# Agent Workflow Diagrams

## 1. Main deploy/run lifecycle

```mermaid
flowchart TD
    A[Local VS Code / Cloud Shell] -->|01-setupenv.sh| B[APIs Enabled + Bucket + SA]
    B -->|02-deploy.sh| C[ADK Python SDK]
    C -->|gcloud auth ADC| D[Gemini Enterprise Agent Platform]
    D -->|Agent Runtime deployed| E[Managed Serverless Runtime]
    E -->|Query via API| F[Agent Response]
    F -->|End of day| G[03-teardown.sh]
    G --> H[Agent Runtime Deleted — Billing Stopped]

    style G fill:#c0392b,color:#fff
    style H fill:#27ae60,color:#fff
```

## 2. Multi-agent / Coordinator delegation flow

```mermaid
flowchart TD
    U[User Input] --> O[Orchestrator LlmAgent]
    O -->|Knowledge question| R[rag_agent]
    O -->|GCP ops question| G[gcp_ops_agent]
    O -->|Memory recall/store| M[memory_agent]
    O -->|Session close| F[farewell_agent]
    R --> V[Vertex AI RAG Engine]
    M --> MB[Memory Bank / Agent Engine]
    O -->|Final answer| U
```

## 3. Agents CLI lifecycle (2026)

```mermaid
flowchart LR
    A[Developer] -->|natural language| B[Agents CLI skills]
    B -->|agents-cli create| C[Scaffolded project]
    C -->|agents-cli run| D[Local test]
    D -->|agents-cli deploy| E{Deploy target}
    E -->|cloud_run| F[Cloud Run service]
    E -->|agent_runtime| G[Agent Runtime — managed]
    E -->|gke| H[GKE cluster]
    F & G & H --> J[Cloud Trace + Logging + Monitoring]
```

## 4. Observability stack

```mermaid
flowchart TD
    A[ADK Agent — deployed] -->|OpenTelemetry| B[Cloud Trace]
    A -->|structured logs| C[Cloud Logging]
    A -->|metrics| D[Cloud Monitoring]
    D -->|alert policy| E[Email / PubSub]
    B --> F[Agent Platform: Traces tab]
    C --> G[Agent Platform: Logs tab]
    D --> H[Dashboards: sessions, latency p50/p95/p99, error rates]
```

## 5. RAG-grounded agent data flow

```mermaid
flowchart LR
    A[User query] --> B[ADK Agent]
    B -->|retrieve| C[Vertex AI RAG Engine]
    C -->|search corpus| D[Vector index]
    D -->|relevant chunks| C
    C -->|grounded context| B
    B -->|generate| E[Gemini model]
    E -->|grounded response| F[User]
    B -->|telemetry| G[Cloud Trace]
```

## 6. CI/CD pipeline

```mermaid
flowchart TD
    P[git push to main] --> T[Cloud Build Trigger]
    T --> B[Build Docker image]
    B --> AR[Push to Artifact Registry]
    AR --> EV[run_eval.py — CI gate]
    EV -->|groundedness >= 0.8| CR[Deploy to Cloud Run]
    EV -->|groundedness < 0.8| FAIL[Build FAILED]
    CR --> LIVE[Live service]
```

## 7. Memory Bank session lifecycle

```
Session Start
    └── Load memories (recall by user_id)
Agent conversation (session.state updates)
Session End
    └── Generate memories (summarize session)
    └── Store in Memory Bank (TTL: 30 days default)
Next Session
    └── Memories retrieved at start
```

## 8. A2A agent communication

```
Orchestrator Agent (Cloud Run Service A)
    │  HTTP POST /tasks (A2A protocol)
    │  Authorization: Bearer <SA token>
    ▼
Sub-Agent B (Cloud Run Service B)
    │  AgentCard: /.well-known/agent.json
    ▼
Response (A2A TaskResult)
    └── Orchestrator aggregates + responds to user
```