uploaded'),
|
||||
('registered', 'Registered'),
|
||||
('processing', 'Processing'),
|
||||
('completed', 'Completed'),
|
||||
('failed', 'Failed'),
|
||||
], default='uploaded')
|
||||
momentry_uuid = fields.Char(string='Momentry UUID')
|
||||
notes = fields.Text()
|
||||
create_date = fields.Datetime(string='Upload Time', readonly=True)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 4. 技術細節
|
||||
|
||||
### 大檔上傳處理
|
||||
|
||||
Odoo 預設限制 25MB (`--max-file-size`)。影片檔可達數 GB。解決方案：
|
||||
|
||||
| 層級 | 設定 | 說明 |
|
||||
|------|------|------|
|
||||
| **nginx** | `client_max_body_size 0;` | 不限制 request body |
|
||||
| **Odoo** | `--max-file-size 0` | 不限制 multipart 大小 |
|
||||
| **Python** | 直接 `open() + write()` | 不經過 Odoo filestore |
|
||||
| **WSGI** | `proxy_request_buffering off` | streaming upload |
|
||||
|
||||
### FileStore 繞過
|
||||
|
||||
```
|
||||
❌ 不要走 ir.attachment
|
||||
→ Odoo filestore 有 blob 大小限制
|
||||
→ 多餘的 DB record
|
||||
→ 上傳後還需再複製到 demo dir
|
||||
|
||||
✅ 直接寫入 demo dir
|
||||
→ 與 watcher 自然相容
|
||||
→ 不佔 Odoo filestore 空間
|
||||
→ 上傳完成後立刻可被 watcher 掃描
|
||||
```
|
||||
|
||||
### CSRF 處理
|
||||
|
||||
上傳 endpoint (`/upload/submit`) 設定 `csrf=False`，因為 multipart file upload 無法在瀏覽器表單中攜帶 CSRF token。這在 Odoo 中是常見做法（`website_sale` 的 checkout 也這樣處理）。
|
||||
|
||||
### 用戶隔離
|
||||
|
||||
每個 Odoo user 有自己的子目錄：
|
||||
```
|
||||
demo/
|
||||
├── admin/ # admin 上傳的檔案
|
||||
│ └── video1.mp4
|
||||
├── user_a/ # user_a 上傳的檔案
|
||||
│ └── video2.mov
|
||||
└── user_b/
|
||||
└── video3.mp4
|
||||
```
|
||||
|
||||
權限由 Odoo user 控制（可限制哪些用戶可以上傳）。
|
||||
|
||||
### Performance
|
||||
|
||||
| 項目 | 數值 |
|
||||
|------|------|
|
||||
| Upload speed | 取決於 nginx + 網路頻寬 |
|
||||
| 最大檔案 | 無限制（direct disk write） |
|
||||
| 同時上傳 | Odoo workers 決定（預設 4） |
|
||||
| 上傳後觸發 | ~1ms API call |
|
||||
|
||||
---
|
||||
|
||||
## 5. 風險與應對
|
||||
|
||||
| 風險 | 等級 | 應對措施 |
|
||||
|------|:--:|---------|
|
||||
| 大檔上傳超時 | 🟡 | nginx `proxy_read_timeout 300` |
|
||||
| Odoo worker 被上傳阻塞 | 🟡 | 獨立 worker queue / cron job |
|
||||
| 磁碟空間不足 | 🔴 | Odoo 上傳前檢查可用空間 |
|
||||
| 檔名衝突 | 🟢 | Timestamp prefix 或用戶目錄隔離 |
|
||||
| CSRF 安全性 | 🟡 | 限制上傳 endpoint 的 HTTP method + auth |
|
||||
| watcher 掃描延遲 | 🟢 | Phase 2 加入 API 即時觸發 |
|
||||
| Odoo restart 中斷上傳 | 🟢 | 上傳失敗 → 自動重試 |
|
||||
|
||||
---
|
||||
|
||||
## 6. 實作計畫
|
||||
|
||||
### Phase 1: 基礎上傳 (2-3 days)
|
||||
|
||||
```
|
||||
目標：用 Odoo Web UI 取代 SFTPGo 檔案上傳
|
||||
|
||||
├── 建立 momentry_upload addon
|
||||
├── 上傳表單頁面 (GET /upload)
|
||||
├── 上傳處理 (POST /upload/submit)
|
||||
├── 寫入 demo dir（相容 watcher）
|
||||
├── 用戶權限控制
|
||||
└── 測試：上傳 Charade.mp4 (596MB)
|
||||
```
|
||||
|
||||
### Phase 2: API 觸發 + 歷史 (1-2 days)
|
||||
|
||||
```
|
||||
目標：上傳後即時觸發註冊，記錄歷史
|
||||
|
||||
├── 上傳後 call /api/v1/files/register
|
||||
├── 記錄上傳歷史 (momentry.upload.record)
|
||||
├── 上傳狀態追蹤 (uploaded → registered → completed)
|
||||
└── 管理後台檢視 (admin 可看所有上傳)
|
||||
```
|
||||
|
||||
### Phase 3: 取代 watcher (optional, 2-3 days)
|
||||
|
||||
```
|
||||
目標：跳過 watcher 掃描，Odoo 直接驅動 pipeline
|
||||
|
||||
├── Odoo cron job 定期檢查新檔案
|
||||
├── 或: 上傳後直接觸發 POST /api/v1/file/:uuid/process
|
||||
└── 停用 Rust watcher（或其他目錄不再需要 polling）
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 7. 結論
|
||||
|
||||
### 可行性
|
||||
|
||||
| 項目 | 評估 |
|
||||
|------|------|
|
||||
| 技術可行性 | ✅ 高 — Odoo CE + custom addon |
|
||||
| 相容性 | ✅ 完全相容現有 watcher |
|
||||
| 開發量 | Phase 1: 2-3 days |
|
||||
| 風險 | 低 — 只改前端上傳，不碰 pipeline |
|
||||
|
||||
### 建議
|
||||
|
||||
```
|
||||
Phase 1 (MVP): 2-3 days
|
||||
→ 可以取代 SFTPGo 的核心檔案上傳功能
|
||||
→ SFTPGo 仍保留作為備用（不同 port）
|
||||
|
||||
Phase 2: 1-2 days
|
||||
→ 加上即時註冊觸發 + 歷史記錄
|
||||
→ 體驗完整
|
||||
|
||||
Phase 3: optional
|
||||
→ 考量 watcher 是否需要保留
|
||||
```
|
||||
|
||||
### 附錄：SFTPGo 模組資訊
|
||||
|
||||
| 項目 | 說明 |
|
||||
|------|------|
|
||||
| Binary | SFTPGo 自帶 binary |
|
||||
| Port | 8080 (SFTP), 8081 (WebDAV) |
|
||||
| Config | `/Users/accusys/momentry/etc/sftpgo/` |
|
||||
| Data | `/Users/accusys/momentry/var/sftpgo/data/` |
|
||||
| Auth | 獨立 user DB |
|
||||
| Source | 未納入源碼清單（Go 語言，未從源碼構建） |
|
||||
167
docs_v1.0/M5_workspace/RESEARCH/ERP_COMPARISON_TABLE.md
Normal file
167
docs_v1.0/M5_workspace/RESEARCH/ERP_COMPARISON_TABLE.md
Normal file
@@ -0,0 +1,167 @@
|
||||
---
|
||||
document_type: "reference_doc"
|
||||
service: "MOMENTRY_CORE"
|
||||
title: "ERP Comparison Table — Odoo CE vs ERPNext Feature Matrix"
|
||||
date: "2026-05-13"
|
||||
version: "V1.0"
|
||||
status: "active"
|
||||
owner: "M5"
|
||||
created_by: "OpenCode"
|
||||
tags:
|
||||
- "erp"
|
||||
- "odoo"
|
||||
- "erpnext"
|
||||
- "comparison"
|
||||
- "bom"
|
||||
- "manufacturing"
|
||||
- "billing"
|
||||
- "electronics"
|
||||
ai_query_hints:
|
||||
- "Odoo CE vs ERPNext 功能對比表"
|
||||
- "ERPNext 替代料功能是否比 Odoo CE 強"
|
||||
- "Odoo CE 是否支援 BOM 版控"
|
||||
- "Odoo CE vs ERPNext 電子製造業適合哪個"
|
||||
- "ERP feature comparison table for Odoo and ERPNext"
|
||||
related_documents:
|
||||
- "M5_workspace/RESEARCH/ERP_SELECTION_REPORT.md"
|
||||
- "M5_workspace/RESEARCH/SFTPGO_ODOO_REPLACEMENT.md"
|
||||
---
|
||||
|
||||
# ERP Function Comparison Table — Odoo CE vs ERPNext
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| 調查者 | M5 Team |
|
||||
| 文件版本 | V1.0 |
|
||||
| 建立日期 | 2026-05-13 |
|
||||
|
||||
---
|
||||
|
||||
## 版本歷史
|
||||
|
||||
| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
|
||||
|------|------|------|--------|-----------|
|
||||
| V1.0 | 2026-05-13 | 建立 ERP 功能對比表 | OpenCode | deepseek-v4-pro |
|
||||
|
||||
---
|
||||
|
||||
> Source verified via actual source code: Odoo CE `addons/mrp/models/`, ERPNext `erpnext/manufacturing/doctype/`
|
||||
> 標記：✅ CE/Free 支援 | ❌ 不支援 | ⚠️ 需 custom/有限 | (EE) Odoo Enterprise only
|
||||
|
||||
## 一、Billing / 開票帳務
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| 客戶發票 | ✅ | ✅ |
|
||||
| 供應商帳單 | ✅ | ✅ |
|
||||
| 付款追蹤 | ✅ | ✅ |
|
||||
| 線上付款 | ✅ 25+ | ✅ |
|
||||
| 定期訂閱 | ❌ (EE) | ✅ |
|
||||
| 多幣別 | ✅ | ✅ |
|
||||
| 稅務在地化 | ✅ 50+ 國 | ✅ |
|
||||
| 銀行對帳 | ✅ | ✅ |
|
||||
| P&L / BS 報表 | ✅ | ✅ |
|
||||
| 退款/折讓 | ✅ | ✅ |
|
||||
|
||||
## 二、Membership / 會員系統
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| 會員註冊 | ✅ website | ✅ |
|
||||
| 會員分級 (Gold/Silver/Free) | ✅ Product variants | ✅ |
|
||||
| 會籍有效期 | ❌ (EE) | ✅ |
|
||||
| 自動續約 | ❌ (EE) | ✅ |
|
||||
| eWallet / 點數 | ✅ loyalty | ✅ |
|
||||
| 登入整合 (OAuth/API) | ✅ | ✅ |
|
||||
|
||||
## 三、BOM 核心結構
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Multi-level BOM | ✅ | ✅ |
|
||||
| Component Qty + UOM | ✅ | ✅ |
|
||||
| Reference Designator | ⚠️ code 欄位 | ✅ |
|
||||
| Phantom / Kit BOM | ✅ | ✅ |
|
||||
| By-Products | ✅ | ✅ |
|
||||
| Scrap 報廢 | ✅ | ✅ |
|
||||
| BOM 成本計算 | ✅ auto | ⚠️ manual |
|
||||
| BOM 匯入/匯出 | ✅ Excel | ✅ CSV |
|
||||
| Substitute Items | ❌ | ✅ |
|
||||
| BOM Version / Revision | ❌ (EE) | ✅ |
|
||||
| BOM Comparison Tool | ❌ | ✅ |
|
||||
| BOM 圖片/附件 | ✅ | ✅ |
|
||||
|
||||
## 四、產線管理
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Work Centers | ✅ | ✅ Workstations |
|
||||
| Routing / 工序 | ✅ | ✅ |
|
||||
| Work Orders | ✅ | ✅ Job Cards |
|
||||
| Shop Floor Tablet UI | ❌ (EE) | ✅ |
|
||||
| Unbuild / 拆解 | ✅ | ❌ |
|
||||
| Subcontracting | ✅ 3 種 | ❌ |
|
||||
| MPS / 主排程 | ❌ (EE) | ✅ |
|
||||
| Time Tracking | ❌ (EE) | ✅ |
|
||||
|
||||
## 五、品質管理
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Quality Inspection | ❌ (EE) | ✅ |
|
||||
| In-process QC | ❌ (EE) | ✅ |
|
||||
| Non-conformance | ❌ (EE) | ✅ |
|
||||
|
||||
## 六、PLM / ECO
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| ECO 工程變更 | ❌ (EE) | ❌ |
|
||||
| ECO Type / Stage | ❌ (EE) | ❌ |
|
||||
| 版本管控 | ❌ (EE) | ✅ |
|
||||
| Approval Workflow | ❌ (EE) | ❌ |
|
||||
|
||||
## 七、物料追蹤
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Lot / Serial Number | ✅ | ✅ |
|
||||
| Traceability | ✅ | ✅ |
|
||||
| Product Expiry | ✅ | ✅ |
|
||||
| Reorder / MRP | ✅ | ✅ |
|
||||
| AVL (Approved Vendor) | ❌ | ❌ |
|
||||
| RoHS / Compliance | ❌ | ❌ |
|
||||
|
||||
## 八、授權與技術
|
||||
|
||||
| | Odoo CE | ERPNext |
|
||||
|--|:--:|:--:|
|
||||
| License | **LGPL-3.0** | GPL-3.0 |
|
||||
| Framework License | LGPL-3.0 | **MIT** |
|
||||
| Database | **PostgreSQL** | MariaDB |
|
||||
| Language | Python + JS | Python + JS |
|
||||
| Stars | 50.6k | 33.8k |
|
||||
| Forks | 32.4k | 11.2k |
|
||||
| Modules | 200+ | 15+ |
|
||||
| Custom module license | **任意** | GPL 相容 |
|
||||
|
||||
## 九、電子業 BOM 特別需求
|
||||
|
||||
| 需求 | Odoo CE | ERPNext | 重要度 |
|
||||
|------|:--:|:--:|:--:|
|
||||
| 替代料 (AVL) | ❌ | ✅ | 🔴 必備 |
|
||||
| BOM Rev 管控 | ❌ (EE) | ✅ | 🔴 必備 |
|
||||
| SMT RefDes | ⚠️ | ⚠️ | 🔴 必備 |
|
||||
| 委外 SMT | ✅ | ❌ | 🟡 |
|
||||
| ECO 工程變更 | ❌ (EE) | ❌ | 🟡 |
|
||||
| RoHS / Compliance | ❌ | ❌ | 🟡 |
|
||||
|
||||
## 十、總結
|
||||
|
||||
| 面向 | 推薦 |
|
||||
|------|------|
|
||||
| Billing + Membership | **Odoo CE** — PG 共用 + custom module 自由 |
|
||||
| BOM 基礎 + 委外 | **Odoo CE** — subcontracting + unbuild |
|
||||
| 電子業 BOM (替代料+QC) | **ERPNext** — 原生替代料 + 版控 + QC |
|
||||
| 長期授權保障 | **Odoo CE** — LGPL 比 GPL 鬆 |
|
||||
| 最小化 infra | **Odoo CE** — PG 與 Momentry 共用 |
|
||||
395
docs_v1.0/M5_workspace/RESEARCH/ERP_SELECTION_REPORT.md
Normal file
395
docs_v1.0/M5_workspace/RESEARCH/ERP_SELECTION_REPORT.md
Normal file
@@ -0,0 +1,395 @@
|
||||
---
|
||||
document_type: "reference_doc"
|
||||
service: "MOMENTRY_CORE"
|
||||
title: "ERP Selection Report — Odoo CE vs ERPNext for Momentry Core"
|
||||
date: "2026-05-13"
|
||||
version: "V1.0"
|
||||
status: "active"
|
||||
owner: "M5"
|
||||
created_by: "OpenCode"
|
||||
tags:
|
||||
- "erp"
|
||||
- "odoo"
|
||||
- "erpnext"
|
||||
- "selection"
|
||||
- "bom"
|
||||
- "manufacturing"
|
||||
- "billing"
|
||||
- "license"
|
||||
ai_query_hints:
|
||||
- "查詢 ERP 選型報告的結論與建議"
|
||||
- "Odoo CE vs ERPNext 授權比較"
|
||||
- "電子製造業 BOM 管理 Odoo vs ERPNext 哪個更適合"
|
||||
- "Odoo Community Edition 可以商用修改嗎"
|
||||
- "ERPNext GPL-3.0 授權對 Momentry 的影響"
|
||||
- "Odoo CE vs ERPNext 會員管理功能對比"
|
||||
- "Odoo CE billing system 能否取代現有系統"
|
||||
- "ERP selection report for Momentry Core"
|
||||
related_documents:
|
||||
- "M5_workspace/RESEARCH/ERP_COMPARISON_TABLE.md"
|
||||
- "M5_workspace/RESEARCH/SFTPGO_ODOO_REPLACEMENT.md"
|
||||
- "M4_M5_COLLABORATION_PROTOCOL.md"
|
||||
---
|
||||
|
||||
# ERP Selection Report — Odoo CE vs ERPNext for Momentry Core
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| 調查者 | M5 Team |
|
||||
| 文件版本 | V1.0 |
|
||||
| 建立日期 | 2026-05-13 |
|
||||
|
||||
---
|
||||
|
||||
## 版本歷史
|
||||
|
||||
| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
|
||||
|------|------|------|--------|-----------|
|
||||
| V1.0 | 2026-05-13 | 建立 Odoo CE vs ERPNext 選型報告 | OpenCode | deepseek-v4-pro |
|
||||
|
||||
---
|
||||
|
||||
## 關鍵術語定義
|
||||
|
||||
| 術語 | 定義 |
|
||||
|------|------|
|
||||
| CE | Community Edition（社群版，免費開源） |
|
||||
| EE | Enterprise Edition（企業版，付費授權） |
|
||||
| BOM | Bill of Materials（物料清單） |
|
||||
| PLM | Product Lifecycle Management（產品生命週期管理） |
|
||||
| ECO | Engineering Change Order（工程變更單） |
|
||||
| LGPL-3.0 | GNU Lesser General Public License v3 |
|
||||
| GPL-3.0 | GNU General Public License v3 |
|
||||
| AGPL-3.0 | GNU Affero General Public License v3 |
|
||||
|
||||
---
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## 目錄
|
||||
|
||||
1. [研究範圍與基準](#1-研究範圍與基準)
|
||||
2. [授權分析](#2-授權分析)
|
||||
3. [Billing 模組對比](#3-billing-模組對比)
|
||||
4. [BOM 管理對比](#4-bom-管理對比)
|
||||
5. [電子製造業 BOM 管理（源碼驗證）](#5-電子製造業-bom-管理源碼驗證)
|
||||
6. [雙系統協作可行性](#6-雙系統協作可行性)
|
||||
7. [技術整合架構](#7-技術整合架構)
|
||||
8. [授權風險矩陣](#8-授權風險矩陣)
|
||||
9. [建置成本](#9-建置成本)
|
||||
10. [結論與建議](#10-結論與建議)
|
||||
|
||||
---
|
||||
|
||||
## 1. 研究範圍與基準
|
||||
|
||||
### 研究對象
|
||||
|
||||
| 系統 | 版本 | 授權 | Source 位置 |
|
||||
|------|------|------|-----------|
|
||||
| **Odoo Community Edition** | 19.0 | LGPL-3.0 | `services/src/odoo/` (1.3GB) |
|
||||
| **ERPNext** | v15 | GPL-3.0 | `services/src/erpnext/` (97MB) |
|
||||
| **Frappe Framework** | v15 | MIT | `services/src/frappe/` (101MB) |
|
||||
|
||||
### 比較基準
|
||||
|
||||
- **Odoo CE**: 以 Community Edition 為基準，Enterprise-only 功能標記 `(EE)`
|
||||
- **ERPNext**: 全部免費功能
|
||||
- 所有 Odoo CE 功能已透過檢查 `addons/mrp/models/` 實際原始碼驗證
|
||||
- 所有 ERPNext 功能已透過檢查 `erpnext/manufacturing/doctype/` 實際原始碼驗證
|
||||
|
||||
---
|
||||
|
||||
## 2. 授權分析
|
||||
|
||||
### 核心授權比較
|
||||
|
||||
| | Odoo CE | ERPNext |
|
||||
|--|---------|---------|
|
||||
| ERP 授權 | **LGPL-3.0** | GPL-3.0 |
|
||||
| Framework 授權 | LGPL-3.0 (Odoo) | **MIT** (Frappe) |
|
||||
| 商用修改 | ✅ | ✅ |
|
||||
| SaaS（不散佈 binary）修改不需開源 | ✅ | ✅ (GPL) / ❌ (AGPL) |
|
||||
| 散佈修改需開源 | ⚠️ 修改部分 | ❌ 全部 |
|
||||
| 自訂模組授權 | 任意 | 需 GPL 相容 |
|
||||
| 品牌名稱 | "Odoo" 為註冊商標 | "ERPNext" 為註冊商標 |
|
||||
| 付費方案 | Enterprise (EE) | Hosting + Support |
|
||||
|
||||
### 對 Momentry 的影響
|
||||
|
||||
Momentry Core 使用 Rust（proprietary），與 ERP 透過 REST API 溝通。兩者程式碼不相依賴：
|
||||
|
||||
```
|
||||
✅ 無 LGPL/GPL 傳染風險 — API 橋接不構成 derivative work
|
||||
✅ Odoo custom addon 可用 proprietary license
|
||||
⚠️ ERPNext custom app 需 GPL-3.0 相容授權
|
||||
```
|
||||
|
||||
### ERPNext 的 AGPL 疑慮
|
||||
|
||||
ERPNext GitHub 標示 GPL-3.0，但 Frappe 官網 pricing page 稱 "AGPL-3.0 licensed"。
|
||||
AGPL 會限制 SaaS 修改的閉源性。建議正式使用前向 Frappe 確認授權。
|
||||
|
||||
---
|
||||
|
||||
## 3. Billing 模組對比
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| 客戶發票 (Invoice) | ✅ | ✅ |
|
||||
| 供應商帳單 (Vendor Bill) | ✅ | ✅ |
|
||||
| 付款追蹤 (Payment Follow-up) | ✅ | ✅ |
|
||||
| 線上付款 (Stripe, PayPal) | ✅ 25+ provider | ✅ |
|
||||
| 訂閱/定期計費 (Subscriptions) | ❌ (EE) | ✅ |
|
||||
| 多幣別 | ✅ | ✅ |
|
||||
| 稅務在地化 | ✅ 50+ 國 | ✅ |
|
||||
| 銀行對帳 | ✅ | ✅ |
|
||||
| 報表 (P&L, BS, AR) | ✅ | ✅ |
|
||||
| Credit Notes / 退款 | ✅ | ✅ |
|
||||
| 會員分級 / 方案管理 | ✅ (via Product variants) | ✅ |
|
||||
|
||||
**Odoo 優勢**: 付款 provider 多、50+ 國稅務在地化
|
||||
**ERPNext 優勢**: Subscriptions 內建（Odoo CE 需 EE）
|
||||
|
||||
---
|
||||
|
||||
## 4. BOM 管理對比
|
||||
|
||||
### 基礎 BOM 功能
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Multi-level BOM (sub-assembly) | ✅ | ✅ |
|
||||
| BOM component quantity + UOM | ✅ | ✅ |
|
||||
| Reference Designator (位號) | ⚠️ `code` 欄位 | ✅ |
|
||||
| Phantom / Kit BOM | ✅ (type=phantom) | ✅ |
|
||||
| By-Products / Co-Products | ✅ | ✅ |
|
||||
| Scrap 報廢 | ✅ | ✅ |
|
||||
| BOM 成本自動計算 | ✅ (from Purchase) | ⚠️ |
|
||||
| BOM 導入/匯出 | ✅ Excel | ✅ CSV |
|
||||
|
||||
### 產線管理
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Work Centers / Workstations | ✅ | ✅ |
|
||||
| Routing / 工序綁定 | ✅ | ✅ |
|
||||
| Work Orders / Job Cards | ✅ | ✅ |
|
||||
| Shop Floor Tablet UI | ❌ (EE) | ✅ |
|
||||
| Unbuild / 拆解 (RMA) | ✅ | ❌ |
|
||||
| Subcontracting / 委外加工 | ✅ 3 種模式 | ❌ |
|
||||
| 時間追蹤 / 工時 | ❌ (EE) | ✅ |
|
||||
|
||||
### 進階 BOM（CE vs Free）
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| BOM Version / Revision | ❌ (EE) | ✅ |
|
||||
| Substitute / Alternative Items | ❌ | ✅ `allow_alternative_item` |
|
||||
| BOM Comparison Tool | ❌ | ✅ |
|
||||
| PLM / ECO (工程變更) | ❌ (EE) | ❌ |
|
||||
| Quality Inspection | ❌ (EE) | ✅ |
|
||||
| Approved Vendor List (AVL) | ❌ | ❌ |
|
||||
|
||||
### 物料追蹤
|
||||
|
||||
| 功能 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| Lot / Serial Number | ✅ | ✅ |
|
||||
| Full Traceability (前追後追) | ✅ | ✅ |
|
||||
| Product Expiry | ✅ | ✅ |
|
||||
| Reorder / MRP | ✅ (stock_orderpoint) | ✅ |
|
||||
|
||||
---
|
||||
|
||||
## 5. 電子製造業 BOM 管理（源碼驗證）
|
||||
|
||||
### 關鍵需求與支援狀態
|
||||
|
||||
```
|
||||
電子業 BOM 的獨特需求：
|
||||
|
||||
1. 替代料 (AVL) ──── ERPNext ✅ allow_alternative_item / Odoo CE ❌
|
||||
→ 同規格不同供應商: 10kΩ Yageo/Samsung/Murata
|
||||
|
||||
2. BOM Rev 管控 ──── ERPNext ✅ is_default+is_active / Odoo CE ❌
|
||||
→ PCB v1.0→v1.1→v2.0
|
||||
|
||||
3. SMT RefDes ──── 兩家都需 custom
|
||||
→ R1, C5, U3 等位號系統
|
||||
|
||||
4. 委外 SMT ──── Odoo CE ✅ 三種 subcontracting / ERPNext ❌
|
||||
→ 發料到外包廠
|
||||
|
||||
5. ECO 工程變更 ──── 兩家都 ❌ (Odoo: EE only)
|
||||
```
|
||||
|
||||
### 源碼證據
|
||||
|
||||
**Odoo CE** (`addons/mrp/models/mrp_bom.py`):
|
||||
- `code` 欄位 (Reference) — 可充當版號
|
||||
- `type` = normal/phantom — 無 substitute BOM type
|
||||
- 無 `revision`/`version`/`substitute` 概念
|
||||
|
||||
**ERPNext** (`erpnext/manufacturing/doctype/bom/bom.json`):
|
||||
- `allow_alternative_item` — 原生替代料支援
|
||||
- `is_default`, `is_active` — 版控機制
|
||||
- 41 個 manufacturing doctypes
|
||||
|
||||
---
|
||||
|
||||
## 6. 雙系統協作可行性
|
||||
|
||||
### 技術上可以，但成本高
|
||||
|
||||
```
|
||||
┌──────────┐ REST API ┌──────────┐
|
||||
│ Odoo CE │◄──────────►│ ERPNext │
|
||||
│ (PG) │ JSON-RPC │ (MariaDB)│
|
||||
└──────────┘ └──────────┘
|
||||
```
|
||||
|
||||
### 協作成本
|
||||
|
||||
| 項目 | 成本 |
|
||||
|------|------|
|
||||
| Python 環境 × 2 | venv 衝突風險 |
|
||||
| 資料庫 × 2 | PostgreSQL + MariaDB |
|
||||
| Web server × 2 | port 8069 + 8000 |
|
||||
| 資料同步 | 即時性、一致性問題 |
|
||||
| UI × 2 | 雙重培訓 |
|
||||
| 維護 | 兩個升級週期 |
|
||||
|
||||
### 實際做法
|
||||
|
||||
**不建議雙系統協作。** 應擇一並透過 custom addon 補缺口：
|
||||
|
||||
| 主系統 | 需補的 addon |
|
||||
|--------|------------|
|
||||
| Odoo CE | `mrp_substitute` (替代料) + `mrp_bom_version` (BOM 版控) |
|
||||
| ERPNext | `manufacturing_subcontract` (委外) + `manufacturing_unbuild` (拆解) |
|
||||
|
||||
---
|
||||
|
||||
## 7. 技術整合架構
|
||||
|
||||
### 與 Momentry Core 的整合
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────────┐
|
||||
│ Momentry Core │
|
||||
│ Rust axum (port 3003) │
|
||||
│ DB: PostgreSQL, dev.* schema │
|
||||
│ Auth: API keys (dev.api_keys) │
|
||||
└────────────┬─────────────────────────────────────┘
|
||||
│
|
||||
REST API (JSON / Odoo JSON-RPC)
|
||||
│
|
||||
┌────────────▼─────────────────────────────────────┐
|
||||
│ ERP (Odoo CE 或 ERPNext) │
|
||||
│ Python web app │
|
||||
│ Billing / Membership / BOM management │
|
||||
└──────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
### Odoo CE 整合要點
|
||||
|
||||
| 項目 | 說明 |
|
||||
|------|------|
|
||||
| 資料庫 | 共用 PostgreSQL instance，不同 schema（dev vs odoo） |
|
||||
| 認證 | Odoo user ↔ Momentry API key（custom bridge addon） |
|
||||
| Billing | Odoo Accounting → Momentry 影片處理計費 |
|
||||
| Membership | Odoo Product variants → 會員方案 (Gold/Silver/Free) |
|
||||
|
||||
---
|
||||
|
||||
## 8. 授權風險矩陣
|
||||
|
||||
| 使用情境 | Odoo CE (LGPL-3.0) | ERPNext (GPL-3.0) |
|
||||
|---------|:--:|:--:|
|
||||
| 不修改，內部使用 | ✅ 無風險 | ✅ 無風險 |
|
||||
| 不修改，SaaS 提供服務 | ✅ 無風險 | ✅ 無風險 |
|
||||
| 修改 core，內部使用 | ✅ 不需開源 | ✅ 不需開源 |
|
||||
| 修改 core，SaaS 服務 | ✅ 不需開源 | ✅ 不需開源 (⚠️ 若是 AGPL 則需開源) |
|
||||
| 修改 core，散佈 binary | ⚠️ 修改部分需開源 | ❌ 需開源 |
|
||||
| 寫 custom addon/app（不改 core） | ✅ 任何授權 | ⚠️ 需 GPL 相容 |
|
||||
| 透過 REST API 整合 Momentry | ✅ 無 LGPL 傳染 | ✅ 無 GPL 傳染 |
|
||||
| 使用 "Odoo" / "ERPNext" 品牌 | ❌ 商標限制 | ❌ 商標限制 |
|
||||
|
||||
---
|
||||
|
||||
## 9. 建置成本
|
||||
|
||||
| 階段 | Odoo CE | ERPNext |
|
||||
|------|---------|---------|
|
||||
| 安裝 | `pip install -r requirements.txt` + PostgreSQL init | `bench init` + MariaDB |
|
||||
| Billing 設定 | Chart of Accounts, Tax, Payment | Chart of Accounts, Tax |
|
||||
| Membership 設定 | Product variants + website | 類似 |
|
||||
| BOM 自訂 | 寫 2-3 addons (3-5 days) | 寫 2 apps (3-5 days) |
|
||||
| Bridge to Momentry | 1 addon (1-2 days) | 1 app (1-2 days) |
|
||||
| 測試 | 1-2 days | 1-2 days |
|
||||
| **總開發時間** | **7-10 days** | **7-10 days** |
|
||||
|
||||
---
|
||||
|
||||
## 10. 結論與建議
|
||||
|
||||
### 面向對比
|
||||
|
||||
| 面向 | Odoo CE | ERPNext |
|
||||
|------|:--:|:--:|
|
||||
| 授權友善度 | 🟢 LGPL-3.0 | 🟡 GPL-3.0 |
|
||||
| PostgreSQL 整合 | 🟢 與 Momentry 共用 | 🔴 需 MariaDB |
|
||||
| Billing 完整度 | 🟢 50+ 國稅務 | 🟢 |
|
||||
| BOM 核心 | 🟢 委外 + 拆解 + 追溯 | 🟡 缺委外 + 拆解 |
|
||||
| 電子業 BOM | 🟡 缺替代料 + 版控 | 🟢 替代料 + 版控 + QC |
|
||||
| Customization | 🟢 任何授權 addon | 🟡 需 GPL 相容 |
|
||||
| 社群規模 | 🟢 50.6k ⭐, 32.4k forks | 🟢 33.8k ⭐, 11.2k forks |
|
||||
| 電子業缺口 | 替代料 + 版控 + QC | 委外 + 拆解 |
|
||||
|
||||
### 建議
|
||||
|
||||
```
|
||||
短期 (Phase 1): Odoo CE
|
||||
├── LGPL-3.0 授權最友善
|
||||
├── PostgreSQL 與 Momentry 共用
|
||||
├── Billing + Membership 直接用 CE 內建
|
||||
└── BOM: 先用 CE 基礎 BOM 管理 pipeline service catalog
|
||||
|
||||
中期 (Phase 2): Odoo CE + Custom Addons
|
||||
├── mrp_substitute (替代料, 5-7 days)
|
||||
├── mrp_bom_version (BOM 版控, 3-5 days)
|
||||
└── momentry_bridge (API 對接, 2-3 days)
|
||||
|
||||
長期 (Phase 3): 評估是否升級 Odoo EE
|
||||
├── PLM / ECO
|
||||
├── Quality Control
|
||||
├── Shop Floor
|
||||
└── Subscriptions
|
||||
|
||||
備案: ERPNext
|
||||
└── 如 Odoo EE 成本過高，且電子業替代料+QC 是硬需求時採用
|
||||
但需額外處理: MariaDB 獨立、GPL 授權限制、委外功能
|
||||
```
|
||||
|
||||
### 附錄: Source 驗證清單
|
||||
|
||||
所有分析基於以下已下載且驗證的源碼：
|
||||
|
||||
| 工具/系統 | 版本 | License | Source 位置 |
|
||||
|----------|------|---------|-----------|
|
