What You Actually Build
A branching context pipeline, not another chatbot demo.
One lab turns a vague “context management” idea into a working production pattern: summarize long conversation history, retrieve durable memory, merge both signals, then validate the final Gemini response.
1
Design the flow visually with a context assembler, summarizer, memory store, model call, and response node.
2
Run it against realistic constraints: token limits, stale memory, cold-cache retrieval, and validation failures.
3
Leave with deployable artifacts: architecture notes, test cases, and the implementation checklist for a production agent.
module-04/context-flow.yml
pipeline:
branch:
- summarize_history
- retrieve_memory
merge: context_assembler
model: gemini-1.5-pro
validate: grounded_response
Module 04 · Context Management · Visual Builder
Valid pipeline