Initial monorepo scaffold for Duoc Thu RAG medical chatbot

2026-07-30 20:38:34 +07:00
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+# Progress Log
+
+Chronological record of work done on this project, newest entry on top. The
+goal is continuity across sessions: if a work session ends unexpectedly
+(context/token limit, interruption), whoever picks this up next — human or
+Claude — should be able to read the latest entry and know exactly what's
+done and what's next, without having to reconstruct it from git history.
+
+**Convention**: add a new entry at the top before ending a session whenever
+meaningful progress was made, and proactively the moment it looks like the
+session might run out of context/tokens mid-task — don't wait until the very
+end if that risk is showing.
+
+---
+
+## 2026-07-30 — Initial monorepo scaffold
+
+**Done:**
+- Designed the microservices architecture (see `docs/architecture.md`):
+  Python/FastAPI `ai-service` for RAG, NestJS for `api-gateway`/`auth-service`/
+  `user-service`/`chat-service`, Next.js `web`, Qdrant for vectors, Postgres
+  for relational data, Redis reserved for caching/queues.
+- Scaffolded the full monorepo directory tree (`apps/`, `packages/`,
+  `ingestion/`, `infra/`, `docs/`) with baseline config (package.json/
+  pyproject.toml stubs, pnpm workspace, docker-compose topology stub).
+- Moved `duoc-thu-quoc-gia-viet-nam-2018.pdf` into `ingestion/data/raw/`.
+- Decided vector DB: **Qdrant** over pgvector (`docs/adr/0001-vector-db-qdrant.md`).
+- Decided deployment: GitOps via the **team's existing ArgoCD instance**,
+  not a custom push-based CD pipeline (`docs/adr/0002-argocd-gitops.md`,
+  `infra/argocd/`). CI's job is build/test/push image + bump the Helm values
+  image tag; ArgoCD does the actual sync.
+- `git init` + initial commit (this scaffold).
+- Created a private GitHub repo and pushed the initial commit.
+
+**Not done yet / next up (Phase 1 of the build roadmap in `docs/architecture.md`):**
+- No business logic exists yet anywhere — this was scaffold only.
+- Phase 1: build the `ingestion/` pipeline for real (PDF extraction via
+  PyMuPDF, monograph/section segmentation, section-aware chunking, OpenAI
+  embeddings, Qdrant upsert) and validate retrieval quality via the
+  `ingestion/notebooks/` QA step.
+- Still pending/TBD: which cloud provider (AWS/GCP/Azure) for Terraform
+  (`infra/terraform/README.md`), and the team's ArgoCD instance's actual
+  cluster/server + project details (`infra/argocd/README.md` TODOs).