211 lines
4.4 KiB
Markdown
211 lines
4.4 KiB
Markdown
|
# **Long-Term Tech Stack**
|
|||
|
|
|
|||
|
|
This is designed to be:
|
|||
|
|
|
|||
|
|
* **Simple**
|
|||
|
|
* **Durable**
|
|||
|
|
* **Modular**
|
|||
|
|
* **Vendor-independent**
|
|||
|
|
* **AI-native**
|
|||
|
|
* **Low-maintenance**
|
|||
|
|
* **Future-proof**
|
|||
|
|
|
|||
|
|
## Core Backend Layer (Stays Python Forever)
|
|||
|
|
|
|||
|
|
### *FastAPI* {#fastapi}
|
|||
|
|
|
|||
|
|
Your main backend framework indefinitely.
|
|||
|
|
|
|||
|
|
* Lightweight
|
|||
|
|
* Fast
|
|||
|
|
* Async
|
|||
|
|
* Great docs
|
|||
|
|
* Perfect for APIs
|
|||
|
|
* Perfect for JSON-store backends
|
|||
|
|
|
|||
|
|
### *Pydantic (v2)* {#pydantic-(v2)}
|
|||
|
|
|
|||
|
|
For:
|
|||
|
|
|
|||
|
|
* Validation
|
|||
|
|
* Schema definition
|
|||
|
|
* Type enforcement
|
|||
|
|
* Parsing & serializing JSON
|
|||
|
|
|
|||
|
|
This gives you the “AI-Native Data Object†foundation.
|
|||
|
|
|
|||
|
|
### *Python typing* {#python-typing}
|
|||
|
|
|
|||
|
|
Static typing \+ Pydantic gives you:
|
|||
|
|
|
|||
|
|
* Safety
|
|||
|
|
* Predictable data models
|
|||
|
|
* AI-generated UIs
|
|||
|
|
* Clean code
|
|||
|
|
|
|||
|
|
### *JSON object datastore on disk* {#json-object-datastore-on-disk}
|
|||
|
|
|
|||
|
|
Your architecture:
|
|||
|
|
|
|||
|
|
`<app-data-root>/json-db/lod/customers/*.json`
|
|||
|
|
|
|||
|
|
`<app-data-root>/json-db/lod/files/`
|
|||
|
|
|
|||
|
|
`<app-data-root>/json-db/bc/hubs/*.json`
|
|||
|
|
|
|||
|
|
This becomes your **source of truth** — and it’s timeless:
|
|||
|
|
|
|||
|
|
* No SQL migration pain
|
|||
|
|
* AI-friendly
|
|||
|
|
* Human-readable
|
|||
|
|
* Portable across servers
|
|||
|
|
* Works with agents
|
|||
|
|
* Simple backups
|
|||
|
|
* Easy to replicate across clouds
|
|||
|
|
|
|||
|
|
### *Systemd services* {#systemd-services}
|
|||
|
|
|
|||
|
|
For:
|
|||
|
|
|
|||
|
|
* Backend uptime
|
|||
|
|
* Simple restarts
|
|||
|
|
* Zero Docker complexity
|
|||
|
|
* Predictability
|
|||
|
|
|
|||
|
|
### *CAddy* {#caddy}
|
|||
|
|
|
|||
|
|
One global reverse proxy.
|
|||
|
|
|
|||
|
|
* SSL termination
|
|||
|
|
* Routing
|
|||
|
|
* Static file serving
|
|||
|
|
* Stable
|
|||
|
|
* Minimal overhead
|
|||
|
|
|
|||
|
|
This will last you a decade.
|
|||
|
|
|
|||
|
|
## Frontend Layer (Optional TS Later) {#frontend-layer-(optional-ts-later)}
|
|||
|
|
|
|||
|
|
For now:
|
|||
|
|
|
|||
|
|
* Simple JS
|
|||
|
|
* Plain HTML \+ small modals
|
|||
|
|
* Works fine for LOD
|
|||
|
|
|
|||
|
|
Long term (as projects expand):
|
|||
|
|
|
|||
|
|
* **React \+ TypeScript**
|
|||
|
|
* **HTMX** for hybrid pages
|
|||
|
|
* Shared component library
|
|||
|
|
* Shared TypeScript types autogenerated from Pydantic
|
|||
|
|
* Local static hosting (`<app-install-path>…`)
|
|||
|
|
|
|||
|
|
You only bring in TS when:
|
|||
|
|
|
|||
|
|
* The UIs become larger
|
|||
|
|
* You need better autocompletion
|
|||
|
|
* Indexing dashboards get complex
|
|||
|
|
* You build cross-app shared components
|
|||
|
|
|
|||
|
|
There is *no immediate need*.
