diff --git a/Last3Mon/65/LAB-01-CONDITION-IN-MINIFLOW.md b/Last3Mon/65/LAB-01-CONDITION-IN-MINIFLOW.md
new file mode 100644
index 0000000..e2b8b24
--- /dev/null
+++ b/Last3Mon/65/LAB-01-CONDITION-IN-MINIFLOW.md
@@ -0,0 +1,82 @@
+# Lab 01 · Condition으로 "결과 없음" 경로 만들기
+
+- 관련 강의: [1단계 · Trigger·Condition·Action](../../Lecture/65/01-STAGE1-TRIGGER-CONDITION-ACTION.md)
+- 소요 시간: 약 40분
+- 목표: 64일차에 멈췄던 워크플로우를 Condition으로 고치고, Switch로 여러 갈래를 만든다.
+
+## 1. 어제 멈춘 장면 다시 보기 (5분)
+
+```bash
+cd ~/aio-01d4-stu/Last3Mon/65/workflow-lab
+uv sync
+uv run pytest -q
+uv run miniflow run flows/05-tech-support-ticket.json -i user=lee -i ticket="점심 메뉴 추천해줘"
+```
+
+FAQ 검색 결과가 없는데 다음 노드가 첫 번째 FAQ를 꺼내려다 멈춥니다. 오늘은 이 경우를 **다른 길(Action)** 로 보냅니다.
+
+## 2. Condition이 들어간 워크플로우 실행 (10분)
+
+```bash
+uv run miniflow show flows/06-request-with-condition.json
+uv run miniflow run flows/06-request-with-condition.json -i user=kim -i text="VPN 접속이 계속 끊겨요"
+uv run miniflow run flows/06-request-with-condition.json -i user=lee -i text="점심 메뉴 추천해줘"
+```
+
+```mermaid
+flowchart LR
+ start[/"start"/] --> classify{{"classify
llm"}}
+ start --> faq["faq
tool"]
+ faq --> has_faq{"has_faq
condition"}
+ classify --> has_faq
+ has_faq -->|true| draft{{"draft
llm"}} --> auto_reply[\"auto_reply"\]
+ has_faq -->|false| hand_off[\"hand_off"\]
+```
+
+확인할 것
+
+1. 두 실행에서 `has_faq` 노드의 출력(`branch`)은 각각 무엇인가요?
+2. 실행 기록에서 `skipped`로 표시된 노드는 어느 것인가요?
+3. 두 번째 실행의 `route` 값은 무엇인가요? 이제 워크플로우가 멈추지 않는 이유를 설명해 보세요.
+
+## 3. Switch로 담당 팀 배정 (10분)
+
+```bash
+uv run miniflow run flows/07-route-by-category.json -i text="비밀번호를 잊어버렸어요"
+uv run miniflow run flows/07-route-by-category.json -i text="회의실 예약은 어떻게 하나요"
+```
+
+- `route` 노드는 분류 결과가 `cases` 중 하나이면 그 길로, 아니면 `default` 길로 보냅니다.
+- LLM이 `Software`처럼 대문자로 답하거나 `software.`처럼 마침표를 붙이면 정해진 값과 달라 `default`로 갑니다. OpenAI 모델은 대부분 지시를 지키지만, 대체용 작은 모델(Ollama)에서는 자주 일어납니다. 이런 경우를 막으려면 어떤 노드가 필요할까요?
+
+## 4. 직접 만들기: 긴급 문의 분기 (15분)
+
+`flows/06-request-with-condition.json`을 복사해 `flows/my-06-urgent.json`을 만들고, 다음 조건을 추가합니다.
+
+- 문의에 "긴급"이라는 단어가 있으면 FAQ 검색과 상관없이 바로 담당자에게 연결합니다.
+
+힌트
+
+```json
+{"id": "is_urgent", "type": "condition", "check": {"left": "{{input.text}}", "op": "contains", "right": "긴급"}}
+```
+
+- `start → is_urgent` 연결을 추가합니다.
+- `is_urgent`의 `true` 길은 새 output 노드 `urgent_call`로 보냅니다.
+- `false` 길이 기존 흐름(`has_faq`)으로 이어지도록 `["is_urgent", "has_faq", "false"]`를 추가합니다.
+
+```bash
+uv run miniflow validate flows/my-06-urgent.json
+uv run miniflow run flows/my-06-urgent.json -i user=kim -i text="긴급! VPN이 끊겼어요"
+uv run miniflow run flows/my-06-urgent.json -i user=kim -i text="VPN이 끊겼어요"
+```
+
+## 5. 설계표 작성 (선택)
+
+[TCA 설계 템플릿](templates/TCA-DESIGN-TEMPLATE.md)을 `my-work/LAB-01-TCA.md`로 복사해, 64일차 Lab 03에서 분석한 시나리오를 Trigger·Condition·Action으로 다시 정리합니다.
+
+## 확인
+
+- [ ] `06` 워크플로우의 true·false 두 길을 모두 실행했다.
+- [ ] `07`에서 `default` 길이 선택되는 경우를 확인했다.
+- [ ] `my-06-urgent.json`이 `validate`와 두 입력의 실행을 통과했다.
diff --git a/Last3Mon/65/LAB-02-N8N-FIRST-WORKFLOWS.md b/Last3Mon/65/LAB-02-N8N-FIRST-WORKFLOWS.md
new file mode 100644
index 0000000..0a2018c
--- /dev/null
+++ b/Last3Mon/65/LAB-02-N8N-FIRST-WORKFLOWS.md
@@ -0,0 +1,102 @@
+# Lab 02 · n8n 화면 익히기와 첫 워크플로우
+
+- 관련 강의: [2단계 · n8n 실습 환경과 기본 설정](../../Lecture/65/02-STAGE2-N8N-ENVIRONMENT.md)
+- 소요 시간: 약 45분
+- 준비: [SETUP-N8N.md](SETUP-N8N.md) 완료, 브라우저에서 http://localhost:5678 로그인
+
+## 1. 워크플로우 가져오기 (5분)
+
+1. 왼쪽 위 **+ (Create)** → **Workflow**로 빈 워크플로우를 엽니다.
+2. 오른쪽 위 **⋯ (더보기)** → **Import from File...** 을 선택합니다.
+3. `Last3Mon/65/n8n/workflows/01-condition-basics.json`을 고릅니다. Windows 파일 선택 창에서는 주소창에 `\\wsl$\Ubuntu\home\<사용자>\aio-01d4-stu\Last3Mon\65\n8n\workflows`를 입력하면 WSL 폴더로 이동합니다.
+4. 오른쪽 위 **Save**를 누릅니다.
+
+같은 방법으로 `02-webhook-router.json`도 새 워크플로우로 가져와 둡니다.
+
+## 2. Manual Trigger + IF: `65-01 Condition basics` (15분)
+
+```mermaid
+flowchart LR
+ T(["Start
Manual Trigger"]) --> C["Sample requests
Code"] --> I{"Is urgent?
IF"}
+ I -->|true| U["Urgent route
Set"]
+ I -->|false| N["Normal route
Set"]
+```
+
+1. 아래쪽 **Execute workflow** 버튼을 누릅니다.
+2. 각 노드를 더블클릭해 **INPUT / OUTPUT** 데이터를 확인합니다.
+
+확인할 것
+
+| 질문 | 내 답 |
+| --- | --- |
+| `Sample requests`가 만든 항목(item)은 몇 개인가? | |
+| `Is urgent?`의 true 출력과 false 출력에는 각각 몇 개의 항목이 있는가? | |
+| `Urgent route` 출력에 새로 생긴 필드 두 개는? | |
+
+n8n은 항목(item) 여러 개를 한 번에 흘려보냅니다. IF 노드는 항목마다 조건을 검사해 두 출력으로 나눕니다.
+
+### 직접 바꿔 보기
+
+1. `Is urgent?` 노드를 열고 조건을 `{{ $json.text }}` **contains** `계정`으로 바꿔 다시 실행합니다. 결과가 어떻게 달라지나요?
+2. 원래 조건(`priority` equals `urgent`)으로 되돌립니다.
+
+## 3. Webhook Trigger + Switch: `65-02 Webhook request router` (20분)
+
+```mermaid
+flowchart LR
+ W(["Request webhook
POST /request-route"]) --> H{"Has text?
IF"}
+ H -->|false| R0["Reject empty
400"]
+ H -->|true| K["Keyword classify
Code"] --> S{"Route by category
Switch"}
+ S -->|account·network·device·software| T1["Team ...
Set"]
+ S -->|other| T5["Team other
Set"]
+ T1 --> R["Send route
Respond"]
+ T5 --> R
+```
+
+### 3-1. 테스트 실행 (Test URL)
+
+1. `Request webhook` 노드를 열고 **Test URL**을 복사합니다. (`http://localhost:5678/webhook-test/request-route`)
+2. 노드 화면의 **Listen for test event**를 누른 상태에서 WSL 터미널에서 요청을 보냅니다.
+
+```bash
+curl -s -X POST http://localhost:5678/webhook-test/request-route \
+ -H 'Content-Type: application/json' -d '{"user":"kim","text":"VPN 접속이 계속 끊겨요"}'
+```
+
+3. 캔버스에서 실제로 지나간 길이 초록색으로 표시되는지 확인합니다.
+
+### 3-2. 게시 후 실행 (Production URL)
+
+1. 오른쪽 위 **Publish**(게시)를 켭니다.
+2. 이제 `/webhook/`(test 없음) 주소로 언제든 호출할 수 있습니다.
+
+```bash
+for t in "VPN 접속이 계속 끊겨요" "모니터가 안 켜져요" "점심 메뉴 추천해줘" ""; do
+ curl -s -w " [HTTP %{http_code}]\n" -X POST http://localhost:5678/webhook/request-route \
+ -H 'Content-Type: application/json' -d "{\"user\":\"kim\",\"text\":\"$t\"}"
+done
+```
+
+3. 왼쪽 메뉴 **Executions**에서 방금 실행된 기록 4건을 열어 봅니다.
+
+| 입력 | 응답의 `team` 또는 오류 | 지나간 길 |
+| --- | --- | --- |
+| VPN 접속이 계속 끊겨요 | | |
+| 모니터가 안 켜져요 | | |
+| 점심 메뉴 추천해줘 | | |
+| (빈 문자열) | | |
+
+### 3-3. 직접 바꿔 보기
+
+`Keyword classify`의 규칙과 `Route by category`에 **"보안"** 분류를 추가해 보세요.
+
+- Code 노드 `rules`에 `{ category: 'security', words: ['해킹', '피싱', '바이러스'] }` 추가
+- Switch 노드에 `security` 규칙 추가, 새 Set 노드 `Team security`(team: `보안 담당`) 연결
+- 저장 후 `"피싱 메일을 받은 것 같아요"`로 호출해 확인
+
+## 확인
+
+- [ ] 두 워크플로우를 가져와 저장했다.
+- [ ] IF 노드의 true/false 출력 항목 수를 확인했다.
+- [ ] Test URL과 Production URL의 차이를 직접 실행해 보았다.
+- [ ] Executions에서 실행 기록을 열어 보았다.
diff --git a/Last3Mon/65/LAB-03-AI-WORKFLOW-FAILOVER.md b/Last3Mon/65/LAB-03-AI-WORKFLOW-FAILOVER.md
new file mode 100644
index 0000000..413ab91
--- /dev/null
+++ b/Last3Mon/65/LAB-03-AI-WORKFLOW-FAILOVER.md
@@ -0,0 +1,125 @@
+# Lab 03 · AI 문의 처리 워크플로우와 플랫폼 전환
+
+- 관련 강의: [3단계 · 샘플 AI 워크플로우와 실행 흐름](../../Lecture/65/03-STAGE3-SAMPLE-AI-WORKFLOW.md)
+- 소요 시간: 약 45분
+- 목표: LLM이 들어간 Trigger·Condition·Action 워크플로우를 실행하고, 같은 업무를 Python에서 플랫폼과 상관없이 호출한다.
+
+## 1. AI 문의 처리 워크플로우 가져오기 (10분)
+
+1. Lab 02와 같은 방법으로 `03-ai-request-flow.json`을 가져와 저장합니다.
+2. `Settings` 노드를 열어 값을 확인합니다.
+
+| 필드 | 값 | 바꿔야 하는 경우 |
+| --- | --- | --- |
+| `llm_url` | `https://api.openai.com/v1` | 대체: Ollama로 바꿀 때 `http://ollama:11434/v1` |
+| `model` | `gpt-4.1-mini` | 대체: Ollama로 바꿀 때 `gemma3:4b` |
+
+ `LLM classify`·`LLM draft reply` 노드의 Authentication이 **OpenAI → `OpenAI (.env)`** 인지 확인합니다 (SETUP 6단계에서 등록한 Credential).
+
+3. **Publish**를 켭니다.
+
+```mermaid
+flowchart LR
+ W(["AI request webhook
POST /ai-request"]) --> S["Settings
Set"] --> H{"Has text?"}
+ H -->|false| R0["Reject empty"]
+ H -->|true| L1{{"LLM classify
HTTP → OpenAI"}} --> N["Normalize and
search FAQ
Code"] --> F{"FAQ found?"}
+ F -->|true| L2{{"LLM draft reply
HTTP → OpenAI"}} --> A["Auto reply
Set"] --> R["Send result"]
+ F -->|false| P["Hand off to staff
Set"] --> R
+```
+
+## 2. 실행과 실행 기록 확인 (10분)
+
+```bash
+for t in "VPN 접속이 계속 끊겨요" "비밀번호를 잊어버려서 로그인이 안 돼요" "점심 메뉴 추천해줘"; do
+ curl -s -m 300 -w " [%{time_total}s]\n" -X POST http://localhost:5678/webhook/ai-request \
+ -H 'Content-Type: application/json' -d "{\"user\":\"kim\",\"text\":\"$t\"}"
+done
+```
+
+요청마다 3초 안팎 걸립니다 (OpenAI 호출 2회). "점심 메뉴"처럼 FAQ가 없는 문의는 LLM을 한 번만 불러 1초 안에 끝납니다.
+
+**Executions**에서 각 실행을 열고 다음을 확인합니다.
+
+| 확인할 것 | 어디서 |
+| --- | --- |
+| LLM이 돌려준 원래 분류값 | `Normalize and search FAQ` 출력의 `raw_label` |
+| 정리된 분류값 | 같은 출력의 `category` |
+| 어느 길로 갔나 | `FAQ found?` 노드의 true/false 출력 |
+| 가장 오래 걸린 노드 | 각 노드 오른쪽 위의 실행 시간 |
+
+## 3. Python에서 플랫폼과 상관없이 호출하기 (15분)
+
+같은 업무(`request`)를 n8n과 `miniflow` 두 플랫폼이 모두 처리할 수 있습니다. 호출하는 쪽은 업무 이름만 알고, 어느 플랫폼에서 실행할지는 설정이 정합니다.
+
+```bash
+cd ~/aio-01d4-stu/Last3Mon/65/workflow-lab
+# LLM 설정은 Last3Mon/.env (MINIFLOW_LLM=openai, gpt-4.1-mini)
+uv run miniflow call request -i user=kim -i text="VPN 접속이 계속 끊겨요"
+```
+
+```text
+Workflow: request platforms: n8n -> miniflow
+ n8n ok 2506.8ms
+Served by: n8n
+```
+
+### 장애 상황 만들기
+
+```bash
+cd ../n8n && docker compose stop n8n && cd ../workflow-lab
+uv run miniflow call request -i user=kim -i text="VPN 접속이 계속 끊겨요"
+```
+
+```text
+ n8n failed 11.7ms n8n is not reachable at http://localhost:5678/webhook/ai-request (...)
+ miniflow ok …ms
+Served by: miniflow
+```
+
+n8n이 멈춰도 `miniflow`가 같은 업무를 이어받습니다. 확인이 끝나면 n8n을 다시 켭니다.
+
+```bash
+cd ../n8n && docker compose start n8n && cd ../workflow-lab
+```
+
+### 순서 바꾸기
+
+```bash
+WORKFLOW_PLATFORMS=miniflow,n8n uv run miniflow call request -i user=kim -i text="프린터가 안 돼요"
+uv run miniflow call request --platforms n8n -i user=kim -i text="프린터가 안 돼요"
+```
+
+어떤 플랫폼을 먼저 쓸지 바꿀 때 코드를 고쳤나요? 설정(환경 변수·옵션)만 바꿨나요?
+
+### LLM도 바꿔 쓸 수 있게: OpenAI → Ollama 대체
+
+플랫폼(n8n → miniflow)과 마찬가지로 LLM에도 대체 경로가 있습니다. `Last3Mon/.env`의 `MINIFLOW_LLM_FALLBACK=ollama` 덕분에 OpenAI 호출이 실패하면 Ollama로 한 번 더 시도합니다. 잘못된 키를 **이 명령에서만** 넣어 실패를 만들어 봅니다 (`.env`는 고치지 않습니다).
+
+```bash
+OPENAI_API_KEY=sk-invalid-key-for-demo-0000000000 \
+ uv run miniflow run flows/06-request-with-condition.json -i user=kim -i text="VPN 접속이 계속 끊겨요"
+```
+
+```text
+[miniflow] openai failed (OpenAI rejected the API key (check OPENAI_API_KEY in .env)); trying ollama
+...
+ "route": "자동 답변",
+```
+
+- 수업 전 측정: OpenAI 대신 Ollama(`gemma3:4b`)가 답해 같은 `자동 답변`이 나왔습니다. 대신 시간이 더 걸립니다 (모델을 처음 올리면 20초 이상).
+- n8n의 HTTP Request 노드는 Settings의 `llm_url`·`model`을 Ollama 값으로 바꾸면 같은 워크플로우가 동작합니다 (Ollama도 `/v1/chat/completions` 형식을 지원).
+
+## 4. 정리 질문 (10분)
+
+`my-work/LAB-03-ANSWERS.md`에 답을 적습니다.
+
+1. n8n 워크플로우와 `06-request-with-condition.json`은 같은 업무를 처리합니다. 노드 구성에서 같은 점과 다른 점을 두 가지씩 적어 보세요.
+2. `Normalize and search FAQ` 노드에서 LLM의 분류값을 정해진 값으로 바꾸는 이유는 무엇인가요?
+3. 플랫폼 전환이 되려면 두 플랫폼의 **입력과 출력 형식**이 같아야 합니다. 이 실습에서 같은 형식으로 맞춘 필드는 무엇인가요?
+4. 플랫폼을 바꿀 때 바꾸지 않아도 되는 것과, 다시 만들어야 하는 것은 각각 무엇인가요?
+
+## 확인
+
+- [ ] `03` 워크플로우의 자동 답변·담당자 전달 두 길을 모두 실행했다.
+- [ ] Executions에서 `raw_label`과 `category`를 비교했다.