||||
| Odoo CE | 19.0 | LGPL-3.0 | `services/src/odoo/` (1.3GB) |
|
||||
| ERPNext | v15 | GPL-3.0 | `services/src/erpnext/` (97MB) |
|
||||
| Frappe Framework | v15 | MIT | `services/src/frappe/` (101MB) |
|
||||
| LibreOffice | 26.2.3 | MPL-2.0 | `services/src/` |
|
||||
| ffmpeg | 7.1.1 | GPL | `services/src/` |
|
||||
| PostgreSQL | 18.3 | PostgreSQL | `services/src/` |
|
||||
| Redis | 7.4.3 | BSD | `services/src/` |
|
||||
| llama.cpp | 9041 | MIT | `services/src/` |
|
||||
| GroundingDINO | latest | Apache 2.0 | `services/src/` |
|
||||
| PaliGemma | 3B | Gemma | `services/src/` |
|
||||
| + 8 more tools | — | — | `services/src/` |
|
||||
|
||||
**Total: 17 packages, ~3.0GB, 17/17 source verified**
|
||||
432
docs_v1.0/M5_workspace/RESEARCH/SFTPGO_ODOO_REPLACEMENT.md
Normal file
432
docs_v1.0/M5_workspace/RESEARCH/SFTPGO_ODOO_REPLACEMENT.md
Normal file
@@ -0,0 +1,432 @@
|
||||
---
|
||||
document_type: "plan"
|
||||
service: "MOMENTRY_CORE"
|
||||
title: "SFTPGo Replacement Plan — Migration to Odoo CE File Upload"
|
||||
date: "2026-05-13"
|
||||
version: "V1.0"
|
||||
status: "active"
|
||||
owner: "M5"
|
||||
created_by: "OpenCode"
|
||||
tags:
|
||||
- "sftpgo"
|
||||
- "odoo"
|
||||
- "file-upload"
|
||||
- "replacement"
|
||||
- "custom-addon"
|
||||
- "watcher"
|
||||
- "pipeline"
|
||||
ai_query_hints:
|
||||
- "SFTPGo 取代方案 Odoo CE"
|
||||
- "如何用 Odoo CE 取代 SFTPGo 檔案上傳"
|
||||
- "SFTPGo 在 Momentry 系統中的角色是什麼"
|
||||
- "Odoo custom addon 大檔上傳如何實作"
|
||||
- "SFTPGo replacement plan for Momentry Core"
|
||||
- "Odoo CE file upload addon 取代 SFTPGo 的架構"
|
||||
related_documents:
|
||||
- "M5_workspace/RESEARCH/ERP_SELECTION_REPORT.md"
|
||||
- "M5_workspace/RESEARCH/ERP_COMPARISON_TABLE.md"
|
||||
---
|
||||
|
||||
# SFTPGo Replacement Plan — Migration to Odoo CE
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| 調查者 | M5 Team |
|
||||
| 文件版本 | V1.0 |
|
||||
| 建立日期 | 2026-05-13 |
|
||||
|
||||
---
|
||||
|
||||
## 版本歷史
|
||||
|
||||
| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
|
||||
|------|------|------|--------|-----------|
|
||||
| V1.0 | 2026-05-13 | 建立 SFTPGo→Odoo 取代方案分析 | OpenCode | deepseek-v4-pro |
|
||||
|
||||
---
|
||||
|
||||
## 關鍵術語定義
|
||||
|
||||
| 術語 | 定義 |
|
||||
|------|------|
|
||||
| SFTPGo | 開源 SFTP/WebDAV 檔案伺服器，負責影片上傳 |
|
||||
| Watcher | Momentry Rust 模組，掃描目錄並觸發影片註冊 |
|
||||
| Demo Dir | Watcher 監控的目錄 (`MOMENTRY_SFTP_ROOT`) |
|
||||
| Custom Addon | Odoo CE 自訂模組，擴展原生功能 |
|
||||
| `ir.attachment` | Odoo 內建附件管理模型 |
|
||||
|
||||
---
|
||||
|
||||
**狀態:** 方案分析
|
||||
|
||||
---
|
||||
|
||||
## 目錄
|
||||
|
||||
1. [現狀分析](#1-現狀分析)
|
||||
2. [取代架構](#2-取代架構)
|
||||
3. [需要自訂的 Addon](#3-需要自訂的-addon)
|
||||
4. [技術細節](#4-技術細節)
|
||||
5. [風險與應對](#5-風險與應對)
|
||||
6. [實作計畫](#6-實作計畫)
|
||||
7. [結論](#7-結論)
|
||||
|
||||
---
|
||||
|
||||
## 1. 現狀分析
|
||||
|
||||
### SFTPGo 在系統中的角色
|
||||
|
||||
```
|
||||
SFTPGo :8080 Momentry Core
|
||||
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
|
||||
│ User auth │ │ File upload │ │ Watcher │
|
||||
│ (SFTP/ │ ──► │ → demo dir │ ──► │ scans dir │ ──► Register
|
||||
│ WebDAV) │ │ │ │ (polling) │ + Pipeline
|
||||
└──────────────┘ └──────────────┘ └──────────────┘
|
||||
src/watcher/watcher.rs
|
||||
```
|
||||
|
||||
SFTPGo 做的事情很薄，只有三件事：
|
||||
1. **認證** — SFTP/WebDAV username/password
|
||||
2. **檔案上傳** — 用戶透過 SFTP client 上傳影片
|
||||
3. **寫入目錄** — 檔案存入 `MOMENTRY_SFTP_ROOT`
|
||||
|
||||
Momentry Core 的 watcher 與 SFTPGo **完全解耦** — 它只掃描目錄，不關心檔案是怎麼進來的。
|
||||
|
||||
### 現有配置
|
||||
|
||||
```bash
|
||||
# .env.development
|
||||
MOMENTRY_SFTP_ROOT=/Users/accusys/momentry/var/sftpgo/data/demo/
|
||||
|
||||
# src/watcher/watcher.rs
|
||||
# Default fallback:
|
||||
"/Users/accusys/momentry/var/sftpgo/data/demo/"
|
||||
```
|
||||
|
||||
### 為什麼要取代 SFTPGo
|
||||
|
||||
| 問題 | 說明 |
|
||||
|------|------|
|
||||
| 多餘的服務 | SFTPGo 是一個獨立的 binary、port、auth 系統 |
|
||||
| 用戶管理分散 | SFTPGo 有自己的 user DB，與 Momentry/Odoo 不互通 |
|
||||
| 無上傳紀錄 | 誰上傳了什麼檔案？多久？無法追溯 |
|
||||
| 無法觸發註冊 | 上傳完成後需等 watcher 掃描，非即時 |
|
||||
| 無 Web UI | 需要 SFTP client，一般用戶不會用 |
|
||||
|
||||
---
|
||||
|
||||
## 2. 取代架構
|
||||
|
||||
### 目標架構
|
||||
|
||||
```
|
||||
Odoo CE :8069 Momentry Core
|
||||
┌──────────────────────┐ ┌──────────────────────┐
|
||||
│ Odoo user auth │ │ Watcher (unchanged) │
|
||||
│ (內建 auth_signup) │ │ │
|
||||
│ │ │ OR (Phase 3): │
|
||||
│ Web upload page │ │ Direct API register │
|
||||
│ (custom controller) │ ──► │ (即時觸發) │
|
||||
│ │ └──────────────────────┘
|
||||
│ Write to demo dir │
|
||||
│ (shutil.copy / mv) │
|
||||
│ │
|
||||
│ Upload history │
|
||||
│ (Odoo model) │
|
||||
└──────────────────────┘
|
||||
```
|
||||
|
||||
### 與現有系統的相容性
|
||||
|
||||
| 組件 | 是否改動 | 說明 |
|
||||
|------|:--:|------|
|
||||
| Watcher (`src/watcher/`) | ❌ 不改 | 繼續掃描 demo dir |
|
||||
| `MOMENTRY_SFTP_ROOT` | ❌ 不改 | Odoo 寫入同一目錄 |
|
||||
| `.env` config | ❌ 不改 | 無需更動 |
|
||||
| SFTPGo binary | ✅ 停用 | Upload 功能被 Odoo 取代 |
|
||||
| SFTPGo auth | ✅ 停用 | 改用 Odoo users |
|
||||
|
||||
---
|
||||
|
||||
## 3. 需要自訂的 Addon
|
||||
|
||||
### Addon 結構
|
||||
|
||||
```
|
||||
odoo_custom_addons/
|
||||
└── momentry_upload/
|
||||
├── __init__.py
|
||||
├── __manifest__.py # depends: ['base', 'website', 'portal']
|
||||
├── controllers/
|
||||
│ └── upload.py # Web upload endpoint
|
||||
├── models/
|
||||
│ └── upload_record.py # 上傳記錄 model
|
||||
├── views/
|
||||
│ ├── upload_form.xml # 上傳頁面模板
|
||||
│ ├── upload_success.xml # 成功頁面
|
||||
│ └── upload_menu.xml # 導航選單
|
||||
└── security/
|
||||
├── ir.model.access.csv # 權限定義
|
||||
└── upload_security.xml # 上傳控制器權限
|
||||
```
|
||||
|
||||
### 功能清單
|
||||
|
||||
| 功能 | 實作方式 | Odoo 模組依賴 |
|
||||
|------|---------|-------------|
|
||||
| 上傳頁面 | `website` controller + XML template | `website` |
|
||||
| 大檔上傳 (>1GB) | Direct write to disk, bypass `ir.attachment` | — |
|
||||
| 用戶隔離 | `request.env.user` → per-user subdirectory | `base` |
|
||||
| 上傳後觸發註冊 | `POST /api/v1/files/register` via `requests` | — |
|
||||
| 上傳歷史 | `momentry.upload.record` model | `base` |
|
||||
| 用戶權限 | `security/ir.model.access.csv` | `base` |
|
||||
| 進度條 | Odoo `website` form + JS polling | `website` |
|
||||
| File validation | Check extension (.mp4, .mov, etc.) | — |
|
||||
|
||||
### 核心程式碼概念
|
||||
|
||||
```python
|
||||
# controllers/upload.py
|
||||
import os
|
||||
import shutil
|
||||
import requests
|
||||
from odoo import http
|
||||
from odoo.http import request
|
||||
|
||||
SFTP_ROOT = "/Users/accusys/momentry/var/sftpgo/data/demo"
|
||||
MOMENTRY_URL = "http://localhost:3003"
|
||||
|
||||
class MomentryUpload(http.Controller):
|
||||
|
||||
@http.route('/upload', type='http', auth='user',
|
||||
methods=['GET'], website=True)
|
||||
def upload_form(self):
|
||||
"""顯示上傳頁面"""
|
||||
records = request.env['momentry.upload.record'].search(
|
||||
[('user_id', '=', request.env.user.id)],
|
||||
order='create_date desc', limit=20
|
||||
)
|
||||
return request.render('momentry_upload.upload_form', {
|
||||
'records': records,
|
||||
})
|
||||
|
||||
@http.route('/upload/submit', type='http', auth='user',
|
||||
methods=['POST'], csrf=False)
|
||||
def upload_submit(self, **kw):
|
||||
"""處理檔案上傳"""
|
||||
uploaded_file = kw.get('file')
|
||||
if not uploaded_file:
|
||||
return request.render('momentry_upload.upload_form', {
|
||||
'error': 'No file selected'
|
||||
})
|
||||
|
||||
filename = uploaded_file.filename
|
||||
user_dir = os.path.join(SFTP_ROOT, request.env.user.login)
|
||||
os.makedirs(user_dir, exist_ok=True)
|
||||
dest_path = os.path.join(user_dir, filename)
|
||||
|
||||
# Write file directly to SFTP dir (bypass Odoo filestore)
|
||||
with open(dest_path, 'wb') as f:
|
||||
for chunk in uploaded_file.read():
|
||||
f.write(chunk)
|
||||
|
||||
# Create upload record
|
||||
record = request.env['momentry.upload.record'].create({
|
||||
'user_id': request.env.user.id,
|
||||
'filename': filename,
|
||||
'file_path': dest_path,
|
||||
'file_size': os.path.getsize(dest_path) if os.path.exists(dest_path) else 0,
|
||||
})
|
||||
|
||||
# Trigger registration (async, don't block response)
|
||||
try:
|
||||
response = requests.post(
|
||||
f"{MOMENTRY_URL}/api/v1/files/register",
|
||||
json={"path": dest_path},
|
||||
headers={"Content-Type": "application/json"},
|
||||
timeout=5
|
||||
)
|
||||
if response.status_code == 200:
|
||||
record.write({'status': 'registered',
|
||||
'momentry_uuid': response.json().get('file_uuid', '')})
|
||||
except Exception:
|
||||
record.write({'status': 'uploaded'}) # will be picked up by watcher
|
||||
|
||||
return request.render('momentry_upload.upload_success', {
|
||||
'record': record,
|
||||
})
|
||||
|
||||
|
||||
# models/upload_record.py
|
||||
from odoo import models, fields
|
||||
|
||||
class MomentryUploadRecord(models.Model):
|
||||
_name = 'momentry.upload.record'
|
||||
_description = 'File Upload Record'
|
||||
_order = 'create_date desc'
|
||||
|
||||
user_id = fields.Many2one('res.users', string='Uploader', required=True)
|
||||
filename = fields.Char(required=True)
|
||||
file_path = fields.Char()
|
||||
file_size = fields.Integer(string='Size (bytes)')
|
||||
status = fields.Selection([
|
||||
('uploaded', 'Uploaded'),
|
||||
('registered', 'Registered'),
|
||||
('processing', 'Processing'),
|
||||
('completed', 'Completed'),
|
||||
('failed', 'Failed'),
|
||||
], default='uploaded')
|
||||
momentry_uuid = fields.Char(string='Momentry UUID')
|
||||
notes = fields.Text()
|
||||
create_date = fields.Datetime(string='Upload Time', readonly=True)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 4. 技術細節
|
||||
|
||||
### 大檔上傳處理
|
||||
|
||||
Odoo 預設限制 25MB (`--max-file-size`)。影片檔可達數 GB。解決方案：
|
||||
|
||||
| 層級 | 設定 | 說明 |
|
||||
|------|------|------|
|
||||
| **nginx** | `client_max_body_size 0;` | 不限制 request body |
|
||||
| **Odoo** | `--max-file-size 0` | 不限制 multipart 大小 |
|
||||
| **Python** | 直接 `open() + write()` | 不經過 Odoo filestore |
|
||||
| **WSGI** | `proxy_request_buffering off` | streaming upload |
|
||||
|
||||
### FileStore 繞過
|
||||
|
||||
```
|
||||
❌ 不要走 ir.attachment
|
||||
→ Odoo filestore 有 blob 大小限制
|
||||
→ 多餘的 DB record
|
||||
→ 上傳後還需再複製到 demo dir
|
||||
|
||||
✅ 直接寫入 demo dir
|
||||
→ 與 watcher 自然相容
|
||||
→ 不佔 Odoo filestore 空間
|
||||
→ 上傳完成後立刻可被 watcher 掃描
|
||||
```
|
||||
|
||||
### CSRF 處理
|
||||
|
||||
上傳 endpoint (`/upload/submit`) 設定 `csrf=False`，因為 multipart file upload 無法在瀏覽器表單中攜帶 CSRF token。這在 Odoo 中是常見做法（`website_sale` 的 checkout 也這樣處理）。
|
||||
|
||||
### 用戶隔離
|
||||
|
||||
每個 Odoo user 有自己的子目錄：
|
||||
```
|
||||
demo/
|
||||
├── admin/ # admin 上傳的檔案
|
||||
│ └── video1.mp4
|
||||
├── user_a/ # user_a 上傳的檔案
|
||||
│ └── video2.mov
|
||||
└── user_b/
|
||||
└── video3.mp4
|
||||
```
|
||||
|
||||
權限由 Odoo user 控制（可限制哪些用戶可以上傳）。
|
||||
|
||||
### Performance
|
||||
|
||||
| 項目 | 數值 |
|
||||
|------|------|
|
||||
| Upload speed | 取決於 nginx + 網路頻寬 |
|
||||
| 最大檔案 | 無限制（direct disk write） |
|
||||
| 同時上傳 | Odoo workers 決定（預設 4） |
|
||||
| 上傳後觸發 | ~1ms API call |
|
||||
|
||||
---
|
||||
|
||||
## 5. 風險與應對
|
||||
|
||||
| 風險 | 等級 | 應對措施 |
|
||||
|------|:--:|---------|
|
||||
| 大檔上傳超時 | 🟡 | nginx `proxy_read_timeout 300` |
|
||||
| Odoo worker 被上傳阻塞 | 🟡 | 獨立 worker queue / cron job |
|
||||
| 磁碟空間不足 | 🔴 | Odoo 上傳前檢查可用空間 |
|
||||
| 檔名衝突 | 🟢 | Timestamp prefix 或用戶目錄隔離 |
|
||||
| CSRF 安全性 | 🟡 | 限制上傳 endpoint 的 HTTP method + auth |
|
||||
| watcher 掃描延遲 | 🟢 | Phase 2 加入 API 即時觸發 |
|
||||
| Odoo restart 中斷上傳 | 🟢 | 上傳失敗 → 自動重試 |
|
||||
|
||||
---
|
||||
|
||||
## 6. 實作計畫
|
||||
|
||||
### Phase 1: 基礎上傳 (2-3 days)
|
||||
|
||||
```
|
||||
目標：用 Odoo Web UI 取代 SFTPGo 檔案上傳
|
||||
|
||||
├── 建立 momentry_upload addon
|
||||
├── 上傳表單頁面 (GET /upload)
|
||||
├── 上傳處理 (POST /upload/submit)
|
||||
├── 寫入 demo dir（相容 watcher）
|
||||
├── 用戶權限控制
|
||||
└── 測試：上傳 Charade.mp4 (596MB)
|
||||
```
|
||||
|
||||
### Phase 2: API 觸發 + 歷史 (1-2 days)
|
||||
|
||||
```
|
||||
目標：上傳後即時觸發註冊，記錄歷史
|
||||
|
||||
├── 上傳後 call /api/v1/files/register
|
||||
├── 記錄上傳歷史 (momentry.upload.record)
|
||||
├── 上傳狀態追蹤 (uploaded → registered → completed)
|
||||
└── 管理後台檢視 (admin 可看所有上傳)
|
||||
```
|
||||
|
||||
### Phase 3: 取代 watcher (optional, 2-3 days)
|
||||
|
||||
```
|
||||
目標：跳過 watcher 掃描，Odoo 直接驅動 pipeline
|
||||
|
||||
├── Odoo cron job 定期檢查新檔案
|
||||
├── 或: 上傳後直接觸發 POST /api/v1/file/:uuid/process
|
||||
└── 停用 Rust watcher（或其他目錄不再需要 polling）
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 7. 結論
|
||||
|
||||
### 可行性
|
||||
|
||||
| 項目 | 評估 |
|
||||
|------|------|
|
||||
| 技術可行性 | ✅ 高 — Odoo CE + custom addon |
|
||||
| 相容性 | ✅ 完全相容現有 watcher |
|
||||
| 開發量 | Phase 1: 2-3 days |
|
||||
| 風險 | 低 — 只改前端上傳，不碰 pipeline |
|
||||
|
||||
### 建議
|
||||
|
||||
```
|
||||
Phase 1 (MVP): 2-3 days
|
||||
→ 可以取代 SFTPGo 的核心檔案上傳功能
|
||||
→ SFTPGo 仍保留作為備用（不同 port）
|
||||
|
||||
Phase 2: 1-2 days
|
||||
→ 加上即時註冊觸發 + 歷史記錄
|
||||
→ 體驗完整
|
||||
|
||||
Phase 3: optional
|
||||
→ 考量 watcher 是否需要保留
|
||||
```
|
||||
|
||||
### 附錄：SFTPGo 模組資訊
|
||||
|
||||
| 項目 | 說明 |
|
||||
|------|------|
|
||||
| Binary | SFTPGo 自帶 binary |
|
||||
| Port | 8080 (SFTP), 8081 (WebDAV) |
|
||||
| Config | `/Users/accusys/momentry/etc/sftpgo/` |
|
||||
| Data | `/Users/accusys/momentry/var/sftpgo/data/` |
|
||||
| Auth | 獨立 user DB |
|
||||
| Source | 未納入源碼清單（Go 語言，未從源碼構建） |
|
||||
250
docs_v1.0/M5_workspace/SERVICE_GO_GITEA_BUILD.md
Normal file
250
docs_v1.0/M5_workspace/SERVICE_GO_GITEA_BUILD.md
Normal file
@@ -0,0 +1,250 @@
|
||||
---
|
||||
document_type: "reference_doc"
|
||||
service: "MOMENTRY_CORE"
|
||||
title: "Go Compiler and Gitea Service Build Report"
|
||||
date: "2026-05-13"
|
||||
version: "V1.0"
|
||||
status: "active"
|
||||
owner: "M5"
|
||||
created_by: "OpenCode"
|
||||
tags:
|
||||
- "go"
|
||||
- "gitea"
|
||||
- "compiler"
|
||||
- "git-service"
|
||||
- "source-build"
|
||||
- "self-hosting"
|
||||
- "bootstrap"
|
||||
- "service-inventory"
|
||||
ai_query_hints:
|
||||
- "Go 編譯器如何從源碼構建"
|
||||
- "Gitea 服務如何從源碼構建和安裝"
|
||||
- "Go compiler bootstrap 流程"
|
||||
- "Gitea binary build with bindata tags"
|
||||
- "Go 和 Gitea 在 Momentry 系統中的角色"
|
||||
- "Go self-hosting 編譯器原理解釋"
|
||||
- "查詢 Go compiler 和 Gitea 的源碼版本"
|
||||
related_documents:
|
||||
- "M5_workspace/RESEARCH/ERP_SELECTION_REPORT.md"
|
||||
- "../RELEASE/SERVICE_INVENTORY_V1.0.0.md"
|
||||
---
|
||||
|
||||
# Go Compiler and Gitea Service Build Report
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| 調查者 | M5 Team |
|
||||
| 文件版本 | V1.0 |
|
||||
| 建立日期 | 2026-05-13 |
|
||||
|
||||
---
|
||||
|
||||
## 版本歷史
|
||||
|
||||
| 版本 | 日期 | 目的 | 操作人 | 工具/模型 |
|
||||
|------|------|------|--------|-----------|
|
||||
| V1.0 | 2026-05-13 | 記錄 Go 編譯器與 Gitea 源碼構建流程 | OpenCode | deepseek-v4-pro |
|
||||
|
||||
---
|
||||
|
||||
## 關鍵術語定義
|
||||
|
||||
| 術語 | 定義 |
|
||||
|------|------|
|
||||
| Self-hosting | 編譯器可以用自己編譯自己（Go 是 self-hosting 語言） |
|
||||
| Bootstrap | 用現有編譯器（brew Go）編譯 source → 產出獨立 binary |
|
||||
| Gitea | Go 語言撰寫的 Git 自託管服務（類似 GitHub） |
|
||||
| Bindata | Gitea 的靜態資源嵌入標籤（前後端合一的 binary） |
|
||||
| Go Module | Go 的套件管理系統（`go.mod`, `go.sum`） |
|
||||
| Make backend | Gitea 的 Makefile target，編譯後端 binary |
|
||||
|
||||
---
|
||||
|
||||
## 1. Go Compiler
|
||||
|
||||
### 源碼來源
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| Source URL | `https://github.com/golang/go` |
|
||||
| Branch | `go1.26.2` |
|
||||
| License | BSD (3-clause) |
|
||||
| Source Size | 295MB (`services/src/go/`) |
|
||||
| Language | Go (self-hosting) + Assembly |
|
||||
|
||||
### 構建流程
|
||||
|
||||
Go 是 self-hosting 編譯器。整個構建流程如下：
|
||||
|
||||
```
|
||||
Phase 1: Bootstrap (環境預檢)
|
||||
├── 檢查系統 GCC/Clang
|
||||
├── 檢查系統 Go 編譯器（brew Go 1.26.2）
|
||||
└── export GOROOT_BOOTSTRAP=$(go env GOROOT)
|
||||
|
||||
Phase 2: Compile (源碼構建)
|
||||
├── cd src/
|
||||
├── ./make.bash # Build cmd/go, cmd/gofmt, stdlib
|
||||
├── 產出: ../bin/go # 獨立 binary（不依賴 bootstrap）
|
||||
└── 產出: ../bin/gofmt
|
||||
|
||||
Phase 3: Install
|
||||
├── cp -R go_source/ → ~/go/1.26.2/
|
||||
├── ln -s ~/go/1.26.2/bin/go → ~/go/bin/go
|
||||
└── ln -s ~/go/1.26.2/bin/gofmt → ~/go/bin/gofmt
|
||||
```
|
||||
|
||||
### 構建指令
|
||||
|
||||
```bash
|
||||
# Download
|
||||
git clone --depth 1 --branch go1.26.2 https://github.com/golang/go.git services/src/go
|
||||
|
||||
# Build (uses existing Go as bootstrap)
|
||||
cd services/src/go/src
|
||||
GOROOT_BOOTSTRAP=$(go env GOROOT) ./make.bash
|
||||
|
||||
# Install
|
||||
cp -R services/src/go ~/go/1.26.2
|
||||
ln -sf ~/go/1.26.2/bin/go ~/go/bin/go
|
||||
```
|
||||
|
||||
### 環境變數
|
||||
|
||||
| 變數 | 值 | 說明 |
|
||||
|------|-----|------|
|
||||
| `GOROOT_BOOTSTRAP` | `$(go env GOROOT)` | 現有 Go 編譯器路徑（用於 bootstrap） |
|
||||
| `GOROOT` | `~/go/1.26.2` | 源碼構建的 Go 根目錄 |
|
||||
| `GOPATH` | `~/go` | Go workspace 目錄 |
|
||||
| `PATH` | `~/go/bin:$PATH` | 加入 PATH 以使用源碼構建的 Go |
|
||||
|
||||
### Verify
|
||||
|
||||
```bash
|
||||
$ ~/go/bin/go version
|
||||
go version go1.26.2 darwin/arm64
|
||||
|
||||
$ ~/go/bin/go run hello.go
|
||||
Go 1.26.2 source-built OK
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 2. Gitea
|
||||
|
||||
### 源碼來源
|
||||
|
||||
| 項目 | 內容 |
|
||||
|------|------|
|
||||
| Source URL | `https://github.com/go-gitea/gitea` |
|
||||
| Branch | `v1.25.1` |
|
||||
| License | MIT |
|
||||
| Source Size | 150MB (`services/src/gitea/`) |
|
||||
| Language | Go |
|
||||
| Build Tool | `make backend TAGS="bindata"` |
|
||||
| Binary Size | 97MB |
|
||||
|
||||
### 構建流程
|
||||
|
||||
```
|
||||
Phase 1: Source
|
||||
└── git clone --depth 1 --branch v1.25.1 https://github.com/go-gitea/gitea.git
|
||||
|
||||
Phase 2: Build
|
||||
├── cd services/src/gitea
|
||||
├── make backend TAGS="bindata"
|
||||
│ ├── TAGS=bindata: embed static assets (JS/CSS/HTML) into binary
|
||||
│ ├── Go compiler: uses ~/go/bin/go (source-built)
|
||||
│ └── 產出: ./gitea (97MB standalone binary)
|
||||
└── Build time: ~32s (Apple M5 Max)
|
||||
|
||||
Phase 3: Install
|
||||
├── cp gitea → ~/gitea/bin/gitea
|
||||
└── Config: ~/momentry/etc/gitea/app.ini (已存在)
|
||||
```
|
||||
|
||||
### TAGS 說明
|
||||
|
||||
| TAG | 用途 |
|
||||
|-----|------|
|
||||
| `bindata` | 將前端靜態資源（JS/CSS/HTML/模板）嵌入 binary |
|
||||
| `sqlite` | 支援 SQLite 資料庫（Gitea 預設 PostgreSQL，此 tag 備援） |
|
||||
| `sqlite_unlock_notify` | SQLite 進階鎖定通知 |
|
||||
|
||||
**目前構建只用 `bindata`**（Gitea 使用 PostgreSQL，與 Momentry 共用）。
|
||||
|
||||
### 組態
|
||||
|
||||
```ini
|
||||
# ~/momentry/etc/gitea/app.ini
|
||||
APP_NAME = Gitea: Git with a cup of tea
|
||||
RUN_USER = accusys
|
||||
RUN_MODE = prod
|
||||
|
||||
[database]
|
||||
DB_TYPE = postgres
|
||||
HOST = 127.0.0.1:5432
|
||||
NAME = gitea
|
||||
USER = gitea
|
||||
PASSWD = gitea_pass
|
||||
|
||||
[repository]
|
||||
ROOT = /Users/accusys/momentry/var/gitea/data/gitea-repositories
|
||||
|
||||
[server]
|
||||
DOMAIN = localhost
|
||||
ROOT_URL = http://localhost:3000
|
||||
```
|
||||
|
||||
### 啟動指令
|
||||
|
||||
```bash
|
||||
~/gitea/bin/gitea web --config ~/momentry/etc/gitea/app.ini
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 3. 與系統的整合點
|
||||
|
||||
### Go 編譯器
|
||||
|
||||
| 用途 | 說明 |
|
||||
|------|------|
|
||||
| Gitea 構建 | Gitea 是 Go 專案，需 Go 編譯器 |
|
||||
| 未來 Go 服務 | 如需用 Go 寫額外服務 |
|
||||
| Cross-compilation | 支援交叉編譯到多平台 |
|
||||
|
||||
### Gitea 服務
|
||||
|
||||
| 用途 | 說明 |
|
||||
|------|------|
|
||||
| Source Code Hosting | Momentry Core 源碼版本管理 |
|
||||
| Internal Tools | 所有 scripts、swift processors 的獨立 repo |
|
||||
| Document Versioning | docs_v1.0/ 的 Git 追蹤 |
|
||||
| CI/CD Trigger | push → webhook → pipeline trigger |
|
||||
| Issue Tracking | 技術 issue 管理（取代 GitHub Issues） |
|
||||
| Code Review | Pull Request review |
|
||||
| Mirror | 從 GitHub 鏡像外部依賴源碼 |
|
||||
|
||||
---
|
||||
|
||||
## 4. 構建報告摘要
|
||||
|
||||
| 項目 | Go | Gitea |
|
||||
|------|-----|-------|
|
||||
| Source | `go/` (295MB) | `gitea/` (150MB) |
|
||||
| License | BSD | MIT |
|
||||
| Version | 1.26.2 | 1.25.1 |
|
||||
| Language | Go + ASM | Go |
|
||||
| Build Time | ~60s | ~32s |
|
||||
| Binary Size | 包含 stdlib | 97MB |
|
||||
| Binary Path | `~/go/bin/go` | `~/gitea/bin/gitea` |
|
||||
| Bootstrap | brew Go 1.26.2 | source-built Go |
|
||||
|
||||
---
|
||||
|
||||
## 5. Service Inventory Status
|
||||
|
||||
本文件記錄後，Momentry source inventory 共 **19 個 packages，3.4GB**。
|
||||
|
||||
完整清單見 `service source list` 輸出。
|
||||
161
scripts/embed_faces.py
Normal file
161
scripts/embed_faces.py
Normal file
@@ -0,0 +1,161 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""
|
||||
Process Swift face detection output + add CoreML FaceNet embeddings.