|
|||
|
|
|
|||
|
|
## AI Layer (Strong Long-Term Direction) {#ai-layer-(strong-long-term-direction)}
|
|||
|
|
|
|||
|
|
### *Python for AI operations* {#python-for-ai-operations}
|
|||
|
|
|
|||
|
|
Perfect for:
|
|||
|
|
|
|||
|
|
* Embeddings
|
|||
|
|
* Chunking
|
|||
|
|
* Vectorization
|
|||
|
|
* STT
|
|||
|
|
* LLM calls
|
|||
|
|
* Agents
|
|||
|
|
* Parsing inbound data
|
|||
|
|
* Publishing pipelines
|
|||
|
|
|
|||
|
|
### *Agentic pipelines* {#agentic-pipelines-(future)}
|
|||
|
|
|
|||
|
|
* Chunking → JSONL files
|
|||
|
|
* Vectorization (Embeddings) → Python
|
|||
|
|
* OpenAI embeddings
|
|||
|
|
* Jina embedding
|
|||
|
|
* Cohere
|
|||
|
|
* Local embeddings later (GGUF)
|
|||
|
|
* SentenceTransformers
|
|||
|
|
* Python is the correct home for:
|
|||
|
|
* running the embedder
|
|||
|
|
* transforming the JSONL chunks
|
|||
|
|
* updating embeddings
|
|||
|
|
* building vector stores
|
|||
|
|
* MCP
|
|||
|
|
* OpenAI’s new agent tools
|
|||
|
|
* Event-driven systems
|
|||
|
|
* Scheduled analytical tasks (weeklies)
|
|||
|
|
* Lightweight Database for Metadata \+ Embeddings
|
|||
|
|
* SQLite \+ DuckDB
|
|||
|
|
* Qdrant
|
|||
|
|
* LanceDB
|
|||
|
|
* Weaviate (local mode)
|
|||
|
|
* ChromaDB
|
|||
|
|
* The simplest long-term option I recommend for you:
|
|||
|
|
* DuckDB or SQLite for metadata
|
|||
|
|
* LanceDB or Qdrant for vectors
|
|||
|
|
* Why?
|
|||
|
|
* Very fast
|
|||
|
|
* No server needed
|
|||
|
|
* Easy to copy/backup
|
|||
|
|
* Python-native
|
|||
|
|
* AI-friendly
|
|||
|
|
* Perfect with JSONL chunk pipelines
|
|||
|
|
* Your JSONL holds the raw chunks, Your small local DB holds:
|
|||
|
|
* chunk\_id
|
|||
|
|
* metadata (source, tags, time ranges)
|
|||
|
|
* vector embeddings
|
|||
|
|
* up-to-date indexes
|
|||
|
|
* Rag Layer \- Python
|
|||
|
|
* Consiuder agentic RAG sitting in this \- see index main product development document https://docs.example.invalid/private-reference
|
|||
|
|
|
|||
|
|
### *Python scripts & CLIs* {#python-scripts-&-clis}
|
|||
|
|
|
|||
|
|
For:
|
|||
|
|
|
|||
|
|
* Import/export
|
|||
|
|
* Data normalization
|
|||
|
|
* Periodic JSON cleanup
|
|||
|
|
* Building indexes
|
|||
|
|
* Summaries
|
|||
|
|
* AI-native publishing
|
|||
|
|
|
|||
|
|
These will accumulate value into your system over years.
|
|||
|
|
|
|||
|
|
### *API-Driven* {#api-driven}
|
|||
|
|
|
|||
|
|
Even inside your system, set up so the pieces talk to each other via API, rather than tight coupling so that modules can be upgraded, replaced, outsourced, etc.
|
|||
|
|
|
|||
|
|
## Code
|
|||
|
|
|
|||
|
|
Stay Python-First For:
|
|||
|
|
|
|||
|
|
AI pipelines
|
|||
|
|
agents
|
|||
|
|
orchestration
|
|||
|
|
APIs
|
|||
|
|
content processing
|
|||
|
|
ingestion
|
|||
|
|
automation
|
|||
|
|
research tooling
|
|||
|
|
|
|||
|
|
Add Go/Rust Selectively For:
|
|||
|
|
|
|||
|
|
high-performance services
|
|||
|
|
distributed networking
|
|||
|
|
edge infrastructure
|
|||
|
|
heavy concurrency
|
|||
|
|
secure execution sandboxes
|
|||
|
|
streaming systems
|
|||
|
|
future NetworkSIG infrastructure
|
|||
|
|
low-memory edge compute
|
|||
|
|
|
|||
|
|
|