+- [ ] n8n을 멈춘 상태에서 `miniflow`로 전환되는 것을 확인했다.
diff --git a/Last3Mon/65/README.md b/Last3Mon/65/README.md
new file mode 100644
index 0000000..42c3c5c
--- /dev/null
+++ b/Last3Mon/65/README.md
@@ -0,0 +1,53 @@
+# 65일차 실습 · Trigger·Condition·Action과 n8n
+
+- 일자: 2026-10-15 (65일차)
+- 교과목: 노코드 멀티 에이전트 워크플로우 설계 및 운영
+- 단원: AI 워크플로우 개념 및 구성 요소 이해
+- 강의 자료: [Lecture/65](../../Lecture/65/README.md)
+
+## 구성
+
+```text
+Last3Mon/65/
+├── README.md
+├── SETUP-N8N.md # 사전 준비 · API 키(.env), n8n 실행, Credential 등록
+├── LAB-01-CONDITION-IN-MINIFLOW.md # 1단계 · Condition·Switch로 분기 만들기
+├── LAB-02-N8N-FIRST-WORKFLOWS.md # 2단계 · n8n 화면 익히기, IF·Webhook·Switch
+├── LAB-03-AI-WORKFLOW-FAILOVER.md # 3단계 · AI 문의 처리 워크플로우와 플랫폼 전환
+├── templates/
+│ └── TCA-DESIGN-TEMPLATE.md # Trigger·Condition·Action 설계표
+├── my-work/ # 여러분의 결과물 (직접 만듭니다)
+├── n8n/
+│ ├── compose.yml # n8n 2.42.6 + Ollama (대체용)
+│ ├── .env.example # 64일차 모델 폴더 연결 설정 (키는 넣지 않음)
+│ ├── register-credentials.sh # Last3Mon/.env의 키를 n8n Credential로 등록
+│ └── workflows/ # n8n에 가져올 워크플로우 3개
+└── workflow-lab/ # miniflow (64일차 버전 + condition·switch·call)
+```
+
+## 실습 순서
+
+```mermaid
+flowchart LR
+ L1["Lab 01
miniflow Condition·Switch
(1~2교시)"] --> L2["Lab 02
n8n 화면·IF·Webhook·Switch
(3~4교시)"] --> L3["Lab 03
AI 문의 처리·플랫폼 전환
(5~6교시)"]
+```
+
+| n8n 워크플로우 | Trigger | Condition | Action |
+| --- | --- | --- | --- |
+| `01-condition-basics.json` | Manual | IF (긴급 여부) | 처리 경로·처리 기한 지정 |
+| `02-webhook-router.json` | Webhook `POST /request-route` | IF (내용 있음) → Switch (분류) | 담당 팀 지정, 응답 |
+| `03-ai-request-flow.json` | Webhook `POST /ai-request` | IF (내용 있음) → IF (FAQ 있음) | LLM 분류·답변 작성, 담당자 전달, 응답 |
+
+| miniflow 워크플로우 | 새로 쓰는 노드 |
+| --- | --- |
+| `06-request-with-condition.json` | `condition` (FAQ 있음?) → 자동 답변 / 담당자 전달 |
+| `07-route-by-category.json` | `switch` (분류값) → 담당 팀 5갈래 |
+
+## 준비
+
+**[SETUP-N8N.md](SETUP-N8N.md)** 를 수업 전날 끝내고, 아래가 모두 되는지 확인합니다.
+
+```bash
+cd ~/aio-01d4-stu/Last3Mon/65/workflow-lab && uv sync && uv run pytest -q # 35 passed, 1 skipped
+cd ../n8n && docker compose ps # n8n, ollama running
+```
diff --git a/Last3Mon/65/SETUP-N8N.md b/Last3Mon/65/SETUP-N8N.md
new file mode 100644
index 0000000..86c89c4
--- /dev/null
+++ b/Last3Mon/65/SETUP-N8N.md
@@ -0,0 +1,173 @@
+# 사전 준비 · n8n 실행과 OpenAI API 키 연결
+
+65일차부터 노코드 워크플로우 도구 **n8n**을 사용합니다. 수업의 LLM은 **OpenAI API**(기본 모델 `gpt-4.1-mini`)입니다. API 키는 git에 올라가지 않는 `.env` 파일 한 곳에만 두고, n8n과 WSL의 `miniflow`가 모두 그 파일에서 키를 읽습니다. 64일차의 Ollama는 **대체용**으로 같은 Compose에서 함께 실행합니다 (OpenAI가 실패하거나 키가 없을 때).
+
+> 이미지 다운로드가 약 5GB입니다(n8n 1.1GB, Ollama 4.2GB). **수업 전날 집에서 5단계까지 끝내 주세요.** 9월에 Docker로 Ollama를 써 봤다면 Ollama 이미지는 이미 있을 수 있습니다.
+
+```mermaid
+flowchart LR
+ B["Windows 브라우저
localhost:5678"] --> N
+ E[".env
OPENAI_API_KEY
(git 제외)"] -.-> M & C
+ subgraph WSL["WSL2 (Ubuntu)"]
+ M["miniflow
(uv 프로젝트)"]
+ subgraph DC["Docker Compose · day65-n8n"]
+ N["n8n :5678"] -. "대체" .-> O["Ollama :11434"]
+ end
+ C["register-credentials.sh"] -->|"Credential 등록"| N
+ M -->|"http://localhost:5678/webhook/..."| N
+ end
+ N -->|"OpenAI (.env) Credential"| AI["OpenAI API
gpt-4.1-mini"]
+ M -->|"OPENAI_API_KEY"| AI
+```
+
+## 1. WSL에 Docker 설치 (10분)
+
+Windows용 Docker Desktop은 쓰지 않습니다. **WSL(Ubuntu) 안에 Docker Engine을 직접 설치**하고, 컨테이너 상태를 보는 도구 **ctop**도 함께 설치합니다. 설치 스크립트와 설명은 [install-sh · 2. 시스템 & 컨테이너 DevOps](https://gl.isitsoft.kr/publicproj/install-sh#-2-%EC%8B%9C%EC%8A%A4%ED%85%9C--%EC%BB%A8%ED%85%8C%EC%9D%B4%EB%84%88-devops-1)의 **Docker**와 **ctop** 항목을 참고합니다.
+
+WSL 터미널에서 실행합니다.
+
+```bash
+# Docker Engine + Compose 플러그인 (Ubuntu 공식 저장소, sudo 비밀번호 입력)
+curl -fsSL "https://gl.isitsoft.kr/publicproj/install-sh/-/raw/main/install-docker.sh?ref_type=heads" | bash
+# ctop: 컨테이너별 CPU·메모리를 실시간으로 보는 도구
+curl -fsSL "https://gl.isitsoft.kr/publicproj/install-sh/-/raw/main/install-ctop.sh?ref_type=heads" | bash
+```
+
+설치 스크립트가 내 계정을 `docker` 그룹에 넣습니다. 그룹은 **새로 로그인해야** 적용되므로 WSL 터미널을 모두 닫고 다시 엽니다 (지금 창에서 바로 쓰려면 `newgrp docker`).
+
+```bash
+docker version # Client와 Server가 모두 나오면 성공
+docker compose version
+sudo systemctl enable --now docker # 노트북을 켤 때 Docker가 자동으로 시작되게 (이미 켜져 있으면 그대로)
+docker run --rm hello-world # "Hello from Docker!"
+```
+
+| 증상 | 해결 |
+| --- | --- |
+| `permission denied ... docker.sock` | `docker` 그룹이 아직 적용 안 됨 → WSL 터미널을 모두 닫고 다시 열기 (또는 `newgrp docker`) |
+| `Cannot connect to the Docker daemon` | `sudo systemctl start docker`. `System has not been booted with systemd`가 나오면 `sudo service docker start` |
+| 이미 Docker Desktop이 설치되어 있음 | Docker Desktop을 종료하고(트레이 아이콘 → Quit), Settings → Resources → WSL integration에서 Ubuntu를 끈 뒤 위 설치를 진행 (두 Docker가 섞이지 않게) |
+| `Docker is already installed ... Skipping` | 이미 WSL에 Docker가 있음. `docker version`의 Server 줄만 확인 |
+
+`ctop`을 실행하면 n8n·Ollama 컨테이너의 CPU·메모리를 실시간으로 볼 수 있습니다 (`q`로 종료). 노트북이 느려질 때 어느 컨테이너 때문인지 확인할 때 씁니다.
+
+## 2. API 키 `.env` 확인 (1분)
+
+64일차에 `Last3Mon/.env`를 만들어 키를 넣었다면 아래 표만 확인하고 넘어갑니다 (`cat`으로 열지 말고 `grep -c '^OPENAI_API_KEY=sk-' ~/aio-01d4-stu/Last3Mon/.env`가 `1`이면 됨). 아직 없다면 다음 순서로 만듭니다.
+
+과정에서 받은 OpenAI API 키를 `Last3Mon/.env` 한 곳에 넣습니다. 64일차 이후 모든 실습이 이 파일을 찾아 읽습니다 (실행한 폴더에서 위로 올라가며 가장 가까운 `.env`).
+
+```bash
+cd ~/aio-01d4-stu/Last3Mon
+cp .env.example .env
+nano .env # OPENAI_API_KEY= 뒤에 키를 붙여 넣고 저장 (Ctrl+O, Enter, Ctrl+X)
+git status --short .env # 아무것도 나오지 않으면 git이 무시하는 파일 (정상)
+```
+
+| 줄 | 뜻 |
+| --- | --- |
+| `OPENAI_API_KEY=` | 받은 키 (`sk-`로 시작). **문서·워크플로우·채팅에 붙여 넣지 않습니다** |
+| `OPENAI_MODEL=gpt-4.1-mini` | 수업 기본 모델 |
+| `OPENAI_EMBED_MODEL=text-embedding-3-large` | 71일차부터 쓰는 임베딩 모델 (한국어 규정 검색에서 small보다 정확) |
+| `MINIFLOW_LLM=openai` | `miniflow`가 OpenAI를 쓰게 함 (`mock`이면 LLM 없이 정해진 답) |
+| `MINIFLOW_LLM_FALLBACK=ollama` | OpenAI 호출이 실패하면 Ollama로 한 번 더 시도 |
+
+> `.env`는 `.gitignore`에 들어 있어 커밋되지 않습니다. 키가 들어간 파일을 다른 이름으로 복사해 두지 마세요 (`.env.bak` 같은 이름도 커밋 대상이 될 수 있습니다).
+
+## 3. WSL의 Ollama 서비스 멈추기 (2분)
+
+64일차에 WSL에 설치한 Ollama가 11434 포트를 쓰고 있으면 Docker의 Ollama가 시작되지 않습니다. 대체용 Ollama는 Docker 쪽 하나만 사용합니다.
+
+```bash
+sudo systemctl stop ollama # 오늘 수업 동안 멈춤
+sudo systemctl disable ollama # (선택) 노트북을 켤 때 자동으로 시작하지 않게 함
+```
+
+64일차 실습을 다시 할 때는 `sudo systemctl start ollama`로 다시 켜면 됩니다.
+
+## 4. 모델 폴더 연결 설정 (2분)
+
+64일차에 받은 모델을 다시 받지 않도록, Docker의 Ollama가 같은 모델 폴더를 쓰게 합니다. 이 `.env`는 Compose 설정용이고 API 키는 넣지 않습니다.
+
+```bash
+cd ~/aio-01d4-stu/Last3Mon/65/n8n
+cp .env.example .env
+ls /usr/share/ollama/.ollama/models 2>/dev/null && echo "서비스 설치 경로 사용" || echo "홈 경로 확인 필요"
+```
+
+| 결과 | `.env`에 둘 줄 |
+| --- | --- |
+| `서비스 설치 경로 사용` | `OLLAMA_DATA=/usr/share/ollama/.ollama` (기본값 그대로) |
+| `홈 경로 확인 필요` | `OLLAMA_DATA=/home//.ollama` 로 바꾸기 |
+
+## 5. n8n 실행과 첫 설정 (이미지 다운로드 10~30분)
+
+```bash
+cd ~/aio-01d4-stu/Last3Mon/65/n8n
+docker compose up -d
+docker compose ps
+```
+
+- `docker compose ps`에서 `n8n`과 `ollama`가 모두 `running`이면 성공입니다.
+- Windows 브라우저에서 **http://localhost:5678** 을 열고, 처음 한 번 관리자 계정(이메일·이름·비밀번호)을 만듭니다. 이 계정은 내 노트북 안에만 저장되며, 외부로 가입되는 것이 아닙니다.
+- 설문 화면이 나오면 건너뛰어도 됩니다.
+
+## 6. n8n에 Credential 등록 (2분)
+
+`.env`의 키를 n8n의 **Credential**로 등록합니다. 키를 화면에 직접 붙여 넣지 않아도 되고, 수업 워크플로우가 쓰는 이름·ID로 만들어집니다.
+
+```bash
+cd ~/aio-01d4-stu/Last3Mon/65/n8n
+bash register-credentials.sh
+```
+
+```text
+Successfully imported 2 credentials.
+Registered 'OpenAI (.env)' and 'Ollama local' from /home/.../Last3Mon/.env
+```
+
+n8n 화면 왼쪽 **Credentials**(또는 Overview → Credentials)에 `OpenAI (.env)`와 `Ollama local`이 보이면 성공입니다. 키를 바꾸면 `.env`를 고치고 이 명령을 다시 실행합니다.
+
+## 7. 확인: OpenAI 호출 한 번
+
+```bash
+cd ~/aio-01d4-stu/Last3Mon/65/workflow-lab
+uv sync
+uv run miniflow check
+```
+
+```text
+MINIFLOW_LLM : openai
+.env : /home/.../Last3Mon/.env
+OPENAI_MODEL : gpt-4.1-mini
+API key : set
+Reply (openai, 2.9s): ready
+```
+
+## 8. 끄고 켜기
+
+```bash
+docker compose stop # 수업이 끝나면 멈춤 (데이터는 유지)
+docker compose start # 다음에 다시 켬
+docker compose down # 컨테이너 삭제 (워크플로우·계정·Credential은 n8n-data 볼륨에 유지)
+```
+
+## 9. 문제 해결
+
+| 증상 | 해결 |
+| --- | --- |
+| `miniflow check`가 `OPENAI_API_KEY is not set` | 2단계: `Last3Mon/.env`에 키가 있는지, 파일 이름이 정확히 `.env`인지 확인 |
+| `HTTP 401` / `rejected the API key` | 키를 잘못 붙여 넣음 (앞뒤 공백·따옴표 확인) → `.env` 수정 후 6단계 다시 |
+| `HTTP 429 insufficient_quota` | 키의 조직에 API 크레딧이 없음 → 강사·운영진에 알림 |
+| `register-credentials.sh`가 `No .env with OPENAI_API_KEY found` | 2단계를 `Last3Mon` 폴더에서 했는지 확인 |
+| `port is already allocated` (11434) | 3단계: `sudo systemctl stop ollama` |
+| `port is already allocated` (5678) | 다른 n8n이 실행 중인지 `docker ps`로 확인 후 멈춤 |
+| 브라우저에서 `localhost:5678`이 열리지 않음 | `docker compose ps`로 상태 확인, `docker compose logs n8n`으로 오류 확인. WSL 안의 컨테이너도 Windows 브라우저에서 `localhost`로 열리는 것이 기본이며, 계속 안 되면 PowerShell에서 `wsl --shutdown` 후 WSL을 다시 열기 |
+| 웹훅 호출이 404 (`not registered`) | 워크플로우 오른쪽 위 **Publish** 토글 확인. 같은 워크플로우를 여러 번 가져왔다면 기존 것을 삭제하고 한 번만 가져온 뒤 Publish |
+
+## 확인
+
+- [ ] `Last3Mon/.env`에 키를 넣었고, `git status`에 `.env`가 보이지 않는다
+- [ ] `docker compose ps` → n8n, ollama 모두 running
+- [ ] n8n Credentials에 `OpenAI (.env)`, `Ollama local`이 있다
+- [ ] `uv run miniflow check` → `Reply (openai, …): ready`
diff --git a/Last3Mon/65/n8n/.env.example b/Last3Mon/65/n8n/.env.example
new file mode 100644
index 0000000..8a6224f
--- /dev/null
+++ b/Last3Mon/65/n8n/.env.example
@@ -0,0 +1,7 @@
+# Compose settings for the day 65 n8n + Ollama (fallback) containers. No API key here:
+# the OpenAI key goes in Last3Mon/.env, and register-credentials.sh puts it into n8n.
+# Copy to .env and keep the line that matches how Ollama was installed on day 64.
+# Ollama installed with the install script (runs as a service):
+OLLAMA_DATA=/usr/share/ollama/.ollama
+# Ollama started by hand with `ollama serve`:
+# OLLAMA_DATA=/home//.ollama
diff --git a/Last3Mon/65/n8n/compose.yml b/Last3Mon/65/n8n/compose.yml
new file mode 100644
index 0000000..2b23735
--- /dev/null
+++ b/Last3Mon/65/n8n/compose.yml
@@ -0,0 +1,35 @@
+# n8n (LLM: OpenAI API, key from Last3Mon/.env via register-credentials.sh) + Ollama as the fallback.
+# docker compose up -d (run from this folder)
+# n8n editor : http://localhost:5678
+# Ollama API : http://localhost:11434 (n8n uses http://ollama:11434 inside the network)
+name: day65-n8n
+
+services:
+ n8n:
+ image: docker.n8n.io/n8nio/n8n:2.42.6
+ ports:
+ - "5678:5678"
+ environment:
+ - GENERIC_TIMEZONE=Asia/Seoul
+ - TZ=Asia/Seoul
+ - N8N_SECURE_COOKIE=false
+ volumes:
+ - n8n-data:/home/node/.n8n
+ - ./workflows:/home/node/workflows:ro
+ depends_on:
+ - ollama
+ restart: unless-stopped
+
+ ollama:
+ image: ollama/ollama:latest
+ ports:
+ - "11434:11434"
+ volumes:
+ # Reuse the models downloaded on day 64 by setting OLLAMA_DATA in .env
+ # (default: a new Docker volume, then run: docker compose exec ollama ollama pull gemma3:4b)
+ - ${OLLAMA_DATA:-ollama-data}:/root/.ollama
+ restart: unless-stopped
+
+volumes:
+ n8n-data:
+ ollama-data:
diff --git a/Last3Mon/65/n8n/register-credentials.sh b/Last3Mon/65/n8n/register-credentials.sh
new file mode 100644
index 0000000..e09ce3d
--- /dev/null
+++ b/Last3Mon/65/n8n/register-credentials.sh
@@ -0,0 +1,45 @@
+#!/usr/bin/env bash
+# Register the course credentials in n8n from the .env file, so the API key is never typed into
+# a workflow or committed to git.
+# cd Last3Mon/65/n8n && docker compose up -d && bash register-credentials.sh
+#
+# Creates (or updates) two credentials with fixed ids that the course workflows already use:
+# OpenAI (.env) id openAiCourse0001 <- OPENAI_API_KEY (and OPENAI_BASE_URL if set)
+# Ollama local id ollamaLocal0001 <- http://ollama:11434 (fallback model)
+#
+# Outage drill (day 72): OPENAI_API_KEY=sk-invalid-key-for-drill-000000 bash register-credentials.sh
+# Restore: bash register-credentials.sh
+set -euo pipefail
+cd "$(dirname "$0")"
+
+# The nearest .env (this folder first, then the folders above) that has OPENAI_API_KEY.
+env_file=""
+dir="$PWD"
+while [ "$dir" != "/" ]; do
+ if [ -f "$dir/.env" ] && grep -q '^OPENAI_API_KEY=' "$dir/.env"; then
+ env_file="$dir/.env"
+ break
+ fi
+ dir="$(dirname "$dir")"
+done
+if [ -z "$env_file" ]; then
+ echo "No .env with OPENAI_API_KEY found. Copy Last3Mon/.env.example to Last3Mon/.env and fill it in." >&2
+ exit 1
+fi
+
+value() { { grep -E "^$1=" "$env_file" || true; } | tail -1 | cut -d= -f2- | sed -e 's/^["'\'']//' -e 's/["'\'']$//'; }
+key="${OPENAI_API_KEY:-$(value OPENAI_API_KEY)}" # a key exported in the shell wins (used for outage drills)
+base_url="$(value OPENAI_BASE_URL)"
+base_url="${base_url:-https://api.openai.com/v1}"
+if ! printf '%s' "$key" | grep -Eq '^[A-Za-z0-9_-]{20,}$'; then
+ echo "OPENAI_API_KEY in $env_file is empty or does not look like an API key." >&2
+ exit 1
+fi
+
+credentials=$(printf '[{"id":"openAiCourse0001","name":"OpenAI (.env)","type":"openAiApi","data":{"apiKey":"%s","url":"%s"}},{"id":"ollamaLocal0001","name":"Ollama local","type":"ollamaApi","data":{"baseUrl":"http://ollama:11434"}}]' "$key" "$base_url")
+
+# The JSON goes through stdin into a temporary file inside the container, then is deleted.