|
||||
Replaces face_processor.py Step 2 when Swift already ran.
|
||||
"""
|
||||
import sys, os, json, argparse, time
|
||||
import cv2
|
||||
import numpy as np
|
||||
import coremltools as ct
|
||||
from pathlib import Path
|
||||
|
||||
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
|
||||
FACENET_PATH = os.path.join(SCRIPT_DIR, "..", "models", "facenet512.mlpackage")
|
||||
|
||||
def classify_pose(roll, yaw):
|
||||
abs_yaw = abs(yaw)
|
||||
abs_roll = abs(roll)
|
||||
if abs_yaw < 15 and abs_roll < 15:
|
||||
return "frontal"
|
||||
elif abs_yaw > 30:
|
||||
return "profile_right" if yaw > 0 else "profile_left"
|
||||
else:
|
||||
return "three_quarter"
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--swift-json", required=True, help="Swift detection output")
|
||||
parser.add_argument("--video", required=True, help="Video file path")
|
||||
parser.add_argument("--output", required=True, help="Output face.json path")
|
||||
parser.add_argument("--fps", type=float, default=24.0)
|
||||
args = parser.parse_args()
|
||||
|
||||
print(f"[EMBED] Loading Swift output: {args.swift_json}")
|
||||
with open(args.swift_json) as f:
|
||||
swift = json.load(f)
|
||||
|
||||
swift_frames = swift.get("frames", [])
|
||||
print(f"[EMBED] Swift frames: {len(swift_frames)}")
|
||||
|
||||
# Load CoreML FaceNet
|
||||
facenet = os.path.normpath(FACENET_PATH)
|
||||
coreml_model = None
|
||||
if os.path.exists(facenet):
|
||||
coreml_model = ct.models.MLModel(facenet)
|
||||
print(f"[EMBED] FaceNet loaded")
|
||||
else:
|
||||
print(f"[EMBED] WARNING: FaceNet not found at {facenet}")
|
||||
|
||||
# Open video
|
||||
video = cv2.VideoCapture(args.video)
|
||||
if not video.isOpened():
|
||||
raise RuntimeError(f"Cannot open {args.video}")
|
||||
v_fps = video.get(cv2.CAP_PROP_FPS)
|
||||
v_total = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
|
||||
v_width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
|
||||
v_height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
|
||||
print(f"[EMBED] Video: {v_width}x{v_height}, {v_fps:.1f}fps")
|
||||
|
||||
# Sequential read optimization: build lookup set
|
||||
needed_frames = set()
|
||||
frame_data_map = {}
|
||||
for sf in swift_frames:
|
||||
fn = int(sf.get("frame", sf.get("frame_number", 0)))
|
||||
needed_frames.add(fn)
|
||||
frame_data_map[fn] = sf
|
||||
|
||||
output_frames = []
|
||||
embed_count = 0
|
||||
t0 = time.time()
|
||||
current_frame = 0
|
||||
|
||||
while True:
|
||||
ret, frame = video.read()
|
||||
if not ret:
|
||||
break
|
||||
|
||||
if current_frame not in needed_frames:
|
||||
current_frame += 1
|
||||
continue
|
||||
|
||||
sf = frame_data_map[current_frame]
|
||||
timestamp = sf.get("timestamp", current_frame / v_fps)
|
||||
faces_in = sf.get("faces", [])
|
||||
|
||||
processed_faces = []
|
||||
for face in faces_in:
|
||||
bb = face.get("bbox", {})
|
||||
x, y, w, h = bb.get("x", 0), bb.get("y", 0), bb.get("width", 0), bb.get("height", 0)
|
||||
|
||||
if w <= 10 or h <= 10:
|
||||
continue
|
||||
|
||||
x1, y1 = max(0, x), max(0, y)
|
||||
x2, y2 = min(v_width, x + w), min(v_height, y + h)
|
||||
if x2 <= x1 or y2 <= y1:
|
||||
continue
|
||||
face_img = frame[y1:y2, x1:x2]
|
||||
if face_img.size == 0:
|
||||
continue
|
||||
|
||||
emb = None
|
||||
if coreml_model is not None and face_img.shape[0] > 0 and face_img.shape[1] > 0:
|
||||
try:
|
||||
resized = cv2.resize(face_img, (160, 160))
|
||||
rgb = cv2.cvtColor(resized, cv2.COLOR_BGR2RGB).astype(np.float32)
|
||||
normalized = rgb / 127.5 - 1.0
|
||||
input_data = np.expand_dims(np.transpose(normalized, (2, 0, 1)), axis=0)
|
||||
result = coreml_model.predict({"input": input_data})
|
||||
emb = list(result.values())[0].flatten().tolist()
|
||||
embed_count += 1
|
||||
except Exception as e:
|
||||
pass
|
||||
|
||||
# Pose
|
||||
pose_info = face.get("pose", {})
|
||||
pose_angle = classify_pose(pose_info.get("roll", 0), pose_info.get("yaw", 0))
|
||||
|
||||
processed_faces.append({
|
||||
"x": x, "y": y, "width": w, "height": h,
|
||||
"confidence": face.get("confidence", 0.5),
|
||||
"embedding": emb,
|
||||
"pose_angle": {
|
||||
"angle": pose_angle,
|
||||
"roll": pose_info.get("roll", 0),
|
||||
"yaw": pose_info.get("yaw", 0),
|
||||
"pitch": pose_info.get("pitch", 0),
|
||||
},
|
||||
"lips": face.get("lips"),
|
||||
"landmarks": face.get("landmarks"),
|
||||
"attributes": None,
|
||||
})
|
||||
|
||||
if processed_faces:
|
||||
output_frames.append({
|
||||
"frame": current_frame,
|
||||
"timestamp": timestamp,
|
||||
"faces": processed_faces,
|
||||
})
|
||||
|
||||
current_frame += 1
|
||||
|
||||
if len(output_frames) % 500 == 0:
|
||||
print(f"[EMBED] {len(output_frames)}/{len(needed_frames)} frames, {embed_count} embeddings, {time.time()-t0:.0f}s")
|
||||
|
||||
video.release()
|
||||
|
||||
output = {
|
||||
"frame_count": len(output_frames),
|
||||
"fps": v_fps,
|
||||
"frames": output_frames,
|
||||
}
|
||||
|
||||
os.makedirs(os.path.dirname(args.output), exist_ok=True)
|
||||
with open(args.output, "w") as f:
|
||||
json.dump(output, f, indent=2, ensure_ascii=False)
|
||||
|
||||
elapsed = time.time() - t0
|
||||
print(f"[EMBED] Done: {len(output_frames)} frames, {embed_count} embeddings, {elapsed:.0f}s → {args.output}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
131
scripts/export_file_package.py
Normal file
131
scripts/export_file_package.py
Normal file
@@ -0,0 +1,131 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""
|
||||
Export a single file's data to SQL file (COPY format).
|
||||
Usage: python3 export_file_package.py <file_uuid> <output_dir>
|
||||
"""
|
||||
import json, os, sys, subprocess
|
||||
|
||||
PG_BIN = "/Users/accusys/pgsql/18.3/bin"
|
||||
DB_URL = "postgresql://accusys@localhost:5432/momentry"
|
||||
|
||||
TABLES = [
|
||||
("dev.videos", "file_uuid"),
|
||||
("dev.chunk", "file_uuid"),
|
||||
("dev.chunk_vectors", "uuid"),
|
||||
("dev.face_detections", "file_uuid"),
|
||||
]
|
||||
|
||||
def main():
|
||||
uuid = sys.argv[1] if len(sys.argv) > 1 else "aeed71342a899fe4b4c57b7d41bcb692"
|
||||
outdir = sys.argv[2] if len(sys.argv) > 2 else "/tmp/file_pkg"
|
||||
os.makedirs(outdir, exist_ok=True)
|
||||
sql_path = os.path.join(outdir, "data.sql")
|
||||
|
||||
print(f"Exporting {uuid} → {sql_path}")
|
||||
with open(sql_path, "w") as f:
|
||||
f.write(f"-- File package: {uuid}\nBEGIN;\n\n")
|
||||
|
||||
for tbl, col in TABLES:
|
||||
f.write(f"-- {tbl} WHERE {col} = '{uuid}'\n")
|
||||
|
||||
# Get column list
|
||||
schema, table = tbl.split(".")
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A",
|
||||
"-c", f"SELECT string_agg(column_name, ', ' ORDER BY ordinal_position) FROM information_schema.columns WHERE table_schema='{schema}' AND table_name='{table}' AND is_updatable='YES'"],
|
||||
capture_output=True, text=True, timeout=15)
|
||||
cols = r.stdout.strip()
|
||||
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-c",
|
||||
f"COPY (SELECT * FROM {tbl} WHERE {col} = '{uuid}') TO STDOUT WITH CSV HEADER"],
|
||||
capture_output=True, text=True, timeout=60)
|
||||
if r.stdout.strip():
|
||||
f.write(f"COPY {tbl} ({cols}) FROM STDIN WITH CSV HEADER;\n")
|
||||
f.write(r.stdout)
|
||||
if not r.stdout.endswith("\n"):
|
||||
f.write("\n")
|
||||
f.write("\\.\n\n")
|
||||
|
||||
# Export identities referenced by this file's face_detections
|
||||
f.write(f"-- dev.identities (referenced by face_detections WHERE file_uuid='{uuid}')\n")
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A",
|
||||
"-c", "SELECT string_agg(column_name, ', ' ORDER BY ordinal_position) FROM information_schema.columns WHERE table_schema='dev' AND table_name='identities' AND is_updatable='YES'"],
|
||||
capture_output=True, text=True, timeout=15)
|
||||
cols = r.stdout.strip()
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-c",
|
||||
f"COPY (SELECT DISTINCT i.* FROM dev.identities i INNER JOIN dev.face_detections fd ON fd.identity_id = i.id WHERE fd.file_uuid = '{uuid}') TO STDOUT WITH CSV HEADER"],
|
||||
capture_output=True, text=True, timeout=60)
|
||||
if r.stdout.strip():
|
||||
f.write(f"COPY dev.identities ({cols}) FROM STDIN WITH CSV HEADER;\n")
|
||||
f.write(r.stdout)
|
||||
if not r.stdout.endswith("\n"):
|
||||
f.write("\n")
|
||||
f.write("\\.\n\n")
|
||||
|
||||
# Export identity_bindings for identities referenced by this file
|
||||
f.write(f"-- dev.identity_bindings (for identities in face_detections WHERE file_uuid='{uuid}')\n")
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A",
|
||||
"-c", "SELECT string_agg(column_name, ', ' ORDER BY ordinal_position) FROM information_schema.columns WHERE table_schema='dev' AND table_name='identity_bindings' AND is_updatable='YES'"],
|
||||
capture_output=True, text=True, timeout=15)
|
||||
cols = r.stdout.strip()
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-c",
|
||||
f"COPY (SELECT DISTINCT ib.* FROM dev.identity_bindings ib INNER JOIN dev.face_detections fd ON fd.identity_id = ib.identity_id WHERE fd.file_uuid = '{uuid}') TO STDOUT WITH CSV HEADER"],
|
||||
capture_output=True, text=True, timeout=60)
|
||||
if r.stdout.strip():
|
||||
f.write(f"COPY dev.identity_bindings ({cols}) FROM STDIN WITH CSV HEADER;\n")
|
||||
f.write(r.stdout)
|
||||
if not r.stdout.endswith("\n"):
|
||||
f.write("\n")
|
||||
f.write("\\.\n\n")
|
||||
|
||||
f.write("COMMIT;\n")
|
||||
|
||||
size = os.path.getsize(sql_path)
|
||||
print(f" {sql_path} ({size/1024/1024:.1f} MB)")
|
||||
|
||||
# Copy video file to package
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A",
|
||||
"-c", f"SELECT file_path FROM dev.videos WHERE file_uuid='{uuid}'"],
|
||||
capture_output=True, text=True, timeout=15)
|
||||
video_path = r.stdout.strip()
|
||||
if video_path and os.path.exists(video_path):
|
||||
video_name = os.path.basename(video_path)
|
||||
dest = os.path.join(outdir, video_name)
|
||||
import shutil
|
||||
shutil.copy2(video_path, dest)
|
||||
vsize = os.path.getsize(dest)
|
||||
print(f" {video_name} ({vsize/1024/1024:.0f} MB)")
|
||||
else:
|
||||
print(f" WARNING: video file not found at {video_path}")
|
||||
|
||||
# file_info.json
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A",
|
||||
"-c", f"SELECT json_build_object('file_uuid', file_uuid, 'file_name', file_name, 'duration', duration, 'fps', fps, 'width', width, 'height', height, 'total_frames', total_frames, 'status', status) FROM dev.videos WHERE file_uuid='{uuid}'"],
|
||||
capture_output=True, text=True, timeout=15)
|
||||
if r.stdout.strip():
|
||||
info = json.loads(r.stdout.strip())
|
||||
with open(os.path.join(outdir, "file_info.json"), "w") as f:
|
||||
json.dump(info, f, indent=2)
|
||||
print(f" file_info.json")
|
||||
|
||||
# Export identities.json (for offline analysis)
|
||||
id_path = os.path.join(outdir, f"{uuid}.identities.json")
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A",
|
||||
"-c", f"SELECT json_build_object('file_uuid', file_uuid) FROM dev.videos WHERE file_uuid='{uuid}'"],
|
||||
capture_output=True, text=True, timeout=15)
|
||||
subprocess.run(
|
||||
["/opt/homebrew/bin/python3.11", os.path.join(os.path.dirname(os.path.abspath(__file__)), "export_identities.py"), uuid, id_path],
|
||||
check=False, timeout=60)
|
||||
if os.path.exists(id_path):
|
||||
print(f" {uuid}.identities.json ({os.path.getsize(id_path)/1024:.0f}KB)")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
74
scripts/export_identities.py
Normal file
74
scripts/export_identities.py
Normal file
@@ -0,0 +1,74 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""
|
||||
Export identity data for a video UUID as JSON (for offline analysis).
|
||||
Usage: python3 export_identities.py <file_uuid> [output.json]
|
||||
"""
|
||||
import sys, json, psycopg2
|
||||
|
||||
UUID = sys.argv[1] if len(sys.argv) > 1 else "aeed71342a899fe4b4c57b7d41bcb692"
|
||||
OUT = sys.argv[2] if len(sys.argv) > 2 else f"/Users/accusys/momentry/output_dev/{UUID}.identities.json"
|
||||
|
||||
conn = psycopg2.connect("dbname=momentry user=accusys")
|
||||
cur = conn.cursor()
|
||||
|
||||
# Get identities referenced by this file's face_detections
|
||||
cur.execute("""
|
||||
SELECT DISTINCT i.id, i.name, i.uuid, i.identity_type, i.source, i.status,
|
||||
i.face_embedding, i.voice_embedding, i.reference_data, i.tmdb_id, i.tmdb_profile
|
||||
FROM dev.identities i
|
||||
INNER JOIN dev.face_detections fd ON fd.identity_id = i.id
|
||||
WHERE fd.file_uuid = %s
|
||||
ORDER BY i.id
|
||||
""", (UUID,))
|
||||
rows = cur.fetchall()
|
||||
|
||||
identities = []
|
||||
for r in rows:
|
||||
identities.append({
|
||||
"id": r[0],
|
||||
"name": r[1],
|
||||
"uuid": str(r[2]) if r[2] else None,
|
||||
"identity_type": r[3],
|
||||
"source": r[4],
|
||||
"status": r[5],
|
||||
"tmdb_id": r[9],
|
||||
"tmdb_profile": r[10],
|
||||
})
|
||||
|
||||
# Get identity_bindings for these identities' traces
|
||||
cur.execute("""
|
||||
SELECT DISTINCT ib.identity_id, ib.identity_type, ib.identity_value, ib.confidence
|
||||
FROM dev.identity_bindings ib
|
||||
WHERE ib.identity_id IN (
|
||||
SELECT DISTINCT fd.identity_id FROM dev.face_detections fd WHERE fd.file_uuid = %s
|
||||
)
|
||||
""", (UUID,))
|
||||
bindings = [{"identity_id": r[0], "identity_type": r[1], "identity_value": r[2], "confidence": float(r[3])} for r in cur.fetchall()]
|
||||
|
||||
# Get trace-to-identity mapping from face_detections
|
||||
cur.execute("""
|
||||
SELECT DISTINCT trace_id, identity_id, COUNT(*) as face_count
|
||||
FROM dev.face_detections
|
||||
WHERE file_uuid = %s AND identity_id IS NOT NULL AND trace_id IS NOT NULL
|
||||
GROUP BY trace_id, identity_id ORDER BY trace_id
|
||||
""", (UUID,))
|
||||
trace_map = [{"trace_id": r[0], "identity_id": r[1], "face_count": r[2]} for r in cur.fetchall()]
|
||||
|
||||
cur.close(); conn.close()
|
||||
|
||||
output = {
|
||||
"file_uuid": UUID,
|
||||
"identity_count": len(identities),
|
||||
"binding_count": len(bindings),
|
||||
"trace_mapping_count": len(trace_map),
|
||||
"identities": identities,
|
||||
"bindings": bindings,
|
||||
"trace_to_identity": trace_map,
|
||||
}
|
||||
|
||||
with open(OUT, 'w') as f:
|
||||
json.dump(output, f, indent=2, ensure_ascii=False)
|
||||
|
||||
size_kb = len(json.dumps(output)) / 1024
|
||||
print(f"Exported {len(identities)} identities, {len(bindings)} bindings, {len(trace_map)} trace mappings")
|
||||
print(f" → {OUT} ({size_kb:.0f}KB)")
|
||||
238
scripts/export_sqlite.py
Normal file
238
scripts/export_sqlite.py
Normal file
@@ -0,0 +1,238 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""
|
||||
Export a video's data to a self-contained SQLite database for offline app use.
|
||||
Uses sqlite-vec extension for native vector storage.
|
||||
The vec0.dylib must be in the script directory or /tmp/.
|
||||
Usage: python3 export_sqlite.py <file_uuid> [output.sqlite]
|
||||
"""
|
||||
import sys, json, sqlite3, psycopg2, os
|
||||
|
||||
UUID = sys.argv[1] if len(sys.argv) > 1 else "aeed71342a899fe4b4c57b7d41bcb692"
|
||||
OUT = sys.argv[2] if len(sys.argv) > 2 else f"/Users/accusys/momentry/output_dev/{UUID}.sqlite"
|
||||
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
|
||||
|
||||
# Find vec0.dylib
|
||||
VEC_DYLIB = None
|
||||
for path in [
|
||||
os.path.join(SCRIPT_DIR, "vec0.dylib"),
|
||||
"/tmp/vec0.dylib",
|
||||
os.path.join(SCRIPT_DIR, "sqlite-vec", "vec0.dylib"),
|
||||
]:
|
||||
if os.path.exists(path):
|
||||
VEC_DYLIB = path
|
||||
break
|
||||
|
||||
print(f"Exporting {UUID} → {OUT}")
|
||||
if VEC_DYLIB:
|
||||
print(f" sqlite-vec: {VEC_DYLIB}")
|
||||
|
||||
# Connect to PostgreSQL
|
||||
pg = psycopg2.connect("dbname=momentry user=accusys")
|
||||
pg_cur = pg.cursor()
|
||||
|
||||
# Connect to SQLite
|
||||
if os.path.exists(OUT):
|
||||
os.remove(OUT)
|
||||
lite = sqlite3.connect(OUT)
|
||||
|
||||
# Load sqlite-vec extension if available
|
||||
if VEC_DYLIB:
|
||||
lite.enable_load_extension(True)
|
||||
try:
|
||||
lite.load_extension(VEC_DYLIB)
|
||||
print(" sqlite-vec extension loaded")
|
||||
except Exception as e:
|
||||
print(f" WARNING: Could not load sqlite-vec: {e}")
|
||||
lite.enable_load_extension(False)
|
||||
|
||||
lite_cur = lite.cursor()
|
||||
|
||||
# ---- Helper ----
|
||||
def pg_to_sqlite(pg_query, lite_table, lite_schema, params=None, transform=None):
|
||||
"""Copy PostgreSQL query result to SQLite table."""
|
||||
lite_cur.execute(lite_schema)
|
||||
pg_cur.execute(pg_query, params or [])
|
||||
rows = pg_cur.fetchall()
|
||||
if not rows:
|
||||
return 0
|
||||
cols = [d[0] for d in pg_cur.description]
|
||||
placeholders = ",".join(["?" for _ in cols])
|
||||
|
||||
count = 0
|
||||
for row in rows:
|
||||
d = dict(zip(cols, row))
|
||||
if transform:
|
||||
d = transform(d)
|
||||
vals = []
|
||||
for c in cols:
|
||||
v = d.get(c)
|
||||
vals.append(None if v is None else v)
|
||||
try:
|
||||
lite_cur.execute(f"INSERT INTO {lite_table} VALUES ({placeholders})", vals)
|
||||
count += 1
|
||||
except Exception:
|
||||
pass
|
||||
lite.commit()
|
||||
return count
|
||||
|
||||
# Create tables (skip WAL — Python sqlite3 may not support PRAGMA with extensions loaded)
|
||||
print("Creating tables...")
|
||||
|
||||
# videos
|
||||
pg_to_sqlite(
|
||||
"SELECT file_uuid, file_name, file_path, duration, fps, width, height, probe_json::text, status FROM dev.videos WHERE file_uuid=%s",
|
||||
"videos",
|
||||
"CREATE TABLE IF NOT EXISTS videos (file_uuid TEXT PRIMARY KEY, file_name TEXT, file_path TEXT, duration REAL, fps REAL, width INTEGER, height INTEGER, probe_json TEXT, status TEXT)",
|
||||
[UUID])
|
||||
|
||||
# chunk
|
||||
pg_to_sqlite(
|
||||
"SELECT file_uuid, chunk_id, chunk_type, start_time, end_time, fps, start_frame, end_frame, text_content, metadata->>'speaker_id' as speaker_id FROM dev.chunk WHERE file_uuid=%s AND chunk_type='sentence' ORDER BY chunk_id",
|
||||
"chunk",
|
||||
"""CREATE TABLE IF NOT EXISTS chunk (
|
||||
file_uuid TEXT, chunk_id TEXT, chunk_type TEXT,
|
||||
start_time REAL, end_time REAL, fps REAL,
|
||||
start_frame INTEGER, end_frame INTEGER, text_content TEXT, speaker_id TEXT,
|
||||
PRIMARY KEY(file_uuid, chunk_id))""",
|
||||
[UUID])
|
||||
|
||||
def parse_pg_array(text):
|
||||
"""Parse PostgreSQL array format {0.1,0.2,...} to Python list."""
|
||||
if not text or text == 'null':
|
||||
return None
|
||||
try:
|
||||
text = text.strip('{}')
|
||||
return [float(x) for x in text.split(',') if x.strip()]
|
||||
except:
|
||||
return None
|
||||
|
||||
# chunk vectors → vec0 virtual table
|
||||
print(" Creating vec0 table: chunk_embeddings (768D)...")
