113 lines
3.1 KiB
Markdown
113 lines
3.1 KiB
Markdown
# Agent Workflow Diagrams
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## 1. Main deploy/run lifecycle
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```mermaid
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flowchart TD
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A[Local VS Code / Cloud Shell] -->|01-setupenv.sh| B[APIs Enabled + Bucket + SA]
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B -->|02-deploy.sh| C[ADK Python SDK]
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C -->|gcloud auth ADC| D[Gemini Enterprise Agent Platform]
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D -->|Agent Runtime deployed| E[Managed Serverless Runtime]
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E -->|Query via API| F[Agent Response]
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F -->|End of day| G[03-teardown.sh]
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G --> H[Agent Runtime Deleted — Billing Stopped]
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style G fill:#c0392b,color:#fff
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style H fill:#27ae60,color:#fff
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```
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## 2. Multi-agent / Coordinator delegation flow
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```mermaid
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flowchart TD
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U[User Input] --> O[Orchestrator LlmAgent]
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O -->|Knowledge question| R[rag_agent]
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O -->|GCP ops question| G[gcp_ops_agent]
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O -->|Memory recall/store| M[memory_agent]
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O -->|Session close| F[farewell_agent]
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R --> V[Vertex AI RAG Engine]
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M --> MB[Memory Bank / Agent Engine]
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O -->|Final answer| U
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```
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## 3. Agents CLI lifecycle (2026)
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```mermaid
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flowchart LR
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A[Developer] -->|natural language| B[Agents CLI skills]
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B -->|agents-cli create| C[Scaffolded project]
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C -->|agents-cli run| D[Local test]
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D -->|agents-cli deploy| E{Deploy target}
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E -->|cloud_run| F[Cloud Run service]
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E -->|agent_runtime| G[Agent Runtime — managed]
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E -->|gke| H[GKE cluster]
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F & G & H --> J[Cloud Trace + Logging + Monitoring]
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```
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## 4. Observability stack
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```mermaid
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flowchart TD
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A[ADK Agent — deployed] -->|OpenTelemetry| B[Cloud Trace]
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A -->|structured logs| C[Cloud Logging]
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A -->|metrics| D[Cloud Monitoring]
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D -->|alert policy| E[Email / PubSub]
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B --> F[Agent Platform: Traces tab]
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C --> G[Agent Platform: Logs tab]
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D --> H[Dashboards: sessions, latency p50/p95/p99, error rates]
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```
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## 5. RAG-grounded agent data flow
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```mermaid
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flowchart LR
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A[User query] --> B[ADK Agent]
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B -->|retrieve| C[Vertex AI RAG Engine]
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C -->|search corpus| D[Vector index]
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D -->|relevant chunks| C
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C -->|grounded context| B
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B -->|generate| E[Gemini model]
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E -->|grounded response| F[User]
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B -->|telemetry| G[Cloud Trace]
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```
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## 6. CI/CD pipeline
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```mermaid
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flowchart TD
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P[git push to main] --> T[Cloud Build Trigger]
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T --> B[Build Docker image]
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B --> AR[Push to Artifact Registry]
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AR --> EV[run_eval.py — CI gate]
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EV -->|groundedness >= 0.8| CR[Deploy to Cloud Run]
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EV -->|groundedness < 0.8| FAIL[Build FAILED]
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CR --> LIVE[Live service]
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```
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## 7. Memory Bank session lifecycle
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```
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Session Start
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└── Load memories (recall by user_id)
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Agent conversation (session.state updates)
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Session End
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└── Generate memories (summarize session)
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└── Store in Memory Bank (TTL: 30 days default)
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Next Session
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└── Memories retrieved at start
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```
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## 8. A2A agent communication
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```
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Orchestrator Agent (Cloud Run Service A)
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│ HTTP POST /tasks (A2A protocol)
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│ Authorization: Bearer <SA token>
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▼
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Sub-Agent B (Cloud Run Service B)
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│ AgentCard: /.well-known/agent.json
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▼
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Response (A2A TaskResult)
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└── Orchestrator aggregates + responds to user
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```
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