+printf '%s' "$credentials" | docker compose exec -T n8n sh -c \
+ 'cat > /tmp/course-credentials.json && n8n import:credentials --input=/tmp/course-credentials.json; status=$?; rm -f /tmp/course-credentials.json; exit $status'
+
+echo "Registered 'OpenAI (.env)' and 'Ollama local' from $env_file"
diff --git a/Last3Mon/65/n8n/workflows/01-condition-basics.json b/Last3Mon/65/n8n/workflows/01-condition-basics.json
new file mode 100644
index 0000000..e69d4ce
--- /dev/null
+++ b/Last3Mon/65/n8n/workflows/01-condition-basics.json
@@ -0,0 +1,170 @@
+{
+ "name": "65-01 Condition basics",
+ "nodes": [
+ {
+ "parameters": {},
+ "id": "26dc330d-6170-5f39-aeb4-d1bc63ed9d26",
+ "name": "Start",
+ "type": "n8n-nodes-base.manualTrigger",
+ "typeVersion": 1,
+ "position": [
+ 0,
+ 0
+ ]
+ },
+ {
+ "parameters": {
+ "jsCode": "// Three sample requests. In a real workflow they would come from a form, mail or webhook.\nreturn [\n { json: { id: 'T-1', text: 'VPN이 끊겨서 고객 미팅에 들어갈 수 없어요', priority: 'urgent' } },\n { json: { id: 'T-2', text: '프린터 토너 교체를 요청합니다', priority: 'normal' } },\n { json: { id: 'T-3', text: '계정이 잠겨서 결재를 올릴 수 없어요', priority: 'urgent' } },\n];"
+ },
+ "id": "636773ca-d229-564c-88cb-54b530628910",
+ "name": "Sample requests",
+ "type": "n8n-nodes-base.code",
+ "typeVersion": 2,
+ "position": [
+ 220,
+ 0
+ ]
+ },
+ {
+ "parameters": {
+ "conditions": {
+ "options": {
+ "caseSensitive": true,
+ "leftValue": "",
+ "typeValidation": "loose",
+ "version": 2
+ },
+ "conditions": [
+ {
+ "id": "4db4fdb9-dbaf-51bb-aaf9-16a54ef93027",
+ "leftValue": "={{ $json.priority }}",
+ "operator": {
+ "type": "string",
+ "operation": "equals"
+ },
+ "rightValue": "urgent"
+ }
+ ],
+ "combinator": "and"
+ },
+ "options": {}
+ },
+ "id": "e54594bf-eb8b-5d83-96db-ef857683c127",
+ "name": "Is urgent?",
+ "type": "n8n-nodes-base.if",
+ "typeVersion": 2.2,
+ "position": [
+ 440,
+ 0
+ ]
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "1f7b6098-3185-56cc-9d8e-4bcfec1e7ba4",
+ "name": "route",
+ "value": "즉시 담당자 연결",
+ "type": "string"
+ },
+ {
+ "id": "c01612ed-a8a0-5a0a-83b9-93f6ad2eaf31",
+ "name": "sla_minutes",
+ "value": "30",
+ "type": "number"
+ }
+ ]
+ },
+ "includeOtherFields": true,
+ "options": {}
+ },
+ "id": "1d7d3d65-295f-599e-909f-8d5708d8ff46",
+ "name": "Urgent route",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 680,
+ -100
+ ]
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "e7c65f93-009f-5a5a-8cad-71abcc7cc569",
+ "name": "route",
+ "value": "일반 접수",
+ "type": "string"
+ },
+ {
+ "id": "7148df87-83e5-54ca-9d67-619c60e6fe54",
+ "name": "sla_minutes",
+ "value": "480",
+ "type": "number"
+ }
+ ]
+ },
+ "includeOtherFields": true,
+ "options": {}
+ },
+ "id": "9b40293c-c2f0-55a6-b1ba-232770d31ee9",
+ "name": "Normal route",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 680,
+ 100
+ ]
+ }
+ ],
+ "connections": {
+ "Start": {
+ "main": [
+ [
+ {
+ "node": "Sample requests",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Sample requests": {
+ "main": [
+ [
+ {
+ "node": "Is urgent?",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Is urgent?": {
+ "main": [
+ [
+ {
+ "node": "Urgent route",
+ "type": "main",
+ "index": 0
+ }
+ ],
+ [
+ {
+ "node": "Normal route",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ }
+ },
+ "active": false,
+ "settings": {
+ "executionOrder": "v1"
+ },
+ "pinData": {},
+ "id": "aeb87743007e5e"
+}
\ No newline at end of file
diff --git a/Last3Mon/65/n8n/workflows/02-webhook-router.json b/Last3Mon/65/n8n/workflows/02-webhook-router.json
new file mode 100644
index 0000000..86f5d31
--- /dev/null
+++ b/Last3Mon/65/n8n/workflows/02-webhook-router.json
@@ -0,0 +1,479 @@
+{
+ "name": "65-02 Webhook request router",
+ "nodes": [
+ {
+ "parameters": {
+ "httpMethod": "POST",
+ "path": "request-route",
+ "responseMode": "responseNode",
+ "options": {}
+ },
+ "id": "8dc39098-cbf2-5da7-b6a3-0541c2838c7d",
+ "name": "Request webhook",
+ "type": "n8n-nodes-base.webhook",
+ "typeVersion": 2,
+ "position": [
+ 0,
+ 0
+ ],
+ "webhookId": "612ab961-6b30-5c73-a4b0-b113262a92e8"
+ },
+ {
+ "parameters": {
+ "conditions": {
+ "options": {
+ "caseSensitive": true,
+ "leftValue": "",
+ "typeValidation": "loose",
+ "version": 2
+ },
+ "conditions": [
+ {
+ "id": "0e03d4eb-275c-5799-8c08-3e744e4692e2",
+ "leftValue": "={{ $json.body.text }}",
+ "operator": {
+ "type": "string",
+ "operation": "notEmpty",
+ "singleValue": true
+ },
+ "rightValue": ""
+ }
+ ],
+ "combinator": "and"
+ },
+ "options": {}
+ },
+ "id": "d19bdfca-d55e-5760-a488-458abc7a5480",
+ "name": "Has text?",
+ "type": "n8n-nodes-base.if",
+ "typeVersion": 2.2,
+ "position": [
+ 220,
+ 0
+ ]
+ },
+ {
+ "parameters": {
+ "respondWith": "json",
+ "responseBody": "={{ { \"error\": \"text is required\" } }}",
+ "options": {
+ "responseCode": 400
+ }
+ },
+ "id": "5adfc553-1a2c-55fd-a4bd-d6564197222a",
+ "name": "Reject empty",
+ "type": "n8n-nodes-base.respondToWebhook",
+ "typeVersion": 1.1,
+ "position": [
+ 460,
+ 160
+ ]
+ },
+ {
+ "parameters": {
+ "jsCode": "// Rule-based classification (no AI yet): the first rule whose keyword appears wins.\nconst rules = [\n { category: 'account', words: ['비밀번호', '계정', '로그인', '잠겨', '잠김'] },\n { category: 'network', words: ['vpn', '인터넷', '와이파이', '접속', '네트워크'] },\n { category: 'device', words: ['프린터', '모니터', '키보드', '마우스', '노트북'] },\n { category: 'software', words: ['설치', '프로그램', '라이선스', '메일', '업데이트'] },\n];\nconst body = $input.first().json.body;\nconst text = String(body.text).toLowerCase();\nconst hit = rules.find(r => r.words.some(w => text.includes(w)));\nreturn [{ json: { user: body.user || 'anonymous', text: body.text, category: hit ? hit.category : 'other' } }];"
+ },
+ "id": "555904e3-48b4-5e74-bbe5-11a9f9153504",
+ "name": "Keyword classify",
+ "type": "n8n-nodes-base.code",
+ "typeVersion": 2,
+ "position": [
+ 460,
+ -40
+ ]
+ },
+ {
+ "parameters": {
+ "rules": {
+ "values": [
+ {
+ "conditions": {
+ "options": {
+ "caseSensitive": true,
+ "leftValue": "",
+ "typeValidation": "loose",
+ "version": 2
+ },
+ "conditions": [
+ {
+ "id": "befaac8f-1c7b-5a01-afb6-1dfca95d48c5",
+ "leftValue": "={{ $json.category }}",
+ "operator": {
+ "type": "string",
+ "operation": "equals"
+ },
+ "rightValue": "account"
+ }
+ ],
+ "combinator": "and"
+ },
+ "renameOutput": true,
+ "outputKey": "account"
+ },
+ {
+ "conditions": {
+ "options": {
+ "caseSensitive": true,
+ "leftValue": "",
+ "typeValidation": "loose",
+ "version": 2
+ },
+ "conditions": [
+ {
+ "id": "fd212d44-e661-5050-b426-360a5d39ad96",
+ "leftValue": "={{ $json.category }}",
+ "operator": {
+ "type": "string",
+ "operation": "equals"
+ },
+ "rightValue": "network"
+ }
+ ],
+ "combinator": "and"
+ },
+ "renameOutput": true,
+ "outputKey": "network"
+ },
+ {
+ "conditions": {
+ "options": {
+ "caseSensitive": true,
+ "leftValue": "",
+ "typeValidation": "loose",
+ "version": 2
+ },
+ "conditions": [
+ {
+ "id": "eff4a459-e7e8-5c5a-84f1-3670a5bd03c6",
+ "leftValue": "={{ $json.category }}",
+ "operator": {
+ "type": "string",
+ "operation": "equals"
+ },
+ "rightValue": "device"
+ }
+ ],
+ "combinator": "and"
+ },
+ "renameOutput": true,
+ "outputKey": "device"
+ },
+ {
+ "conditions": {
+ "options": {
+ "caseSensitive": true,
+ "leftValue": "",
+ "typeValidation": "loose",
+ "version": 2
+ },
+ "conditions": [
+ {
+ "id": "862c0a38-3a85-5499-99f8-f0ffee9a6825",
+ "leftValue": "={{ $json.category }}",
+ "operator": {
+ "type": "string",
+ "operation": "equals"
+ },
+ "rightValue": "software"
+ }
+ ],
+ "combinator": "and"
+ },
+ "renameOutput": true,
+ "outputKey": "software"
+ }
+ ]
+ },
+ "options": {
+ "fallbackOutput": "extra",
+ "renameFallbackOutput": "other"
+ }
+ },
+ "id": "2c251693-82e5-56cf-9a73-ed6bc2eebdf4",
+ "name": "Route by category",
+ "type": "n8n-nodes-base.switch",
+ "typeVersion": 3.2,
+ "position": [
+ 680,
+ -40
+ ]
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "241fe967-6e70-51db-b65d-a59655f888b0",
+ "name": "team",
+ "value": "계정 관리 담당",
+ "type": "string"
+ }
+ ]
+ },
+ "includeOtherFields": true,
+ "options": {}
+ },
+ "id": "65675630-6d1a-55f5-adaa-b40125e2d453",
+ "name": "Team account",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 920,
+ -240
+ ]
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "91e77bc6-3674-5f2a-a997-d831997f5a28",
+ "name": "team",
+ "value": "네트워크 담당",
+ "type": "string"
+ }
+ ]
+ },
+ "includeOtherFields": true,
+ "options": {}
+ },
+ "id": "0b91914c-9289-5f56-adc2-6d697240358c",
+ "name": "Team network",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 920,
+ -130
+ ]
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "3fdfa927-2342-5f8a-95c2-bc5a1e0b87d9",
+ "name": "team",
+ "value": "장비 지원 담당",
+ "type": "string"
+ }
+ ]
+ },
+ "includeOtherFields": true,
+ "options": {}
+ },
+ "id": "0b918a6f-2ed5-5007-90f8-cc7911628ce7",
+ "name": "Team device",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 920,
+ -20
+ ]
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "251f69b0-7fa1-52d0-b73f-4a3f102fff35",
+ "name": "team",
+ "value": "소프트웨어 담당",
+ "type": "string"
+ }
+ ]
+ },
+ "includeOtherFields": true,
+ "options": {}
+ },
+ "id": "ac9cabd3-3a8a-5055-af0a-3ad481eba531",
+ "name": "Team software",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 920,
+ 90
+ ]
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "7602acd9-08cd-500a-acbd-bd4656159712",
+ "name": "team",
+ "value": "IT 문의 접수 창구",
+ "type": "string"
+ }
+ ]
+ },
+ "includeOtherFields": true,
+ "options": {}
+ },
+ "id": "71c63724-4e06-5a26-bec9-ff4b97f9328c",
+ "name": "Team other",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 920,
+ 200
+ ]
+ },
+ {
+ "parameters": {
+ "respondWith": "json",
+ "responseBody": "={{ $json }}",
+ "options": {}
+ },
+ "id": "365b7747-c4de-5b2e-9dcc-3dc3f3d2d9ac",
+ "name": "Send route",
+ "type": "n8n-nodes-base.respondToWebhook",
+ "typeVersion": 1.1,
+ "position": [
+ 1160,
+ -40
+ ]
+ }
+ ],
+ "connections": {
+ "Request webhook": {
+ "main": [
+ [
+ {
+ "node": "Has text?",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Has text?": {
+ "main": [
+ [
+ {
+ "node": "Keyword classify",
+ "type": "main",
+ "index": 0
+ }
+ ],
+ [
+ {
+ "node": "Reject empty",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Keyword classify": {
+ "main": [
+ [
+ {
+ "node": "Route by category",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Route by category": {
+ "main": [
+ [
+ {
+ "node": "Team account",
+ "type": "main",
+ "index": 0
+ }
+ ],
+ [
+ {
+ "node": "Team network",
+ "type": "main",
+ "index": 0
+ }
+ ],
+ [
+ {
+ "node": "Team device",
+ "type": "main",
+ "index": 0
+ }
+ ],
+ [
+ {
+ "node": "Team software",
+ "type": "main",
+ "index": 0
+ }
+ ],
+ [
+ {
+ "node": "Team other",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Team account": {
+ "main": [
+ [
+ {
+ "node": "Send route",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Team network": {
+ "main": [
+ [
+ {
+ "node": "Send route",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Team device": {
+ "main": [
+ [
+ {
+ "node": "Send route",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Team software": {
+ "main": [
+ [
+ {
+ "node": "Send route",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Team other": {
+ "main": [
+ [
+ {
+ "node": "Send route",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ }
+ },
+ "active": false,
+ "settings": {
+ "executionOrder": "v1"
+ },
+ "pinData": {},
+ "id": "af8dc0f7ef905c"
+}
\ No newline at end of file
diff --git a/Last3Mon/65/n8n/workflows/03-ai-request-flow.json b/Last3Mon/65/n8n/workflows/03-ai-request-flow.json
new file mode 100644
index 0000000..c256649
--- /dev/null
+++ b/Last3Mon/65/n8n/workflows/03-ai-request-flow.json
@@ -0,0 +1,438 @@
+{
+ "name": "65-03 AI request flow",
+ "nodes": [
+ {
+ "parameters": {
+ "httpMethod": "POST",
+ "path": "ai-request",
+ "responseMode": "responseNode",
+ "options": {}
+ },
+ "id": "07b51032-62c2-549b-8cfb-e3f16a851ed7",
+ "name": "AI request webhook",
+ "type": "n8n-nodes-base.webhook",
+ "typeVersion": 2,
+ "position": [
+ 0,
+ 0
+ ],
+ "webhookId": "26aa9aad-522f-5f3d-8b58-ae0d7c18ce66"
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "cf988cf6-5aec-59ef-887c-93252d7d366b",
+ "name": "llm_url",
+ "value": "https://api.openai.com/v1",
+ "type": "string"
+ },
+ {
+ "id": "6d229077-7077-5e85-8ebb-8f6046227539",
+ "name": "model",
+ "value": "gpt-4.1-mini",
+ "type": "string"
+ },
+ {
+ "id": "8a827ce4-4716-5aad-ad39-9c105afcf895",
+ "name": "user",
+ "value": "={{ $json.body.user || 'anonymous' }}",
+ "type": "string"
+ },
+ {
+ "id": "462379ca-3e96-599d-9a1c-64bae0b1095a",
+ "name": "text",
+ "value": "={{ $json.body.text }}",
+ "type": "string"
+ }
+ ]
+ },
+ "includeOtherFields": false,
+ "options": {}
+ },
+ "id": "6c57d7cf-acd9-5007-b34a-b741afa2c060",
+ "name": "Settings",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 220,
+ 0
+ ]
+ },
+ {
+ "parameters": {
+ "conditions": {
+ "options": {
+ "caseSensitive": true,
+ "leftValue": "",
+ "typeValidation": "loose",
+ "version": 2
+ },
+ "conditions": [
+ {
+ "id": "f2c175d2-9545-570a-99a6-e7cdfb17162f",
+ "leftValue": "={{ $json.text }}",
+ "operator": {
+ "type": "string",
+ "operation": "notEmpty",
+ "singleValue": true
+ },
+ "rightValue": ""
+ }
+ ],
+ "combinator": "and"
+ },
+ "options": {}
+ },
+ "id": "d19bdfca-d55e-5760-a488-458abc7a5480",
+ "name": "Has text?",
+ "type": "n8n-nodes-base.if",
+ "typeVersion": 2.2,
+ "position": [
+ 440,
+ 0
+ ]
+ },
+ {
+ "parameters": {
+ "respondWith": "json",
+ "responseBody": "={{ { \"error\": \"text is required\" } }}",