|
||||
lite_cur.execute("""
|
||||
CREATE VIRTUAL TABLE IF NOT EXISTS chunk_embeddings USING vec0(
|
||||
embedding float[768]
|
||||
)
|
||||
""")
|
||||
pg_cur.execute("SELECT chunk_id, COALESCE(embedding::text, 'null'), uuid FROM dev.chunk_vectors WHERE uuid=%s", [UUID])
|
||||
chunk_vecs = pg_cur.fetchall()
|
||||
if chunk_vecs:
|
||||
for chunk_id, emb_text, _ in chunk_vecs:
|
||||
# chunk_vectors uses JSONB format, not PG array format
|
||||
emb = None
|
||||
try:
|
||||
emb = json.loads(emb_text) if emb_text else None
|
||||
except:
|
||||
pass
|
||||
if not emb:
|
||||
emb = parse_pg_array(emb_text) # fallback
|
||||
if emb and len(emb) == 768:
|
||||
lite_cur.execute(
|
||||
"INSERT INTO chunk_embeddings (rowid, embedding) VALUES (?, ?)",
|
||||
[int(chunk_id) if chunk_id.isdigit() else hash(chunk_id) & 0x7fffffff,
|
||||
json.dumps(emb)])
|
||||
lite.commit()
|
||||
print(f" chunk_embeddings: {len(chunk_vecs)} vectors")
|
||||
|
||||
# face detections
|
||||
def transform_face(row):
|
||||
return row # embedding moved to vec0 table
|
||||
|
||||
pg_to_sqlite(
|
||||
"""SELECT file_uuid, face_id, frame_number, x, y, width, height, confidence,
|
||||
identity_id, trace_id,
|
||||
COALESCE(timestamp_secs, frame_number / 25.0) as timestamp_secs
|
||||
FROM dev.face_detections WHERE file_uuid=%s ORDER BY frame_number""",
|
||||
"face_detections",
|
||||
"""CREATE TABLE IF NOT EXISTS face_detections (
|
||||
file_uuid TEXT, face_id TEXT, frame_number INTEGER,
|
||||
x INTEGER, y INTEGER, width INTEGER, height INTEGER,
|
||||
confidence REAL, identity_id INTEGER, trace_id INTEGER,
|
||||
timestamp_secs REAL)""",
|
||||
[UUID], transform_face)
|
||||
|
||||
# face embeddings → vec0 virtual table (512D)
|
||||
print(" Creating vec0 table: face_embeddings (512D)...")
|
||||
lite_cur.execute("""
|
||||
CREATE VIRTUAL TABLE IF NOT EXISTS face_embeddings USING vec0(
|
||||
embedding float[512]
|
||||
)
|
||||
""")
|
||||
pg_cur.execute("SELECT id, COALESCE(embedding::text, 'null') FROM dev.face_detections WHERE file_uuid=%s", [UUID])
|
||||
face_vecs = pg_cur.fetchall()
|
||||
if face_vecs:
|
||||
batch = []
|
||||
for db_id, emb_text in face_vecs:
|
||||
emb = parse_pg_array(emb_text)
|
||||
if emb and len(emb) == 512:
|
||||
batch.append((db_id, json.dumps(emb)))
|
||||
if len(batch) >= 500:
|
||||
lite_cur.executemany("INSERT INTO face_embeddings VALUES (?, ?)", batch)
|
||||
batch = []
|
||||
if batch:
|
||||
lite_cur.executemany("INSERT INTO face_embeddings VALUES (?, ?)", batch)
|
||||
lite.commit()
|
||||
print(f" face_embeddings: {len(face_vecs)} vectors")
|
||||
|
||||
# identities
|
||||
def transform_identity(row):
|
||||
return row
|
||||
|
||||
pg_to_sqlite(
|
||||
"""SELECT DISTINCT i.id, i.name, i.uuid, i.identity_type, i.source, i.status,
|
||||
i.tmdb_id, i.tmdb_profile, i.tmdb_poster
|
||||
FROM dev.identities i
|
||||
INNER JOIN dev.face_detections fd ON fd.identity_id = i.id
|
||||
WHERE fd.file_uuid=%s""",
|
||||
"identities",
|
||||
"""CREATE TABLE IF NOT EXISTS identities (
|
||||
id INTEGER PRIMARY KEY, name TEXT, uuid TEXT, identity_type TEXT,
|
||||
source TEXT, status TEXT, tmdb_id INTEGER,
|
||||
tmdb_profile TEXT, tmdb_poster TEXT)""",
|
||||
[UUID], transform_identity)
|
||||
|
||||
# identity_bindings
|
||||
pg_to_sqlite(
|
||||
"""SELECT DISTINCT ib.identity_id, ib.identity_type, ib.identity_value, ib.confidence
|
||||
FROM dev.identity_bindings ib
|
||||
INNER JOIN dev.face_detections fd ON fd.identity_id = ib.identity_id
|
||||
WHERE fd.file_uuid=%s""",
|
||||
"identity_bindings",
|
||||
"CREATE TABLE IF NOT EXISTS identity_bindings (identity_id INTEGER, identity_type TEXT, identity_value TEXT, confidence REAL)",
|
||||
[UUID])
|
||||
|
||||
# ---- Create indexes ----
|
||||
print("Creating indexes...")
|
||||
lite_cur.execute("CREATE INDEX IF NOT EXISTS idx_fd_trace ON face_detections(trace_id)")
|
||||
lite_cur.execute("CREATE INDEX IF NOT EXISTS idx_fd_identity ON face_detections(identity_id)")
|
||||
lite_cur.execute("CREATE INDEX IF NOT EXISTS idx_fd_frame ON face_detections(frame_number)")
|
||||
lite_cur.execute("CREATE INDEX IF NOT EXISTS idx_fd_time ON face_detections(timestamp_secs)")
|
||||
lite_cur.execute("CREATE INDEX IF NOT EXISTS idx_chunk_chunkid ON chunk(chunk_id)")
|
||||
lite.commit()
|
||||
|
||||
# ---- Stats ----
|
||||
pg_cur.close(); pg.close()
|
||||
lite_cur.close(); lite.close()
|
||||
|
||||
size_mb = os.path.getsize(OUT) / 1024 / 1024
|
||||
print(f"\n {OUT} ({size_mb:.0f}MB)")
|
||||
|
||||
# Verify
|
||||
lite = sqlite3.connect(OUT)
|
||||
if VEC_DYLIB:
|
||||
lite.enable_load_extension(True)
|
||||
lite.load_extension(VEC_DYLIB)
|
||||
lite.enable_load_extension(False)
|
||||
c = lite.cursor()
|
||||
for tbl in ['videos', 'chunk', 'face_detections', 'identities', 'identity_bindings']:
|
||||
c.execute(f"SELECT COUNT(*) FROM {tbl}")
|
||||
print(f" {tbl}: {c.fetchone()[0]} rows")
|
||||
# Check vec tables
|
||||
try:
|
||||
c.execute("SELECT COUNT(*) FROM chunk_embeddings")
|
||||
print(f" chunk_embeddings (vec0, 768D): {c.fetchone()[0]} vectors")
|
||||
except: print(" chunk_embeddings: N/A")
|
||||
try:
|
||||
c.execute("SELECT COUNT(*) FROM face_embeddings")
|
||||
print(f" face_embeddings (vec0, 512D): {c.fetchone()[0]} vectors")
|
||||
except: print(" face_embeddings: N/A")
|
||||
c.close(); lite.close()
|
||||
@@ -49,7 +49,7 @@ def classify_pose(roll: float, yaw: float) -> str:
|
||||
|
||||
class FaceProcessorVision:
|
||||
def __init__(self, video_path: str, output_path: str, uuid: str = "",
|
||||
sample_interval: int = 30):
|
||||
sample_interval: int = 3):
|
||||
self.video_path = video_path
|
||||
self.output_path = output_path
|
||||
self.uuid = uuid
|
||||
@@ -205,7 +205,7 @@ class FaceProcessorVision:
|
||||
"pitch": pose_info.get("pitch", 0),
|
||||
},
|
||||
"lips": face.get("lips"),
|
||||
"landmarks": None,
|
||||
"landmarks": face.get("landmarks"),
|
||||
"attributes": None,
|
||||
})
|
||||
|
||||
@@ -255,7 +255,7 @@ def main():
|
||||
parser.add_argument("video_path", help="Video file path")
|
||||
parser.add_argument("output_path", help="Output JSON path")
|
||||
parser.add_argument("--uuid", "-u", default="")
|
||||
parser.add_argument("--sample-interval", type=int, default=30)
|
||||
parser.add_argument("--sample-interval", type=int, default=3)
|
||||
parser.add_argument("--force", action="store_true")
|
||||
args = parser.parse_args()
|
||||
|
||||
|
||||
129
scripts/identity_bind.py
Normal file
129
scripts/identity_bind.py
Normal file
@@ -0,0 +1,129 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""
|
||||
Identity Binding: cluster face traces → identity bindings.
|
||||
Uses face embeddings from face_detections, clusters per trace, creates identities.
|
||||
"""
|
||||
import json, sys, time
|
||||
import psycopg2
|
||||
import numpy as np
|
||||
from sklearn.cluster import AgglomerativeClustering
|
||||
|
||||
UUID = sys.argv[1] if len(sys.argv) > 1 else "23b1c872379d4ec06479e5ed39eef4c5"
|
||||
DB = "dbname=momentry user=accusys"
|
||||
DISTANCE_THRESHOLD = 0.55 # Cosine distance threshold for clustering
|
||||
|
||||
print(f"=== Identity Binding for {UUID} ===")
|
||||
|
||||
conn = psycopg2.connect(DB)
|
||||
cur = conn.cursor()
|
||||
|
||||
# Step 1: Get trace embeddings from face_detections
|
||||
print("Loading face trace data...")
|
||||
cur.execute("""
|
||||
SELECT trace_id, embedding
|
||||
FROM dev.face_detections
|
||||
WHERE file_uuid = %s AND trace_id IS NOT NULL AND embedding IS NOT NULL
|
||||
ORDER BY trace_id, id
|
||||
""", (UUID,))
|
||||
rows = cur.fetchall()
|
||||
print(f"Face detections with embeddings: {len(rows)}")
|
||||
|
||||
# Group by trace_id and compute average embedding
|
||||
trace_embs = {}
|
||||
for trace_id, emb in rows:
|
||||
if trace_id not in trace_embs:
|
||||
trace_embs[trace_id] = []
|
||||
trace_embs[trace_id].append(emb)
|
||||
|
||||
print(f"Unique traces: {len(trace_embs)}")
|
||||
|
||||
# Compute mean embeddings per trace
|
||||
trace_ids = []
|
||||
trace_vectors = []
|
||||
for tid, embs in sorted(trace_embs.items()):
|
||||
mean_emb = np.mean(embs, axis=0)
|
||||
mean_emb = mean_emb / (np.linalg.norm(mean_emb) + 1e-10)
|
||||
trace_ids.append(tid)
|
||||
trace_vectors.append(mean_emb)
|
||||
|
||||
X = np.array(trace_vectors)
|
||||
print(f"Trace vectors shape: {X.shape}")
|
||||
|
||||
# Step 2: Cluster traces
|
||||
print("Clustering traces...")
|
||||
if len(X) > 1:
|
||||
clustering = AgglomerativeClustering(
|
||||
n_clusters=None,
|
||||
distance_threshold=DISTANCE_THRESHOLD,
|
||||
metric='cosine',
|
||||
linkage='average'
|
||||
)
|
||||
labels = clustering.fit_predict(X)
|
||||
else:
|
||||
labels = [0]
|
||||
|
||||
n_clusters = len(set(labels))
|
||||
print(f"Clusters/identities: {n_clusters}")
|
||||
|
||||
# Step 3: Get or create identity records
|
||||
print("Creating identity records...")
|
||||
# Get existing identities
|
||||
cur.execute("SELECT id, uuid FROM dev.identities")
|
||||
existing = {row[0]: row[1] for row in cur.fetchall()}
|
||||
|
||||
# Map cluster -> identity_id
|
||||
cluster_to_identity = {}
|
||||
for cluster_id in sorted(set(labels)):
|
||||
# Create new identity
|
||||
identity_uuid = None
|
||||
cur.execute("""
|
||||
INSERT INTO dev.identities (name, identity_type, source, status, created_at)
|
||||
VALUES (%s, 'face', 'auto', 'active', NOW())
|
||||
ON CONFLICT (name) DO UPDATE SET status = 'active'
|
||||
RETURNING id
|
||||
""", (f"PERSON_{UUID[:8]}_{cluster_id}",))
|
||||
identity_id = cur.fetchone()[0]
|
||||
cluster_to_identity[cluster_id] = identity_id
|
||||
print(f" Cluster {cluster_id}: new identity {identity_id} (PERSON_{cluster_id})")
|
||||
|
||||
# Step 4: Create identity bindings
|
||||
print("Creating identity bindings...")
|
||||
bindings = 0
|
||||
for tid, label in zip(trace_ids, labels):
|
||||
identity_id = cluster_to_identity[label]
|
||||
# Get a representative face_id for this trace
|
||||
cur.execute("""
|
||||
SELECT face_id FROM dev.face_detections
|
||||
WHERE file_uuid = %s AND trace_id = %s
|
||||
LIMIT 1
|
||||
""", (UUID, tid))
|
||||
row = cur.fetchone()
|
||||
if row:
|
||||
face_id = row[0]
|
||||
# Create binding
|
||||
cur.execute("""
|
||||
INSERT INTO dev.identity_bindings (identity_id, identity_type, identity_value, confidence, created_at)
|
||||
VALUES (%s, 'trace', %s, 0.8, NOW())
|
||||
ON CONFLICT DO NOTHING
|
||||
""", (identity_id, str(tid)))
|
||||
bindings += 1
|
||||
|
||||
# Also update face_detection with identity_id
|
||||
cur.execute("""
|
||||
UPDATE dev.face_detections SET identity_id = %s
|
||||
WHERE file_uuid = %s AND trace_id = %s
|
||||
""", (identity_id, UUID, tid))
|
||||
|
||||
conn.commit()
|
||||
print(f"Created {bindings} identity bindings for {n_clusters} identities")
|
||||
|
||||
# Summary
|
||||
print(f"\n=== Summary ===")
|
||||
cur.execute("SELECT COUNT(*) FROM dev.identities WHERE source = 'auto'")
|
||||
print(f"Total auto-generated identities: {cur.fetchone()[0]}")
|
||||
cur.execute("SELECT COUNT(*) FROM dev.identity_bindings")
|
||||
print(f"Total identity bindings: {cur.fetchone()[0]}")
|
||||
|
||||
cur.close()
|
||||
conn.close()
|
||||
print("=== Done ===")
|
||||
48
scripts/insert_chunks.py
Normal file
48
scripts/insert_chunks.py
Normal file
@@ -0,0 +1,48 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""Insert sentence chunks from transcribe.py output into dev.chunk table."""
|
||||
import json, sys
|
||||
import psycopg2
|
||||
|
||||
DB = "dbname=momentry user=accusys"
|
||||
UUID = sys.argv[1] if len(sys.argv) > 1 else "23b1c872379d4ec06479e5ed39eef4c5"
|
||||
ASR_PATH = f"/Users/accusys/momentry/output_dev/{UUID}.asr.json"
|
||||
FPS = 23.976023976023978
|
||||
|
||||
with open(ASR_PATH) as f:
|
||||
asr = json.load(f)
|
||||
|
||||
segments = asr.get("segments", [])
|
||||
print(f"Inserting {len(segments)} sentence chunks for {UUID}...")
|
||||
|
||||
conn = psycopg2.connect(DB)
|
||||
cur = conn.cursor()
|
||||
|
||||
inserted = 0
|
||||
for seg in segments:
|
||||
chunk_id = seg["chunk_id"]
|
||||
start_time = seg["start_time"]
|
||||
end_time = seg["end_time"]
|
||||
start_frame = int(start_time * FPS)
|
||||
end_frame = int(end_time * FPS)
|
||||
text = seg.get("text", "")
|
||||
speaker_change = seg.get("speaker_change", False)
|
||||
|
||||
content = json.dumps({
|
||||
"source": "transcribe",
|
||||
"speaker_change": speaker_change,
|
||||
"pass1_index": seg.get("pass1_index", 0),
|
||||
})
|
||||
|
||||
cur.execute("""
|
||||
INSERT INTO dev.chunk (file_uuid, chunk_id, chunk_type, start_time, end_time,
|
||||
start_frame, end_frame, fps, text_content, content, created_at)
|
||||
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s::jsonb, NOW())
|
||||
ON CONFLICT (file_uuid, chunk_id) DO NOTHING
|
||||
""", (UUID, chunk_id, "sentence", start_time, end_time,
|
||||
start_frame, end_frame, FPS, text, content))
|
||||
inserted += 1
|
||||
|
||||
conn.commit()
|
||||
cur.close()
|
||||
conn.close()
|
||||
print(f"Done: {inserted} chunks inserted")
|
||||
344
scripts/release_manager.py
Normal file
344
scripts/release_manager.py
Normal file
@@ -0,0 +1,344 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""
|
||||
Release Manager - Deploy / Undeploy video release packages.
|
||||
|
||||
Usage:
|
||||
python3 release_manager.py deploy <package.tar.gz>
|
||||
python3 release_manager.py undeploy <file_uuid>
|
||||
python3 release_manager.py list
|
||||
python3 release_manager.py package <file_uuid> # Create new release package
|
||||
"""
|
||||
|
||||
import json, os, sys, shutil, subprocess, tarfile, tempfile, argparse, time
|
||||
import psycopg2
|
||||
from urllib.request import Request, urlopen
|
||||
|
||||
PG_BIN = "/Users/accusys/pgsql/18.3/bin"
|
||||
DB = "dbname=momentry user=accusys"
|
||||
QDRANT = "http://localhost:6333"
|
||||
DEMO_DIR = "/Users/accusys/momentry/var/sftpgo/data/demo"
|
||||
OUTPUT_DIR = "/Users/accusys/momentry/output_dev"
|
||||
RELEASE_DIR = "/Users/accusys/momentry_core_0.1/release/files"
|
||||
|
||||
# ---- Helpers ----
|
||||
|
||||
def psql_cmd(sql, db=DB):
|
||||
"""Run a SQL command via psql."""
|
||||
r = subprocess.run(
|
||||
[f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A", "-c", sql],
|
||||
capture_output=True, text=True, timeout=30)
|
||||
return r.stdout.strip()
|
||||
|
||||
def pg_execute(sql, params=None):
|
||||
"""Execute SQL via psycopg2."""
|
||||
conn = psycopg2.connect(DB)
|
||||
cur = conn.cursor()
|
||||
if params:
|
||||
cur.execute(sql, params)
|
||||
else:
|
||||
cur.execute(sql)
|
||||
conn.commit()
|
||||
cur.close()
|
||||
conn.close()
|
||||
|
||||
def pg_query(sql, params=None):
|
||||
"""Query via psycopg2."""
|
||||
conn = psycopg2.connect(DB)
|
||||
cur = conn.cursor()
|
||||
if params:
|
||||
cur.execute(sql, params)
|
||||
else:
|
||||
cur.execute(sql)
|
||||
rows = cur.fetchall()
|
||||
cur.close()
|
||||
conn.close()
|
||||
return rows
|
||||
|
||||
def qdrant_delete_points(uuid, collection):
|
||||
"""Delete points from Qdrant collection by payload filter."""
|
||||
try:
|
||||
req = Request(f"{QDRANT}/collections/{collection}/points/delete",
|
||||
data=json.dumps({
|
||||
"filter": {"must": [{"key": "file_uuid", "match": {"value": uuid}}]}
|
||||
}).encode(),
|
||||
headers={"Content-Type": "application/json"}, method="POST")
|
||||
urlopen(req)
|
||||
return True
|
||||
except:
|
||||
return False
|
||||
|
||||
# ---- Deploy ----
|
||||
|
||||
def cmd_deploy(tarball_path):
|
||||
"""Deploy a release package."""
|
||||
if not os.path.exists(tarball_path):
|
||||
print(f"ERROR: {tarball_path} not found")
|
||||
return 1
|
||||
|
||||
t0 = time.time()
|
||||
print(f"=== Deploy: {os.path.basename(tarball_path)} ===")
|
||||
|
||||
# 1. Extract
|
||||
tmpdir = tempfile.mkdtemp(prefix="release_deploy_")
|
||||
print(f"Extracting to {tmpdir}...")
|
||||
with tarfile.open(tarball_path) as tar:
|
||||
tar.extractall(tmpdir)
|
||||
|
||||
# Find UUID from directory name or file_info.json
|
||||
uuid = None
|
||||
for item in os.listdir(tmpdir):
|
||||
info_path = os.path.join(tmpdir, item, "file_info.json")
|
||||
if os.path.exists(info_path):
|
||||
with open(info_path) as f:
|
||||
info = json.load(f)
|
||||
uuid = info.get("file_uuid", "")
|
||||
break
|
||||
|
||||
if not uuid:
|
||||
print("ERROR: Could not find file_info.json with UUID")
|
||||
return 1
|
||||
|
||||
pkg_dir = os.path.join(tmpdir, uuid)
|
||||
print(f"UUID: {uuid}")
|
||||
|
||||
# 2. Import data.sql
|
||||
sql_path = os.path.join(pkg_dir, "data.sql")
|
||||
if os.path.exists(sql_path):
|
||||
print(f"Importing data.sql ({os.path.getsize(sql_path)/1024/1024:.0f} MB)...")
|
||||
r = subprocess.run([f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-f", sql_path],
|
||||
capture_output=True, text=True, timeout=300)
|
||||
if r.returncode != 0:
|
||||
print(f"WARNING: SQL import may have issues")
|
||||
print(r.stderr[-500:] if r.stderr else "")
|
||||
else:
|
||||
print("WARNING: data.sql not found in package")
|
||||
|
||||
# 3. Copy video to demo dir
|
||||
for fname in os.listdir(pkg_dir):
|
||||
fpath = os.path.join(pkg_dir, fname)
|
||||
if fname.endswith(('.mp4', '.mov', '.avi', '.mkv')):
|
||||
dest = os.path.join(DEMO_DIR, fname)
|
||||
if not os.path.exists(dest):
|
||||
shutil.copy2(fpath, dest)
|
||||
print(f"Video: {fname} → {DEMO_DIR}/")
|
||||
else:
|
||||
print(f"Video: {fname} already exists in demo dir")
|
||||
|
||||
# 4. Copy JSON outputs
|
||||
for fname in os.listdir(pkg_dir):
|
||||
if fname.endswith('.json'):
|
||||
src = os.path.join(pkg_dir, fname)
|
||||
dest = os.path.join(OUTPUT_DIR, fname)
|
||||
shutil.copy2(src, dest)
|
||||
|
||||
print(f"Output files copied to {OUTPUT_DIR}/")
|
||||
|
||||
# 5. Verify deployment
|
||||
rows = pg_query("SELECT COUNT(*) FROM dev.chunk WHERE file_uuid = %s", (uuid,))
|
||||
chunks = rows[0][0] if rows else 0
|
||||
rows = pg_query("SELECT COUNT(*) FROM dev.face_detections WHERE file_uuid = %s", (uuid,))
|
||||
faces = rows[0][0] if rows else 0
|
||||
rows = pg_query("SELECT file_name, duration FROM dev.videos WHERE file_uuid = %s", (uuid,))
|
||||
video_info = rows[0] if rows else ("?", "?")
|
||||
|
||||
elapsed = time.time() - t0
|
||||
print(f"\n=== Deploy Complete ({elapsed:.0f}s) ===")
|
||||
print(f" Video: {video_info[0]} ({float(video_info[1]):.0f}s)")
|
||||
print(f" Chunks: {chunks}")
|
||||
print(f" Face detections: {faces}")
|
||||
|
||||
shutil.rmtree(tmpdir, ignore_errors=True)
|
||||
return 0
|
||||
|
||||
# ---- Undeploy ----
|
||||
|
||||
def cmd_undeploy(uuid):
|
||||
"""Undeploy: remove all trace of a UUID from the system."""
|
||||
print(f"=== Undeploy: {uuid} ===")
|
||||
|
||||
# Confirm
|
||||
rows = pg_query("SELECT file_name FROM dev.videos WHERE file_uuid = %s", (uuid,))
|
||||
if not rows:
|
||||
print(f"ERROR: UUID {uuid} not found in DB")
|
||||
return 1
|
||||
filename = rows[0][0]
|
||||
print(f"Video: {filename}")
|
||||
print("This will DELETE all data for this video. Are you sure? (y/N): ", end="")
|
||||
confirm = sys.stdin.readline().strip().lower()
|
||||
if confirm != 'y':
|
||||
print("Cancelled")
|
||||
return 0
|
||||
|
||||
t0 = time.time()
|
||||
|
||||
# Get video path before deleting
|
||||
rows = pg_query("SELECT file_path FROM dev.videos WHERE file_uuid = %s", (uuid,))
|
||||
video_path = rows[0][0] if rows else ""
|
||||
|
||||
# 1. Delete DB data
|
||||
tables = [
|
||||
("dev.chunk", "file_uuid"),
|
||||
("dev.chunk_vectors", "uuid"),
|
||||
("dev.face_detections", "file_uuid"),
|
||||
("dev.processor_results", "file_uuid"),
|
||||
("dev.monitor_jobs", "uuid"),
|
||||
("dev.pre_chunks", "file_uuid"),
|
||||
]
|
||||
for tbl, col in tables:
|
||||
pg_execute(f"DELETE FROM {tbl} WHERE {col} = %s", (uuid,))
|
||||
print(f" {tbl}: cleared")
|
||||
pg_execute("DELETE FROM dev.videos WHERE file_uuid = %s", (uuid,))
|
||||
print(f" dev.videos: removed")
|
||||
|
||||
# Clean orphaned identity bindings
|
||||
pg_execute("DELETE FROM dev.identity_bindings WHERE identity_value NOT IN (SELECT face_id FROM dev.face_detections)")
|
||||
|
||||
# 2. Delete output files
|
||||
for f in os.listdir(OUTPUT_DIR):
|
||||
if f.startswith(uuid):
|
||||
os.remove(os.path.join(OUTPUT_DIR, f))
|
||||
print(f" Output files: removed")
|
||||
|
||||
# 3. Delete video from demo dir
|
||||
if video_path and os.path.exists(video_path):
|
||||
os.remove(video_path)
|
||||
print(f" Video file: removed ({os.path.basename(video_path)})")
|
||||
|
||||
# 4. Clean Qdrant (skip - Qdrant points don't have easy UUID filter)
|
||||
# Instead rely on upsert behavior
|
||||
|
||||
# 5. Delete release package
|
||||
pkg_path = os.path.join(RELEASE_DIR, uuid)
|
||||
if os.path.exists(pkg_path):
|
||||
shutil.rmtree(pkg_path)
|
||||
print(f" Release dir: removed")
|
||||
for f in os.listdir(RELEASE_DIR):
|
||||
if f.startswith(uuid):
|
||||
os.remove(os.path.join(RELEASE_DIR, f))
|
||||
print(f" Release file: {f} removed")
|
||||
|
||||
elapsed = time.time() - t0
|
||||
print(f"\n=== Undeploy Complete ({elapsed:.0f}s) ===")
|
||||
return 0
|
||||
|
||||
# ---- List ----
|
||||
|
||||
def cmd_list():
|
||||
"""List deployed videos."""
|
||||
rows = pg_query("""
|
||||
SELECT file_uuid, file_name,
|
||||
TO_CHAR((duration/60)::int, 'FM999"min"') as dur,
|
||||
status,
|
||||
(SELECT COUNT(*) FROM dev.chunk WHERE file_uuid = v.file_uuid) as chunks,
|
||||
(SELECT COUNT(*) FROM dev.face_detections WHERE file_uuid = v.file_uuid) as faces
|
||||
FROM dev.videos v ORDER BY id DESC
|
||||
""")
|
||||
print(f"{'UUID':36s} {'Name':40s} {'Duration':8s} {'Status':10s} {'Chunks':>6s} {'Faces':>6s}")
|
||||
print("-" * 120)
|
||||
for r in rows:
|
||||
uuid, name, dur, status, chunks, faces = r
|
||||
short_name = (name or "")[:38] + ".." if len(name or "") > 40 else (name or "")
|
||||
print(f"{uuid:36s} {short_name:40s} {dur or '?':8s} {status or '?':10s} {chunks or 0:>6d} {faces or 0:>6d}")
|
||||
|
||||
# ---- Package ----
|
||||
|
||||
def cmd_package(uuid):
|
||||
"""Create a release package for a deployed video."""
|
||||
print(f"=== Package: {uuid} ===")
|
||||
|
||||
# Check video exists
|
||||
rows = pg_query("SELECT file_uuid, file_name, file_path FROM dev.videos WHERE file_uuid = %s", (uuid,))
|
||||
if not rows:
|
||||
print(f"ERROR: UUID {uuid} not found")
|
||||
return 1
|
||||
|
||||
outdir = os.path.join(RELEASE_DIR, uuid)
|
||||
shutil.rmtree(outdir, ignore_errors=True)
|
||||
os.makedirs(outdir, exist_ok=True)
|
||||
|
||||
# Export data.sql
|
||||
r = subprocess.run([f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A",
|
||||
"-c", f"SELECT json_build_object('file_uuid', file_uuid, 'file_name', file_name, 'duration', duration, 'fps', fps, 'width', width, 'height', height, 'total_frames', total_frames, 'status', status) FROM dev.videos WHERE file_uuid='{uuid}'"],
|
||||
capture_output=True, text=True, timeout=15)
|
||||
if r.stdout.strip():
|
||||
info = json.loads(r.stdout.strip())
|
||||
with open(os.path.join(outdir, "file_info.json"), "w") as f:
|
||||
json.dump(info, f, indent=2)
|
||||
|
||||
# Export SQL
|
||||
sql_path = os.path.join(outdir, "data.sql")
|
||||
with open(sql_path, "w") as f:
|
||||
f.write(f"-- Release package: {uuid}\nBEGIN;\n\n")
|
||||
for tbl, col in [("dev.videos", "file_uuid"), ("dev.chunk", "file_uuid"),
|
||||
("dev.chunk_vectors", "uuid"), ("dev.face_detections", "file_uuid")]:
|
||||
r = subprocess.run([f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-c",
|
||||
f"COPY (SELECT * FROM {tbl} WHERE {col} = '{uuid}') TO STDOUT WITH CSV HEADER"],
|
||||
capture_output=True, text=True, timeout=60)
|
||||
if r.stdout.strip():
|
||||
# Get column names
|
||||
schema, table = tbl.split(".")
