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Product phased roadmap

Last updated: 2026-05-19

Delivery phases for Campus RAG Assistant — what is shipped on main versus optional follow-ups. Design context: DESIGN.md.

Roadmap index

Doc Purpose
This file Phases, priorities, what’s next
LANGGRAPH.md RAG_ENGINE, graph nodes, latency
WEB_RESEARCH.md research_mode=web (Vue toggle + API)
EVALUATION.md RAGAS vs LangSmith
archive/SPRINT_2026-05-18_LANGGRAPH.md Completed AWS KB validation sprint (log)
archive/PHASED_IMPROVEMENT_ROADMAP.md Campus / production scale (Redis HA, EB) — optional

Quick dev commands

tox -e lint,backend,frontend-vue   # CI-style checks (mock RAG)
PIP_SYNC=0 ./scripts/run-backend-venv.sh
./scripts/run-frontend-vue.sh

CI: GitHub Actions on push/PR to main (docs/CI.md). Live AWS / LangGraph: set RAG_ENGINE=langgraph in local .env only (not required for tox).

Goals

Goal How we measure success
Runnable without cloud Clone → mock mode → login → chat with sources in <15 min
Credible AI engineering Providers, RAGAS harness, LangSmith traces, LangGraph
Measurable quality RAGAS golden set, LangSmith traces, documented baselines
Clean repo story README attribution; upstream LICENSE retained

Phase map

flowchart LR
  P0[Phase0_Publish]
  P1[Phase1_CommitAndDemo]
  P2[Phase2_PlatformProviders]
  P4[Phase4_LangGraph]
  P6W[Phase6b_WebResearch]
  P3[Phase3_Eval]
  P5[Phase5_RAGQuality]
  P6[Phase6_SSE_Agentic]
  P0 --> P1 --> P2 --> P4 --> P6W --> P3 --> P5 --> P6
Phase Focus Status
0–2 Publish repo, platform + providers + tox Done
4 LangGraph KB graph (RAG_ENGINE); per-node traces Done — LANGGRAPH.md
6b Opt-in web research (research_mode=web) Done — WEB_RESEARCH.md
3 RAGAS baseline + README quality + LangSmith screenshots Done (lite) — EVALUATION.md; strict gates on release only
5 Retrieval nodes (multi-query, filters, rerank) Done — re-run RAGAS for full gates (baseline)
6 LangGraph SSE; bounded rewrite loop Optional

Campus production (Redis HA, tenant budgets, Elastic Beanstalk): archive/PHASED_IMPROVEMENT_ROADMAP.md (separate phase numbering).

Completed on main (summary)

  • Repo: campus-rag-assistant; README + screenshots; docs/assets/README.md demo script.
  • Platform: request context, Prometheus, rate limits, Alembic, Vue 3 + Streamlit, k6.
  • RAG: provider registry; RAG_ENGINE=langgraph with condense → multi_query → retrieve → rerank → generate (KB); web branch with disclaimer.
  • Eval: 10-row golden set, eval_baseline_2026-05-19.md, tox -e eval, LangSmith trace PNGs in README.
  • OAuth (local): API-port OAuth + handoff to Vue — PRODUCTION_TLS.md.

Phase 3 — Evaluation (done, lite)

Tool Role
RAGAS Golden dataset + baseline; RAGAS_QUALITY_GATE=1 on release
LangSmith Per-node traces; screenshots in README Quality section

Detail: EVALUATION.md.

Phase 4 — LangGraph (done)

Explicit RAG pipeline; same { message, metadata } contract as chain. Detail: LANGGRAPH.md. Sprint log: archive/SPRINT_2026-05-18_LANGGRAPH.md.

Phase 5 — RAG quality (done)

Item Status
Multi-query + RRF fusion Shipped
Metadata filters Shipped
Rerank node (FlashRank + keyword) Shipped
RAGAS tuned run eval_baseline_2026-05-19.md — recall passes; faithfulness/precision below gate

Optional next: ingestion/chunking, stricter RAGAS gates, chain vs graph parity run.

Phase 6b — Web research (done)

Opt-in research_mode=web, Tavily optional, disclaimer UI. WEB_RESEARCH.md.

Phase 6 — Optional

Slice Description
6a LangGraph astream_events → same SSE shape as chain
6c Bounded grade_documents / rewrite loop (RAG_AGENTIC_ENABLED)

What to defer

Defer Why
Multi-agent swarms Cost, flakiness
Knowledge-graph RAG Only if hybrid RAG fails eval
Semantic cache After exact cache + baselines (campus track)
Production Redis HA / tenant budgets Org roadmap
Stripping UC LICENSE Requires OTL permission

What’s next

Priority Focus
Now Ship product increments; optional branch protection on main
Optional Phase 6a LangGraph SSE; grow golden set; faithfulness/precision via ingestion
Later Campus scale track — PHASED_IMPROVEMENT_ROADMAP.md