+ "options": {
+ "responseCode": 400
+ }
+ },
+ "id": "5adfc553-1a2c-55fd-a4bd-d6564197222a",
+ "name": "Reject empty",
+ "type": "n8n-nodes-base.respondToWebhook",
+ "typeVersion": 1.1,
+ "position": [
+ 680,
+ 180
+ ]
+ },
+ {
+ "parameters": {
+ "method": "POST",
+ "url": "={{ $('Settings').first().json.llm_url }}/chat/completions",
+ "sendBody": true,
+ "specifyBody": "json",
+ "jsonBody": "={{ JSON.stringify({ model: $('Settings').first().json.model, temperature: 0, messages: [ { role: 'system', content: \"Classify the IT request into exactly one of: account, network, device, software, other. Reply with the label only.\" }, { role: 'user', content: $('Settings').first().json.text } ] }) }}",
+ "options": {
+ "timeout": 180000
+ },
+ "authentication": "predefinedCredentialType",
+ "nodeCredentialType": "openAiApi"
+ },
+ "id": "d084b606-aad9-5341-98cd-490070f907ac",
+ "name": "LLM classify",
+ "type": "n8n-nodes-base.httpRequest",
+ "typeVersion": 4.2,
+ "position": [
+ 680,
+ -40
+ ],
+ "credentials": {
+ "openAiApi": {
+ "id": "openAiCourse0001",
+ "name": "OpenAI (.env)"
+ }
+ }
+ },
+ {
+ "parameters": {
+ "jsCode": "// 1) Clean up the LLM label 2) Search the FAQ list\nconst allowed = ['account', 'network', 'device', 'software', 'other'];\nconst raw = String($input.first().json.choices?.[0]?.message?.content ?? '').trim().toLowerCase();\nconst category = allowed.find(a => raw.includes(a)) ?? 'other';\n\nconst faqs = [\n {\n \"id\": \"FAQ-001\",\n \"title\": \"비밀번호 재설정\",\n \"keywords\": [\n \"비밀번호\",\n \"패스워드\",\n \"password\",\n \"재설정\",\n \"초기화\"\n ],\n \"answer\": \"사내 포털 로그인 화면의 '비밀번호 찾기'에서 휴대폰 인증 후 새 비밀번호를 설정합니다.\"\n },\n {\n \"id\": \"FAQ-002\",\n \"title\": \"계정 잠김 해제\",\n \"keywords\": [\n \"계정\",\n \"잠김\",\n \"잠금\",\n \"로그인\",\n \"실패\"\n ],\n \"answer\": \"로그인 5회 실패 시 30분 동안 잠깁니다. 30분 후 다시 시도하거나 헬프데스크에 잠금 해제를 요청합니다.\"\n },\n {\n \"id\": \"FAQ-003\",\n \"title\": \"VPN 접속 오류\",\n \"keywords\": [\n \"vpn\",\n \"원격\",\n \"재택\",\n \"접속\",\n \"연결\"\n ],\n \"answer\": \"VPN 클라이언트를 최신 버전으로 업데이트하고, 인증서 만료 여부를 확인한 뒤 다시 접속합니다.\"\n },\n {\n \"id\": \"FAQ-004\",\n \"title\": \"프린터 출력 안 됨\",\n \"keywords\": [\n \"프린터\",\n \"출력\",\n \"인쇄\",\n \"용지\"\n ],\n \"answer\": \"프린터 전원과 네트워크 연결을 확인하고, 인쇄 대기열을 비운 뒤 다시 출력합니다.\"\n },\n {\n \"id\": \"FAQ-005\",\n \"title\": \"메일함 용량 초과\",\n \"keywords\": [\n \"메일\",\n \"용량\",\n \"메일함\",\n \"첨부\"\n ],\n \"answer\": \"오래된 메일과 큰 첨부 파일을 보관함으로 옮기거나 삭제해 용량을 확보합니다.\"\n },\n {\n \"id\": \"FAQ-006\",\n \"title\": \"소프트웨어 설치 요청\",\n \"keywords\": [\n \"설치\",\n \"소프트웨어\",\n \"프로그램\",\n \"라이선스\"\n ],\n \"answer\": \"IT 포털의 '소프트웨어 신청' 메뉴에서 승인 요청을 올리면 승인 후 원격으로 설치됩니다.\"\n }\n];\nconst settings = $('Settings').first().json;\nconst words = String(settings.text).toLowerCase().split(/\\s+/).filter(w => w.length > 1);\nconst scored = faqs\n .map(f => ({ ...f, score: words.filter(w => f.keywords.some(k => w.includes(k) || k.includes(w))).length }))\n .filter(f => f.score > 0)\n .sort((a, b) => b.score - a.score);\nconst faq = scored[0] ?? null;\n\nreturn [{ json: { user: settings.user, text: settings.text, raw_label: raw, category, found: faq !== null, faq } }];"
+ },
+ "id": "aa4be834-45fb-563b-95f5-c6a0dbeb2903",
+ "name": "Normalize and search FAQ",
+ "type": "n8n-nodes-base.code",
+ "typeVersion": 2,
+ "position": [
+ 920,
+ -40
+ ]
+ },
+ {
+ "parameters": {
+ "conditions": {
+ "options": {
+ "caseSensitive": true,
+ "leftValue": "",
+ "typeValidation": "loose",
+ "version": 2
+ },
+ "conditions": [
+ {
+ "id": "6a4b578f-d9da-5899-933d-7e05d901e3eb",
+ "leftValue": "={{ $json.found }}",
+ "operator": {
+ "type": "boolean",
+ "operation": "true",
+ "singleValue": true
+ },
+ "rightValue": ""
+ }
+ ],
+ "combinator": "and"
+ },
+ "options": {}
+ },
+ "id": "21f335b6-8a0a-5331-b8df-43d3c9f9aafc",
+ "name": "FAQ found?",
+ "type": "n8n-nodes-base.if",
+ "typeVersion": 2.2,
+ "position": [
+ 1160,
+ -40
+ ]
+ },
+ {
+ "parameters": {
+ "method": "POST",
+ "url": "={{ $('Settings').first().json.llm_url }}/chat/completions",
+ "sendBody": true,
+ "specifyBody": "json",
+ "jsonBody": "={{ JSON.stringify({ model: $('Settings').first().json.model, temperature: 0, messages: [ { role: 'system', content: \"Write a polite 2-sentence Korean reply using only the FAQ answer. End with the FAQ id in parentheses.\" }, { role: 'user', content: '문의: ' + $('Normalize and search FAQ').first().json.text + '\\nFAQ: ' + JSON.stringify($('Normalize and search FAQ').first().json.faq) } ] }) }}",
+ "options": {
+ "timeout": 180000
+ },
+ "authentication": "predefinedCredentialType",
+ "nodeCredentialType": "openAiApi"
+ },
+ "id": "a1e86429-1ee7-585c-bdaa-f1aa0d10f49b",
+ "name": "LLM draft reply",
+ "type": "n8n-nodes-base.httpRequest",
+ "typeVersion": 4.2,
+ "position": [
+ 1400,
+ -140
+ ],
+ "credentials": {
+ "openAiApi": {
+ "id": "openAiCourse0001",
+ "name": "OpenAI (.env)"
+ }
+ }
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "1e3762b6-7dae-5e2f-9538-8a5b0f5dcae0",
+ "name": "category",
+ "value": "={{ $('Normalize and search FAQ').first().json.category }}",
+ "type": "string"
+ },
+ {
+ "id": "230f5390-e5c9-5e6a-90ec-03e6965652f7",
+ "name": "faq_id",
+ "value": "={{ $('Normalize and search FAQ').first().json.faq.id }}",
+ "type": "string"
+ },
+ {
+ "id": "1f78eb57-6478-5590-94f9-bacb9b2c89b9",
+ "name": "route",
+ "value": "자동 답변",
+ "type": "string"
+ },
+ {
+ "id": "756cec4c-d91f-516a-9d9f-ae74098227e9",
+ "name": "reply",
+ "value": "={{ $json.choices[0].message.content.trim() }}",
+ "type": "string"
+ }
+ ]
+ },
+ "includeOtherFields": false,
+ "options": {}
+ },
+ "id": "da512682-1045-5a8e-83d1-52975eb08e97",
+ "name": "Auto reply",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 1640,
+ -140
+ ]
+ },
+ {
+ "parameters": {
+ "assignments": {
+ "assignments": [
+ {
+ "id": "bf4ced71-6e32-5ed2-ad7d-4124d462e3d2",
+ "name": "category",
+ "value": "={{ $json.category }}",
+ "type": "string"
+ },
+ {
+ "id": "79bffc37-152f-5b3e-9018-e30121faed11",
+ "name": "faq_id",
+ "value": "",
+ "type": "string"
+ },
+ {
+ "id": "86fde04e-b2a1-5782-97c1-caba13a9ed10",
+ "name": "route",
+ "value": "담당자 확인",
+ "type": "string"
+ },
+ {
+ "id": "d760805f-73f1-5d0a-a7cf-8eb67d03e978",
+ "name": "reply",
+ "value": "관련 안내를 찾지 못해 담당자가 확인 후 답변드리겠습니다.",
+ "type": "string"
+ }
+ ]
+ },
+ "includeOtherFields": false,
+ "options": {}
+ },
+ "id": "604eb70d-bff2-5270-b1a4-f94a3a6c681d",
+ "name": "Hand off to staff",
+ "type": "n8n-nodes-base.set",
+ "typeVersion": 3.4,
+ "position": [
+ 1400,
+ 80
+ ]
+ },
+ {
+ "parameters": {
+ "respondWith": "json",
+ "responseBody": "={{ $json }}",
+ "options": {}
+ },
+ "id": "2de33965-f060-5f8b-bd91-2a7c72a1e618",
+ "name": "Send result",
+ "type": "n8n-nodes-base.respondToWebhook",
+ "typeVersion": 1.1,
+ "position": [
+ 1880,
+ -40
+ ]
+ }
+ ],
+ "connections": {
+ "AI request webhook": {
+ "main": [
+ [
+ {
+ "node": "Settings",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Settings": {
+ "main": [
+ [
+ {
+ "node": "Has text?",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Has text?": {
+ "main": [
+ [
+ {
+ "node": "LLM classify",
+ "type": "main",
+ "index": 0
+ }
+ ],
+ [
+ {
+ "node": "Reject empty",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "LLM classify": {
+ "main": [
+ [
+ {
+ "node": "Normalize and search FAQ",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Normalize and search FAQ": {
+ "main": [
+ [
+ {
+ "node": "FAQ found?",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "FAQ found?": {
+ "main": [
+ [
+ {
+ "node": "LLM draft reply",
+ "type": "main",
+ "index": 0
+ }
+ ],
+ [
+ {
+ "node": "Hand off to staff",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "LLM draft reply": {
+ "main": [
+ [
+ {
+ "node": "Auto reply",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Auto reply": {
+ "main": [
+ [
+ {
+ "node": "Send result",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ },
+ "Hand off to staff": {
+ "main": [
+ [
+ {
+ "node": "Send result",
+ "type": "main",
+ "index": 0
+ }
+ ]
+ ]
+ }
+ },
+ "active": false,
+ "settings": {
+ "executionOrder": "v1"
+ },
+ "pinData": {},
+ "id": "493c961026875d"
+}
\ No newline at end of file
diff --git a/Last3Mon/65/templates/TCA-DESIGN-TEMPLATE.md b/Last3Mon/65/templates/TCA-DESIGN-TEMPLATE.md
new file mode 100644
index 0000000..80b1104
--- /dev/null
+++ b/Last3Mon/65/templates/TCA-DESIGN-TEMPLATE.md
@@ -0,0 +1,48 @@
+# Trigger·Condition·Action 설계표
+
+- 작성자:
+- 업무 이름:
+
+## 1. Trigger (언제 시작하나)
+
+| 항목 | 내용 |
+| --- | --- |
+| 시작 방식 | 수동 / 웹훅·폼 / 일정 / 이벤트 중 선택 |
+| 시작할 때 받는 데이터 (필드) | |
+| 데이터가 비었거나 형식이 틀리면? | |
+
+## 2. Condition (어느 길로 갈까)
+
+| 번호 | 검사할 값 | 조건 | 참일 때 | 거짓일 때 |
+| --- | --- | --- | --- | --- |
+| C1 | | | | |
+| C2 | | | | |
+
+여러 갈래(Switch)가 필요하면:
+
+| 값 | 보낼 길 |
+| --- | --- |
+| | |
+| (그 밖의 값, default) | |
+
+## 3. Action (무엇을 하나)
+
+| 번호 | 길 | 할 일 | 노드 종류 (LLM·Tool·데이터 처리·저장·응답·사람 확인) |
+| --- | --- | --- | --- |
+| A1 | | | |
+| A2 | | | |
+
+## 4. 흐름 그림
+
+```mermaid
+flowchart LR
+ T(["Trigger"]) --> C{"Condition"}
+ C -->|"참"| A1["Action 1"]
+ C -->|"거짓"| A2["Action 2"]
+```
+
+## 5. 점검
+
+- [ ] 모든 길의 끝에 결과(응답·저장·알림)가 있다.
+- [ ] 정해진 값에 맞지 않는 경우를 받는 default 길이 있다.
+- [ ] LLM 출력으로 분기할 때 값을 정리하거나 검증하는 단계가 있다.
diff --git a/Last3Mon/65/workflow-lab/.gitignore b/Last3Mon/65/workflow-lab/.gitignore
new file mode 100644
index 0000000..e938d04
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/.gitignore
@@ -0,0 +1,5 @@
+runs/
+.miniflow-memory.json
+.venv/
+.pytest_cache/
+__pycache__/
diff --git a/Last3Mon/65/workflow-lab/README.md b/Last3Mon/65/workflow-lab/README.md
new file mode 100644
index 0000000..29e763b
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/README.md
@@ -0,0 +1,111 @@
+# workflow-lab (65일차): 조건 분기와 플랫폼 전환
+
+64일차 `miniflow`에 **조건 분기(condition·switch)** 와 **플랫폼 전환(n8n ↔ miniflow) 실행기**를 더한 버전입니다.
+
+노코드 워크플로우 도구는 화면에서 **노드를 놓고 선으로 연결**합니다. 이 실습에서는 같은 구조를 JSON 파일로 적고 `miniflow`로 실행합니다. 화면 대신 파일을 쓸 뿐, 노드·연결·데이터 전달이라는 개념은 같습니다.
+
+```mermaid
+flowchart LR
+ J["flows/*.json
노드와 연결 정의"] --> E["miniflow 엔진
순서 계산 · 실행"]
+ E --> L{{"LLM 노드
openai · ollama · mock · anthropic · gemini"}}
+ E --> T["Tool 노드
get_weather · search_faq"]
+ E --> M[("Memory 노드
.miniflow-memory.json")]
+ E --> R["runs/*.json
실행 기록(Trace)"]
+```
+
+## 1. 설치와 확인
+
+```bash
+cd Last3Mon/64/workflow-lab
+uv sync
+uv run miniflow tools
+uv run pytest -q
+```
+
+## 2. 명령어
+
+| 명령 | 하는 일 |
+| --- | --- |
+| `uv run miniflow run flows/01-llm-only.json -i text="..."` | 워크플로우 실행. 입력은 `-i 이름=값`으로 여러 개 전달 |
+| `uv run miniflow validate flows/02-llm-tool.json` | 실행하지 않고 구조만 검사, 실행 순서 출력 |
+| `uv run miniflow show flows/04-recommend-with-memory.json` | 워크플로우를 Mermaid 다이어그램으로 출력 |
+| `uv run miniflow tools` | 사용할 수 있는 Tool 목록 |
+| `uv run miniflow call request -i user=kim -i text="..."` | 같은 업무를 n8n → miniflow 순서로 실행 (앞 플랫폼이 실패하면 다음으로 전환) |
+| `uv run miniflow check` | 설정한 LLM에 연결되는지 확인 |
+| `uv run miniflow memory` / `--clear` | Memory 내용 보기 / 지우기 |
+
+실행할 때마다 각 노드의 입력·출력·소요 시간이 `runs/` 폴더에 JSON으로 저장됩니다.
+
+## 3. 노드 종류
+
+| type | 역할 | 필수 필드 |
+| --- | --- | --- |
+| `input` | 실행 시 받은 입력을 흐름에 넣음 | 없음 |
+| `llm` | 프롬프트를 LLM에 보내고 답을 받음 | `prompt` (선택: `system`, `temperature`, `mock`) |
+| `tool` | 등록된 함수를 호출해 데이터를 가져옴 | `tool`, `args` |
+| `memory_read` | 저장된 기억을 키로 읽음 | `key` |
+| `memory_write` | 기억을 키에 저장(기존 값과 병합) | `key`, `value` |
+| `output` | 최종 결과를 만듦 (분기마다 하나씩 둘 수 있음) | `value` |
+| `condition` | 조건을 검사해 `true`/`false` 중 한 길로 보냄 | `check` (`left`, `op`, `right`) |
+| `switch` | 값에 따라 여러 길 중 하나로 보냄. 맞는 값이 없으면 `default` | `value`, `cases` |
+
+`condition`의 `op`: `equals`, `not_equals`, `contains`, `empty`, `not_empty`, `in`, `gt`, `lt`
+
+분기 노드에서 나가는 연결에는 세 번째 값으로 길 이름을 적습니다. 실행 규칙은 다음과 같습니다.
+
+- 길 이름이 있는 연결은 **관문**입니다. 분기 노드가 다른 길을 골랐거나 분기 노드 자체가 건너뛰어졌으면, 연결된 노드는 실행되지 않고 실행 기록에 `skipped`로 남습니다.
+- 길 이름이 없는 일반 연결은 하나라도 이어지면 실행됩니다. 그래서 갈라졌던 두 길이 다시 만나는 노드는 정상적으로 실행됩니다.
+
+```json
+"edges": [["has_faq", "draft", "true"], ["has_faq", "hand_off", "false"], ["route", "team_device", "device"]]
+```
+
+## 4. 데이터 전달 규칙
+
+앞 노드의 결과는 `{{...}}`로 꺼내 씁니다.
+
+| 표현 | 의미 |
+| --- | --- |
+| `{{input.city}}` | 실행할 때 받은 입력 `city` |
+| `{{nodes.weather.output}}` | `weather` 노드의 결과 전체 |
+| `{{nodes.weather.output.temp_c}}` | 결과 안의 특정 값 |
+| `{{nodes.faq.output.0.answer}}` | 목록의 첫 번째 항목 안의 값 |
+
+## 5. LLM 선택
+
+`MINIFLOW_LLM`으로 LLM을 고릅니다. 수업 기본값은 **OpenAI API**(`gpt-4.1-mini`)이고, 설정은 `Last3Mon/.env` 한 곳에 둡니다. `miniflow`는 실행한 폴더에서 위로 올라가며 가장 가까운 `.env`를 읽습니다 (셸에서 `export`한 값이 있으면 그 값이 우선). `.env`는 `.gitignore`에 들어 있어 커밋되지 않습니다. 준비 방법은 [65일차 SETUP-N8N.md](../../65/SETUP-N8N.md) 2절을 참고하세요.
+
+| `MINIFLOW_LLM` | LLM | 필요한 것 |
+| --- | --- | --- |
+| `openai` (수업 기본) | OpenAI (`OPENAI_MODEL`, 기본 `gpt-4.1-mini`) | `.env`의 `OPENAI_API_KEY` |
+| `ollama` (대체) | 로컬 모델 (`OLLAMA_MODEL`, 기본 `gemma3:4b`) | 65일차 Compose의 Ollama, 모델 다운로드 |
+| `mock` (설정하지 않았을 때) | 노드의 `mock` 설정대로 정해진 답 | 없음 (자동 테스트, 키 없이 연습) |
+| `anthropic` | Anthropic Claude (`ANTHROPIC_MODEL`, 기본 `claude-opus-5-5`) | `uv sync --extra anthropic`, `ANTHROPIC_API_KEY` |
+| `gemini` | Google Gemini (`GEMINI_MODEL`) | `uv sync --extra gemini`, `GEMINI_API_KEY` |
+
+`MINIFLOW_LLM_FALLBACK=ollama`이면 OpenAI 호출이 실패할 때(키 없음, 크레딧 부족, 네트워크 오류) Ollama로 한 번 더 시도하고, 화면에 `[miniflow] openai failed (...); trying ollama`를 남깁니다.
+
+```bash
+cat ../../.env | grep -v API_KEY # 설정 확인 (키는 화면에 띄우지 않기)
+uv run miniflow check # 연결 확인: Reply (openai, …): ready
+uv run miniflow check # 대체 모델 확인 (한 번만 바꿔 실행)
+```
+
+## 6. 플랫폼 전환 실행 (`call`)
+
+`platforms.json`에 업무 이름(`request`)과 플랫폼별 실행 방법을 적어 둡니다. 실행 코드는 업무 이름만 알고, 어느 플랫폼에서 실행할지는 설정이 정합니다.