|
||||
r2 = subprocess.run([f"{PG_BIN}/psql", "-U", "accusys", "-d", "momentry", "-t", "-A",
|
||||
"-c", f"SELECT string_agg(column_name, ', ' ORDER BY ordinal_position) FROM information_schema.columns WHERE table_schema='{schema}' AND table_name='{table}' AND is_updatable='YES'"],
|
||||
capture_output=True, text=True, timeout=15)
|
||||
cols = r2.stdout.strip()
|
||||
f.write(f"COPY {tbl} ({cols}) FROM STDIN WITH CSV HEADER;\n")
|
||||
f.write(r.stdout)
|
||||
if not r.stdout.endswith("\n"):
|
||||
f.write("\n")
|
||||
f.write("\\.\n\n")
|
||||
f.write("COMMIT;\n")
|
||||
|
||||
size = os.path.getsize(sql_path)
|
||||
print(f" data.sql ({size/1024/1024:.0f} MB)")
|
||||
|
||||
# Copy video
|
||||
video_path = rows[0][2]
|
||||
if video_path and os.path.exists(video_path):
|
||||
dest = os.path.join(outdir, os.path.basename(video_path))
|
||||
shutil.copy2(video_path, dest)
|
||||
print(f" {os.path.basename(video_path)} ({os.path.getsize(dest)/1024/1024:.0f} MB)")
|
||||
|
||||
# Copy output JSONs
|
||||
for fname in os.listdir(OUTPUT_DIR):
|
||||
if fname.startswith(uuid) and fname.endswith('.json'):
|
||||
shutil.copy2(os.path.join(OUTPUT_DIR, fname), os.path.join(outdir, fname))
|
||||
|
||||
# tar.gz
|
||||
tarball = os.path.join(RELEASE_DIR, f"{uuid}_v{int(time.time())}.tar.gz")
|
||||
subprocess.run(["tar", "-czf", tarball, "-C", RELEASE_DIR, uuid], check=True, timeout=300)
|
||||
tsize = os.path.getsize(tarball)
|
||||
print(f" Package: {tarball} ({tsize/1024/1024:.0f} MB)")
|
||||
return 0
|
||||
|
||||
# ---- Main ----
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description="Release Manager — deploy/undeploy/list video packages")
|
||||
sub = parser.add_subparsers(dest="cmd")
|
||||
|
||||
p_deploy = sub.add_parser("deploy", help="Deploy a release package")
|
||||
p_deploy.add_argument("tarball", help="Path to .tar.gz package")
|
||||
|
||||
p_undeploy = sub.add_parser("undeploy", help="Undeploy (remove all data for a UUID)")
|
||||
p_undeploy.add_argument("uuid", help="File UUID")
|
||||
|
||||
p_list = sub.add_parser("list", help="List deployed videos")
|
||||
|
||||
p_package = sub.add_parser("package", help="Create release package for deployed video")
|
||||
p_package.add_argument("uuid", help="File UUID")
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
if args.cmd == "deploy":
|
||||
sys.exit(cmd_deploy(args.tarball))
|
||||
elif args.cmd == "undeploy":
|
||||
sys.exit(cmd_undeploy(args.uuid))
|
||||
elif args.cmd == "list":
|
||||
cmd_list()
|
||||
elif args.cmd == "package":
|
||||
sys.exit(cmd_package(args.uuid))
|
||||
else:
|
||||
parser.print_help()
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
222
scripts/render_face_heatmap.py
Normal file
222
scripts/render_face_heatmap.py
Normal file
@@ -0,0 +1,222 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""Face Trace Heatmap + Timeline Visualization for Momentry.
|
||||
Usage:
|
||||
python3 render_face_heatmap.py <uuid> [output.html] [--identity ID]
|
||||
"""
|
||||
import sys, psycopg2, argparse
|
||||
from collections import defaultdict
|
||||
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("uuid")
|
||||
parser.add_argument("output", nargs="?", default=None)
|
||||
parser.add_argument("--identity", "-i", type=int, default=None, help="Filter by identity_id")
|
||||
args = parser.parse_args()
|
||||
|
||||
UUID = args.uuid
|
||||
OUT = args.output or f"/tmp/face_report_{UUID[:8]}.html"
|
||||
IDENTITY = args.identity
|
||||
|
||||
conn = psycopg2.connect("dbname=momentry user=accusys")
|
||||
cur = conn.cursor()
|
||||
|
||||
cur.execute("SELECT duration, file_name, COALESCE(fps, 25.0) FROM dev.videos WHERE file_uuid=%s", (UUID,))
|
||||
row = cur.fetchone()
|
||||
if not row:
|
||||
print("UUID not found")
|
||||
sys.exit(1)
|
||||
duration, video_name, fps = float(row[0] or 6785), row[1] or UUID, float(row[2] or 25.0)
|
||||
|
||||
# Get sample interval from face.json metadata (or default 3 = 8Hz)
|
||||
sample_interval = 3
|
||||
hz = fps / sample_interval
|
||||
|
||||
# Build identity filter
|
||||
identity_filter = ""
|
||||
identity_params = [UUID]
|
||||
identity_label = ""
|
||||
identity_info = None # full identity record when filtered
|
||||
top_identities = [] # top identities summary (all view)
|
||||
|
||||
if IDENTITY is not None:
|
||||
identity_filter = " AND identity_id = %s"
|
||||
identity_params.append(IDENTITY)
|
||||
cur.execute("SELECT id, name, identity_type, source, status FROM dev.identities WHERE id=%s", (IDENTITY,))
|
||||
id_row = cur.fetchone()
|
||||
if id_row:
|
||||
identity_info = {"id": id_row[0], "name": id_row[1], "type": id_row[2], "source": id_row[3], "status": id_row[4]}
|
||||
identity_label = f" (identity: {id_row[1]})"
|
||||
else:
|
||||
identity_label = f" (identity #{IDENTITY})"
|
||||
identity_params = [UUID, IDENTITY]
|
||||
|
||||
# Query trace spans
|
||||
cur.execute(f"""
|
||||
SELECT trace_id, MIN(frame_number), MAX(frame_number),
|
||||
COALESCE(MIN(timestamp_secs), MIN(frame_number) / {fps}) as first_t,
|
||||
COALESCE(MAX(timestamp_secs), MAX(frame_number) / {fps}) as last_t,
|
||||
COUNT(*)
|
||||
FROM dev.face_detections
|
||||
WHERE file_uuid=%s AND trace_id IS NOT NULL{identity_filter}
|
||||
GROUP BY trace_id ORDER BY first_t
|
||||
""", identity_params)
|
||||
trace_spans = cur.fetchall()
|
||||
|
||||
# Query density per time bucket (5s)
|
||||
cur.execute(f"""
|
||||
SELECT FLOOR(COALESCE(timestamp_secs, frame_number / {fps}) / 5)::int as bkt, COUNT(*) as cnt
|
||||
FROM dev.face_detections
|
||||
WHERE file_uuid=%s AND trace_id IS NOT NULL{identity_filter}
|
||||
GROUP BY bkt ORDER BY bkt
|
||||
""", identity_params)
|
||||
density = {b: c for b, c in cur.fetchall()}
|
||||
|
||||
# Count total detections
|
||||
cur.execute(f"SELECT COUNT(*) FROM dev.face_detections WHERE file_uuid=%s{identity_filter}", identity_params)
|
||||
total_detections = cur.fetchone()[0]
|
||||
|
||||
# Get top identities (for all view) and trace↔identity mapping
|
||||
if IDENTITY is None:
|
||||
cur.execute("""
|
||||
SELECT fd.identity_id, i.name, COUNT(*) as faces, COUNT(DISTINCT fd.trace_id) as traces
|
||||
FROM dev.face_detections fd
|
||||
LEFT JOIN dev.identities i ON i.id = fd.identity_id
|
||||
WHERE fd.file_uuid=%s AND fd.identity_id IS NOT NULL
|
||||
GROUP BY fd.identity_id, i.name ORDER BY faces DESC LIMIT 10
|
||||
""", (UUID,))
|
||||
top_identities = cur.fetchall()
|
||||
else:
|
||||
# Get trace→identity mapping for tooltip enrichment
|
||||
cur.execute("""
|
||||
SELECT DISTINCT fd.trace_id, i.name
|
||||
FROM dev.face_detections fd
|
||||
LEFT JOIN dev.identities i ON i.id = fd.identity_id
|
||||
WHERE fd.file_uuid=%s AND fd.identity_id IS NOT NULL
|
||||
""", (UUID,))
|
||||
trace_to_identity = {r[0]: r[1] for r in cur.fetchall()}
|
||||
|
||||
cur.close(); conn.close()
|
||||
|
||||
BUCKET = 5
|
||||
num_buckets = int(duration / BUCKET) + 1
|
||||
max_density = max(density.values()) if density else 1
|
||||
|
||||
def build_html():
|
||||
h = []
|
||||
h.append('<!DOCTYPE html><html><head><meta charset="utf-8"><title>Face Trace Report</title>')
|
||||
h.append('<style>')
|
||||
h.append('body{font-family:-apple-system,BlinkMacSystemFont,sans-serif;margin:20px;background:#0d1117;color:#c9d1d9}')
|
||||
h.append('h1,h2{color:#e94560}')
|
||||
h.append('.stats{display:flex;gap:12px;margin:8px 0;flex-wrap:wrap}')
|
||||
h.append('.stat{background:#161b22;padding:6px 14px;border-radius:6px}')
|
||||
h.append('.stat .num{font-size:20px;font-weight:bold;color:#e94560}')
|
||||
h.append('.stat .label{font-size:10px;color:#8b949e}')
|
||||
h.append('.viz{position:relative;background:#0d1117;border:1px solid #30363d;margin:8px 0;overflow:hidden}')
|
||||
h.append('.bar{display:block;position:absolute;height:3px;background:#e94560;opacity:0.7;border-radius:1px}')
|
||||
h.append('.bar:hover{height:8px;opacity:1}')
|
||||
h.append('</style></head><body>')
|
||||
sub = identity_label if identity_label else ""
|
||||
h.append('<h1>Face Trace Report — ' + video_name[:60] + sub + '</h1>')
|
||||
|
||||
# Identity card (when filtering by identity)
|
||||
if identity_info:
|
||||
h.append('<div style="background:#161b22;border:1px solid #30363d;border-radius:8px;padding:16px;margin:12px 0;">')
|
||||
h.append('<h3 style="margin:0;color:#e94560">Identity Details</h3>')
|
||||
h.append(f'<table style="width:100%;margin-top:8px;color:#c9d1d9;border-collapse:collapse">')
|
||||
h.append(f'<tr><td style="padding:4px 12px 4px 0;color:#8b949e;width:80px">ID</td><td>{identity_info["id"]}</td></tr>')
|
||||
h.append(f'<tr><td style="padding:4px 12px 4px 0;color:#8b949e">Name</td><td style="font-weight:bold">{identity_info["name"]}</td></tr>')
|
||||
h.append(f'<tr><td style="padding:4px 12px 4px 0;color:#8b949e">Type</td><td>{identity_info["type"]}</td></tr>')
|
||||
h.append(f'<tr><td style="padding:4px 12px 4px 0;color:#8b949e">Source</td><td>{identity_info["source"]}</td></tr>')
|
||||
h.append(f'<tr><td style="padding:4px 12px 4px 0;color:#8b949e">Status</td><td>{identity_info["status"]}</td></tr>')
|
||||
h.append('</table></div>')
|
||||
|
||||
# Top identities table (all view)
|
||||
if top_identities:
|
||||
h.append('<h2>Top Identities</h2>')
|
||||
h.append('<div style="overflow-x:auto">')
|
||||
h.append('<table style="width:100%;color:#c9d1d9;border-collapse:collapse;font-size:13px">')
|
||||
h.append('<tr style="background:#161b22;text-align:left"><th style="padding:6px 10px">Identity</th><th style="padding:6px 10px">Name</th><th style="padding:6px 10px;text-align:right">Faces</th><th style="padding:6px 10px;text-align:right">Traces</th></tr>')
|
||||
for iid, name, fc, tc in top_identities:
|
||||
short_name = (name or f"#{iid}")[:60]
|
||||
h.append(f'<tr style="border-bottom:1px solid #21262d"><td style="padding:4px 10px;color:#8b949e">{iid}</td><td style="padding:4px 10px">{short_name}</td><td style="padding:4px 10px;text-align:right">{fc:,}</td><td style="padding:4px 10px;text-align:right">{tc}</td></tr>')
|
||||
h.append('</table></div>')
|
||||
|
||||
# Stats row
|
||||
h.append('<div class="stats">')
|
||||
h.append(f'<div class="stat"><div class="num">{len(trace_spans):,}</div><div class="label">traces</div></div>')
|
||||
h.append(f'<div class="stat"><div class="num">{total_detections:,}</div><div class="label">detections</div></div>')
|
||||
h.append(f'<div class="stat"><div class="num">{duration:.0f}s</div><div class="label">duration</div></div>')
|
||||
h.append(f'<div class="stat"><div class="num">{max_density}</div><div class="label">max per {BUCKET}s</div></div>')
|
||||
h.append(f'<div class="stat"><div class="num">{fps:.0f}fps</div><div class="label">video fps</div></div>')
|
||||
h.append(f'<div class="stat"><div class="num">{hz:.0f}Hz</div><div class="label">sample rate (every {sample_interval}frames)</div></div>')
|
||||
h.append(f'<div class="stat"><div class="num">{num_buckets}</div><div class="label">{BUCKET}s buckets</div></div>')
|
||||
h.append('</div>')
|
||||
|
||||
# 1. Density histogram
|
||||
h.append('<h2>Face Density Over Time</h2>')
|
||||
h.append('<div style="color:#666;font-size:12px;margin-bottom:4px">Number of face detections per 5-second interval</div>')
|
||||
w_px = num_buckets * 2 + 20
|
||||
h.append(f'<div class="viz" style="width:{w_px}px;height:80px">')
|
||||
for b in range(num_buckets):
|
||||
v = density.get(b, 0)
|
||||
h_px = max(2, int(60 * v / max(1, max_density * 0.6))) if v > 0 else 0
|
||||
if v == 0:
|
||||
color = "#0d1117"
|
||||
else:
|
||||
i = min(v / (max(1, max_density * 0.5)), 1.0)
|
||||
r = int(233 * i + 13 * (1 - i))
|
||||
g = int(69 * i + 13 * (1 - i))
|
||||
bv = int(96 * i + 23 * (1 - i))
|
||||
color = f"rgb({r},{g},{bv})"
|
||||
title = f"{b * BUCKET:.0f}s: {v} faces"
|
||||
h.append(f'<span style="position:absolute;left:{b*2+10}px;bottom:0;width:2px;height:{h_px}px;background:{color}" title="{title}"></span>')
|
||||
h.append('</div>')
|
||||
h.append(f'<div style="font-size:10px;color:#444;width:{w_px}px;display:flex;justify-content:space-between"><span>0s</span><span>{duration:.0f}s</span></div>')
|
||||
|
||||
# 2. Trace timeline (Gantt)
|
||||
h.append('<h2>Trace Timeline</h2>')
|
||||
h.append('<div style="color:#666;font-size:12px;margin-bottom:4px">First → last appearance for each trace. Hover for details.</div>')
|
||||
show_traces = min(len(trace_spans), 2000)
|
||||
bar_h = 2
|
||||
chart_height = show_traces * (bar_h + 1) + 10
|
||||
h.append(f'<div class="viz" style="width:{w_px}px;height:{chart_height}px">')
|
||||
for i, (tid, fn0, fn1, t0, t1, cnt) in enumerate(trace_spans[:show_traces]):
|
||||
left = int(t0 / duration * (w_px - 20)) + 10
|
||||
width = max(3, int((t1 - t0) / duration * (w_px - 20)))
|
||||
top = i * (bar_h + 1) + 5
|
||||
opacity = 1.0 if cnt > 5 else 0.3
|
||||
identity_note = ""
|
||||
if IDENTITY is not None and tid in trace_to_identity:
|
||||
identity_note = f", identity: {trace_to_identity[tid]}"
|
||||
title = f"T{tid}: {t0:.0f}s–{t1:.0f}s, {cnt} faces, f{fn0}–f{fn1}{identity_note}"
|
||||
h.append(f'<span class="bar" style="left:{left}px;top:{top}px;width:{width}px;height:{bar_h}px;opacity:{opacity}" title="{title}"></span>')
|
||||
h.append('</div>')
|
||||
h.append(f'<div style="font-size:10px;color:#444;width:{w_px}px;display:flex;justify-content:space-between"><span>0s (showing {show_traces}/{len(trace_spans)} traces)</span><span>{duration:.0f}s</span></div>')
|
||||
|
||||
# 3. Per-trace heatmap
|
||||
h.append('<h2>Per-Trace Heatmap (top 500, every 10th trace)</h2>')
|
||||
h.append(f'<div style="overflow-x:scroll;max-width:100%">')
|
||||
step = max(1, num_buckets // 120)
|
||||
for i, (tid, fn0, fn1, t0, t1, cnt) in enumerate(trace_spans[:500]):
|
||||
if i % 10 != 0:
|
||||
continue
|
||||
start_bkt = int(t0 / BUCKET)
|
||||
end_bkt = int(t1 / BUCKET) + 1
|
||||
row = f'<div style="white-space:nowrap;line-height:6px"><span style="display:inline-block;width:45px;font-size:6px;color:#555">T{tid}</span>'
|
||||
for b in range(0, num_buckets, step):
|
||||
active = start_bkt <= b <= end_bkt
|
||||
color = "#e94560" if active else "#161b22"
|
||||
row += f'<span style="display:inline-block;width:2px;height:4px;background:{color};margin:0"></span>'
|
||||
row += '</div>'
|
||||
h.append(row)
|
||||
h.append('</div>')
|
||||
|
||||
h.append('</body></html>')
|
||||
return '\n'.join(h)
|
||||
|
||||
html = build_html()
|
||||
with open(OUT, 'w') as f:
|
||||
f.write(html)
|
||||
|
||||
print(f"Saved: {OUT}")
|
||||
print(f"Traces: {len(trace_spans)}, Detections: {total_detections}, Density max: {max_density}, Duration: {duration:.0f}s, Sample: {hz:.0f}Hz")
|
||||
print(f"Size: {len(html) / 1024:.0f}KB")
|
||||
164
scripts/speaker_assign.py
Normal file
164
scripts/speaker_assign.py
Normal file
@@ -0,0 +1,164 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""
|
||||
Speaker Assignment: cluster voice vectors from Qdrant, assign speaker IDs to DB chunks.
|
||||
"""
|
||||
import json, sys, time
|
||||
import psycopg2
|
||||
import numpy as np
|
||||
from urllib.request import Request, urlopen
|
||||
from sklearn.cluster import AgglomerativeClustering
|
||||
from sklearn.metrics.pairwise import cosine_similarity
|
||||
|
||||
UUID = sys.argv[1] if len(sys.argv) > 1 else "23b1c872379d4ec06479e5ed39eef4c5"
|
||||
QDRANT = "http://localhost:6333"
|
||||
DB = "dbname=momentry user=accusys"
|
||||
COLLECTION = "momentry_dev_voice"
|
||||
|
||||
print(f"=== Speaker Assignment for {UUID} ===")
|
||||
|
||||
# Step 1: Read voice vectors from Qdrant
|
||||
print("Reading voice vectors from Qdrant...")
|
||||
vectors = []
|
||||
chunk_ids = []
|
||||
# We need to scroll through all points
|
||||
offset = None
|
||||
while True:
|
||||
data = {"limit": 100, "with_payload": True, "with_vector": True}
|
||||
if offset is not None:
|
||||
data["offset"] = offset
|
||||
req = Request(f"{QDRANT}/collections/{COLLECTION}/points/scroll",
|
||||
data=json.dumps(data).encode(),
|
||||
headers={"Content-Type": "application/json"}, method="POST")
|
||||
resp = json.loads(urlopen(req).read())
|
||||
result = resp["result"]
|
||||
points = result.get("points", [])
|
||||
if not points:
|
||||
break
|
||||
for pt in points:
|
||||
payload = pt.get("payload", {})
|
||||
cid = payload.get("chunk_id", "")
|
||||
# Only get vectors for THIS UUID's chunks
|
||||
# Filter by checking DB later, or rely on Qdrant payload
|
||||
vectors.append(pt["vector"])
|
||||
chunk_ids.append(cid)
|
||||
offset = result.get("next_page_offset")
|
||||
if offset is None:
|
||||
break
|
||||
print(f" Read {len(vectors)} vectors...")
|
||||
|
||||
print(f"Total vectors: {len(vectors)}")
|
||||
|
||||
# Step 2: Filter to only our UUID's chunks (from DB)
|
||||
conn = psycopg2.connect(DB)
|
||||
cur = conn.cursor()
|
||||
cur.execute("SELECT chunk_id FROM dev.chunk WHERE file_uuid = %s AND chunk_type = 'sentence' ORDER BY id", (UUID,))
|
||||
db_chunk_ids = set(row[0] for row in cur.fetchall())
|
||||
print(f"DB chunk_ids: {len(db_chunk_ids)}")
|
||||
|
||||
# Filter vectors to match DB chunks
|
||||
filtered_vectors = []
|
||||
filtered_chunk_ids = []
|
||||
for v, cid in zip(vectors, chunk_ids):
|
||||
if cid in db_chunk_ids:
|
||||
filtered_vectors.append(v)
|
||||
filtered_chunk_ids.append(cid)
|
||||
|
||||
vectors = filtered_vectors
|
||||
chunk_ids = filtered_chunk_ids
|
||||
print(f"Matched vectors: {len(vectors)}")
|
||||
|
||||
# Sort by chunk_id (which is numeric string)
|
||||
indices = sorted(range(len(chunk_ids)), key=lambda i: int(chunk_ids[i]) if chunk_ids[i].isdigit() else 0)
|
||||
vectors = [vectors[i] for i in indices]
|
||||
chunk_ids = [chunk_ids[i] for i in indices]
|
||||
|
||||
# Step 3: Read speaker_change from asr.json
|
||||
asr_path = f"/Users/accusys/momentry/output_dev/{UUID}.asr.json"
|
||||
with open(asr_path) as f:
|
||||
asr_data = json.load(f)
|
||||
segments = asr_data.get("segments", [])
|
||||
speaker_changes = {}
|
||||
for seg in segments:
|
||||
speaker_changes[seg["chunk_id"]] = seg.get("speaker_change", False)
|
||||
|
||||
# Step 4: Cluster embeddings
|
||||
print("Clustering...")
|
||||
X = np.array(vectors)
|
||||
|
||||
# Compute cosine distance matrix
|
||||
# Cosine distance = 1 - cosine_similarity
|
||||
cos_sim = cosine_similarity(X)
|
||||
cos_dist = 1 - cos_sim
|
||||
|
||||
# Use AgglomerativeClustering with cosine distance
|
||||
# Determine optimal n_clusters by looking at speaker_change boundaries
|
||||
# First pass: use speaker_change as hard boundaries to get initial clusters
|
||||
# Then refine
|
||||
|
||||
# Simpler: use a distance threshold
|
||||
n = len(vectors)
|
||||
labels = np.full(n, -1, dtype=int)
|
||||
current_speaker = 0
|
||||
|
||||
# Start with first chunk as speaker 0
|
||||
labels[0] = current_speaker
|
||||
centroids = [np.array(vectors[0])] # per-cluster centroid
|
||||
|
||||
for i in range(1, n):
|
||||
has_change = speaker_changes.get(chunk_ids[i], False)
|
||||
vec = np.array(vectors[i])
|
||||
|
||||
if has_change:
|
||||
# Speaker change: check if this is a NEW speaker or returning to a previous one
|
||||
# Compare with centroid of current speaker vs others
|
||||
similarities = [float(np.dot(vec, c) / (np.linalg.norm(vec) * np.linalg.norm(c) + 1e-10)) for c in centroids]
|
||||
best_sim = max(similarities) if similarities else 0
|
||||
best_cluster = similarities.index(best_sim) if similarities else 0
|
||||
|
||||
if best_sim > 0.65 and best_cluster != current_speaker:
|
||||
# Returning to a previous speaker
|
||||
labels[i] = best_cluster
|
||||
elif best_sim < 0.55:
|
||||
# New speaker
|
||||
current_speaker = len(centroids)
|
||||
labels[i] = current_speaker
|
||||
centroids.append(vec)
|
||||
else:
|
||||
# Stay with current speaker (false change detection)
|
||||
labels[i] = current_speaker
|
||||
centroids[current_speaker] = (centroids[current_speaker] + vec) / 2
|
||||
else:
|
||||
# No speaker change: same speaker as previous
|
||||
labels[i] = current_speaker
|
||||
centroids[current_speaker] = (centroids[current_speaker] + vec) / 2
|
||||
|
||||
n_speakers = len(set(labels))
|
||||
print(f"Identified {n_speakers} unique speakers")
|
||||
|
||||
# Step 5: Update DB chunks with speaker assignment
|
||||
print("Updating DB chunks...")
|
||||
# Map: chunk_id -> speaker_id
|
||||
speaker_map = {}
|
||||
for cid, label in zip(chunk_ids, labels):
|
||||
speaker_map[cid] = f"SPEAKER_{label}"
|
||||
|
||||
updated = 0
|
||||
for cid, spk_id in speaker_map.items():
|
||||
cur.execute("""
|
||||
UPDATE dev.chunk SET metadata = COALESCE(metadata, '{}'::jsonb) || %s::jsonb
|
||||
WHERE file_uuid = %s AND chunk_id = %s AND chunk_type = 'sentence'
|
||||
""", (json.dumps({"speaker_id": spk_id}), UUID, cid))
|
||||
updated += 1
|
||||
|
||||
conn.commit()
|
||||
print(f"Updated {updated} chunks with speaker IDs")
|
||||
|
||||
# Step 6: Save speaker map
|
||||
speaker_map_path = f"/Users/accusys/momentry/output_dev/{UUID}.speaker_map.json"
|
||||
with open(speaker_map_path, "w") as f:
|
||||
json.dump({"speakers": n_speakers, "assignments": speaker_map}, f, indent=2)
|
||||
print(f"Speaker map saved: {speaker_map_path}")
|
||||
|
||||
cur.close()
|
||||
conn.close()
|
||||
print("=== Done ===")
|
||||
284
scripts/transcribe.py
Normal file
284
scripts/transcribe.py
Normal file
@@ -0,0 +1,284 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""
|
||||
One-pass ASR + Speaker Change Detection + Split → asr.json
|
||||
"""
|
||||
import json, os, sys, time, argparse, subprocess, tempfile, shutil
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "asrx_self"))
|
||||
from speaker_encoder import load_speaker_encoder, extract_speaker_embedding, normalize_embeddings
|
||||
import torchaudio
|
||||
from faster_whisper import WhisperModel
|
||||
|
||||
SUB_WIN = 0.5
|
||||
SUB_STRIDE = 0.25
|
||||
MIN_DUR = 0.3
|
||||
SIM_THRESHOLD = 0.45
|
||||
CHANGE_CONFIRM = 2
|
||||
|
||||
def extract_audio(video_path, tmp_dir, sr=16000):
|
||||
wav_path = os.path.join(tmp_dir, "audio.wav")
|
||||
subprocess.run(["ffmpeg", "-y", "-v", "quiet", "-i", video_path,
|
||||
"-ar", str(sr), "-ac", "1", "-sample_fmt", "s16", wav_path],
|
||||
check=True, capture_output=True, timeout=300)
|
||||
wav_data, sr_actual = torchaudio.load(wav_path)
|
||||
if wav_data.shape[0] > 1:
|
||||
wav_data = wav_data.mean(dim=0, keepdim=True)
|
||||
return wav_data, sr_actual
|
||||
|
||||
def transcribe_pass1(model, wav_path, vad_params=None):
|
||||
print(" [faster-whisper] Transcribing...")
|
||||
if vad_params is None:
|
||||
vad_params = {"min_silence_duration_ms": 500, "speech_pad_ms": 200}
|
||||
segments, info = model.transcribe(wav_path, beam_size=5,
|
||||
vad_filter=True, word_timestamps=True, vad_parameters=vad_params)
|
||||
pass1 = []
|
||||
for i, seg in enumerate(segments):
|
||||
words = []
|
||||
if seg.words:
|
||||
for w in seg.words:
|
||||
words.append({"word": w.word.strip(), "start": round(w.start,3), "end": round(w.end,3)})
|
||||
pass1.append({
|
||||
"index": i,
|
||||
"start": round(seg.start, 3),
|
||||
"end": round(seg.end, 3),
|
||||
"text": seg.text.strip(),
|
||||
"words": words,
|
||||
})
|
||||
print(f" Pass1 segments: {len(pass1)}")
|
||||
return pass1
|
||||
|
||||
def detect_speaker_changes(wav_data, sr, pass1_segs, encoder, progress_step=100):
|
||||
print(" [Speaker Detection] Scanning...")
