Week 17: High-Concurrency FastAPI Backend & Multi-Turn Chatbot Architecture

1. Executive Overview

In modern AI Engineering, writing an LLM prompt or LangGraph agent is only 20% of the job. In production, that agent must be served to tens of thousands of concurrent users with:

1. Asynchronous Non-Blocking I/O (ASGI / Uvicorn): Serving hundreds of parallel connections without tying up operating system threads while waiting on 2-second LLM API responses.
2. Server-Sent Events (SSE): Streaming tokens, tool thoughts, and citations to user frontends token-by-token with zero buffering.
3. Multi-Turn Chat Memory & Sliding Window Trimming: Storing conversational state across user sessions, preventing context window overflow, and summarizing background history.
4. Tenant Security, Token-Bucket Rate Limiting & Spend Quotas: Protecting enterprise APIs from runaway loops, malicious scrapers, and denial-of-wallet attacks.
5. Decoupled Background Tasks & Webhooks: Offloading heavy document ingestion and post-turn telemetry logging from the critical HTTP response path.

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2. Weekly Curriculum Roadmap

• Day 1: Production FastAPI Architecture (ASGI event loops, Pydantic v2 schemas, Lifespan state management, and Dependency Injection Depends).
• Day 2: Real-Time Streaming APIs (Server-Sent Events text/event-stream, SSE framing data: ...\n\n, and token generator yields).
• Day 3: Multi-Turn Chat Memory Systems (Session stores, sliding window token budgets, fact extraction, and background compaction).
• Day 4: API Security, Authentication, Token-Bucket Rate Limiting & Daily Tenant Dollar Quotas.
• Day 5: Asynchronous Background Tasks & Webhook Dispatchers (BackgroundTasks and non-blocking event queues).
• Day 6: Concurrency Profiling, Little's Law ($L = \lambda W$), and Benchmarking p50, p95, and p99 latencies.
• Day 7 Mini-Project: End-to-end production FastAPI Streaming SRE Copilot Microservice uniting Days 1–6.