+
+```json
+{"workflows": {"request": {
+ "n8n": {"webhook": "ai-request"},
+ "miniflow": {"flow": "flows/06-request-with-condition.json"}
+}}}
+```
+
+| 환경 변수 | 의미 | 기본값 |
+| --- | --- | --- |
+| `WORKFLOW_PLATFORMS` | 시도할 플랫폼 순서 | `n8n,miniflow` |
+| `N8N_BASE_URL` | n8n 주소 | `http://localhost:5678` |
+| `N8N_TIMEOUT` | n8n 응답 대기 시간(초) | `120` |
+
+플랫폼을 추가할 때는 `src/miniflow/platforms.py`에 `run(workflow, inputs)`를 가진 어댑터 클래스를 만들고 `register_platform()`으로 등록합니다. `call`을 쓰는 코드는 바꾸지 않습니다.
diff --git a/Last3Mon/65/workflow-lab/data/faq.json b/Last3Mon/65/workflow-lab/data/faq.json
new file mode 100644
index 0000000..10eb7f1
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/data/faq.json
@@ -0,0 +1,14 @@
+[
+ {"id": "FAQ-001", "title": "비밀번호 재설정", "keywords": ["비밀번호", "패스워드", "password", "재설정", "초기화"],
+ "answer": "사내 포털 로그인 화면의 '비밀번호 찾기'에서 휴대폰 인증 후 새 비밀번호를 설정합니다."},
+ {"id": "FAQ-002", "title": "계정 잠김 해제", "keywords": ["계정", "잠김", "잠금", "로그인", "실패"],
+ "answer": "로그인 5회 실패 시 30분 동안 잠깁니다. 30분 후 다시 시도하거나 헬프데스크에 잠금 해제를 요청합니다."},
+ {"id": "FAQ-003", "title": "VPN 접속 오류", "keywords": ["vpn", "원격", "재택", "접속", "연결"],
+ "answer": "VPN 클라이언트를 최신 버전으로 업데이트하고, 인증서 만료 여부를 확인한 뒤 다시 접속합니다."},
+ {"id": "FAQ-004", "title": "프린터 출력 안 됨", "keywords": ["프린터", "출력", "인쇄", "용지"],
+ "answer": "프린터 전원과 네트워크 연결을 확인하고, 인쇄 대기열을 비운 뒤 다시 출력합니다."},
+ {"id": "FAQ-005", "title": "메일함 용량 초과", "keywords": ["메일", "용량", "메일함", "첨부"],
+ "answer": "오래된 메일과 큰 첨부 파일을 보관함으로 옮기거나 삭제해 용량을 확보합니다."},
+ {"id": "FAQ-006", "title": "소프트웨어 설치 요청", "keywords": ["설치", "소프트웨어", "프로그램", "라이선스"],
+ "answer": "IT 포털의 '소프트웨어 신청' 메뉴에서 승인 요청을 올리면 승인 후 원격으로 설치됩니다."}
+]
diff --git a/Last3Mon/65/workflow-lab/data/weather.json b/Last3Mon/65/workflow-lab/data/weather.json
new file mode 100644
index 0000000..20fe5fc
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/data/weather.json
@@ -0,0 +1,6 @@
+{
+ "서울": {"condition": "맑음", "temp_c": 19, "rain_chance": 10, "air": "보통"},
+ "부산": {"condition": "흐림", "temp_c": 21, "rain_chance": 40, "air": "좋음"},
+ "제주": {"condition": "비", "temp_c": 20, "rain_chance": 80, "air": "좋음"},
+ "강릉": {"condition": "맑음", "temp_c": 17, "rain_chance": 0, "air": "좋음"}
+}
diff --git a/Last3Mon/65/workflow-lab/flows/01-llm-only.json b/Last3Mon/65/workflow-lab/flows/01-llm-only.json
new file mode 100644
index 0000000..14268f0
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/flows/01-llm-only.json
@@ -0,0 +1,14 @@
+{
+ "name": "01 LLM only",
+ "description": "입력 → LLM → 출력. 가장 단순한 AI 워크플로우",
+ "inputs": ["text"],
+ "nodes": [
+ {"id": "start", "type": "input"},
+ {"id": "summarize", "type": "llm",
+ "system": "You are a helpful assistant that writes concise Korean summaries.",
+ "prompt": "다음 글을 3줄 이내의 한국어로 요약해 주세요.\n\n{{input.text}}",
+ "mock": {"template": "(Mock 응답) 실제 LLM을 연결하면 아래 글이 3줄로 요약됩니다.\n원문: {{input.text}}"}},
+ {"id": "result", "type": "output", "value": "{{nodes.summarize.output}}"}
+ ],
+ "edges": [["start", "summarize"], ["summarize", "result"]]
+}
diff --git a/Last3Mon/65/workflow-lab/flows/02-llm-tool.json b/Last3Mon/65/workflow-lab/flows/02-llm-tool.json
new file mode 100644
index 0000000..ddd9a39
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/flows/02-llm-tool.json
@@ -0,0 +1,15 @@
+{
+ "name": "02 LLM + Tool",
+ "description": "Tool이 가져온 데이터를 LLM이 근거로 사용해 답변",
+ "inputs": ["city", "question"],
+ "nodes": [
+ {"id": "start", "type": "input"},
+ {"id": "weather", "type": "tool", "tool": "get_weather", "args": {"city": "{{input.city}}"}},
+ {"id": "answer", "type": "llm",
+ "system": "Answer only from the given weather data. Reply in Korean.",
+ "prompt": "날씨 데이터: {{nodes.weather.output}}\n질문: {{input.question}}",
+ "mock": {"template": "{{nodes.weather.output.city}}의 오늘 날씨는 {{nodes.weather.output.condition}}, 기온 {{nodes.weather.output.temp_c}}도, 강수 확률 {{nodes.weather.output.rain_chance}}%입니다."}},
+ {"id": "result", "type": "output", "value": "{{nodes.answer.output}}"}
+ ],
+ "edges": [["start", "weather"], ["weather", "answer"], ["answer", "result"]]
+}
diff --git a/Last3Mon/65/workflow-lab/flows/03-save-profile.json b/Last3Mon/65/workflow-lab/flows/03-save-profile.json
new file mode 100644
index 0000000..171f9e8
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/flows/03-save-profile.json
@@ -0,0 +1,12 @@
+{
+ "name": "03 Save profile to memory",
+ "description": "사용자 선호를 Memory에 저장 (다음 실행에서 다시 사용)",
+ "inputs": ["user", "preference"],
+ "nodes": [
+ {"id": "start", "type": "input"},
+ {"id": "remember", "type": "memory_write", "key": "user:{{input.user}}",
+ "value": {"preference": "{{input.preference}}"}},
+ {"id": "result", "type": "output", "value": {"saved_for": "{{input.user}}", "memory": "{{nodes.remember.output}}"}}
+ ],
+ "edges": [["start", "remember"], ["remember", "result"]]
+}
diff --git a/Last3Mon/65/workflow-lab/flows/04-recommend-with-memory.json b/Last3Mon/65/workflow-lab/flows/04-recommend-with-memory.json
new file mode 100644
index 0000000..6832320
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/flows/04-recommend-with-memory.json
@@ -0,0 +1,19 @@
+{
+ "name": "04 LLM + Tool + Memory",
+ "description": "Memory(선호) + Tool(날씨) → LLM 추천 → Memory(방문 기록) 갱신",
+ "inputs": ["user", "city"],
+ "nodes": [
+ {"id": "start", "type": "input"},
+ {"id": "recall", "type": "memory_read", "key": "user:{{input.user}}"},
+ {"id": "weather", "type": "tool", "tool": "get_weather", "args": {"city": "{{input.city}}"}},
+ {"id": "recommend", "type": "llm",
+ "system": "You are a travel assistant. Use the user's memory and the weather. Reply in Korean, 2 sentences.",
+ "prompt": "사용자 기억: {{nodes.recall.output}}\n날씨: {{nodes.weather.output}}\n오늘 {{input.city}}에서 할 일을 추천해 주세요.",
+ "mock": {"template": "{{input.user}}님은 '{{nodes.recall.output.preference}}'을(를) 좋아하시죠. {{input.city}}은(는) 오늘 {{nodes.weather.output.condition}}이니 그에 맞는 일정을 추천합니다."}},
+ {"id": "remember", "type": "memory_write", "key": "user:{{input.user}}",
+ "value": {"last_city": "{{input.city}}", "last_recommendation": "{{nodes.recommend.output}}"}},
+ {"id": "result", "type": "output", "value": "{{nodes.recommend.output}}"}
+ ],
+ "edges": [["start", "recall"], ["start", "weather"], ["recall", "recommend"], ["weather", "recommend"],
+ ["recommend", "remember"], ["remember", "result"]]
+}
diff --git a/Last3Mon/65/workflow-lab/flows/05-tech-support-ticket.json b/Last3Mon/65/workflow-lab/flows/05-tech-support-ticket.json
new file mode 100644
index 0000000..8b89684
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/flows/05-tech-support-ticket.json
@@ -0,0 +1,30 @@
+{
+ "name": "05 Tech support ticket",
+ "description": "업무 자동화 시나리오: 문의 접수 → 분류 → FAQ 검색 → 답변 초안 → 이력 저장",
+ "inputs": ["user", "ticket"],
+ "nodes": [
+ {"id": "start", "type": "input"},
+ {"id": "history", "type": "memory_read", "key": "ticket:{{input.user}}"},
+ {"id": "classify", "type": "llm",
+ "system": "Classify the ticket into one of: account, network, device, software, other. Reply with the label only.",
+ "prompt": "문의: {{input.ticket}}",
+ "mock": {"rules": [
+ {"if_contains": ["비밀번호", "계정", "로그인", "잠김"], "then": "account"},
+ {"if_contains": ["vpn", "인터넷", "와이파이", "접속"], "then": "network"},
+ {"if_contains": ["프린터", "모니터", "키보드"], "then": "device"},
+ {"if_contains": ["설치", "프로그램", "메일"], "then": "software"}
+ ], "default": "other"}},
+ {"id": "faq", "type": "tool", "tool": "search_faq", "args": {"query": "{{input.ticket}}", "top_k": 2}},
+ {"id": "draft", "type": "llm",
+ "system": "Write a polite Korean reply using only the FAQ results. Mention the FAQ id.",
+ "prompt": "문의: {{input.ticket}}\n분류: {{nodes.classify.output}}\n이전 문의: {{nodes.history.output}}\nFAQ 검색 결과: {{nodes.faq.output}}",
+ "mock": {"template": "안녕하세요 {{input.user}}님. 문의하신 내용은 [{{nodes.faq.output.0.title}}]에 해당합니다. {{nodes.faq.output.0.answer}} (참고: {{nodes.faq.output.0.id}})"}},
+ {"id": "log", "type": "memory_write", "key": "ticket:{{input.user}}",
+ "value": {"last_ticket": "{{input.ticket}}", "last_category": "{{nodes.classify.output}}"}},
+ {"id": "result", "type": "output",
+ "value": {"category": "{{nodes.classify.output}}", "faq_id": "{{nodes.faq.output.0.id}}", "reply": "{{nodes.draft.output}}"}}
+ ],
+ "edges": [["start", "history"], ["start", "classify"], ["start", "faq"],
+ ["history", "draft"], ["classify", "draft"], ["faq", "draft"],
+ ["draft", "log"], ["log", "result"]]
+}
diff --git a/Last3Mon/65/workflow-lab/flows/06-request-with-condition.json b/Last3Mon/65/workflow-lab/flows/06-request-with-condition.json
new file mode 100644
index 0000000..907c79f
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/flows/06-request-with-condition.json
@@ -0,0 +1,38 @@
+{
+ "name": "06 Request flow with condition",
+ "description": "Trigger(입력) → 분류·FAQ 검색 → Condition(FAQ 있음?) → Action(자동 답변 또는 담당자 전달)",
+ "inputs": ["user", "text"],
+ "nodes": [
+ {"id": "start", "type": "input"},
+ {"id": "history", "type": "memory_read", "key": "request:{{input.user}}"},
+ {"id": "classify", "type": "llm",
+ "system": "Classify the IT request into exactly one of: account, network, device, software, other. Reply with the label only.",
+ "prompt": "문의: {{input.text}}",
+ "mock": {"rules": [
+ {"if_contains": ["비밀번호", "계정", "로그인", "잠김", "잠겨"], "then": "account"},
+ {"if_contains": ["vpn", "인터넷", "와이파이", "접속"], "then": "network"},
+ {"if_contains": ["프린터", "모니터", "키보드"], "then": "device"},
+ {"if_contains": ["설치", "프로그램", "메일"], "then": "software"}
+ ], "default": "other"}},
+ {"id": "faq", "type": "tool", "tool": "search_faq", "args": {"query": "{{input.text}}", "top_k": 1}},
+ {"id": "log", "type": "memory_write", "key": "request:{{input.user}}",
+ "value": {"last_text": "{{input.text}}", "last_category": "{{nodes.classify.output}}"}},
+ {"id": "has_faq", "type": "condition", "check": {"left": "{{nodes.faq.output}}", "op": "not_empty"}},
+ {"id": "draft", "type": "llm",
+ "system": "Write a polite 2-sentence Korean reply using only the FAQ answer. End with the FAQ id in parentheses.",
+ "prompt": "문의: {{input.text}}\n이전 문의: {{nodes.history.output}}\nFAQ: {{nodes.faq.output}}",
+ "mock": {"template": "{{input.user}}님, {{nodes.faq.output.0.answer}} ({{nodes.faq.output.0.id}})"}},
+ {"id": "auto_reply", "type": "output",
+ "value": {"category": "{{nodes.classify.output}}", "faq_id": "{{nodes.faq.output.0.id}}", "route": "자동 답변", "reply": "{{nodes.draft.output}}"}},
+ {"id": "hand_off", "type": "output",
+ "value": {"category": "{{nodes.classify.output}}", "faq_id": "", "route": "담당자 확인", "reply": "관련 안내를 찾지 못해 담당자가 확인 후 답변드리겠습니다."}}
+ ],
+ "edges": [
+ ["start", "history"], ["start", "classify"], ["start", "faq"],
+ ["classify", "log"],
+ ["faq", "has_faq"], ["classify", "has_faq"],
+ ["has_faq", "draft", "true"], ["history", "draft"],
+ ["draft", "auto_reply"],
+ ["has_faq", "hand_off", "false"]
+ ]
+}
diff --git a/Last3Mon/65/workflow-lab/flows/07-route-by-category.json b/Last3Mon/65/workflow-lab/flows/07-route-by-category.json
new file mode 100644
index 0000000..76b5dba
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/flows/07-route-by-category.json
@@ -0,0 +1,29 @@
+{
+ "name": "07 Route by category",
+ "description": "LLM 분류 결과로 Switch 분기 → 담당 팀 배정 (정해진 값이 아니면 default)",
+ "inputs": ["text"],
+ "nodes": [
+ {"id": "start", "type": "input"},
+ {"id": "classify", "type": "llm",
+ "system": "Classify the IT request into exactly one of: account, network, device, software, other. Reply with the label only.",
+ "prompt": "문의: {{input.text}}",
+ "mock": {"rules": [
+ {"if_contains": ["비밀번호", "계정", "로그인", "잠김", "잠겨"], "then": "account"},
+ {"if_contains": ["vpn", "인터넷", "와이파이", "접속"], "then": "network"},
+ {"if_contains": ["프린터", "모니터", "키보드"], "then": "device"},
+ {"if_contains": ["설치", "프로그램", "메일"], "then": "software"}
+ ], "default": "other"}},
+ {"id": "route", "type": "switch", "value": "{{nodes.classify.output}}", "cases": ["account", "network", "device", "software"]},
+ {"id": "team_account", "type": "output", "value": {"category": "account", "team": "계정 관리 담당"}},
+ {"id": "team_network", "type": "output", "value": {"category": "network", "team": "네트워크 담당"}},
+ {"id": "team_device", "type": "output", "value": {"category": "device", "team": "장비 지원 담당"}},
+ {"id": "team_software", "type": "output", "value": {"category": "software", "team": "소프트웨어 담당"}},
+ {"id": "team_default", "type": "output", "value": {"category": "{{nodes.classify.output}}", "team": "IT 문의 접수 창구"}}
+ ],
+ "edges": [
+ ["start", "classify"], ["classify", "route"],
+ ["route", "team_account", "account"], ["route", "team_network", "network"],
+ ["route", "team_device", "device"], ["route", "team_software", "software"],
+ ["route", "team_default", "default"]
+ ]
+}
diff --git a/Last3Mon/65/workflow-lab/platforms.json b/Last3Mon/65/workflow-lab/platforms.json
new file mode 100644
index 0000000..a930353
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/platforms.json
@@ -0,0 +1,9 @@
+{
+ "n8n": {"base_url": "http://localhost:5678", "timeout": 120},
+ "workflows": {
+ "request": {
+ "n8n": {"webhook": "ai-request"},
+ "miniflow": {"flow": "flows/06-request-with-condition.json"}
+ }
+ }
+}
diff --git a/Last3Mon/65/workflow-lab/pyproject.toml b/Last3Mon/65/workflow-lab/pyproject.toml
new file mode 100644
index 0000000..da7e3f6
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/pyproject.toml
@@ -0,0 +1,28 @@
+[project]
+name = "miniflow"
+version = "0.1.0"
+description = "A tiny JSON-defined AI workflow runner for learning LLM, Tool and Memory nodes"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = ["openai>=1.40"] # course default LLM (key in .env)
+
+[project.optional-dependencies]
+gemini = ["google-genai>=1.0"]
+openai = ["openai>=1.40"]
+anthropic = ["anthropic>=1.13"]
+
+[project.scripts]
+miniflow = "miniflow.cli:main"
+
+[dependency-groups]
+dev = ["pytest>=8.0"]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src/miniflow"]
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/__init__.py b/Last3Mon/65/workflow-lab/src/miniflow/__init__.py
new file mode 100644
index 0000000..b4e5140
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/__init__.py
@@ -0,0 +1,5 @@
+"""miniflow: run small AI workflows described as JSON nodes and edges."""
+
+from miniflow.engine import Workflow, WorkflowError, load_workflow, run_workflow
+
+__all__ = ["Workflow", "WorkflowError", "load_workflow", "run_workflow"]
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/cli.py b/Last3Mon/65/workflow-lab/src/miniflow/cli.py
new file mode 100644
index 0000000..a269ae6
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/cli.py
@@ -0,0 +1,158 @@
+"""Command line entry point: uv run miniflow ..."""