|
||||
ws = int(SUB_WIN * sr)
|
||||
sw = int(SUB_STRIDE * sr)
|
||||
change_points = [] # List[List[float]] → change times per pass1 segment
|
||||
t0 = time.time()
|
||||
|
||||
for si, seg in enumerate(pass1_segs):
|
||||
st = int(seg["start"] * sr)
|
||||
et = int(seg["end"] * sr)
|
||||
dur = seg["end"] - seg["start"]
|
||||
|
||||
if dur < 1.0:
|
||||
change_points.append([])
|
||||
continue
|
||||
|
||||
sub_embs = []
|
||||
sub_times = []
|
||||
for wpos in range(st, et - ws + 1, sw):
|
||||
chunk = wav_data[:, wpos:wpos+ws]
|
||||
emb = extract_speaker_embedding(encoder, chunk.numpy(), sr)
|
||||
emb = emb / (np.linalg.norm(emb) + 1e-10)
|
||||
sub_embs.append(emb)
|
||||
sub_times.append(wpos / sr)
|
||||
|
||||
if len(sub_embs) < 3:
|
||||
change_points.append([])
|
||||
continue
|
||||
|
||||
sub_embs = normalize_embeddings(np.array(sub_embs))
|
||||
cps = []
|
||||
# Require CHANGE_CONFIRM consecutive low-similarity windows before registering a change
|
||||
low_run = 0
|
||||
for i in range(1, len(sub_embs)):
|
||||
sim = float(np.dot(sub_embs[i-1], sub_embs[i]))
|
||||
if sim < SIM_THRESHOLD:
|
||||
low_run += 1
|
||||
if low_run >= CHANGE_CONFIRM:
|
||||
# Change point at the START of the low-sim run
|
||||
cps.append(round(sub_times[i - low_run + 1], 2))
|
||||
low_run = 0
|
||||
else:
|
||||
low_run = 0
|
||||
change_points.append(cps)
|
||||
|
||||
if (si + 1) % progress_step == 0:
|
||||
pct = (si + 1) * 100 // len(pass1_segs)
|
||||
print(f" {si+1}/{len(pass1_segs)} ({pct}%) [{time.time()-t0:.0f}s]")
|
||||
|
||||
total_changes = sum(len(cps) for cps in change_points)
|
||||
print(f" Speaker changes detected: {total_changes} in {len(pass1_segs)} segments ({time.time()-t0:.0f}s)")
|
||||
return change_points
|
||||
|
||||
def build_segments(pass1_segs, change_points, wav_data, sr, asr_model, tmp_dir, fps=24.0):
|
||||
print(" [Split] Building final segments...")
|
||||
final = []
|
||||
chunk_idx = 0
|
||||
|
||||
for si, seg in enumerate(pass1_segs):
|
||||
cps = change_points[si]
|
||||
if not cps:
|
||||
final.append({
|
||||
"chunk_id": str(chunk_idx),
|
||||
"pass1_index": si,
|
||||
"start_time": seg["start"],
|
||||
"end_time": seg["end"],
|
||||
"start_frame": int(seg["start"] * fps),
|
||||
"end_frame": int(seg["end"] * fps),
|
||||
"text": seg["text"],
|
||||
})
|
||||
chunk_idx += 1
|
||||
continue
|
||||
|
||||
seg["split"] = True
|
||||
boundaries = [seg["start"]] + cps + [seg["end"]]
|
||||
for pi in range(len(boundaries) - 1):
|
||||
ps, pe = boundaries[pi], boundaries[pi+1]
|
||||
if pe - ps < MIN_DUR:
|
||||
continue
|
||||
|
||||
# Try word_timestamp mapping first (wider tolerance)
|
||||
sub_words = [w["word"] for w in seg["words"] if w["start"] >= ps - 0.3 and w["end"] <= pe + 0.3]
|
||||
text = " ".join(sub_words).strip() if sub_words else ""
|
||||
|
||||
# Fallback: call faster-whisper on the sub-audio chunk
|
||||
if not text:
|
||||
import soundfile as sf
|
||||
chunk_path = os.path.join(tmp_dir, f"sub_{chunk_idx}.wav")
|
||||
a_chunk = wav_data[:, int(ps*sr):int(pe*sr)].numpy()[0]
|
||||
if len(a_chunk) > sr * 0.3: # skip if < 0.3s
|
||||
sf.write(chunk_path, a_chunk, sr)
|
||||
try:
|
||||
sub_segs, _ = asr_model.transcribe(chunk_path, beam_size=5,
|
||||
vad_filter=True, vad_parameters={"min_silence_duration_ms": 100})
|
||||
text = " ".join(s.text.strip() for s in sub_segs)
|
||||
except:
|
||||
pass
|
||||
os.remove(chunk_path)
|
||||
if not text:
|
||||
text = " ".join([w["word"] for w in seg["words"]
|
||||
if w["start"] >= ps - 0.5 and w["end"] <= pe + 0.5]).strip()
|
||||
if not text:
|
||||
text = seg["text"][:60]
|
||||
|
||||
final.append({
|
||||
"chunk_id": str(chunk_idx),
|
||||
"pass1_index": si,
|
||||
"start_time": round(ps, 3),
|
||||
"end_time": round(pe, 3),
|
||||
"start_frame": int(ps * fps),
|
||||
"end_frame": int(pe * fps),
|
||||
"text": text,
|
||||
"speaker_change": True,
|
||||
})
|
||||
chunk_idx += 1
|
||||
|
||||
print(f" Final segments: {len(final)}")
|
||||
return final
|
||||
|
||||
def voice_vectors_to_qdrant(wav_data, sr, final_segs, encoder, qdrant_url="http://localhost:6333"):
|
||||
print(" [Voice Vectors] Extracting 192D embeddings...")
|
||||
embeddings = []
|
||||
t0 = time.time()
|
||||
for si, seg in enumerate(final_segs):
|
||||
st = int(seg["start_time"] * sr)
|
||||
et = int(seg["end_time"] * sr)
|
||||
a_chunk = wav_data[:, st:et]
|
||||
emb = extract_speaker_embedding(encoder, a_chunk.numpy(), sr)
|
||||
emb = emb / (np.linalg.norm(emb) + 1e-10)
|
||||
embeddings.append({"chunk_id": seg["chunk_id"], "embedding": emb.tolist()})
|
||||
if (si + 1) % 500 == 0:
|
||||
print(f" {si+1}/{len(final_segs)} [{time.time()-t0:.0f}s]")
|
||||
|
||||
print(f" Writing to Qdrant...")
|
||||
from urllib.request import Request, urlopen
|
||||
batch = []
|
||||
for i, e in enumerate(embeddings):
|
||||
batch.append({"id": i + 1, "vector": e["embedding"],
|
||||
"payload": {"chunk_id": e["chunk_id"], "chunk_type": "sentence"}})
|
||||
if len(batch) >= 100:
|
||||
req = Request(f"{qdrant_url}/collections/momentry_dev_voice/points?wait=true",
|
||||
data=json.dumps({"points": batch}).encode(),
|
||||
headers={"Content-Type": "application/json"}, method="PUT")
|
||||
try: urlopen(req)
|
||||
except: pass
|
||||
batch = []
|
||||
# Flush remaining
|
||||
if batch:
|
||||
req = Request(f"{qdrant_url}/collections/momentry_dev_voice/points?wait=true",
|
||||
data=json.dumps({"points": batch}).encode(),
|
||||
headers={"Content-Type": "application/json"}, method="PUT")
|
||||
try: urlopen(req)
|
||||
except: pass
|
||||
|
||||
print(f" Voice vectors: {len(embeddings)} pts → Qdrant [{time.time()-t0:.0f}s]")
|
||||
return embeddings
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--video", default="/Users/accusys/momentry/var/sftpgo/data/demo/Charade (1963) Cary Grant & Audrey Hepburn ｜ Comedy Mystery Romance Thriller ｜ Full Movie.mp4")
|
||||
parser.add_argument("--output", help="Output path for asr.json", default="/Users/accusys/momentry/output_dev/aeed71342a899fe4b4c57b7d41bcb692.asr.json")
|
||||
parser.add_argument("--sample", type=int, help="Process only first N pass1 segments (for testing)")
|
||||
parser.add_argument("--no-qdrant", action="store_true", help="Skip Qdrant upload")
|
||||
args = parser.parse_args()
|
||||
|
||||
t0 = time.time()
|
||||
|
||||
# Load models
|
||||
print("=== Loading Models ===")
|
||||
asr_model = WhisperModel("small", device="cpu", compute_type="int8")
|
||||
print(" faster-whisper small loaded")
|
||||
encoder = load_speaker_encoder()
|
||||
print(" ECAPA-TDNN loaded")
|
||||
print()
|
||||
|
||||
# Extract audio
|
||||
print("=== Audio Extraction ===")
|
||||
tmp_dir = tempfile.mkdtemp(prefix="transcribe_")
|
||||
wav_data, sr = extract_audio(args.video, tmp_dir)
|
||||
print(f" Audio: {wav_data.shape[1]/sr:.0f}s, {sr}Hz")
|
||||
wav_path = os.path.join(tmp_dir, "audio.wav")
|
||||
print()
|
||||
|
||||
# Step 1: faster-whisper pass1
|
||||
print("=== Step 1: Pass1 Transcription ===")
|
||||
pass1_segs = transcribe_pass1(asr_model, wav_path)
|
||||
if args.sample:
|
||||
pass1_segs = pass1_segs[:args.sample]
|
||||
print(f" SAMPLE MODE: limiting to {args.sample} segments")
|
||||
print()
|
||||
|
||||
# Step 2: Speaker change detection
|
||||
print("=== Step 2: Speaker Change Detection ===")
|
||||
change_points = detect_speaker_changes(wav_data, sr, pass1_segs, encoder)
|
||||
print()
|
||||
|
||||
# Step 3: Build final segments
|
||||
print("=== Step 3: Build Final Segments ===")
|
||||
final_segs = build_segments(pass1_segs, change_points, wav_data, sr, asr_model, tmp_dir)
|
||||
print()
|
||||
|
||||
# Step 4: Voice vectors → Qdrant
|
||||
if not args.no_qdrant:
|
||||
print("=== Step 4: Voice Vectors → Qdrant ===")
|
||||
voice_vectors_to_qdrant(wav_data, sr, final_segs, encoder)
|
||||
print()
|
||||
|
||||
# Step 5: Write asr.json
|
||||
print("=== Step 5: Write asr.json ===")
|
||||
uuid = os.path.basename(args.output).replace(".asr.json", "")
|
||||
output = {
|
||||
"file_uuid": uuid,
|
||||
"pass1": pass1_segs,
|
||||
"segments": final_segs,
|
||||
}
|
||||
with open(args.output, "w") as f:
|
||||
json.dump(output, f, indent=2, ensure_ascii=False)
|
||||
sz = os.path.getsize(args.output)
|
||||
print(f" {args.output} ({sz/1024:.0f} KB)")
|
||||
|
||||
# Cleanup
|
||||
shutil.rmtree(tmp_dir, ignore_errors=True)
|
||||
|
||||
elapsed = time.time() - t0
|
||||
print(f"\n=== Done ({elapsed:.0f}s) ===")
|
||||
print(f" Pass1 segments: {len(pass1_segs)}")
|
||||
print(f" Final segments: {len(final_segs)}")
|
||||
fp = args.output
|
||||
print(f" Output: {fp}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
BIN
scripts/vec0.dylib
Normal file
BIN
scripts/vec0.dylib
Normal file
Binary file not shown.
69
scripts/vectorize_chunks.py
Normal file
69
scripts/vectorize_chunks.py
Normal file
@@ -0,0 +1,69 @@
|
||||
#!/opt/homebrew/bin/python3.11
|
||||
"""Vectorize sentence chunks via Ollama mxbai-embed-large and store in DB + Qdrant."""
|
||||
import json, sys, time
|
||||
import psycopg2
|
||||
from urllib.request import Request, urlopen
|
||||
|
||||
DB = "dbname=momentry user=accusys"
|
||||
UUID = sys.argv[1] if len(sys.argv) > 1 else "23b1c872379d4ec06479e5ed39eef4c5"
|
||||
OLLAMA = "http://localhost:11434/api/embeddings"
|
||||
QDRANT = "http://localhost:6333"
|
||||
|
||||
conn = psycopg2.connect(DB)
|
||||
cur = conn.cursor()
|
||||
|
||||
cur.execute("""
|
||||
SELECT chunk_id, text_content FROM dev.chunk
|
||||
WHERE file_uuid = %s AND chunk_type = 'sentence'
|
||||
AND (text_content IS NOT NULL AND text_content != '')
|
||||
ORDER BY id
|
||||
""", (UUID,))
|
||||
rows = cur.fetchall()
|
||||
print(f"Vectorizing {len(rows)} chunks for {UUID}...")
|
||||
|
||||
stored = 0
|
||||
batch = []
|
||||
for chunk_id, text in rows:
|
||||
req = Request(OLLAMA, data=json.dumps({
|
||||
"model": "nomic-embed-text-v2-moe:latest",
|
||||
"prompt": text
|
||||
}).encode(), headers={"Content-Type": "application/json"})
|
||||
resp = json.loads(urlopen(req).read())
|
||||
embedding = resp["embedding"]
|
||||
|
||||
# Store in PostgreSQL chunk_vectors
|
||||
cur.execute("""
|
||||
INSERT INTO dev.chunk_vectors (chunk_id, uuid, chunk_type, embedding)
|
||||
VALUES (%s, %s, 'sentence', %s::jsonb)
|
||||
ON CONFLICT (chunk_id, uuid) DO UPDATE SET embedding = EXCLUDED.embedding
|
||||
""", (chunk_id, UUID, json.dumps(embedding)))
|
||||
|
||||
# Batch for Qdrant
|
||||
batch.append({
|
||||
"id": int(chunk_id) + 1 if chunk_id.isdigit() else len(batch) + 10000,
|
||||
"vector": embedding,
|
||||
"payload": {"chunk_id": chunk_id, "chunk_type": "sentence"}
|
||||
})
|
||||
|
||||
if len(batch) >= 100:
|
||||
req = Request(f"{QDRANT}/collections/momentry_dev_rule1_v2/points?wait=true",
|
||||
data=json.dumps({"points": batch}).encode(),
|
||||
headers={"Content-Type": "application/json"}, method="PUT")
|
||||
urlopen(req)
|
||||
batch = []
|
||||
|
||||
stored += 1
|
||||
if stored % 50 == 0:
|
||||
print(f" {stored}/{len(rows)}")
|
||||
conn.commit()
|
||||
|
||||
if batch:
|
||||
req = Request(f"{QDRANT}/collections/momentry_dev_rule1_v2/points?wait=true",
|
||||
data=json.dumps({"points": batch}).encode(),
|
||||
headers={"Content-Type": "application/json"}, method="PUT")
|
||||
urlopen(req)
|
||||
|
||||
conn.commit()
|
||||
cur.close()
|
||||
conn.close()
|
||||
print(f"Done: {stored} vectors stored")
|
||||
618
src/bin/release.rs
Normal file
618
src/bin/release.rs
Normal file
@@ -0,0 +1,618 @@
|
||||
//! Release Manager — deploy/undeploy/list video packages.
|
||||
//! Binary: `cargo run --bin release -- <command>`
|
||||
|
||||
use anyhow::{Context, Result};
|
||||
use chrono::Utc;
|
||||
use clap::{Parser, Subcommand};
|
||||
use momentry_core::core::config;
|
||||
use momentry_core::core::db::PostgresDb;
|
||||
use sqlx::Row;
|
||||
use std::fs;
|
||||
use std::io::Write;
|
||||
use std::path::{Path, PathBuf};
|
||||
use std::process::Command;
|
||||
|
||||
const DEMO_DIR: &str = "/Users/accusys/momentry/var/sftpgo/data/demo";
|
||||
const OUTPUT_DIR: &str = "/Users/accusys/momentry/output_dev";
|
||||
const RELEASE_DIR: &str = "/Users/accusys/momentry_core_0.1/release/files";
|
||||
const PG_BIN: &str = "/Users/accusys/pgsql/18.3/bin";
|
||||
|
||||
#[derive(Parser)]
|
||||
#[command(name = "release", about = "Release Manager — deploy/undeploy video packages")]
|
||||
struct Cli {
|
||||
#[command(subcommand)]
|
||||
command: Commands,
|
||||
}
|
||||
|
||||
#[derive(Subcommand)]
|
||||
enum Commands {
|
||||
/// Deploy a release package (.tar.gz)
|
||||
Deploy {
|
||||
/// Path to .tar.gz package
|
||||
tarball: String,
|
||||
},
|
||||
/// Undeploy (remove all data for a video UUID)
|
||||
Undeploy {
|
||||
/// File UUID
|
||||
uuid: String,
|
||||
/// Skip confirmation
|
||||
#[arg(short = 'y', long)]
|
||||
yes: bool,
|
||||
},
|
||||
/// List deployed videos
|
||||
List,
|
||||
/// Create release package for a deployed video
|
||||
Package {
|
||||
/// File UUID
|
||||
uuid: String,
|
||||
},
|
||||
/// Show package contents and statistics
|
||||
Stats,
|
||||
/// Generate visual reports from video data
|
||||
Visualize {
|
||||
/// File UUID
|
||||
uuid: String,
|
||||
/// Visualization type: heatmap, timeline
|
||||
#[arg(short, long, default_value = "heatmap")]
|
||||
typ: String,
|
||||
/// Output path (default: output_dev/<uuid>_heatmap.html)
|
||||
#[arg(short, long)]
|
||||
output: Option<String>,
|
||||
/// Filter by identity_id
|
||||
#[arg(short = 'i', long)]
|
||||
identity: Option<i64>,
|
||||
},
|
||||
}
|
||||
|
||||
/// Run psql command and return stdout
|
||||
fn psql_exec(sql: &str) -> Result<String> {
|
||||
let output = Command::new(format!("{}/psql", PG_BIN))
|
||||
.args(["-U", "accusys", "-d", "momentry", "-t", "-A", "-c", sql])
|
||||
.output()
|
||||
.context("psql command failed")?;
|
||||
Ok(String::from_utf8_lossy(&output.stdout).trim().to_string())
|
||||
}
|
||||
|
||||
/// Run a SQL file via psql
|
||||
fn psql_file(path: &Path) -> Result<()> {
|
||||
let status = Command::new(format!("{}/psql", PG_BIN))
|
||||
.args(["-U", "accusys", "-d", "momentry", "-f"])
|
||||
.arg(path)
|
||||
.status()
|
||||
.context("psql file execution failed")?;
|
||||
if !status.success() {
|
||||
anyhow::bail!("psql returned non-zero exit code");
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Extract tar.gz archive to a temp directory, return the top-level dir
|
||||
fn extract_tarball(tarball: &Path) -> Result<PathBuf> {
|
||||
let tmpdir = std::env::temp_dir().join(format!("release_{}", Utc::now().timestamp()));
|
||||
fs::create_dir_all(&tmpdir)?;
|
||||
|
||||
let status = Command::new("tar")
|
||||
.args(["-xzf", tarball.to_str().unwrap(), "-C", tmpdir.to_str().unwrap()])
|
||||
.status()
|
||||
.context("tar extraction failed")?;
|
||||
if !status.success() {
|
||||
anyhow::bail!("tar returned non-zero");
|
||||
}
|
||||
|
||||
// Find the UUID directory (first subdir)
|
||||
for entry in fs::read_dir(&tmpdir)? {
|
||||
let entry = entry?;
|
||||
if entry.file_type()?.is_dir() {
|
||||
return Ok(entry.path());
|
||||
}
|
||||
}
|
||||
anyhow::bail!("no directory found in tarball");
|
||||
}
|
||||
|
||||
/// Get file_info.json from package directory
|
||||
fn read_file_info(pkg_dir: &Path) -> Result<serde_json::Value> {
|
||||
let info_path = pkg_dir.join("file_info.json");
|
||||
let content = fs::read_to_string(&info_path)
|
||||
.with_context(|| format!("Cannot read {:?}", info_path))?;
|
||||
serde_json::from_str(&content).context("Invalid file_info.json")
|
||||
}
|
||||
|
||||
// ---- Deploy ----
|
||||
|
||||
async fn cmd_deploy(db: &PostgresDb, tarball: &str) -> Result<()> {
|
||||
let tarball_path = Path::new(tarball);
|
||||
if !tarball_path.exists() {
|
||||
anyhow::bail!("File not found: {}", tarball);
|
||||
}
|
||||
|
||||
println!("=== Deploy: {} ===", tarball_path.file_name().unwrap().to_str().unwrap());
|
||||
|
||||
// Extract
|
||||
let pkg_dir = extract_tarball(tarball_path)?;
|
||||
println!("Extracted to {:?}", pkg_dir);
|
||||
|
||||
// Read file_info
|
||||
let info = read_file_info(&pkg_dir)?;
|
||||
let uuid = info["file_uuid"].as_str().context("Missing file_uuid in file_info.json")?;
|
||||
let file_name = info["file_name"].as_str().unwrap_or("?");
|
||||
println!("UUID: {}\nVideo: {}", uuid, file_name);
|
||||
|
||||
// Import data.sql
|
||||
let sql_path = pkg_dir.join("data.sql");
|
||||
if sql_path.exists() {
|
||||
let size = fs::metadata(&sql_path)?.len();
|
||||
println!("Importing data.sql ({} MB)...", size / 1024 / 1024);
|
||||
psql_file(&sql_path)?;
|
||||
println!(" SQL imported OK");
|
||||
} else {
|
||||
println!(" No data.sql in package");
|
||||
}
|
||||
|
||||
// Copy video to demo dir
|
||||
for entry in fs::read_dir(&pkg_dir)? {
|
||||
let entry = entry?;
|
||||
let fname = entry.file_name();
|
||||
let fname_str = fname.to_str().unwrap_or("");
|
||||
if fname_str.ends_with(".mp4") || fname_str.ends_with(".mov") || fname_str.ends_with(".avi") {
|
||||
let dest = Path::new(DEMO_DIR).join(&fname);
|
||||
if !dest.exists() {
|
||||
fs::copy(entry.path(), &dest)?;
|
||||
println!("Video: {} → {}", fname_str, DEMO_DIR);
|
||||
} else {
|
||||
println!("Video: {} already in demo dir", fname_str);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Copy output JSONs
|
||||
for entry in fs::read_dir(&pkg_dir)? {
|
||||
let entry = entry?;
|
||||
let fname = entry.file_name();
|
||||
let fname_str = fname.to_str().unwrap_or("");
|
||||
if fname_str.ends_with(".json") && fname_str != "file_info.json" {
|
||||
let dest = Path::new(OUTPUT_DIR).join(&fname);
|
||||
fs::copy(entry.path(), &dest)?;
|
||||
}
|
||||
}
|
||||
println!("Output files copied to {}", OUTPUT_DIR);
|
||||
|
||||
// Verify
|
||||
let chunk_count: (i64,) = sqlx::query_as(
|
||||
"SELECT COUNT(*) FROM dev.chunk WHERE file_uuid = $1"
|
||||
).bind(uuid).fetch_one(db.pool()).await?;
|
||||
let face_count: (i64,) = sqlx::query_as(
|
||||
"SELECT COUNT(*) FROM dev.face_detections WHERE file_uuid = $1"
|
||||
).bind(uuid).fetch_one(db.pool()).await?;
|
||||
|
||||
// Cleanup
|
||||
fs::remove_dir_all(&pkg_dir.parent().unwrap_or(&pkg_dir))?;
|
||||
|
||||
println!("\n=== Deploy Complete ===");
|
||||
println!(" Video: {}", file_name);
|
||||
println!(" Chunks: {}", chunk_count.0);
|
||||
println!(" Face detections: {}", face_count.0);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Undeploy ----
|
||||
|
||||
async fn cmd_undeploy(db: &PostgresDb, uuid: &str, skip_confirm: bool) -> Result<()> {
|
||||
// Get video info
|
||||
let rows: Vec<(String, String)> = sqlx::query_as(
|
||||
"SELECT file_name, file_path FROM dev.videos WHERE file_uuid = $1"
|
||||
).bind(uuid).fetch_all(db.pool()).await?;
|
||||
|
||||
if rows.is_empty() {
|
||||
anyhow::bail!("UUID {} not found in DB", uuid);
|
||||
}
|
||||
|
||||
let (file_name, file_path) = &rows[0];
|
||||
println!("=== Undeploy: {} ===", uuid);
|
||||
println!("Video: {}", file_name);
|
||||
println!("This will DELETE all data for this video.");
|
||||
|
||||
if !skip_confirm {
|
||||
print!("Continue? (y/N): ");
|
||||
std::io::stdout().flush()?;
|
||||
let mut input = String::new();
|
||||
std::io::stdin().read_line(&mut input)?;
|
||||
if input.trim().to_lowercase() != "y" {
|
||||
println!("Cancelled");
|
||||
return Ok(());
|
||||
}
|
||||
}
|
||||
|
||||
// Delete DB data
|
||||
let tables = [
|
||||
("dev.chunk", "file_uuid"),
|
||||
("dev.chunk_vectors", "uuid"),
|
||||
("dev.face_detections", "file_uuid"),
|
||||
("dev.processor_results", "file_uuid"),
|
||||
("dev.monitor_jobs", "uuid"),
|
||||
("dev.pre_chunks", "file_uuid"),
|
||||
];
|
||||
for (tbl, col) in &tables {
|
||||
let sql = format!("DELETE FROM {} WHERE {} = $1", tbl, col);
|
||||
let result = sqlx::query(&sql).bind(uuid).execute(db.pool()).await?;
|
||||
println!(" {}: {} rows deleted", tbl, result.rows_affected());
|
||||
}
|
||||
sqlx::query("DELETE FROM dev.videos WHERE file_uuid = $1")
|
||||
.bind(uuid).execute(db.pool()).await?;
|
||||
println!(" dev.videos: removed");
|
||||
|
||||
// Delete output files
|
||||
for entry in fs::read_dir(OUTPUT_DIR)? {
|
||||
let entry = entry?;
|
||||
let fname = entry.file_name().to_string_lossy().to_string();
|
||||
if fname.starts_with(uuid) {
|
||||
fs::remove_file(entry.path())?;
|
||||
}
|
||||
}
|
||||
println!(" Output files: removed");
|
||||
|
||||
// Delete video file
|
||||
if !file_path.is_empty() {
|
||||
let vp = Path::new(file_path);
|
||||
if vp.exists() {
|
||||
fs::remove_file(vp)?;
|
||||
println!(" Video file: removed ({})", vp.file_name().unwrap().to_str().unwrap_or("?"));
|
||||
}
|
||||
}
|
||||
|
||||
// Delete release directory
|
||||
let release_path = Path::new(RELEASE_DIR).join(uuid);
|
||||
if release_path.exists() {
|
||||
fs::remove_dir_all(&release_path)?;
|
||||
println!(" Release dir: removed");
|
||||
}
|
||||
|
||||
println!("\n=== Undeploy Complete ===");
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- List ----
|
||||
|
||||
async fn cmd_list(db: &PostgresDb) -> Result<()> {
|
||||
let rows = sqlx::query(
|
||||
"SELECT file_uuid, file_name, duration, status,
|
||||
(SELECT COUNT(*) FROM dev.chunk WHERE file_uuid = v.file_uuid) as chunks,
|
||||
(SELECT COUNT(*) FROM dev.face_detections WHERE file_uuid = v.file_uuid) as faces
|
||||
FROM dev.videos v ORDER BY id DESC"
|
||||
).fetch_all(db.pool()).await?;
|
||||
|
||||
println!("{:<36} {:<44} {:>8} {:>10} {:>6} {:>6}",
|
||||
"UUID", "Name", "Duration", "Status", "Chunks", "Faces");
|
||||
println!("{}", "-".repeat(116));
|
||||
|
||||
for row in &rows {
|
||||
let uuid: String = row.get(0);
|
||||
let name: String = row.get::<Option<String>, _>(1).unwrap_or_default();
|
||||
let duration: Option<f64> = row.get(2);
|
||||
let status: Option<String> = row.get(3);
|
||||
let chunks: Option<i64> = row.get(4);
|
||||
let faces: Option<i64> = row.get(5);
|
||||
|
||||
let dur_str = match duration {
|
||||
Some(d) if d > 60.0 => format!("{:5.0}min", d / 60.0),
|
||||
Some(d) => format!("{:5.0}s", d),
|
||||
None => "?".to_string(),
|
||||
};
|
||||
let short_name = if name.chars().count() > 42 {
|
||||
format!("{}..", name.chars().take(40).collect::<String>())
|
||||
} else {
|
||||
name.clone()
|
||||
};
|
||||
|
||||
println!("{:<36} {:<44} {:>8} {:>10} {:>6} {:>6}",
|
||||
uuid, short_name, dur_str,
|
||||
status.as_deref().unwrap_or("?"),
|
||||
chunks.unwrap_or(0), faces.unwrap_or(0));
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Package ----
|
||||
|
||||
async fn cmd_package(db: &PostgresDb, uuid: &str) -> Result<()> {
|
||||
println!("=== Package: {} ===", uuid);
|
||||
|
||||
// Verify video exists
|
||||
let row = sqlx::query(
|
||||
"SELECT file_uuid, file_name, file_path, duration, fps, width, height FROM dev.videos WHERE file_uuid = $1"
|
||||
).bind(uuid).fetch_optional(db.pool()).await?;
|
||||
let (_, file_name, file_path, duration, fps, width, height): (
|
||||
String, String, String, Option<f64>, Option<f64>, Option<i32>, Option<i32>
|
||||
) = match row {
|
||||
Some(r) => (r.get(0), r.get(1), r.get(2), r.get(3), r.get(4), r.get(5), r.get(6)),
|
||||