+
+import argparse
+import json
+import sys
+from datetime import datetime
+from pathlib import Path
+
+from miniflow import memory, tools
+from miniflow.engine import WorkflowError, load_workflow, run_workflow
+
+
+def parse_inputs(pairs: list[str]) -> dict[str, str]:
+ inputs = {}
+ for pair in pairs:
+ if "=" not in pair:
+ raise WorkflowError(f"Input must look like name=value, got '{pair}'")
+ name, value = pair.split("=", 1)
+ inputs[name.strip()] = value
+ return inputs
+
+
+def cmd_run(args: argparse.Namespace) -> int:
+ workflow = load_workflow(args.flow)
+ print(f"Workflow: {workflow.name}")
+ if workflow.description:
+ print(f" {workflow.description}")
+ print("-" * 72)
+ report = run_workflow(workflow, parse_inputs(args.input))
+ print("-" * 72)
+ print(f"Status: {report['status']}")
+ print("Result:")
+ result = report["result"]
+ print(result if isinstance(result, str) else json.dumps(result, ensure_ascii=False, indent=2))
+
+ runs = Path("runs")
+ runs.mkdir(exist_ok=True)
+ log_file = runs / f"{datetime.now():%Y%m%d-%H%M%S}-{Path(args.flow).stem}.json"
+ log_file.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8")
+ print(f"Trace saved: {log_file}")
+ return 0 if report["status"] == "completed" else 1
+
+
+def cmd_validate(args: argparse.Namespace) -> int:
+ workflow = load_workflow(args.flow)
+ print(f"OK: {workflow.name} ({len(workflow.nodes)} nodes, {len(workflow.edges)} edges)")
+ print("Execution order: " + " -> ".join(workflow.order()))
+ return 0
+
+
+def cmd_show(args: argparse.Namespace) -> int:
+ print(load_workflow(args.flow).to_mermaid())
+ return 0
+
+
+def cmd_tools(_: argparse.Namespace) -> int:
+ for name, doc in tools.describe_tools():
+ print(f"{name:<14} {doc}")
+ return 0
+
+
+def cmd_check(_: argparse.Namespace) -> int:
+ import os
+ import time
+
+ from miniflow import llm
+
+ provider = os.getenv("MINIFLOW_LLM", "mock").lower()
+ print(f"MINIFLOW_LLM : {provider}")
+ print(f".env : {llm.envfile.LOADED[0] if llm.envfile.LOADED else '(none)'}")
+ if provider == "openai":
+ print(f"OPENAI_MODEL : {os.getenv('OPENAI_MODEL', 'gpt-4.1-mini')}")
+ print(f"API key : {'set' if os.getenv('OPENAI_API_KEY') else 'MISSING (put OPENAI_API_KEY in .env)'}")
+ if provider == "ollama" or os.getenv("MINIFLOW_LLM_FALLBACK", "").lower() == "ollama":
+ print(f"OLLAMA_HOST : {os.getenv('OLLAMA_HOST', 'http://localhost:11434')}")
+ print(f"OLLAMA_MODEL : {os.getenv('OLLAMA_MODEL', 'gemma3:4b')}")
+ if os.getenv("MINIFLOW_LLM_FALLBACK"):
+ print(f"FALLBACK : {os.getenv('MINIFLOW_LLM_FALLBACK')}")
+ started = time.perf_counter()
+ try:
+ reply, used = llm.complete({"temperature": 0}, "Reply with exactly one word: ready", "", {})
+ except llm.LLMError as error:
+ print(f"FAILED: {error}")
+ return 1
+ print(f"Reply ({used}, {time.perf_counter() - started:.1f}s): {reply[:80]}")
+ return 0
+
+
+def cmd_call(args: argparse.Namespace) -> int:
+ import os
+
+ from miniflow.platforms import FailoverRunner, PlatformError
+
+ order = [name.strip() for name in (args.platforms or os.getenv("WORKFLOW_PLATFORMS", "n8n,miniflow")).split(",")]
+ print(f"Workflow: {args.workflow} platforms: {' -> '.join(order)}")
+ try:
+ report = FailoverRunner(order).run(args.workflow, parse_inputs(args.input))
+ except PlatformError as error:
+ print(f"FAILED: {error}")
+ return 1
+ for attempt in report["attempts"]:
+ detail = attempt.get("error", "")
+ print(f" {attempt['platform']:<10} {attempt['status']:<7} {attempt['ms']:>8}ms {detail}")
+ print(f"Served by: {report['served_by']}")
+ print(json.dumps(report["result"], ensure_ascii=False, indent=2))
+ return 0
+
+
+def cmd_memory(args: argparse.Namespace) -> int:
+ if args.clear:
+ memory.clear()
+ print("Memory cleared")
+ return 0
+ path = memory.memory_path()
+ print(path.read_text(encoding="utf-8") if path.exists() else "{}")
+ return 0
+
+
+def main(argv: list[str] | None = None) -> int:
+ parser = argparse.ArgumentParser(prog="miniflow", description="Run JSON-defined AI workflows")
+ sub = parser.add_subparsers(dest="command", required=True)
+
+ run = sub.add_parser("run", help="run a workflow file")
+ run.add_argument("flow")
+ run.add_argument("--input", "-i", action="append", default=[], metavar="NAME=VALUE")
+ run.set_defaults(func=cmd_run)
+
+ validate = sub.add_parser("validate", help="check a workflow file without running it")
+ validate.add_argument("flow")
+ validate.set_defaults(func=cmd_validate)
+
+ show = sub.add_parser("show", help="print the workflow as a Mermaid diagram")
+ show.add_argument("flow")
+ show.set_defaults(func=cmd_show)
+
+ sub.add_parser("tools", help="list available tools").set_defaults(func=cmd_tools)
+ sub.add_parser("check", help="check the configured LLM provider").set_defaults(func=cmd_check)
+
+ call = sub.add_parser("call", help="run a business workflow on platforms with failover")
+ call.add_argument("workflow", help="workflow name in platforms.json, e.g. request")
+ call.add_argument("--input", "-i", action="append", default=[], metavar="NAME=VALUE")
+ call.add_argument("--platforms", help="comma-separated order, default: $WORKFLOW_PLATFORMS or n8n,miniflow")
+ call.set_defaults(func=cmd_call)
+
+ mem = sub.add_parser("memory", help="show or clear the memory store")
+ mem.add_argument("--clear", action="store_true")
+ mem.set_defaults(func=cmd_memory)
+
+ args = parser.parse_args(argv)
+ try:
+ return args.func(args)
+ except (WorkflowError, FileNotFoundError, json.JSONDecodeError) as error:
+ print(f"Error: {error}", file=sys.stderr)
+ return 2
+
+
+if __name__ == "__main__":
+ raise SystemExit(main())
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/engine.py b/Last3Mon/65/workflow-lab/src/miniflow/engine.py
new file mode 100644
index 0000000..3e3bcc0
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/engine.py
@@ -0,0 +1,255 @@
+"""Load, validate and run a workflow made of nodes and edges.
+
+Day 65 adds branching: `condition` (true/false) and `switch` (one case per value)
+nodes, and edges that carry a branch label: ["check", "draft", "true"].
+"""
+
+import json
+import time
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any
+
+from miniflow import llm, memory, tools
+from miniflow.template import render
+
+NODE_TYPES = {"input", "llm", "tool", "memory_read", "memory_write", "output", "condition", "switch"}
+BRANCH_TYPES = {"condition", "switch"}
+REQUIRED_FIELDS = {
+ "llm": ["prompt"],
+ "tool": ["tool"],
+ "memory_read": ["key"],
+ "memory_write": ["key", "value"],
+ "output": ["value"],
+ "condition": ["check"],
+ "switch": ["value", "cases"],
+}
+CHECK_OPS = {"equals", "not_equals", "contains", "not_empty", "empty", "in", "gt", "lt"}
+
+Edge = tuple[str, str, str | None]
+
+
+class WorkflowError(ValueError):
+ pass
+
+
+@dataclass
+class Workflow:
+ name: str
+ nodes: dict[str, dict[str, Any]]
+ edges: list[Edge]
+ description: str = ""
+ inputs: list[str] = field(default_factory=list)
+
+ def order(self) -> list[str]:
+ """Topological order of node ids (Kahn's algorithm, file order breaks ties)."""
+ indegree = {node_id: 0 for node_id in self.nodes}
+ for _, target, _ in self.edges:
+ indegree[target] += 1
+ ready = [node_id for node_id in self.nodes if indegree[node_id] == 0]
+ ordered = []
+ while ready:
+ current = ready.pop(0)
+ ordered.append(current)
+ for source, target, _ in self.edges:
+ if source == current:
+ indegree[target] -= 1
+ if indegree[target] == 0:
+ ready.append(target)
+ if len(ordered) != len(self.nodes):
+ raise WorkflowError("Edges contain a cycle. Workflows must flow in one direction.")
+ return ordered
+
+ def to_mermaid(self) -> str:
+ shapes = {
+ "input": ('[/"', '"/]'),
+ "llm": ('{{"', '"}}'),
+ "tool": ('["', '"]'),
+ "memory_read": ('[("', '")]'),
+ "memory_write": ('[("', '")]'),
+ "output": ('[\\"', '"\\]'),
+ "condition": ('{"', '"}'),
+ "switch": ('{"', '"}'),
+ }
+ lines = ["flowchart LR"]
+ for node_id, node in self.nodes.items():
+ left, right = shapes[node["type"]]
+ label = f"{node_id}
{node['type']}"
+ if node["type"] == "tool":
+ label += f": {node['tool']}"
+ lines.append(f" {node_id}{left}{label}{right}")
+ for source, target, branch in self.edges:
+ arrow = f" -->|{branch}| " if branch is not None else " --> "
+ lines.append(f" {source}{arrow}{target}")
+ return "\n".join(lines)
+
+
+def _parse_edge(raw: list[Any]) -> Edge:
+ if not isinstance(raw, list) or len(raw) not in (2, 3):
+ raise WorkflowError(f"Edge must be [source, target] or [source, target, branch]: {raw}")
+ return (raw[0], raw[1], str(raw[2]) if len(raw) == 3 else None)
+
+
+def load_workflow(path: str | Path) -> Workflow:
+ data = json.loads(Path(path).read_text(encoding="utf-8"))
+ nodes: dict[str, dict[str, Any]] = {}
+ for node in data.get("nodes", []):
+ node_id = node.get("id")
+ if not node_id:
+ raise WorkflowError("Every node needs an 'id'")
+ if node_id in nodes:
+ raise WorkflowError(f"Duplicate node id: {node_id}")
+ if node.get("type") not in NODE_TYPES:
+ raise WorkflowError(f"Node '{node_id}' has unknown type '{node.get('type')}'. Use one of {sorted(NODE_TYPES)}")
+ missing = [name for name in REQUIRED_FIELDS.get(node["type"], []) if name not in node]
+ if missing:
+ raise WorkflowError(f"Node '{node_id}' ({node['type']}) is missing: {', '.join(missing)}")
+ if node["type"] == "tool" and node["tool"] not in tools.TOOLS:
+ raise WorkflowError(f"Node '{node_id}' uses unknown tool '{node['tool']}'")
+ if node["type"] == "condition" and node["check"].get("op") not in CHECK_OPS:
+ raise WorkflowError(f"Node '{node_id}' uses unknown check op. Use one of {sorted(CHECK_OPS)}")
+ nodes[node_id] = node
+ if not nodes:
+ raise WorkflowError("Workflow has no nodes")
+
+ edges = [_parse_edge(edge) for edge in data.get("edges", [])]
+ for source, target, branch in edges:
+ for node_id in (source, target):
+ if node_id not in nodes:
+ raise WorkflowError(f"Edge {source} -> {target} points to unknown node '{node_id}'")
+ kind = nodes[source]["type"]
+ if branch is not None and kind not in BRANCH_TYPES:
+ raise WorkflowError(f"Edge {source} -> {target} has branch '{branch}' but '{source}' is a {kind} node")
+ if kind == "condition" and branch not in ("true", "false"):
+ raise WorkflowError(f"Edge {source} -> {target} needs branch 'true' or 'false'")
+ if kind == "switch" and branch not in [*map(str, nodes[source]["cases"]), "default"]:
+ raise WorkflowError(f"Edge {source} -> {target} needs a branch from cases {nodes[source]['cases']} or 'default'")
+ workflow = Workflow(
+ name=data.get("name", Path(path).stem),
+ description=data.get("description", ""),
+ inputs=data.get("inputs", []),
+ nodes=nodes,
+ edges=edges,
+ )
+ workflow.order()
+ return workflow
+
+
+def evaluate_check(check: dict[str, Any], context: dict[str, Any]) -> bool:
+ left = render(check.get("left", ""), context)
+ right = render(check.get("right"), context)
+ op = check["op"]
+ if op == "equals":
+ return left == right
+ if op == "not_equals":
+ return left != right
+ if op == "contains":
+ return str(right) in str(left)
+ if op == "empty":
+ return left in (None, "", [], {})
+ if op == "not_empty":
+ return left not in (None, "", [], {})
+ if op == "in":
+ return left in (right or [])
+ if op == "gt":
+ return float(left) > float(right)
+ if op == "lt":
+ return float(left) < float(right)
+ raise WorkflowError(f"Unsupported check op: {op}")
+
+
+def run_node(node: dict[str, Any], context: dict[str, Any]) -> tuple[Any, dict[str, Any]]:
+ """Execute one node. Returns (output, extra trace info)."""
+ kind = node["type"]
+ if kind == "input":
+ return context["input"], {}
+ if kind == "llm":
+ system = str(render(node.get("system", ""), context))
+ prompt = str(render(node["prompt"], context))
+ reply, provider = llm.complete(node, prompt, system, context)
+ return reply, {"provider": provider, "prompt": prompt}
+ if kind == "tool":
+ args = render(node.get("args", {}), context)
+ return tools.call_tool(node["tool"], args), {"args": args}
+ if kind == "memory_read":
+ key = str(render(node["key"], context))
+ return memory.read(key), {"key": key}
+ if kind == "memory_write":
+ key = str(render(node["key"], context))
+ return memory.write(key, render(node["value"], context)), {"key": key}
+ if kind == "output":
+ return render(node["value"], context), {}
+ if kind == "condition":
+ passed = evaluate_check(node["check"], context)
+ return {"result": passed, "branch": "true" if passed else "false"}, {}
+ if kind == "switch":
+ value = render(node["value"], context)
+ cases = [str(case) for case in node["cases"]]
+ branch = str(value) if str(value) in cases else "default"
+ return {"value": value, "branch": branch}, {}
+ raise WorkflowError(f"Unsupported node type: {kind}")
+
+
+def _is_active(node_id: str, workflow: Workflow, status: dict[str, str], context: dict[str, Any]) -> bool:
+ """Decide whether a node runs.
+
+ - A branch edge works as a gate: if its source was skipped or chose another
+ branch, the node is skipped.
+ - Otherwise the node runs if at least one incoming edge is taken, so a node
+ where two exclusive branches meet again (plain edges) still runs.
+ """
+ incoming = [(source, branch) for source, target, branch in workflow.edges if target == node_id]
+ if not incoming:
+ return True
+ taken = False
+ for source, branch in incoming:
+ ran = status.get(source) == "ok"
+ if branch is not None:
+ if not ran or context["nodes"][source]["output"].get("branch") != branch:
+ return False
+ taken = True
+ elif ran:
+ taken = True
+ return taken
+
+
+def run_workflow(workflow: Workflow, inputs: dict[str, Any], verbose: bool = True) -> dict[str, Any]:
+ missing = [name for name in workflow.inputs if name not in inputs]
+ if missing:
+ raise WorkflowError(f"Missing inputs: {', '.join(missing)} (pass with --input name=value)")
+
+ context: dict[str, Any] = {"input": inputs, "nodes": {}}
+ trace: list[dict[str, Any]] = []
+ status: dict[str, str] = {}
+ order = workflow.order()
+ result: Any = None
+ for index, node_id in enumerate(order, start=1):
+ node = workflow.nodes[node_id]
+ step = {"step": index, "id": node_id, "type": node["type"]}
+ if not _is_active(node_id, workflow, status, context):
+ status[node_id] = "skipped"
+ step["status"] = "skipped"
+ trace.append(step)
+ if verbose:
+ print(f"[{index}/{len(order)}] {node_id:<14} {node['type']:<12} skipped (branch not taken)")
+ continue
+ started = time.perf_counter()
+ try:
+ output, extra = run_node(node, context)
+ except Exception as error:
+ step.update(status="failed", error=f"{type(error).__name__}: {error}")
+ trace.append(step)
+ if verbose:
+ print(f"[{index}/{len(order)}] {node_id:<14} {node['type']:<12} FAILED {step['error']}")
+ return {"workflow": workflow.name, "status": "failed", "result": None, "trace": trace}
+ elapsed = round((time.perf_counter() - started) * 1000, 1)
+ context["nodes"][node_id] = {"output": output}
+ status[node_id] = "ok"
+ step.update(status="ok", ms=elapsed, output=output, **extra)
+ trace.append(step)
+ if node["type"] == "output":
+ result = output
+ if verbose:
+ preview = json.dumps(output, ensure_ascii=False)
+ print(f"[{index}/{len(order)}] {node_id:<14} {node['type']:<12} ok {elapsed:>6}ms {preview[:70]}")
+ return {"workflow": workflow.name, "status": "completed", "result": result, "trace": trace}
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/envfile.py b/Last3Mon/65/workflow-lab/src/miniflow/envfile.py
new file mode 100644
index 0000000..ca0e044
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/envfile.py
@@ -0,0 +1,50 @@
+"""Load settings from the nearest .env file (KEY=VALUE lines, no extra package needed).
+
+Search order: the current folder and its parents, then the folders above this package
+(so one Last3Mon/.env serves every day). Only the nearest file is read, and variables
+already set in the shell win. Set MINIFLOW_DOTENV=0 to skip (the tests do this).
+The .env file holds API keys: it is listed in .gitignore and must never be committed.
+"""
+
+import os
+from pathlib import Path
+
+LOADED: list[str] = [] # the .env file that was read, if any
+
+
+def parse(text: str) -> dict[str, str]:
+ values = {}
+ for line in text.splitlines():
+ line = line.strip()
+ if not line or line.startswith("#") or "=" not in line:
+ continue
+ key, value = line.split("=", 1)
+ key = key.removeprefix("export ").strip()
+ value = value.strip()
+ if len(value) >= 2 and value[0] == value[-1] and value[0] in "\"'":
+ value = value[1:-1]
+ elif " #" in value:
+ value = value.split(" #", 1)[0].rstrip()
+ values[key] = value
+ return values
+
+
+def candidates() -> list[Path]:
+ paths: list[Path] = []
+ for start in (Path.cwd(), Path(__file__).resolve().parent):
+ for folder in (start, *start.parents):
+ if folder / ".env" not in paths:
+ paths.append(folder / ".env")
+ return paths
+
+
+def load() -> Path | None:
+ if os.getenv("MINIFLOW_DOTENV", "1") == "0":
+ return None
+ for path in candidates():
+ if path.is_file():
+ for key, value in parse(path.read_text(encoding="utf-8")).items():
+ os.environ.setdefault(key, value)
+ LOADED.append(str(path))
+ return path
+ return None
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/llm.py b/Last3Mon/65/workflow-lab/src/miniflow/llm.py
new file mode 100644
index 0000000..eb8a51c
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/llm.py
@@ -0,0 +1,192 @@
+"""LLM providers: mock (default, no API key), openai (course default, key in .env), ollama (local), anthropic, gemini.
+
+Select with MINIFLOW_LLM (usually set in .env). MINIFLOW_LLM_FALLBACK=ollama retries a failed call locally.
+"""
+
+import json
+import os
+import sys
+import time
+import urllib.error
+import urllib.request
+from typing import Any
+
+from miniflow import envfile
+from miniflow.template import render
+
+envfile.load() # OPENAI_API_KEY and other settings from .env
+
+
+class LLMError(RuntimeError):
+ pass
+
+
+def mock_reply(prompt: str, mock: dict[str, Any] | None, context: dict[str, Any]) -> str:
+ """Deterministic reply so the workflow runs without any API key.
+
+ mock.rules: first rule whose keywords appear in the prompt wins.
+ mock.template: rendered with the workflow context.
+ """
+ mock = mock or {}
+ lowered = prompt.lower()
+ for rule in mock.get("rules", []):
+ if any(word.lower() in lowered for word in rule.get("if_contains", [])):
+ return str(render(rule["then"], context))
+ if "template" in mock:
+ return str(render(mock["template"], context))
+ if "default" in mock:
+ return str(render(mock["default"], context))
+ first_line = prompt.strip().splitlines()[0] if prompt.strip() else ""
+ return f"[mock-llm] received {len(prompt)} chars. first line: {first_line[:60]}"
+
+
+def call_ollama(system: str, prompt: str, temperature: float) -> str:
+ """Call a local Ollama server through its /api/chat endpoint (no extra package needed)."""
+ host = os.getenv("OLLAMA_HOST", "http://localhost:11434").rstrip("/")
+ if not host.startswith("http"):
+ host = f"http://{host}"
+ model = os.getenv("OLLAMA_MODEL", "gemma3:4b")
+ messages = ([{"role": "system", "content": system}] if system else []) + [{"role": "user", "content": prompt}]
+ body = json.dumps({
+ "model": model,
+ "messages": messages,
+ "stream": False,
+ "options": {"temperature": temperature},
+ }).encode("utf-8")
+ request = urllib.request.Request(f"{host}/api/chat", data=body, headers={"Content-Type": "application/json"})
+ timeout = float(os.getenv("OLLAMA_TIMEOUT", "180"))
+ try:
+ with urllib.request.urlopen(request, timeout=timeout) as response:
+ data = json.loads(response.read().decode("utf-8"))
+ except urllib.error.HTTPError as error:
+ detail = error.read().decode("utf-8", errors="replace")
+ if error.code == 404:
+ raise LLMError(f"Model '{model}' not found on Ollama. Run: ollama pull {model}") from error
+ raise LLMError(f"Ollama returned HTTP {error.code}: {detail[:200]}") from error
+ except (urllib.error.URLError, TimeoutError, ConnectionError) as error:
+ raise LLMError(f"Cannot reach Ollama at {host}. Is 'ollama serve' running? ({error})") from error
+ return data.get("message", {}).get("content", "").strip()
+
+
+def call_anthropic(system: str, prompt: str) -> str:
+ """Call Claude through the Anthropic SDK.