None => anyhow::bail!("UUID {} not found", uuid),
|
||||
};
|
||||
|
||||
let outdir = Path::new(RELEASE_DIR).join(uuid);
|
||||
if outdir.exists() {
|
||||
fs::remove_dir_all(&outdir)?;
|
||||
}
|
||||
fs::create_dir_all(&outdir)?;
|
||||
|
||||
// Write file_info.json
|
||||
let info = serde_json::json!({
|
||||
"file_uuid": uuid,
|
||||
"file_name": file_name,
|
||||
"duration": duration,
|
||||
"fps": fps,
|
||||
"width": width,
|
||||
"height": height,
|
||||
"status": "completed",
|
||||
});
|
||||
fs::write(outdir.join("file_info.json"), serde_json::to_string_pretty(&info)?)?;
|
||||
|
||||
// Export data.sql
|
||||
let sql_path = outdir.join("data.sql");
|
||||
let tables = [
|
||||
("dev.videos", "file_uuid"),
|
||||
("dev.chunk", "file_uuid"),
|
||||
("dev.chunk_vectors", "uuid"),
|
||||
("dev.face_detections", "file_uuid"),
|
||||
];
|
||||
|
||||
{
|
||||
let mut f = fs::File::create(&sql_path)?;
|
||||
writeln!(f, "-- Release package: {}", uuid)?;
|
||||
writeln!(f, "BEGIN;")?;
|
||||
writeln!(f)?;
|
||||
|
||||
for (tbl, col) in &tables {
|
||||
writeln!(f, "-- {} WHERE {} = '{}'", tbl, col, uuid)?;
|
||||
// Get columns
|
||||
let parts: Vec<&str> = tbl.split('.').collect();
|
||||
let cols = psql_exec(&format!(
|
||||
"SELECT string_agg(column_name, ', ' ORDER BY ordinal_position) FROM information_schema.columns WHERE table_schema='{}' AND table_name='{}' AND is_updatable='YES'",
|
||||
parts[0], parts[1]
|
||||
))?;
|
||||
|
||||
// COPY
|
||||
let data = psql_exec(&format!(
|
||||
"COPY (SELECT * FROM {} WHERE {} = '{}') TO STDOUT WITH CSV HEADER",
|
||||
tbl, col, uuid
|
||||
))?;
|
||||
|
||||
if !data.is_empty() {
|
||||
writeln!(f, "COPY {} ({}) FROM STDIN WITH CSV HEADER;", tbl, cols)?;
|
||||
writeln!(f, "{}", data)?;
|
||||
writeln!(f, "\\.")?;
|
||||
writeln!(f)?;
|
||||
}
|
||||
}
|
||||
// Export identities referenced by this file
|
||||
writeln!(f, "-- dev.identities (referenced by face_detections)")?;
|
||||
let cols = psql_exec("SELECT string_agg(column_name, ', ' ORDER BY ordinal_position) FROM information_schema.columns WHERE table_schema='dev' AND table_name='identities' AND is_updatable='YES'")?;
|
||||
let data = psql_exec(&format!(
|
||||
"COPY (SELECT DISTINCT i.* FROM dev.identities i INNER JOIN dev.face_detections fd ON fd.identity_id = i.id WHERE fd.file_uuid = '{}') TO STDOUT WITH CSV HEADER", uuid
|
||||
))?;
|
||||
if !data.is_empty() {
|
||||
writeln!(f, "COPY dev.identities ({}) FROM STDIN WITH CSV HEADER;", cols)?;
|
||||
writeln!(f, "{}", data)?;
|
||||
writeln!(f, "\\.")?;
|
||||
writeln!(f)?;
|
||||
}
|
||||
|
||||
// Export identity_bindings for identities referenced by this file
|
||||
writeln!(f, "-- dev.identity_bindings (for identities in face_detections)")?;
|
||||
let cols = psql_exec("SELECT string_agg(column_name, ', ' ORDER BY ordinal_position) FROM information_schema.columns WHERE table_schema='dev' AND table_name='identity_bindings' AND is_updatable='YES'")?;
|
||||
let data = psql_exec(&format!(
|
||||
"COPY (SELECT DISTINCT ib.* FROM dev.identity_bindings ib INNER JOIN dev.face_detections fd ON fd.identity_id = ib.identity_id WHERE fd.file_uuid = '{}') TO STDOUT WITH CSV HEADER", uuid
|
||||
))?;
|
||||
if !data.is_empty() {
|
||||
writeln!(f, "COPY dev.identity_bindings ({}) FROM STDIN WITH CSV HEADER;", cols)?;
|
||||
writeln!(f, "{}", data)?;
|
||||
writeln!(f, "\\.")?;
|
||||
writeln!(f)?;
|
||||
}
|
||||
|
||||
writeln!(f, "COMMIT;")?;
|
||||
}
|
||||
|
||||
let sql_size = fs::metadata(&sql_path)?.len();
|
||||
println!(" data.sql ({} MB)", sql_size / 1024 / 1024);
|
||||
|
||||
// Copy video file
|
||||
if !file_path.is_empty() {
|
||||
let vp = Path::new(&file_path);
|
||||
if vp.exists() {
|
||||
let dest = outdir.join(vp.file_name().unwrap());
|
||||
fs::copy(vp, &dest)?;
|
||||
let vsize = fs::metadata(&dest)?.len();
|
||||
println!(" {} ({} MB)", vp.file_name().unwrap().to_str().unwrap_or("?"), vsize / 1024 / 1024);
|
||||
}
|
||||
}
|
||||
|
||||
// Generate identities.json for offline analysis
|
||||
let id_script = "/Users/accusys/momentry_core_0.1/scripts/export_identities.py";
|
||||
let id_out = format!("{}/{}.identities.json", OUTPUT_DIR, uuid);
|
||||
let _ = Command::new("/opt/homebrew/bin/python3.11")
|
||||
.args([id_script, uuid, &id_out])
|
||||
.status();
|
||||
if Path::new(&id_out).exists() {
|
||||
println!(" Identities JSON generated");
|
||||
}
|
||||
|
||||
// Generate SQLite database for offline app use
|
||||
let sqlite_script = "/Users/accusys/momentry_core_0.1/scripts/export_sqlite.py";
|
||||
let sqlite_out = format!("{}/{}.sqlite", OUTPUT_DIR, uuid);
|
||||
let _ = Command::new("/opt/homebrew/bin/python3.11")
|
||||
.args([sqlite_script, uuid, &sqlite_out])
|
||||
.status();
|
||||
if Path::new(&sqlite_out).exists() {
|
||||
let sz = fs::metadata(&sqlite_out)?.len();
|
||||
println!(" SQLite database: {}MB", sz / 1048576);
|
||||
}
|
||||
|
||||
// Copy output files (JSONs + SQLite + any data files)
|
||||
for entry in fs::read_dir(OUTPUT_DIR)? {
|
||||
let entry = entry?;
|
||||
let fname = entry.file_name().to_string_lossy().to_string();
|
||||
if fname.starts_with(uuid) {
|
||||
fs::copy(entry.path(), outdir.join(&fname))?;
|
||||
}
|
||||
}
|
||||
println!(" Output files copied");
|
||||
|
||||
// Create tar.gz
|
||||
let tarball = Path::new(RELEASE_DIR).join(format!("{}_v{}.tar.gz", uuid, Utc::now().format("%Y%m%d_%H%M%S")));
|
||||
let status = Command::new("tar")
|
||||
.args(["-czf", tarball.to_str().unwrap(), "-C", RELEASE_DIR, uuid])
|
||||
.status()?;
|
||||
if !status.success() {
|
||||
anyhow::bail!("tar creation failed");
|
||||
}
|
||||
let tsize = fs::metadata(&tarball)?.len();
|
||||
println!("\n Package: {} ({} MB)", tarball.display(), tsize / 1024 / 1024);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Visualize ----
|
||||
|
||||
fn cmd_visualize(uuid: &str, typ: &str, output: Option<&str>, identity: Option<i64>) -> Result<()> {
|
||||
let outpath = match output {
|
||||
Some(p) => p.to_string(),
|
||||
None => format!("/Users/accusys/momentry/output_dev/{}_heatmap.html", uuid),
|
||||
};
|
||||
|
||||
match typ {
|
||||
"heatmap" | "density" => generate_face_heatmap(uuid, &outpath, identity)?,
|
||||
"timeline" => generate_face_timeline(uuid, &outpath, identity)?,
|
||||
_ => anyhow::bail!("Unknown visualization type: {}. Try: heatmap, density, timeline", typ),
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn generate_face_heatmap(uuid: &str, outpath: &str, identity: Option<i64>) -> Result<()> {
|
||||
let script = "/Users/accusys/momentry_core_0.1/scripts/render_face_heatmap.py";
|
||||
let mut args: Vec<String> = vec![script.to_string(), uuid.to_string(), outpath.to_string()];
|
||||
if let Some(id) = identity {
|
||||
args.push("--identity".to_string());
|
||||
args.push(id.to_string());
|
||||
}
|
||||
let output = Command::new("/opt/homebrew/bin/python3.11")
|
||||
.args(&args)
|
||||
.output()
|
||||
.context("Python heatmap script failed")?;
|
||||
if !output.status.success() {
|
||||
anyhow::bail!("Heatmap: {}", String::from_utf8_lossy(&output.stderr));
|
||||
}
|
||||
println!("{}", String::from_utf8_lossy(&output.stdout));
|
||||
println!("\n Open: {}", outpath);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn generate_face_timeline(uuid: &str, outpath: &str, identity: Option<i64>) -> Result<()> {
|
||||
generate_face_heatmap(uuid, outpath, identity)
|
||||
}
|
||||
|
||||
// ---- Stats ----
|
||||
|
||||
fn cmd_stats() -> Result<()> {
|
||||
let pkg_dir = Path::new(RELEASE_DIR);
|
||||
if !pkg_dir.exists() {
|
||||
println!("No release packages found at {}", pkg_dir.display());
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let mut packages: Vec<PathBuf> = Vec::new();
|
||||
for entry in fs::read_dir(&pkg_dir)? {
|
||||
let entry = entry?;
|
||||
let name = entry.file_name().to_string_lossy().to_string();
|
||||
if name.ends_with(".tar.gz") {
|
||||
packages.push(entry.path());
|
||||
}
|
||||
}
|
||||
packages.sort_by(|a, b| b.cmp(a)); // newest first
|
||||
|
||||
if packages.is_empty() {
|
||||
println!("No .tar.gz packages found.");
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
for pkg_path in &packages {
|
||||
let pkg_name = pkg_path.file_name().unwrap().to_str().unwrap_or("?");
|
||||
let pkg_size = fs::metadata(pkg_path)?.len();
|
||||
|
||||
println!("📦 {} ({} MB)", pkg_name, pkg_size / 1024 / 1024);
|
||||
|
||||
// List contents via tar -tvzf (shows sizes without extraction)
|
||||
let output = Command::new("tar")
|
||||
.args(["-tvzf", pkg_path.to_str().unwrap()])
|
||||
.output()
|
||||
.context("tar list failed")?;
|
||||
|
||||
let listing = String::from_utf8_lossy(&output.stdout);
|
||||
let mut total_sql = 0u64;
|
||||
let mut total_video = 0u64;
|
||||
let mut total_json = 0u64;
|
||||
let mut sql_count = 0u64;
|
||||
let mut video_count = 0u64;
|
||||
let mut json_count = 0u64;
|
||||
|
||||
for line in listing.lines() {
|
||||
let trimmed = line.trim();
|
||||
if trimmed.is_empty() || trimmed.ends_with('/') { continue; }
|
||||
|
||||
// tar -tvzf format: perms link owner group size date_month date_day time path...
|
||||
// Fields are space-separated; size is 5th field, path starts at 8th field
|
||||
let parts: Vec<&str> = trimmed.split_whitespace().collect();
|
||||
if parts.len() < 8 { continue; }
|
||||
let fsize = parts[4].parse::<u64>().unwrap_or(0);
|
||||
let fpath = parts[8..].join(" ");
|
||||
let fname = Path::new(&fpath).file_name().unwrap_or_default().to_str().unwrap_or("?");
|
||||
let ext = Path::new(&fpath).extension().unwrap_or_default().to_str().unwrap_or("");
|
||||
|
||||
match ext {
|
||||
"sql" => {
|
||||
println!(" 📄 {} ({:.0} MB)", fname, fsize as f64 / 1048576.0);
|
||||
total_sql += fsize;
|
||||
sql_count += 1;
|
||||
}
|
||||
"mp4" | "mov" | "avi" | "mkv" => {
|
||||
println!(" 🎬 {} ({:.0} MB)", fname, fsize as f64 / 1048576.0);
|
||||
total_video += fsize;
|
||||
video_count += 1;
|
||||
}
|
||||
"json" => {
|
||||
if fname != "file_info.json" {
|
||||
println!(" 📋 {} ({:.0} MB)", fname, fsize as f64 / 1048576.0);
|
||||
}
|
||||
total_json += fsize;
|
||||
json_count += 1;
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
}
|
||||
|
||||
println!(" ─────────────────────────────");
|
||||
println!(" SQL: {} files, {:.0} MB", sql_count, total_sql as f64 / 1048576.0);
|
||||
println!(" Video: {} files, {:.0} MB", video_count, total_video as f64 / 1048576.0);
|
||||
println!(" JSON: {} files, {:.0} MB", json_count, total_json as f64 / 1048576.0);
|
||||
println!(" Total: {:.0} MB (compressed: {:.0} MB)", (total_sql + total_video + total_json) as f64 / 1048576.0, pkg_size as f64 / 1048576.0);
|
||||
println!();
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Main ----
|
||||
|
||||
#[tokio::main]
|
||||
async fn main() -> Result<()> {
|
||||
dotenv::from_filename(".env.development").ok();
|
||||
let cli = Cli::parse();
|
||||
let db = PostgresDb::new(&config::DATABASE_URL).await?;
|
||||
|
||||
match cli.command {
|
||||
Commands::Deploy { tarball } => cmd_deploy(&db, &tarball).await?,
|
||||
Commands::Undeploy { uuid, yes } => cmd_undeploy(&db, &uuid, yes).await?,
|
||||
Commands::List => cmd_list(&db).await?,
|
||||
Commands::Package { uuid } => cmd_package(&db, &uuid).await?,
|
||||
Commands::Stats => cmd_stats()?,
|
||||
Commands::Visualize { uuid, typ, output, identity } => cmd_visualize(&uuid, &typ, output.as_deref(), identity)?,
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
853
src/bin/service.rs
Normal file
853
src/bin/service.rs
Normal file
@@ -0,0 +1,853 @@
|
||||
//! Service Lifecycle Manager — source, build, install, config, launch, env
|
||||
//! Binary: `cargo run --bin service -- <command>`
|
||||
|
||||
use anyhow::{Context, Result};
|
||||
use chrono::Local;
|
||||
use clap::{Parser, Subcommand};
|
||||
use std::fs;
|
||||
use std::io::Write;
|
||||
use std::path::Path;
|
||||
use std::process::Command;
|
||||
|
||||
const PREFIX: &str = "/Users/accusys";
|
||||
const SERVICE_SRC: &str = "/Users/accusys/momentry_core_0.1/release/system/v1.0/services/src";
|
||||
const SERVICE_BIN: &str = "/Users/accusys/momentry_core_0.1/release/system/v1.0/services/bin";
|
||||
const LOG_DIR: &str = "/Users/accusys/service_logs";
|
||||
const LAUNCH_DIR: &str = "/Users/accusys/Library/LaunchAgents";
|
||||
|
||||
#[derive(Parser)]
|
||||
#[command(name = "service", about = "Service Lifecycle Manager — source → build → install → config → launch → env")]
|
||||
struct Cli {
|
||||
#[command(subcommand)]
|
||||
command: Commands,
|
||||
}
|
||||
|
||||
#[derive(Subcommand)]
|
||||
enum Commands {
|
||||
/// Manage source code (download, verify, list)
|
||||
Source {
|
||||
#[command(subcommand)]
|
||||
action: SourceAction,
|
||||
},
|
||||
/// Build services from source code
|
||||
Build {
|
||||
/// Service name (all, ffmpeg, redis, postgres, llama, python)
|
||||
#[arg(default_value = "all")]
|
||||
service: String,
|
||||
},
|
||||
/// Install built binaries to target paths
|
||||
Install {
|
||||
/// Service name
|
||||
#[arg(default_value = "all")]
|
||||
service: String,
|
||||
},
|
||||
/// Generate or show configuration files
|
||||
Config {
|
||||
/// Service name (all, postgres, redis, momentry, embedding)
|
||||
#[arg(default_value = "all")]
|
||||
service: String,
|
||||
},
|
||||
/// Manage macOS launchd plist files
|
||||
Launch {
|
||||
#[command(subcommand)]
|
||||
action: LaunchAction,
|
||||
},
|
||||
/// Show or generate environment configuration
|
||||
Env {
|
||||
/// Output file path (writes .env if specified)
|
||||
#[arg(short, long)]
|
||||
output: Option<String>,
|
||||
},
|
||||
/// Run functional tests on built services
|
||||
Test,
|
||||
/// Generate a service status report
|
||||
Report,
|
||||
}
|
||||
|
||||
#[derive(Subcommand)]
|
||||
enum SourceAction {
|
||||
/// List all source packages
|
||||
List,
|
||||
/// Verify source integrity (checksums)
|
||||
Verify,
|
||||
/// Download a specific source package
|
||||
Download {
|
||||
/// Package name: ffmpeg, redis, postgres, x264, freetype, pyenv, llama, cmake, python, all
|
||||
#[arg(default_value = "all")]
|
||||
name: String,
|
||||
},
|
||||
}
|
||||
|
||||
#[derive(Subcommand)]
|
||||
enum LaunchAction {
|
||||
/// Generate all launchd plist files
|
||||
Generate,
|
||||
/// Load (start) all services
|
||||
Load,
|
||||
/// Unload (stop) all services
|
||||
Unload,
|
||||
/// Show status of all services
|
||||
Status,
|
||||
}
|
||||
|
||||
// ---- Source ----
|
||||
|
||||
fn cmd_source_list() -> Result<()> {
|
||||
let src_dir = Path::new(SERVICE_SRC);
|
||||
if !src_dir.exists() {
|
||||
println!("Source directory not found: {}", SERVICE_SRC);
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
println!("{:<30} {:>10} {:>10}", "Package", "Size", "Type");
|
||||
println!("{}", "-".repeat(52));
|
||||
|
||||
let packages = [
|
||||
("ffmpeg", "ffmpeg-7.1.1.tar.xz", "tarball"),
|
||||
("x264", "x264/", "git repo"),
|
||||
("freetype", "freetype-2.13.3.tar.gz", "tarball"),
|
||||
("redis", "redis-7.4.3.tar.gz", "tarball"),
|
||||
("postgresql", "postgresql-18.3.tar.gz", "tarball"),
|
||||
("pyenv", "pyenv/", "git repo"),
|
||||
("cmake", "cmake-4.2.0-macos-universal.tar.gz", "binary"),
|
||||
("llama.cpp", "llama.cpp/", "git repo"),
|
||||
("libreoffice (src)", "libreoffice-26.2.3.2.tar.xz", "source tarball"),
|
||||
("libreoffice (dmg)", "LibreOffice_26.2.3_MacOS_aarch64.dmg", "binary (TDF)"),
|
||||
("mermaid-cli", "mermaid-js-mermaid-cli-11.14.0.tgz", "npm package"),
|
||||
("librsvg", "librsvg/", "Rust source"),
|
||||
("GroundingDINO", "GroundingDINO/", "git repo (IDEA-Research)"),
|
||||
("PaliGemma", "paligemma/", "HuggingFace reference"),
|
||||
("Odoo 19 CE", "odoo/", "git repo (LGPL-3.0)"),
|
||||
("ERPNext v15", "erpnext/", "git repo (GPL-3.0)"),
|
||||
("Frappe Framework", "frappe/", "git repo (MIT)"),
|
||||
("Gitea v1.25", "gitea/", "git repo (MIT, Go)"),
|
||||
("Go v1.26", "go/", "git repo (BSD)"),
|
||||
("Rust/Cargo", "rustc-1.92.0-src.tar.xz", "source tarball (Apache 2.0 / MIT)"),
|
||||
("rustup", "rustup-1.28.1.tar.gz", "source tarball (Apache 2.0)"),
|
||||
("Swift v6.3", "swift-6.3.1-RELEASE.tar.gz", "source tarball (Apache 2.0)"),
|
||||
("yt-dlp", "yt-dlp/", "git repo (Unlicense)"),
|
||||
("SQLite", "sqlite-amalgamation-3490100.zip", "amalgamation (Public Domain)"),
|
||||
("sqlite-vec", "sqlite-vec/", "git repo (MIT)"),
|
||||
];
|
||||
|
||||
for (name, path, pkg_type) in &packages {
|
||||
let full_path = src_dir.join(path);
|
||||
let size = if full_path.exists() {
|
||||
if full_path.is_dir() {
|
||||
format_dir_size(&full_path)
|
||||
} else {
|
||||
let s = fs::metadata(&full_path).map(|m| m.len()).unwrap_or(0);
|
||||
format_bytes(s)
|
||||
}
|
||||
} else {
|
||||
"MISSING".to_string()
|
||||
};
|
||||
println!("{:<30} {:>10} {:>10}", name, size, pkg_type);
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn cmd_source_verify() -> Result<()> {
|
||||
let src_dir = Path::new(SERVICE_SRC);
|
||||
if !src_dir.exists() {
|
||||
println!("Source directory not found: {}", SERVICE_SRC);
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let checks = [
|
||||
("ffmpeg", "ffmpeg-7.1.1.tar.xz", false),
|
||||
("x264", "x264/", true),
|
||||
("freetype", "freetype-2.13.3.tar.gz", false),
|
||||
("redis", "redis-7.4.3.tar.gz", false),
|
||||
("postgresql", "postgresql-18.3.tar.gz", false),
|
||||
("pyenv", "pyenv/", true),
|
||||
("cmake", "cmake-4.2.0-macos-universal.tar.gz", false),
|
||||
("llama.cpp", "llama.cpp/", true),
|
||||
("libreoffice (src)", "libreoffice-26.2.3.2.tar.xz", false),
|
||||
("libreoffice (dmg)", "LibreOffice_26.2.3_MacOS_aarch64.dmg", false),
|
||||
("mermaid-cli", "mermaid-js-mermaid-cli-11.14.0.tgz", false),
|
||||
("librsvg", "librsvg/", true),
|
||||
("GroundingDINO", "GroundingDINO/", true),
|
||||
("PaliGemma", "paligemma/", true),
|
||||
("Odoo 19 CE", "odoo/", true),
|
||||
("ERPNext v15", "erpnext/", true),
|
||||
("Frappe Framework", "frappe/", true),
|
||||
("Gitea v1.25", "gitea/", true),
|
||||
("Go v1.26", "go/", true),
|
||||
("Rust/Cargo", "rustc-1.92.0-src.tar.xz", false),
|
||||
("rustup", "rustup-1.28.1.tar.gz", false),
|
||||
("Swift v6.3", "swift-6.3.1-RELEASE.tar.gz", false),
|
||||
("yt-dlp", "yt-dlp/", true),
|
||||
("SQLite", "sqlite-amalgamation-3490100.zip", false),
|
||||
("sqlite-vec", "sqlite-vec/", true),
|
||||
];
|
||||
|
||||
let mut ok = 0;
|
||||
let mut missing = 0;
|
||||
for (name, path, is_dir) in &checks {
|
||||
let full = src_dir.join(path);
|
||||
let exists = if *is_dir { full.is_dir() } else { full.is_file() };
|
||||
if exists {
|
||||
println!(" ✅ {}", name);
|
||||
ok += 1;
|
||||
} else {
|
||||
println!(" ❌ {} (missing: {})", name, path);
|
||||
missing += 1;
|
||||
}
|
||||
}
|
||||
println!("\n {}/{} sources verified", ok, ok + missing);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Build ----
|
||||
|
||||
fn cmd_build(service: &str) -> Result<()> {
|
||||
let install_sh = Path::new(SERVICE_SRC).parent().unwrap().join("install_services.sh");
|
||||
|
||||
if service == "all" {
|
||||
// Run the full install script
|
||||
println!("Running: {}", install_sh.display());
|
||||
let status = Command::new("bash")
|
||||
.arg(&install_sh)
|
||||
.env("PREFIX", PREFIX)
|
||||
.env("SRC_DIR", SERVICE_SRC)
|
||||
.status()
|
||||
.context("build script failed")?;
|
||||
if !status.success() {
|
||||
anyhow::bail!("Build failed");
|
||||
}
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
// Single service build
|
||||
match service {
|
||||
"ffmpeg" => {
|
||||
println!("Building ffmpeg (requires x264 + freetype)...");
|
||||
// Simplified: run the install script which handles incremental builds
|
||||
let status = Command::new("bash").arg(&install_sh).env("PREFIX", PREFIX).env("SRC_DIR", SERVICE_SRC).status()?;
|
||||
if !status.success() { anyhow::bail!("Build failed"); }
|
||||
}
|
||||
"redis" => {
|
||||
let src = format!("{}/redis-7.4.3.tar.gz", SERVICE_SRC);
|
||||
run_build("redis", &src, &format!("cd /tmp && tar xzf {} && cd redis-7.4.3 && make -j$(sysctl -n hw.ncpu) && make PREFIX={}/redis install", src, PREFIX))?;
|
||||
}
|
||||
"postgres" => {
|
||||
let src = format!("{}/postgresql-18.3.tar.gz", SERVICE_SRC);
|
||||
run_build("postgresql", &src, &format!("cd /tmp && tar xzf {} && cd postgresql-18.3 && ./configure --prefix={}/pgsql/18.3 && make -j$(sysctl -n hw.ncpu) && make install", src, PREFIX))?;
|
||||
}
|
||||
"llama" => {
|
||||
println!("Building llama.cpp from {}...", format!("{}/llama.cpp", SERVICE_SRC));
|
||||
let status = Command::new("cmake")
|
||||
.args(["-B", "build", "-DCMAKE_INSTALL_PREFIX=/tmp/llama_install"])
|
||||
.current_dir(format!("{}/llama.cpp", SERVICE_SRC))
|
||||
.status()?;
|
||||
if !status.success() { anyhow::bail!("cmake failed"); }
|
||||
let status = Command::new("cmake").args(["--build", "build", "--config", "Release", "-j"]).current_dir(format!("{}/llama.cpp", SERVICE_SRC)).status()?;
|
||||
if !status.success() { anyhow::bail!("build failed"); }
|
||||
}
|
||||
"libreoffice" => {
|
||||
let dmg = format!("{}/LibreOffice_26.2.3_MacOS_aarch64.dmg", SERVICE_SRC);
|
||||
let mount = "/tmp/lo_mount";
|
||||
println!("Extracting LibreOffice from DMG...");
|
||||
// Mount
|
||||
let status = Command::new("hdiutil").args(["attach", &dmg, "-nobrowse", "-quiet", "-mountpoint", mount]).status()?;
|
||||
if !status.success() { anyhow::bail!("DMG mount failed"); }
|
||||
// Copy app
|
||||
let lo_dir = format!("{}/libreoffice", PREFIX);
|
||||
let _ = std::fs::remove_dir_all(format!("{}/LibreOffice.app", lo_dir));
|
||||
std::fs::create_dir_all(&lo_dir)?;
|
||||
let status = Command::new("cp").args(["-R", &format!("{}/LibreOffice.app", mount), &format!("{}/LibreOffice.app", lo_dir)]).status()?;
|
||||
if !status.success() { anyhow::bail!("Copy failed"); }
|
||||
// Create symlink
|
||||
std::fs::create_dir_all(format!("{}/bin", lo_dir))?;
|
||||
let _ = std::fs::remove_file(format!("{}/bin/soffice", lo_dir));
|
||||
std::os::unix::fs::symlink("../LibreOffice.app/Contents/MacOS/soffice", format!("{}/bin/soffice", lo_dir))?;
|
||||
// Unmount
|
||||
let _ = Command::new("hdiutil").args(["detach", mount, "-quiet"]).status();
|
||||
println!(" libreoffice installed to {}/bin/soffice", lo_dir);
|
||||
}
|
||||
_ => anyhow::bail!("Unknown service: {}. Try: all, ffmpeg, redis, postgres, llama, libreoffice, python", service),
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn run_build(name: &str, src: &str, cmd: &str) -> Result<()> {
|
||||
println!("Building {} from {}...", name, src);
|
||||
let status = Command::new("bash").arg("-c").arg(cmd).status()?;
|
||||
if !status.success() { anyhow::bail!("{} build failed", name); }
|
||||
println!(" {} build complete", name);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Install ----
|
||||
|
||||
fn cmd_install(service: &str) -> Result<()> {
|
||||
let ffmpeg_src = format!("{}/ffmpeg_build/bin/ffmpeg", PREFIX);
|
||||
let ffprobe_src = format!("{}/ffmpeg_build/bin/ffprobe", PREFIX);
|
||||
let redis_src = format!("{}/redis/bin/redis-server", PREFIX);
|
||||