+
+ Current Claude models reject sampling parameters, so temperature is not sent.
+ A server-side fallback model answers if the first model declines the request.
+ """
+ try:
+ import anthropic
+ except ImportError as error:
+ raise LLMError("Install the extra first: uv sync --extra anthropic") from error
+ client = anthropic.Anthropic()
+ try:
+ response = client.beta.messages.create(
+ model=os.getenv("ANTHROPIC_MODEL", "claude-opus-5-5"),
+ max_tokens=16000,
+ system=system or anthropic.omit,
+ messages=[{"role": "user", "content": prompt}],
+ betas=["server-side-fallback-2026-07-01"],
+ fallbacks="default",
+ )
+ except anthropic.AuthenticationError as error:
+ raise LLMError("Anthropic credentials are missing or invalid (set ANTHROPIC_API_KEY)") from error
+ except anthropic.APIConnectionError as error:
+ raise LLMError(f"Cannot reach the Anthropic API ({error})") from error
+ except anthropic.APIStatusError as error:
+ raise LLMError(f"Anthropic API returned HTTP {error.status_code}: {error.message}") from error
+ if response.stop_reason == "refusal":
+ raise LLMError("Claude declined this request (stop_reason=refusal)")
+ return "".join(block.text for block in response.content if block.type == "text").strip()
+
+
+def call_gemini(system: str, prompt: str, temperature: float) -> str:
+ try:
+ from google import genai
+ from google.genai import types
+ except ImportError as error:
+ raise LLMError("Install the extra first: uv sync --extra gemini") from error
+ if not os.getenv("GEMINI_API_KEY"):
+ raise LLMError("GEMINI_API_KEY is not set")
+ client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
+ response = client.models.generate_content(
+ model=os.getenv("GEMINI_MODEL", "gemini-2.5-flash"),
+ contents=prompt,
+ config=types.GenerateContentConfig(system_instruction=system or None, temperature=temperature),
+ )
+ return response.text or ""
+
+
+def call_openai(system: str, prompt: str, temperature: float, schema: dict | None = None,
+ max_tokens: int | None = None) -> str:
+ """Call the OpenAI Responses API (OPENAI_MODEL, default gpt-4.1-mini).
+
+ When `schema` is given, the answer is JSON that follows it (structured output).
+ A model that does not accept temperature is called again without it.
+ """
+ try:
+ import openai
+ except ImportError as error:
+ raise LLMError("The openai package is missing. Run: uv sync") from error
+ if not os.getenv("OPENAI_API_KEY"):
+ raise LLMError("OPENAI_API_KEY is not set (put it in the .env file)")
+ client = openai.OpenAI(timeout=float(os.getenv("OPENAI_TIMEOUT", "60")),
+ max_retries=int(os.getenv("OPENAI_MAX_RETRIES", "2")))
+ model = os.getenv("OPENAI_MODEL", "gpt-4.1-mini")
+ request: dict[str, Any] = {"model": model, "input": prompt, "temperature": temperature}
+ if system:
+ request["instructions"] = system
+ if max_tokens:
+ request["max_output_tokens"] = max(16, int(max_tokens)) # the API minimum is 16
+ if schema:
+ request["text"] = {"format": {"type": "json_schema", "name": "reply", "schema": schema, "strict": False}}
+ started = time.perf_counter()
+ try:
+ try:
+ response = client.responses.create(**request)
+ except openai.BadRequestError as error:
+ if "temperature" not in str(error):
+ raise
+ request.pop("temperature")
+ response = client.responses.create(**request)
+ except openai.AuthenticationError as error:
+ raise LLMError("OpenAI rejected the API key (check OPENAI_API_KEY in .env)") from error
+ except openai.APIConnectionError as error:
+ raise LLMError(f"Cannot reach the OpenAI API ({error})") from error
+ except openai.APIStatusError as error:
+ raise LLMError(f"OpenAI API returned HTTP {error.status_code}: {error.message}") from error
+ return (response.output_text or "").strip()
+
+
+def complete(node: dict[str, Any], prompt: str, system: str, context: dict[str, Any]) -> tuple[str, str]:
+ """Return (reply, provider_name).
+
+ With MINIFLOW_LLM_FALLBACK set (for example ollama), a call that fails on the main provider
+ is tried once more there, and the reply says which provider answered.
+ """
+ primary = os.getenv("MINIFLOW_LLM", "mock").lower()
+ try:
+ return _complete_once(node, prompt, system, context, primary)
+ except LLMError as error:
+ fallback = os.getenv("MINIFLOW_LLM_FALLBACK", "").strip().lower()
+ if not fallback or fallback == primary or type(error).__name__ == "BudgetError":
+ raise
+ print(f"[miniflow] {primary} failed ({error}); trying {fallback}", file=sys.stderr)
+ try:
+ return _complete_once(node, prompt, system, context, fallback)
+ except LLMError as second:
+ raise LLMError(f"{primary} failed: {error} / fallback {fallback} failed: {second}") from second
+
+
+def _complete_once(node: dict[str, Any], prompt: str, system: str, context: dict[str, Any], provider: str) -> tuple[str, str]:
+ temperature = float(node.get("temperature", 0.2))
+ if provider == "mock":
+ return mock_reply(prompt, node.get("mock"), context), "mock"
+ if provider == "ollama":
+ return call_ollama(system, prompt, temperature), "ollama"
+ if provider == "anthropic":
+ return call_anthropic(system, prompt), "anthropic"
+ if provider == "gemini":
+ return call_gemini(system, prompt, temperature), "gemini"
+ if provider == "openai":
+ return call_openai(system, prompt, temperature, node.get("json_schema")), "openai"
+ raise LLMError(f"Unknown MINIFLOW_LLM value: {provider} (use mock, ollama, openai, anthropic or gemini)")
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/memory.py b/Last3Mon/65/workflow-lab/src/miniflow/memory.py
new file mode 100644
index 0000000..6909c47
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/memory.py
@@ -0,0 +1,33 @@
+"""A JSON-file memory store shared across workflow runs."""
+
+import json
+import os
+from pathlib import Path
+from typing import Any
+
+
+def memory_path() -> Path:
+ return Path(os.getenv("MINIFLOW_MEMORY_FILE", ".miniflow-memory.json"))
+
+
+def _load() -> dict[str, Any]:
+ path = memory_path()
+ if not path.exists():
+ return {}
+ return json.loads(path.read_text(encoding="utf-8"))
+
+
+def read(key: str) -> dict[str, Any]:
+ return _load().get(key, {})
+
+
+def write(key: str, value: dict[str, Any]) -> dict[str, Any]:
+ store = _load()
+ merged = {**store.get(key, {}), **value}
+ store[key] = merged
+ memory_path().write_text(json.dumps(store, ensure_ascii=False, indent=2), encoding="utf-8")
+ return merged
+
+
+def clear() -> None:
+ memory_path().unlink(missing_ok=True)
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/platforms.py b/Last3Mon/65/workflow-lab/src/miniflow/platforms.py
new file mode 100644
index 0000000..ba1a5e2
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/platforms.py
@@ -0,0 +1,117 @@
+"""Run the same business workflow on interchangeable platforms, with failover.
+
+Application code calls `FailoverRunner(["n8n", "miniflow"]).run("request", inputs)`.
+Which platforms exist and how each one runs a workflow is decided by adapters
+and `platforms.json`, so the calling code never changes when a platform is swapped.
+"""
+
+import json
+import os
+import time
+import urllib.error
+import urllib.request
+from pathlib import Path
+from typing import Any, Protocol
+
+from miniflow.engine import WorkflowError, load_workflow, run_workflow
+
+PROJECT_DIR = Path(__file__).resolve().parents[2]
+CONFIG_FILE = PROJECT_DIR / "platforms.json"
+
+
+class PlatformError(RuntimeError):
+ """A platform could not run the workflow (down, timeout, bad answer)."""
+
+
+class WorkflowPlatform(Protocol):
+ name: str
+
+ def run(self, workflow: str, inputs: dict[str, Any]) -> dict[str, Any]: ...
+
+
+def load_config(path: Path = CONFIG_FILE) -> dict[str, Any]:
+ return json.loads(path.read_text(encoding="utf-8"))
+
+
+class N8nPlatform:
+ """Calls an n8n workflow through its production webhook URL."""
+
+ name = "n8n"
+
+ def __init__(self, config: dict[str, Any]):
+ self.workflows = config["workflows"]
+ self.base_url = os.getenv("N8N_BASE_URL", config.get("n8n", {}).get("base_url", "http://localhost:5678"))
+ self.timeout = float(os.getenv("N8N_TIMEOUT", config.get("n8n", {}).get("timeout", 120)))
+
+ def run(self, workflow: str, inputs: dict[str, Any]) -> dict[str, Any]:
+ settings = self.workflows.get(workflow, {}).get("n8n")
+ if not settings:
+ raise PlatformError(f"n8n has no mapping for workflow '{workflow}'")
+ url = f"{self.base_url.rstrip('/')}/webhook/{settings['webhook']}"
+ request = urllib.request.Request(url, data=json.dumps(inputs).encode("utf-8"),
+ headers={"Content-Type": "application/json"}, method="POST")
+ try:
+ with urllib.request.urlopen(request, timeout=self.timeout) as response:
+ return json.loads(response.read().decode("utf-8"))
+ except urllib.error.HTTPError as error:
+ raise PlatformError(f"n8n returned HTTP {error.code} for {url}") from error
+ except (urllib.error.URLError, TimeoutError, ConnectionError) as error:
+ raise PlatformError(f"n8n is not reachable at {url} ({error})") from error
+ except json.JSONDecodeError as error:
+ raise PlatformError("n8n answered with something that is not JSON") from error
+
+
+class MiniflowPlatform:
+ """Runs the matching JSON flow with the local miniflow engine."""
+
+ name = "miniflow"
+
+ def __init__(self, config: dict[str, Any]):
+ self.workflows = config["workflows"]
+
+ def run(self, workflow: str, inputs: dict[str, Any]) -> dict[str, Any]:
+ settings = self.workflows.get(workflow, {}).get("miniflow")
+ if not settings:
+ raise PlatformError(f"miniflow has no mapping for workflow '{workflow}'")
+ try:
+ report = run_workflow(load_workflow(PROJECT_DIR / settings["flow"]), inputs, verbose=False)
+ except WorkflowError as error:
+ raise PlatformError(str(error)) from error
+ if report["status"] != "completed":
+ failed = report["trace"][-1]
+ raise PlatformError(f"miniflow failed at node '{failed['id']}': {failed.get('error')}")
+ return report["result"]
+
+
+PLATFORMS: dict[str, type] = {"n8n": N8nPlatform, "miniflow": MiniflowPlatform}
+
+
+def register_platform(name: str, adapter: type) -> None:
+ """Add another platform adapter without touching the calling code."""
+ PLATFORMS[name] = adapter
+
+
+class FailoverRunner:
+ """Try platforms in order; when one raises PlatformError, move on to the next."""
+
+ def __init__(self, order: list[str], config: dict[str, Any] | None = None):
+ config = config or load_config()
+ unknown = [name for name in order if name not in PLATFORMS]
+ if unknown:
+ raise PlatformError(f"Unknown platform(s): {', '.join(unknown)}. Registered: {', '.join(PLATFORMS)}")
+ self.platforms = [PLATFORMS[name](config) for name in order]
+
+ def run(self, workflow: str, inputs: dict[str, Any]) -> dict[str, Any]:
+ attempts = []
+ for platform in self.platforms:
+ started = time.perf_counter()
+ try:
+ result = platform.run(workflow, inputs)
+ except PlatformError as error:
+ attempts.append({"platform": platform.name, "status": "failed", "error": str(error),
+ "ms": round((time.perf_counter() - started) * 1000, 1)})
+ continue
+ attempts.append({"platform": platform.name, "status": "ok",
+ "ms": round((time.perf_counter() - started) * 1000, 1)})
+ return {"workflow": workflow, "served_by": platform.name, "result": result, "attempts": attempts}
+ raise PlatformError("All platforms failed: " + "; ".join(f"{a['platform']}: {a['error']}" for a in attempts))
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/template.py b/Last3Mon/65/workflow-lab/src/miniflow/template.py
new file mode 100644
index 0000000..7d3566b
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/template.py
@@ -0,0 +1,48 @@
+"""Resolve {{path.to.value}} placeholders against the workflow context."""
+
+import json
+import re
+from typing import Any
+
+PLACEHOLDER = re.compile(r"\{\{\s*([a-zA-Z0-9_.\-]+)\s*\}\}")
+
+
+class TemplateError(KeyError):
+ pass
+
+
+def lookup(context: dict[str, Any], path: str) -> Any:
+ value: Any = context
+ for part in path.split("."):
+ if isinstance(value, dict) and part in value:
+ value = value[part]
+ elif isinstance(value, list) and part.isdigit() and int(part) < len(value):
+ value = value[int(part)]
+ else:
+ raise TemplateError(f"Cannot resolve '{{{{{path}}}}}': '{part}' not found")
+ return value
+
+
+def _to_text(value: Any) -> str:
+ if isinstance(value, str):
+ return value
+ return json.dumps(value, ensure_ascii=False)
+
+
+def render(template: Any, context: dict[str, Any]) -> Any:
+ """Render strings, lists and dicts recursively.
+
+ A string that is exactly one placeholder keeps the original type
+ (dict, list, number). Mixed text is rendered as a string.
+ """
+ if isinstance(template, dict):
+ return {key: render(value, context) for key, value in template.items()}
+ if isinstance(template, list):
+ return [render(item, context) for item in template]
+ if not isinstance(template, str):
+ return template
+
+ whole = PLACEHOLDER.fullmatch(template.strip())
+ if whole:
+ return lookup(context, whole.group(1))
+ return PLACEHOLDER.sub(lambda m: _to_text(lookup(context, m.group(1))), template)
diff --git a/Last3Mon/65/workflow-lab/src/miniflow/tools.py b/Last3Mon/65/workflow-lab/src/miniflow/tools.py
new file mode 100644
index 0000000..cf3aad7
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/src/miniflow/tools.py
@@ -0,0 +1,62 @@
+"""Tools a workflow can call. Each tool reads local sample data, so no network is needed."""
+
+import json
+from collections.abc import Callable
+from pathlib import Path
+from typing import Any
+
+DATA_DIR = Path(__file__).resolve().parents[2] / "data"
+
+
+class ToolError(RuntimeError):
+ pass
+
+
+def _load(name: str) -> Any:
+ return json.loads((DATA_DIR / name).read_text(encoding="utf-8"))
+
+
+def get_weather(city: str) -> dict[str, Any]:
+ """Return today's sample weather for a city."""
+ table = _load("weather.json")
+ if city not in table:
+ raise ToolError(f"Unknown city '{city}'. Available: {', '.join(table)}")
+ return {"city": city, **table[city]}
+
+
+def search_faq(query: str, top_k: int = 2) -> list[dict[str, Any]]:
+ """Return FAQ entries ranked by keyword overlap with the query."""
+ words = {word for word in query.lower().split() if len(word) > 1}
+ scored = []
+ for item in _load("faq.json"):
+ keywords = {keyword.lower() for keyword in item["keywords"]}
+ score = sum(1 for word in words if any(keyword in word or word in keyword for keyword in keywords))
+ if score:
+ scored.append({"score": score, **item})
+ scored.sort(key=lambda item: item["score"], reverse=True)
+ return scored[: int(top_k)]
+
+
+def count_chars(text: str) -> dict[str, int]:
+ """Count characters and words of a text."""
+ return {"chars": len(text), "words": len(text.split())}
+
+
+TOOLS: dict[str, Callable[..., Any]] = {
+ "get_weather": get_weather,
+ "search_faq": search_faq,
+ "count_chars": count_chars,
+}
+
+
+def call_tool(name: str, args: dict[str, Any]) -> Any:
+ if name not in TOOLS:
+ raise ToolError(f"Tool '{name}' is not registered. Available: {', '.join(TOOLS)}")
+ try:
+ return TOOLS[name](**args)
+ except TypeError as error:
+ raise ToolError(f"Wrong arguments for tool '{name}': {error}") from error
+
+
+def describe_tools() -> list[tuple[str, str]]:
+ return [(name, (func.__doc__ or "").strip()) for name, func in TOOLS.items()]
diff --git a/Last3Mon/65/workflow-lab/tests/conftest.py b/Last3Mon/65/workflow-lab/tests/conftest.py
new file mode 100644
index 0000000..aa78190
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/tests/conftest.py
@@ -0,0 +1,3 @@
+import os
+
+os.environ["MINIFLOW_DOTENV"] = "0" # tests never read the real .env (it may hold API keys)
diff --git a/Last3Mon/65/workflow-lab/tests/test_anthropic_provider.py b/Last3Mon/65/workflow-lab/tests/test_anthropic_provider.py
new file mode 100644
index 0000000..bfa7c99
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/tests/test_anthropic_provider.py
@@ -0,0 +1,68 @@
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, HTTPServer
+
+import pytest
+
+pytest.importorskip("anthropic")
+
+from miniflow import llm # noqa: E402
+
+
+class FakeAnthropic(BaseHTTPRequestHandler):
+ received: list[dict] = []
+ headers_seen: list[dict] = []
+ stop_reason = "end_turn"
+
+ def do_POST(self):
+ body = json.loads(self.rfile.read(int(self.headers["Content-Length"])))
+ FakeAnthropic.received.append(body)
+ FakeAnthropic.headers_seen.append(dict(self.headers))
+ reply = {
+ "id": "msg_test", "type": "message", "role": "assistant", "model": body["model"],
+ "content": [{"type": "text", "text": " network "}],
+ "stop_reason": FakeAnthropic.stop_reason, "stop_sequence": None,
+ "usage": {"input_tokens": 10, "output_tokens": 2},
+ }
+ payload = json.dumps(reply).encode()
+ self.send_response(200)
+ self.send_header("Content-Type", "application/json")
+ self.send_header("Content-Length", str(len(payload)))
+ self.end_headers()
+ self.wfile.write(payload)
+
+ def log_message(self, *args):
+ pass
+
+
+@pytest.fixture()
+def fake_server(monkeypatch):
+ server = HTTPServer(("127.0.0.1", 0), FakeAnthropic)
+ threading.Thread(target=server.serve_forever, daemon=True).start()
+ FakeAnthropic.received.clear()
+ FakeAnthropic.headers_seen.clear()
+ FakeAnthropic.stop_reason = "end_turn"
+ monkeypatch.setenv("MINIFLOW_LLM", "anthropic")
+ monkeypatch.setenv("ANTHROPIC_API_KEY", "test-key")
+ monkeypatch.setenv("ANTHROPIC_BASE_URL", f"http://127.0.0.1:{server.server_port}")
+ monkeypatch.delenv("ANTHROPIC_MODEL", raising=False)
+ yield server
+ server.shutdown()
+
+
+def test_anthropic_request_and_reply(fake_server):
+ reply, provider = llm.complete({"temperature": 0}, "문의: VPN", "Reply with the label only.", {})
+ assert (reply, provider) == ("network", "anthropic")
+ sent = FakeAnthropic.received[-1]
+ assert sent["model"] == "claude-opus-5-5"
+ assert sent["system"] == "Reply with the label only."