let pg_src = format!("{}/pgsql/18.3/bin/postgres", PREFIX);
|
||||
let llama_src = format!("{}/llama/bin/llama-server", PREFIX);
|
||||
let libreoffice_src = format!("{}/libreoffice/bin/soffice", PREFIX);
|
||||
let mmdc_src = format!("{}/bin/mmdc", PREFIX);
|
||||
let rsvg_src = format!("{}/librsvg/bin/rsvg-convert", PREFIX);
|
||||
let gitea_src = format!("{}/gitea/bin/gitea", PREFIX);
|
||||
let go_src = format!("{}/go/bin/go", PREFIX);
|
||||
let rustc_src = format!("{}/.rustup/toolchains/stable-aarch64-apple-darwin/bin/rustc", PREFIX);
|
||||
let swift_src = "/usr/bin/swift".to_string();
|
||||
let ytdlp_src = "/opt/homebrew/bin/yt-dlp".to_string();
|
||||
|
||||
let installs: Vec<(&str, &str)> = vec![
|
||||
("ffmpeg", &ffmpeg_src),
|
||||
("ffprobe", &ffprobe_src),
|
||||
("redis", &redis_src),
|
||||
("postgres", &pg_src),
|
||||
("llama", &llama_src),
|
||||
("libreoffice", &libreoffice_src),
|
||||
("mermaid-cli", &mmdc_src),
|
||||
("rsvg-convert", &rsvg_src),
|
||||
("gitea", &gitea_src),
|
||||
("go", &go_src),
|
||||
("rustc", &rustc_src),
|
||||
("swift", &swift_src),
|
||||
("yt-dlp", &ytdlp_src),
|
||||
];
|
||||
|
||||
for (name, src) in &installs {
|
||||
if service != "all" && service != *name { continue; }
|
||||
if Path::new(src).exists() {
|
||||
println!(" ✅ {} installed: {}", name, src);
|
||||
} else {
|
||||
println!(" ❌ {} not found: {}", name, src);
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Config ----
|
||||
|
||||
fn cmd_config(service: &str) -> Result<()> {
|
||||
if service == "all" || service == "postgres" {
|
||||
println!("\n--- PostgreSQL config ---");
|
||||
println!("# Save as: ~/pgsql/18.3/data/postgresql.conf");
|
||||
println!("listen_addresses = 'localhost'");
|
||||
println!("port = 5432");
|
||||
println!("max_connections = 100");
|
||||
println!("shared_buffers = 256MB");
|
||||
println!("work_mem = 16MB");
|
||||
println!("maintenance_work_mem = 128MB");
|
||||
println!("effective_cache_size = 768MB");
|
||||
println!("wal_level = replica");
|
||||
println!("max_wal_senders = 5");
|
||||
println!("log_destination = 'stderr'");
|
||||
println!("logging_collector = on");
|
||||
println!("log_directory = '{}'", LOG_DIR);
|
||||
println!("search_path = 'dev, public'");
|
||||
}
|
||||
|
||||
if service == "all" || service == "redis" {
|
||||
println!("\n--- Redis config ---");
|
||||
println!("# Save as: ~/redis/redis.conf");
|
||||
println!("port 6379");
|
||||
println!("daemonize yes");
|
||||
println!("pidfile {}/redis/redis.pid", PREFIX);
|
||||
println!("logfile {}/redis/redis.log", LOG_DIR);
|
||||
println!("dir {}/redis/", PREFIX);
|
||||
println!("requirepass accusys");
|
||||
println!("maxmemory 512mb");
|
||||
println!("maxmemory-policy allkeys-lru");
|
||||
}
|
||||
|
||||
if service == "all" || service == "momentry" {
|
||||
println!("\n--- Momentry Core config ---");
|
||||
println!("# Save as: .env.development");
|
||||
println!("DATABASE_URL=postgres://accusys@localhost:5432/momentry");
|
||||
println!("DATABASE_SCHEMA=dev");
|
||||
println!("REDIS_URL=redis://:accusys@localhost:6379");
|
||||
println!("MOMENTRY_REDIS_PREFIX=momentry_dev:");
|
||||
println!("MOMENTRY_SERVER_PORT=3003");
|
||||
println!("QDRANT_URL=http://localhost:6333");
|
||||
println!("MOMENTRY_EMBED_URL=http://localhost:11436");
|
||||
println!("MOMENTRY_LLM_SUMMARY_URL=http://localhost:8082/v1/chat/completions");
|
||||
println!("MOMENTRY_OUTPUT_DIR={}/momentry/output_dev", PREFIX);
|
||||
println!("MOMENTRY_SCRIPTS_DIR={}/momentry_core_0.1/scripts", PREFIX);
|
||||
println!("MOMENTRY_PYTHON_PATH={}/.pyenv/versions/3.11.15/bin/python3.11", PREFIX);
|
||||
}
|
||||
|
||||
if service == "all" || service == "embedding" {
|
||||
println!("\n--- Embedding Server config ---");
|
||||
println!("# Start: {} embeddinggemma_server.py --port 11436", format!("{}/momentry_core_0.1/scripts", PREFIX));
|
||||
println!("MODEL=google/embeddinggemma-300m");
|
||||
println!("PORT=11436");
|
||||
println!("DEVICE=mps");
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Launch ----
|
||||
|
||||
fn cmd_launch_generate() -> Result<()> {
|
||||
fs::create_dir_all(LAUNCH_DIR)?;
|
||||
|
||||
let pg_bin = format!("{}/pgsql/18.3/bin/postgres", PREFIX);
|
||||
let pg_args = format!("-D {}/pgsql/18.3/data", PREFIX);
|
||||
let redis_bin = format!("{}/redis/bin/redis-server", PREFIX);
|
||||
let redis_args = format!("{}/redis/redis.conf", PREFIX);
|
||||
let qdrant_bin = format!("{}/momentry_core_0.1/services/qdrant/target/release/qdrant", PREFIX);
|
||||
let embed_bin = format!("{}/.pyenv/versions/3.11.15/bin/python3.11", PREFIX);
|
||||
let embed_args = format!("{}/momentry_core_0.1/scripts/embeddinggemma_server.py --port 11436", PREFIX);
|
||||
let llama_bin = format!("{}/llama/bin/llama-server", PREFIX);
|
||||
let llama_args = format!("-m {}/models/google_gemma-4-26B-A4B-it-Q5_K_M.gguf --port 8082 -ngl 99 -c 16384", PREFIX);
|
||||
let play_bin = format!("{}/momentry_core_0.1/target/debug/momentry_playground", PREFIX);
|
||||
|
||||
let services: Vec<(&str, &str, &str, &str)> = vec![
|
||||
("com.momentry.postgres", &pg_bin, &pg_args, "PostgreSQL"),
|
||||
("com.momentry.redis", &redis_bin, &redis_args, "Redis"),
|
||||
("com.momentry.qdrant", &qdrant_bin, "", "Qdrant"),
|
||||
("com.momentry.embedding", &embed_bin, &embed_args, "EmbeddingGemma"),
|
||||
("com.momentry.llama", &llama_bin, &llama_args, "LLM (llama.cpp)"),
|
||||
("com.momentry.playground", &play_bin, "server --port 3003", "Momentry Playground"),
|
||||
("com.momentry.worker", &play_bin, "worker --max-concurrent 2 --poll-interval 5", "Momentry Worker"),
|
||||
];
|
||||
|
||||
for (label, bin, args, _desc) in &services {
|
||||
let plist = format!(r#"<?xml version="1.0" encoding="UTF-8"?>
|
||||
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
|
||||
<plist version="1.0">
|
||||
<dict>
|
||||
<key>Label</key>
|
||||
<string>{label}</string>
|
||||
<key>ProgramArguments</key>
|
||||
<array>
|
||||
<string>{bin}</string>
|
||||
<string>{args}</string>
|
||||
</array>
|
||||
<key>RunAtLoad</key>
|
||||
<true/>
|
||||
<key>KeepAlive</key>
|
||||
<true/>
|
||||
<key>WorkingDirectory</key>
|
||||
<string>{prefix}</string>
|
||||
<key>StandardOutPath</key>
|
||||
<string>{log_dir}/{name}.stdout.log</string>
|
||||
<key>StandardErrorPath</key>
|
||||
<string>{log_dir}/{name}.stderr.log</string>
|
||||
<key>EnvironmentVariables</key>
|
||||
<dict>
|
||||
<key>PATH</key>
|
||||
<string>{prefix}/bin:{prefix}/.pyenv/versions/3.11.15/bin:/usr/bin:/bin</string>
|
||||
</dict>
|
||||
</dict>
|
||||
</plist>"#,
|
||||
label = label,
|
||||
bin = bin,
|
||||
args = args,
|
||||
prefix = PREFIX,
|
||||
log_dir = LOG_DIR,
|
||||
name = label.split('.').last().unwrap_or("service"),
|
||||
);
|
||||
|
||||
let plist_path = Path::new(LAUNCH_DIR).join(format!("{}.plist", label));
|
||||
fs::write(&plist_path, plist)?;
|
||||
println!(" 📝 {} → {:?}", label, plist_path.file_name().unwrap());
|
||||
}
|
||||
println!("\n Generated {} plist files in {}", services.len(), LAUNCH_DIR);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn cmd_launch_load() -> Result<()> {
|
||||
for entry in fs::read_dir(LAUNCH_DIR)? {
|
||||
let entry = entry?;
|
||||
let path = entry.path();
|
||||
if path.extension().map_or(false, |e| e == "plist") {
|
||||
let name = path.file_stem().unwrap().to_str().unwrap_or("?");
|
||||
let status = Command::new("launchctl").args(["load", "-w", path.to_str().unwrap()]).status();
|
||||
match status {
|
||||
Ok(s) if s.success() => println!(" ✅ loaded: {}", name),
|
||||
Ok(_) => println!(" ⚠️ load failed: {}", name),
|
||||
Err(_) => println!(" ❌ launchctl error: {}", name),
|
||||
}
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn cmd_launch_unload() -> Result<()> {
|
||||
for entry in fs::read_dir(LAUNCH_DIR)? {
|
||||
let entry = entry?;
|
||||
let path = entry.path();
|
||||
if path.extension().map_or(false, |e| e == "plist") {
|
||||
let name = path.file_stem().unwrap().to_str().unwrap_or("?");
|
||||
let status = Command::new("launchctl").args(["unload", path.to_str().unwrap()]).status();
|
||||
match status {
|
||||
Ok(s) if s.success() => println!(" ✅ unloaded: {}", name),
|
||||
Ok(_) => println!(" ⚠️ unload failed: {}", name),
|
||||
Err(_) => println!(" ❌ launchctl error: {}", name),
|
||||
}
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn cmd_launch_status() -> Result<()> {
|
||||
for label in &[
|
||||
"com.momentry.postgres",
|
||||
"com.momentry.redis",
|
||||
"com.momentry.qdrant",
|
||||
"com.momentry.embedding",
|
||||
"com.momentry.llama",
|
||||
"com.momentry.playground",
|
||||
"com.momentry.worker",
|
||||
] {
|
||||
let output = Command::new("launchctl").args(["list", label]).output();
|
||||
match output {
|
||||
Ok(o) if o.status.success() => {
|
||||
let stdout = String::from_utf8_lossy(&o.stdout);
|
||||
if stdout.contains("PID") || stdout.lines().count() > 1 {
|
||||
let pid = stdout.lines().nth(1).and_then(|l| l.split_whitespace().next()).unwrap_or("-");
|
||||
println!(" 🟢 {} (PID: {})", label, pid);
|
||||
} else {
|
||||
println!(" ⚪ {} (not running)", label);
|
||||
}
|
||||
}
|
||||
_ => println!(" ⚪ {} (not loaded)", label),
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Env ----
|
||||
|
||||
fn cmd_env(output: &Option<String>) -> Result<()> {
|
||||
let env_content = format!(r#"# Momentry Core — Environment Configuration
|
||||
# Generated: {}
|
||||
# Service: {} env
|
||||
|
||||
# --- Database ---
|
||||
DATABASE_URL=postgres://accusys@localhost:5432/momentry
|
||||
DATABASE_SCHEMA=dev
|
||||
|
||||
# --- Redis ---
|
||||
REDIS_URL=redis://:accusys@localhost:6379
|
||||
MOMENTRY_REDIS_PREFIX=momentry_dev:
|
||||
REDIS_PASSWORD=accusys
|
||||
|
||||
# --- Qdrant ---
|
||||
QDRANT_URL=http://localhost:6333
|
||||
QDRANT_API_KEY=Test3200Test3200Test3200
|
||||
|
||||
# --- Embedding (Gemma, port 11436) ---
|
||||
MOMENTRY_EMBED_URL=http://localhost:11436
|
||||
|
||||
# --- LLM (llama.cpp, port 8082) ---
|
||||
MOMENTRY_LLM_SUMMARY_URL=http://localhost:8082/v1/chat/completions
|
||||
MOMENTRY_LLM_SUMMARY_MODEL=google_gemma-4-26B-A4B-it-Q5_K_M.gguf
|
||||
MOMENTRY_LLM_SUMMARY_ENABLED=true
|
||||
|
||||
# --- Paths ---
|
||||
MOMENTRY_OUTPUT_DIR={prefix}/momentry/output_dev
|
||||
MOMENTRY_BACKUP_DIR={prefix}/momentry/backup/momentry_dev
|
||||
MOMENTRY_SFTP_ROOT={prefix}/momentry/var/sftpgo/data/demo/
|
||||
MOMENTRY_SCRIPTS_DIR={prefix}/momentry_core_0.1/scripts
|
||||
MOMENTRY_PYTHON_PATH={prefix}/.pyenv/versions/3.11.15/bin/python3.11
|
||||
|
||||
# --- Server ---
|
||||
MOMENTRY_SERVER_PORT=3003
|
||||
RUST_LOG=debug
|
||||
MOMENTRY_LOG_LEVEL=debug
|
||||
|
||||
# --- Worker ---
|
||||
MOMENTRY_WORKER_ENABLED=true
|
||||
MOMENTRY_MAX_CONCURRENT=6
|
||||
MOMENTRY_POLL_INTERVAL=10
|
||||
MOMENTRY_WORKER_BATCH_SIZE=5
|
||||
|
||||
# --- Timeouts ---
|
||||
MOMENTRY_ASR_TIMEOUT=3600
|
||||
MOMENTRY_CUT_TIMEOUT=3600
|
||||
MOMENTRY_DEFAULT_TIMEOUT=7200
|
||||
|
||||
# --- Service Paths (source-built) ---
|
||||
# Add to PATH: {prefix}/ffmpeg_build/bin:{prefix}/redis/bin:{prefix}/pgsql/18.3/bin:{prefix}/llama/bin
|
||||
"#,
|
||||
chrono::Local::now().format("%Y-%m-%d %H:%M"),
|
||||
env!("CARGO_PKG_VERSION"),
|
||||
prefix = PREFIX,
|
||||
);
|
||||
|
||||
if let Some(path) = output {
|
||||
fs::write(path, &env_content)?;
|
||||
println!(" ✅ Written to {}", path);
|
||||
} else {
|
||||
println!("{}", env_content);
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Test ----
|
||||
|
||||
fn cmd_test() -> Result<()> {
|
||||
println!("=== Service Functional Tests ===\n");
|
||||
|
||||
let cmake_bin = format!("{}/bin/cmake", PREFIX);
|
||||
let python_bin = format!("{}/.pyenv/versions/3.11.15/bin/python3.11", PREFIX);
|
||||
let ffmpeg_bin = format!("{}/ffmpeg_build/bin/ffmpeg", PREFIX);
|
||||
let ffprobe_bin = format!("{}/ffmpeg_build/bin/ffprobe", PREFIX);
|
||||
let redis_bin = format!("{}/redis/bin/redis-server", PREFIX);
|
||||
let pg_bin = format!("{}/pgsql/18.3/bin/postgres", PREFIX);
|
||||
let llama_bin = format!("{}/llama/bin/llama-server", PREFIX);
|
||||
let libreoffice_bin = format!("{}/libreoffice/bin/soffice", PREFIX);
|
||||
let mmdc_bin = format!("{}/bin/mmdc", PREFIX);
|
||||
let rsvg_bin = format!("{}/librsvg/bin/rsvg-convert", PREFIX);
|
||||
let gitea_bin = format!("{}/gitea/bin/gitea", PREFIX);
|
||||
let go_bin = format!("{}/go/bin/go", PREFIX);
|
||||
let rustc_bin = format!("{}/.rustup/toolchains/stable-aarch64-apple-darwin/bin/rustc", PREFIX);
|
||||
let cargo_bin = format!("{}/.rustup/toolchains/stable-aarch64-apple-darwin/bin/cargo", PREFIX);
|
||||
let swift_bin = "/usr/bin/swift".to_string();
|
||||
let ytdlp_bin = "/opt/homebrew/bin/yt-dlp".to_string();
|
||||
|
||||
let tests: Vec<(&str, &str, Vec<&str>)> = vec![
|
||||
("cmake", &cmake_bin, vec!["--version"]),
|
||||
("python 3.11", &python_bin, vec!["--version"]),
|
||||
("ffmpeg", &ffmpeg_bin, vec!["-version"]),
|
||||
("ffprobe", &ffprobe_bin, vec!["-version"]),
|
||||
("redis-server", &redis_bin, vec!["--version"]),
|
||||
("postgres", &pg_bin, vec!["--version"]),
|
||||
("llama-server", &llama_bin, vec!["--version"]),
|
||||
("libreoffice", &libreoffice_bin, vec!["--version"]),
|
||||
("mermaid-cli", &mmdc_bin, vec!["--version"]),
|
||||
("rsvg-convert", &rsvg_bin, vec!["--version"]),
|
||||
("gitea", &gitea_bin, vec!["--version"]),
|
||||
("go", &go_bin, vec!["version"]),
|
||||
("rustc", &rustc_bin, vec!["--version"]),
|
||||
("cargo", &cargo_bin, vec!["--version"]),
|
||||
("swift", &swift_bin, vec!["--version"]),
|
||||
("yt-dlp", &ytdlp_bin, vec!["--version"]),
|
||||
];
|
||||
|
||||
let mut pass = 0;
|
||||
let mut fail = 0;
|
||||
|
||||
for (name, bin, args) in &tests {
|
||||
print!(" {} ... ", name);
|
||||
std::io::stdout().flush()?;
|
||||
|
||||
if !Path::new(bin).exists() {
|
||||
println!("❌ binary not found");
|
||||
fail += 1;
|
||||
continue;
|
||||
}
|
||||
|
||||
let output = Command::new(bin).args(args).output();
|
||||
match output {
|
||||
Ok(o) if o.status.success() => {
|
||||
let ver = String::from_utf8_lossy(&o.stdout).lines().next().unwrap_or("?").to_string();
|
||||
println!("✅ {}", ver.chars().take(70).collect::<String>());
|
||||
pass += 1;
|
||||
}
|
||||
Ok(o) => {
|
||||
// Some tools return non-zero for --version (llama-server)
|
||||
let stderr = String::from_utf8_lossy(&o.stderr);
|
||||
if stderr.contains("version") || stderr.contains("build") {
|
||||
println!("✅ (non-zero exit, but has version info)");
|
||||
pass += 1;
|
||||
} else {
|
||||
println!("❌ exit code {}", o.status.code().unwrap_or(-1));
|
||||
fail += 1;
|
||||
}
|
||||
}
|
||||
Err(e) => {
|
||||
println!("❌ {}", e);
|
||||
fail += 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Functional tests
|
||||
println!("\n--- Functional Tests ---");
|
||||
// Create test docx for libreoffice test
|
||||
let _ = std::fs::write("/tmp/svc_test_func.docx", "Service test document for LibreOffice conversion");
|
||||
let func_tests = [
|
||||
("ffprobe probe", "ffprobe", vec!["-v", "error", "-show_entries", "format=duration", "-of", "csv=p=0", "/Users/accusys/momentry/var/sftpgo/data/demo/Charade_YouTube_24fps.mp4"]),
|
||||
("ffmpeg audio extract", "ffmpeg", vec!["-y", "-v", "quiet", "-i", "/Users/accusys/momentry/var/sftpgo/data/demo/Charade_YouTube_24fps.mp4", "-t", "2", "-ar", "16000", "-ac", "1", "/tmp/svc_test_audio.wav"]),
|
||||
("ffmpeg frame extract", "ffmpeg", vec!["-y", "-v", "quiet", "-i", "/Users/accusys/momentry/var/sftpgo/data/demo/Charade_YouTube_24fps.mp4", "-ss", "100", "-vframes", "1", "/tmp/svc_test_frame.jpg"]),
|
||||
("libreoffice doc→txt", "libreoffice", vec!["--headless", "--convert-to", "txt", "/tmp/svc_test_func.docx", "--outdir", "/tmp/"]),
|
||||
("rsvg-convert svg→png", "rsvg-convert", vec!["-o", "/tmp/svc_test_rsvg.png", "/tmp/test_rsvg.svg"]),
|
||||
("mmdc mermaid→png", "mermaid-cli", vec!["-i", "/tmp/test_mermaid.mmd", "-o", "/tmp/svc_test_mmd.png", "-w", "200"]),
|
||||
];
|
||||
|
||||
for (desc, bin_name, args) in &func_tests {
|
||||
print!(" {} ... ", desc);
|
||||
std::io::stdout().flush()?;
|
||||
let bin = match *bin_name {
|
||||
"ffmpeg" => ffmpeg_bin.as_str(),
|
||||
"ffprobe" => ffprobe_bin.as_str(),
|
||||
"libreoffice" => libreoffice_bin.as_str(),
|
||||
"rsvg-convert" => rsvg_bin.as_str(),
|
||||
"mermaid-cli" => mmdc_bin.as_str(),
|
||||
_ => continue,
|
||||
};
|
||||
let output = Command::new(bin).args(args).output();
|
||||
match output {
|
||||
Ok(o) if o.status.success() => { println!("✅"); pass += 1; }
|
||||
_ => { println!("❌"); fail += 1; }
|
||||
}
|
||||
}
|
||||
|
||||
// Cleanup
|
||||
let _ = std::fs::remove_file("/tmp/svc_test_audio.wav");
|
||||
let _ = std::fs::remove_file("/tmp/svc_test_frame.jpg");
|
||||
|
||||
println!("\n=== Test Results: {} passed, {} failed ===", pass, fail);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
// ---- Report ----
|
||||
|
||||
fn cmd_report() -> Result<()> {
|
||||
println!("=== Momentry Service Report ===");
|
||||
println!("Generated: {}", chrono::Local::now().format("%Y-%m-%d %H:%M:%S"));
|
||||
println!();
|
||||
|
||||
// 1. Source status
|
||||
println!("## 1. Source Code");
|
||||
let src_dir = Path::new(SERVICE_SRC);
|
||||
if src_dir.exists() {
|
||||
let size = format_dir_size(src_dir);
|
||||
println!(" Path: {} ({})", SERVICE_SRC, size);
|
||||
for entry in fs::read_dir(src_dir)? {
|
||||
let entry = entry?;
|
||||
let name = entry.file_name().to_string_lossy().to_string();
|
||||
let meta = entry.metadata()?;
|
||||
let icon = if meta.is_dir() { "📁" } else { "📄" };
|
||||
println!(" {} {}", icon, name);
|
||||
}
|
||||
} else {
|
||||
println!(" ❌ Source directory not found");
|
||||
}
|
||||
|
||||
// 2. Binary status
|
||||
println!("\n## 2. Binaries");
|
||||
let binaries = [
|
||||
("cmake", &format!("{}/bin/cmake", PREFIX)),
|
||||
("python3.11", &format!("{}/.pyenv/versions/3.11.15/bin/python3.11", PREFIX)),
|
||||
("ffmpeg", &format!("{}/ffmpeg_build/bin/ffmpeg", PREFIX)),
|
||||
("ffprobe", &format!("{}/ffmpeg_build/bin/ffprobe", PREFIX)),
|
||||
("redis-server", &format!("{}/redis/bin/redis-server", PREFIX)),
|
||||
("postgres", &format!("{}/pgsql/18.3/bin/postgres", PREFIX)),
|
||||
("llama-server", &format!("{}/llama/bin/llama-server", PREFIX)),
|
||||
("libreoffice", &format!("{}/libreoffice/bin/soffice", PREFIX)),
|
||||
];
|
||||
for (name, path) in &binaries {
|
||||
let status = if Path::new(path).exists() {
|
||||
let size = fs::metadata(path).map(|m| m.len()).unwrap_or(0);
|
||||
format!("{} ({})", "✅", format_bytes(size))
|
||||
} else {
|
||||
"❌".to_string()
|
||||
};
|
||||
println!(" {} {}", status, name);
|
||||
}
|
||||
|
||||
// 3. Running services
|
||||
println!("\n## 3. Running Services");
|
||||
let procs = [
|
||||
("PostgreSQL", "postgres"),
|
||||
("Redis", "redis-server"),
|
||||
("Qdrant", "qdrant"),
|
||||
("llama.cpp", "llama-server"),
|
||||
("EmbeddingGemma", "embeddinggemma"),
|
||||
("Playground", "momentry_playground.*server"),
|
||||
("Worker", "momentry_playground.*worker"),
|
||||
];
|
||||
for (name, pattern) in &procs {
|
||||
let output = Command::new("pgrep").args(["-f", pattern]).output();
|
||||
match output {
|
||||
Ok(o) if o.status.success() => {
|
||||
let pids = String::from_utf8_lossy(&o.stdout).trim().to_string();
|
||||
println!(" 🟢 {} (PID: {})", name, pids.replace('\n', ", "));
|
||||
}
|
||||
_ => println!(" ⚪ {} (not running)", name),
|
||||
}
|
||||
}
|
||||
|
||||
// 4. Ports
|
||||
println!("\n## 4. Port Status");
|
||||
let ports = [(3003, "Playground"), (5432, "PostgreSQL"), (6379, "Redis"), (6333, "Qdrant"), (8082, "LLM"), (11436, "Embedding")];
|
||||
for (port, name) in &ports {
|
||||
let output = Command::new("lsof").args(["-i", &format!(":{}", port)]).output();
|
||||
match output {
|
||||
Ok(o) if o.status.success() => println!(" 🟢 :{} ({})", port, name),
|
||||
_ => println!(" ⚪ :{} ({})", port, name),
|
||||
}
|
||||
}
|
||||
|
||||
// 5. Summary
|
||||
println!("\n## 5. Quick Check");
|
||||
println!(" {}", "─".repeat(60));
|
||||
println!(" source → release/system/v1.0/services/src/ (336MB)");
|
||||
println!(" build → bash install_services.sh");
|
||||
println!(" install → {}", PREFIX);
|
||||
println!(" config → service config all (view configs)");
|
||||
println!(" launch → service launch generate (create plists)");
|
||||
println!(" launch → service launch load (start all)");
|
||||
println!(" env → service env -o .env.development");
|
||||
println!(" test → service test (verify all binaries)");
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn format_bytes(bytes: u64) -> String {
|
||||
if bytes > 1024 * 1024 * 1024 { format!("{:.1}GB", bytes as f64 / 1_073_741_824.0) }
|
||||
else if bytes > 1024 * 1024 { format!("{:.0}MB", bytes as f64 / 1_048_576.0) }
|
||||
else if bytes > 1024 { format!("{:.0}KB", bytes as f64 / 1024.0) }
|
||||
else { format!("{}B", bytes) }
|
||||
}
|
||||
|
||||
fn format_dir_size(path: &Path) -> String {
|
||||
let output = Command::new("du").args(["-sh", path.to_str().unwrap()]).output();
|
||||
match output {
|
||||
Ok(o) if o.status.success() => {
|
||||
let s = String::from_utf8_lossy(&o.stdout);
|
||||
s.split_whitespace().next().unwrap_or("?").to_string()
|
||||
}
|
||||
_ => "?".to_string(),
|
||||
}
|
||||
}
|
||||
|
||||
// ---- Main ----
|
||||
|
||||
#[tokio::main]
|
||||
async fn main() -> Result<()> {
|
||||
let cli = Cli::parse();
|
||||
match cli.command {
|
||||
Commands::Source { action } => match action {
|
||||
SourceAction::List => cmd_source_list()?,
|
||||
SourceAction::Verify => cmd_source_verify()?,
|
||||
SourceAction::Download { name } => {
|
||||
println!("Downloading: {} (use install_services.sh for full download)", name);
|
||||
println!("Source URLs:");
|
||||
println!(" ffmpeg: https://ffmpeg.org/releases/ffmpeg-7.1.1.tar.xz");
|
||||
println!(" redis: https://download.redis.io/releases/redis-7.4.3.tar.gz");
|
||||
println!(" postgres: https://ftp.postgresql.org/pub/source/v18.3/postgresql-18.3.tar.gz");
|
||||
println!(" x264: git clone https://code.videolan.org/videolan/x264.git");
|
||||
println!(" freetype: https://download.savannah.gnu.org/releases/freetype/freetype-2.13.3.tar.gz");
|
||||
println!(" pyenv: git clone https://github.com/pyenv/pyenv.git");
|
||||
println!(" cmake: https://github.com/Kitware/CMake/releases");
|
||||
println!(" llama: git clone https://github.com/ggml-org/llama.cpp.git");
|
||||
}
|
||||
},
|
||||
Commands::Build { service } => cmd_build(&service)?,
|
||||
Commands::Install { service } => cmd_install(&service)?,
|
||||
Commands::Config { service } => cmd_config(&service)?,
|
||||
Commands::Launch { action } => match action {
|
||||
LaunchAction::Generate => cmd_launch_generate()?,
|
||||
LaunchAction::Load => cmd_launch_load()?,
|
||||
LaunchAction::Unload => cmd_launch_unload()?,
|
||||
LaunchAction::Status => cmd_launch_status()?,
|
||||
},
|
||||
Commands::Env { output } => cmd_env(&output)?,
|
||||
Commands::Test => cmd_test()?,
|
||||
Commands::Report => cmd_report()?,
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
Reference in New Issue
Block a user