+ assert sent["messages"] == [{"role": "user", "content": "문의: VPN"}]
+ assert sent["fallbacks"] == "default"
+ assert "temperature" not in sent
+ assert "server-side-fallback-2026-07-01" in FakeAnthropic.headers_seen[-1].get("anthropic-beta", "")
+
+
+def test_refusal_is_reported(fake_server):
+ FakeAnthropic.stop_reason = "refusal"
+ with pytest.raises(llm.LLMError, match="declined"):
+ llm.complete({}, "hi", "", {})
diff --git a/Last3Mon/65/workflow-lab/tests/test_branching.py b/Last3Mon/65/workflow-lab/tests/test_branching.py
new file mode 100644
index 0000000..1916bd7
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/tests/test_branching.py
@@ -0,0 +1,104 @@
+import json
+from pathlib import Path
+
+import pytest
+
+from miniflow import WorkflowError, load_workflow, run_workflow
+from miniflow.engine import evaluate_check
+
+FLOWS = Path(__file__).resolve().parents[1] / "flows"
+
+
+@pytest.fixture(autouse=True)
+def isolated(tmp_path, monkeypatch):
+ monkeypatch.setenv("MINIFLOW_MEMORY_FILE", str(tmp_path / "memory.json"))
+ monkeypatch.setenv("MINIFLOW_LLM", "mock")
+
+
+def statuses(report):
+ return {step["id"]: step["status"] for step in report["trace"]}
+
+
+def test_condition_true_branch_gives_auto_reply():
+ report = run_workflow(load_workflow(FLOWS / "06-request-with-condition.json"),
+ {"user": "kim", "text": "VPN 접속이 계속 끊겨요"}, verbose=False)
+ assert report["status"] == "completed"
+ assert report["result"]["route"] == "자동 답변"
+ assert report["result"]["faq_id"] == "FAQ-003"
+ assert statuses(report)["hand_off"] == "skipped"
+
+
+def test_condition_false_branch_hands_off():
+ report = run_workflow(load_workflow(FLOWS / "06-request-with-condition.json"),
+ {"user": "lee", "text": "점심 메뉴 추천해줘"}, verbose=False)
+ assert report["status"] == "completed"
+ assert report["result"]["route"] == "담당자 확인"
+ assert statuses(report)["draft"] == "skipped"
+
+
+@pytest.mark.parametrize("text,team", [
+ ("비밀번호를 잊어버렸어요", "계정 관리 담당"),
+ ("프린터 출력이 안 돼요", "장비 지원 담당"),
+ ("회의실 예약은 어떻게 하나요", "IT 문의 접수 창구"),
+])
+def test_switch_routes(text, team):
+ report = run_workflow(load_workflow(FLOWS / "07-route-by-category.json"), {"text": text}, verbose=False)
+ assert report["result"]["team"] == team
+
+
+def test_join_after_exclusive_branches_runs(tmp_path):
+ flow = {
+ "inputs": ["n"],
+ "nodes": [
+ {"id": "start", "type": "input"},
+ {"id": "big", "type": "condition", "check": {"left": "{{input.n}}", "op": "gt", "right": 10}},
+ {"id": "yes", "type": "output", "value": "big"},
+ {"id": "no", "type": "output", "value": "small"},
+ {"id": "done", "type": "output", "value": "done"},
+ ],
+ "edges": [["start", "big"], ["big", "yes", "true"], ["big", "no", "false"], ["yes", "done"], ["no", "done"]],
+ }
+ path = tmp_path / "join.json"
+ path.write_text(json.dumps(flow), encoding="utf-8")
+ report = run_workflow(load_workflow(path), {"n": "3"}, verbose=False)
+ assert statuses(report) == {"start": "ok", "big": "ok", "yes": "skipped", "no": "ok", "done": "ok"}
+
+
+def test_branch_label_validation(tmp_path):
+ flow = {
+ "nodes": [{"id": "a", "type": "input"}, {"id": "b", "type": "output", "value": 1}],
+ "edges": [["a", "b", "true"]],
+ }
+ path = tmp_path / "bad.json"
+ path.write_text(json.dumps(flow), encoding="utf-8")
+ with pytest.raises(WorkflowError):
+ load_workflow(path)
+
+
+@pytest.mark.parametrize("check,expected", [
+ ({"left": "abc", "op": "contains", "right": "b"}, True),
+ ({"left": "", "op": "empty"}, True),
+ ({"left": "network", "op": "in", "right": ["network", "device"]}, True),
+ ({"left": "5", "op": "lt", "right": 3}, False),
+])
+def test_evaluate_check(check, expected):
+ assert evaluate_check(check, {"input": {}, "nodes": {}}) is expected
+
+
+def test_branch_gate_blocks_even_with_other_plain_input(tmp_path):
+ """A node behind a skipped condition stays skipped even if another plain edge reaches it."""
+ flow = json.loads((FLOWS / "06-request-with-condition.json").read_text(encoding="utf-8"))
+ flow["nodes"].insert(1, {"id": "is_urgent", "type": "condition",
+ "check": {"left": "{{input.text}}", "op": "contains", "right": "긴급"}})
+ flow["nodes"].append({"id": "urgent_call", "type": "output", "value": {"route": "긴급 담당자 연결"}})
+ flow["edges"] += [["start", "is_urgent"], ["is_urgent", "urgent_call", "true"], ["is_urgent", "has_faq", "false"]]
+ path = tmp_path / "urgent.json"
+ path.write_text(json.dumps(flow, ensure_ascii=False), encoding="utf-8")
+
+ urgent = run_workflow(load_workflow(path), {"user": "kim", "text": "긴급! VPN이 끊겼어요"}, verbose=False)
+ assert urgent["result"]["route"] == "긴급 담당자 연결"
+ assert statuses(urgent)["draft"] == "skipped"
+
+ normal = run_workflow(load_workflow(path), {"user": "kim", "text": "VPN이 끊겼어요"}, verbose=False)
+ assert normal["result"]["route"] == "자동 답변"
+ assert statuses(normal)["urgent_call"] == "skipped"
diff --git a/Last3Mon/65/workflow-lab/tests/test_ollama_provider.py b/Last3Mon/65/workflow-lab/tests/test_ollama_provider.py
new file mode 100644
index 0000000..683e605
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/tests/test_ollama_provider.py
@@ -0,0 +1,66 @@
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, HTTPServer
+
+import pytest
+
+from miniflow import llm
+
+
+class FakeOllama(BaseHTTPRequestHandler):
+ received: list[dict] = []
+
+ def do_POST(self):
+ body = json.loads(self.rfile.read(int(self.headers["Content-Length"])))
+ FakeOllama.received.append(body)
+ if body["model"] == "missing-model":
+ self.send_response(404)
+ self.end_headers()
+ self.wfile.write(b'{"error":"model not found"}')
+ return
+ reply = {"message": {"role": "assistant", "content": " network \n"}, "done": True}
+ payload = json.dumps(reply).encode()
+ self.send_response(200)
+ self.send_header("Content-Type", "application/json")
+ self.send_header("Content-Length", str(len(payload)))
+ self.end_headers()
+ self.wfile.write(payload)
+
+ def log_message(self, *args):
+ pass
+
+
+@pytest.fixture()
+def fake_server(monkeypatch):
+ server = HTTPServer(("127.0.0.1", 0), FakeOllama)
+ threading.Thread(target=server.serve_forever, daemon=True).start()
+ FakeOllama.received.clear()
+ monkeypatch.setenv("MINIFLOW_LLM", "ollama")
+ monkeypatch.setenv("OLLAMA_HOST", f"127.0.0.1:{server.server_port}")
+ monkeypatch.setenv("OLLAMA_MODEL", "gemma3:1b")
+ yield server
+ server.shutdown()
+
+
+def test_ollama_request_and_reply(fake_server):
+ reply, provider = llm.complete({"temperature": 0}, "문의: VPN", "Reply with the label only.", {})
+ assert (reply, provider) == ("network", "ollama")
+ sent = FakeOllama.received[-1]
+ assert sent["model"] == "gemma3:1b"
+ assert sent["stream"] is False
+ assert sent["messages"][0] == {"role": "system", "content": "Reply with the label only."}
+ assert sent["messages"][1]["content"] == "문의: VPN"
+
+
+def test_missing_model_gives_pull_hint(fake_server, monkeypatch):
+ monkeypatch.setenv("OLLAMA_MODEL", "missing-model")
+ with pytest.raises(llm.LLMError, match="ollama pull missing-model"):
+ llm.complete({}, "hi", "", {})
+
+
+def test_unreachable_server(monkeypatch):
+ monkeypatch.setenv("MINIFLOW_LLM", "ollama")
+ monkeypatch.setenv("OLLAMA_HOST", "http://127.0.0.1:9")
+ monkeypatch.setenv("OLLAMA_TIMEOUT", "2")
+ with pytest.raises(llm.LLMError, match="Cannot reach Ollama"):
+ llm.complete({}, "hi", "", {})
diff --git a/Last3Mon/65/workflow-lab/tests/test_openai_provider.py b/Last3Mon/65/workflow-lab/tests/test_openai_provider.py
new file mode 100644
index 0000000..1c33aea
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/tests/test_openai_provider.py
@@ -0,0 +1,80 @@
+"""OpenAI provider, .env loading and the Ollama fallback, without network access."""
+
+import types
+
+import pytest
+
+from miniflow import envfile, llm
+
+
+def test_parse_env_lines():
+ values = envfile.parse('# comment\nexport A=1\nB="two words"\nC=3 # note\n\nbroken line\n')
+ assert values == {"A": "1", "B": "two words", "C": "3"}
+
+
+def test_load_keeps_shell_values(tmp_path, monkeypatch):
+ (tmp_path / ".env").write_text("MINIFLOW_TEST_A=from-file\nMINIFLOW_TEST_B=from-file\n", encoding="utf-8")
+ monkeypatch.chdir(tmp_path)
+ monkeypatch.setenv("MINIFLOW_DOTENV", "1")
+ monkeypatch.setenv("MINIFLOW_TEST_A", "from-shell")
+ monkeypatch.delenv("MINIFLOW_TEST_B", raising=False)
+ assert envfile.load() == tmp_path / ".env"
+ assert llm.os.environ["MINIFLOW_TEST_A"] == "from-shell"
+ assert llm.os.environ["MINIFLOW_TEST_B"] == "from-file"
+ monkeypatch.delenv("MINIFLOW_TEST_B")
+
+
+def test_openai_without_key(monkeypatch):
+ monkeypatch.setenv("MINIFLOW_LLM", "openai")
+ monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+ monkeypatch.delenv("MINIFLOW_LLM_FALLBACK", raising=False)
+ with pytest.raises(llm.LLMError, match="OPENAI_API_KEY"):
+ llm.complete({}, "hello", "", {})
+
+
+def test_openai_request_shape(monkeypatch):
+ sent = {}
+
+ class FakeResponses:
+ def create(self, **kwargs):
+ sent.update(kwargs)
+ return types.SimpleNamespace(output_text='{"ok": true}', usage=None)
+
+ class FakeClient:
+ def __init__(self, **_):
+ self.responses = FakeResponses()
+
+ import openai
+
+ monkeypatch.setattr(openai, "OpenAI", FakeClient)
+ monkeypatch.setenv("MINIFLOW_LLM", "openai")
+ monkeypatch.setenv("OPENAI_API_KEY", "test-key")
+ monkeypatch.setenv("OPENAI_MODEL", "test-model")
+ schema = {"type": "object", "properties": {"ok": {"type": "boolean"}}}
+ reply, used = llm.complete({"temperature": 0, "json_schema": schema}, "hello", "be brief", {})
+ assert (reply, used) == ('{"ok": true}', "openai")
+ assert sent["model"] == "test-model" and sent["instructions"] == "be brief" and sent["temperature"] == 0
+ assert sent["text"]["format"]["schema"] == schema
+
+
+def test_fallback_to_second_provider(monkeypatch, capsys):
+ monkeypatch.setenv("MINIFLOW_LLM", "openai")
+ monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+ monkeypatch.setenv("MINIFLOW_LLM_FALLBACK", "ollama")
+ monkeypatch.setattr(llm, "call_ollama", lambda *args, **kwargs: "from ollama")
+ reply, used = llm.complete({}, "hello", "", {})
+ assert (reply, used) == ("from ollama", "ollama")
+ assert "openai failed" in capsys.readouterr().err
+
+
+def test_both_providers_fail(monkeypatch):
+ monkeypatch.setenv("MINIFLOW_LLM", "openai")
+ monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+ monkeypatch.setenv("MINIFLOW_LLM_FALLBACK", "ollama")
+
+ def broken(*args, **kwargs):
+ raise llm.LLMError("Cannot reach Ollama")
+
+ monkeypatch.setattr(llm, "call_ollama", broken)
+ with pytest.raises(llm.LLMError, match="OPENAI_API_KEY.*fallback ollama failed"):
+ llm.complete({}, "hello", "", {})
diff --git a/Last3Mon/65/workflow-lab/tests/test_platforms.py b/Last3Mon/65/workflow-lab/tests/test_platforms.py
new file mode 100644
index 0000000..e1f1c5c
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/tests/test_platforms.py
@@ -0,0 +1,79 @@
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, HTTPServer
+
+import pytest
+
+from miniflow.platforms import FailoverRunner, PlatformError, load_config
+
+
+class FakeN8n(BaseHTTPRequestHandler):
+ mode = "ok"
+ received: list = []
+
+ def do_POST(self):
+ body = json.loads(self.rfile.read(int(self.headers["Content-Length"])))
+ FakeN8n.received.append((self.path, body))
+ if FakeN8n.mode == "error":
+ self.send_response(500)
+ self.end_headers()
+ return
+ payload = json.dumps({"category": "network", "faq_id": "FAQ-003", "route": "자동 답변", "reply": "n8n reply"}).encode()
+ self.send_response(200)
+ self.send_header("Content-Type", "application/json")
+ self.send_header("Content-Length", str(len(payload)))
+ self.end_headers()
+ self.wfile.write(payload)
+
+ def log_message(self, *args):
+ pass
+
+
+@pytest.fixture()
+def n8n(monkeypatch, tmp_path):
+ server = HTTPServer(("127.0.0.1", 0), FakeN8n)
+ threading.Thread(target=server.serve_forever, daemon=True).start()
+ FakeN8n.mode, FakeN8n.received = "ok", []
+ monkeypatch.setenv("N8N_BASE_URL", f"http://127.0.0.1:{server.server_port}")
+ monkeypatch.setenv("MINIFLOW_LLM", "mock")
+ monkeypatch.setenv("MINIFLOW_MEMORY_FILE", str(tmp_path / "memory.json"))
+ yield server
+ server.shutdown()
+
+
+INPUTS = {"user": "kim", "text": "VPN 접속이 계속 끊겨요"}
+
+
+def test_n8n_serves_when_healthy(n8n):
+ report = FailoverRunner(["n8n", "miniflow"]).run("request", INPUTS)
+ assert report["served_by"] == "n8n"
+ assert FakeN8n.received[-1] == ("/webhook/ai-request", INPUTS)
+
+
+def test_failover_to_miniflow_when_n8n_errors(n8n):
+ FakeN8n.mode = "error"
+ report = FailoverRunner(["n8n", "miniflow"]).run("request", INPUTS)
+ assert report["served_by"] == "miniflow"
+ assert [a["status"] for a in report["attempts"]] == ["failed", "ok"]
+ assert report["result"]["route"] == "자동 답변"
+
+
+def test_failover_when_n8n_is_down(monkeypatch, tmp_path):
+ monkeypatch.setenv("N8N_BASE_URL", "http://127.0.0.1:9")
+ monkeypatch.setenv("N8N_TIMEOUT", "2")
+ monkeypatch.setenv("MINIFLOW_LLM", "mock")
+ monkeypatch.setenv("MINIFLOW_MEMORY_FILE", str(tmp_path / "memory.json"))
+ report = FailoverRunner(["n8n", "miniflow"]).run("request", {"user": "lee", "text": "점심 메뉴 추천해줘"})
+ assert report["served_by"] == "miniflow"
+ assert report["result"]["route"] == "담당자 확인"
+
+
+def test_all_platforms_failing_raises(n8n):
+ FakeN8n.mode = "error"
+ with pytest.raises(PlatformError, match="All platforms failed"):
+ FailoverRunner(["n8n"]).run("request", INPUTS)
+
+
+def test_unknown_platform_is_rejected():
+ with pytest.raises(PlatformError, match="Unknown platform"):
+ FailoverRunner(["nowhere"], load_config())
diff --git a/Last3Mon/65/workflow-lab/tests/test_workflows.py b/Last3Mon/65/workflow-lab/tests/test_workflows.py
new file mode 100644
index 0000000..e3853e2
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/tests/test_workflows.py
@@ -0,0 +1,80 @@
+import json
+from pathlib import Path
+
+import pytest
+
+from miniflow import WorkflowError, load_workflow, run_workflow
+from miniflow.template import TemplateError, render
+
+FLOWS = Path(__file__).resolve().parents[1] / "flows"
+
+
+@pytest.fixture(autouse=True)
+def isolated_memory(tmp_path, monkeypatch):
+ monkeypatch.setenv("MINIFLOW_MEMORY_FILE", str(tmp_path / "memory.json"))
+ monkeypatch.setenv("MINIFLOW_LLM", "mock")
+
+
+def run(name, **inputs):
+ return run_workflow(load_workflow(FLOWS / name), inputs, verbose=False)
+
+
+def test_every_sample_flow_is_valid():
+ for path in FLOWS.glob("*.json"):
+ assert load_workflow(path).order()
+
+
+def test_template_keeps_type_for_whole_placeholder():
+ context = {"nodes": {"tool": {"output": {"temp": 20}}}}
+ assert render("{{nodes.tool.output}}", context) == {"temp": 20}
+ assert render("temp={{nodes.tool.output.temp}}", context) == "temp=20"
+ with pytest.raises(TemplateError):
+ render("{{nodes.missing.output}}", context)
+
+
+def test_llm_only():
+ report = run("01-llm-only.json", text="오늘 회의에서 일정이 확정되었습니다.")
+ assert report["status"] == "completed"
+ assert "Mock" in report["result"]
+
+
+def test_tool_data_flows_into_llm():
+ report = run("02-llm-tool.json", city="제주", question="우산이 필요할까?")
+ assert "제주" in report["result"] and "80%" in report["result"]
+
+
+def test_unknown_city_fails_at_tool_node():
+ report = run("02-llm-tool.json", city="평양", question="날씨?")
+ assert report["status"] == "failed"
+ assert report["trace"][-1]["id"] == "weather"
+
+
+def test_memory_survives_between_runs():
+ run("03-save-profile.json", user="minji", preference="실내 전시")
+ report = run("04-recommend-with-memory.json", user="minji", city="부산")
+ assert "실내 전시" in report["result"]
+ again = run("04-recommend-with-memory.json", user="minji", city="강릉")
+ recall = next(step for step in again["trace"] if step["id"] == "recall")
+ assert recall["output"]["last_city"] == "부산"
+
+
+def test_tech_support_ticket():
+ report = run("05-tech-support-ticket.json", user="kim", ticket="비밀번호를 잊어버려서 로그인이 안 돼요")
+ assert report["result"]["category"] == "account"
+ assert report["result"]["faq_id"] == "FAQ-001"
+
+
+def test_cycle_is_rejected(tmp_path):
+ flow = {
+ "nodes": [{"id": "a", "type": "input"}, {"id": "b", "type": "output", "value": "x"}],
+ "edges": [["a", "b"], ["b", "a"]],
+ }
+ path = tmp_path / "cycle.json"
+ path.write_text(json.dumps(flow), encoding="utf-8")
+ with pytest.raises(WorkflowError):
+ load_workflow(path)
+
+
+def test_missing_input_is_reported():
+ with pytest.raises(WorkflowError):
+ run("02-llm-tool.json", city="서울")
diff --git a/Last3Mon/65/workflow-lab/uv.lock b/Last3Mon/65/workflow-lab/uv.lock
new file mode 100644
index 0000000..73f1e10
--- /dev/null
+++ b/Last3Mon/65/workflow-lab/uv.lock
@@ -0,0 +1,1058 @@
+version = 1
+revision = 3
+requires-python = ">=3.11"
+resolution-markers = [
+ "python_full_version >= '3.14'",
+ "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'emscripten'",
+ "(python_full_version < '3.14' and sys_platform != 'emscripten') or (python_full_version < '3.12' and sys_platform == 'emscripten')",
+]
+
+[[package]]
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