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data/knowledge-builder-mvp.md

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+# Knowledge Builder MVP — Product Spec
+
+*Defined by D J — 2026-02-15 | Revised 2026-02-15 (v3: AgentZero self-processing + NotebookLM UI)*
+
+## What It Is
+
+A deployment tool that spins up pre-configured AgentZero containers and hands them source material to self-process. The Builder does NOT process data itself — it launches the expert and tells it what to learn. Each deployed agent includes a NotebookLM-style frontend for ongoing knowledge evolution.
+
+## Architecture
+
+### Layer 1: Builder UI (the "factory") — Lightweight Launcher
+Our onboarding application. Collects config and deploys containers. Does NOT download or process any data.
+
+**Onboarding Workflow:**
+1. Create a new project (name, description, persona/domain)
+2. Add data sources — paste YouTube URLs, upload files, add web pages
+3. Configure AI backend: Claude API key, OpenAI key, or local llama.cpp/Ollama endpoint
+4. Configure agent persona: name, system prompt, behavior guidelines
+5. **Deploy:** Spins up an AgentZero container, passes source list + config
+6. AgentZero takes over — downloads, processes, and learns from the sources autonomously
+7. User gets a running expert agent with a link to access it
+
+**Data sources supported (passed to AgentZero, NOT processed by Builder):**
+- YouTube videos (single URL)
+- YouTube channels (bulk)
+- PDFs (uploaded files copied into container)
+- Text files
+- Web pages / URLs
+- Any other parseable format
+
+### Layer 2: AgentZero Container (the "expert") — Self-Processing
+Each deployed container:
+- **Receives source list from Builder** at deploy time
+- **Downloads and processes its own data** — YouTube (yt-dlp), PDFs, web scraping, transcription
+- **Builds its own knowledge base** — chunks, embeds, stores in its local RAG
+- **Has full agent capabilities** — code execution, terminal, web search, tool creation
+- **Knows how to consume all data formats** — Builder ensures this via system prompt + pre-installed tools
+- **Self-contained** — runs independently once deployed
+
+### Layer 3: NotebookLM-Style Frontend (inside container)
+A separate web UI inside each container for ongoing knowledge management:
+- **Source Manager** — add new sources (YouTube URLs, upload PDFs, paste text, web URLs)
+- **Knowledge Browser** — see what the agent knows, browse indexed content, view source citations
+- **Chat Interface** — ask questions, get answers grounded in the knowledge base
+- **Audio Overview** — generate podcast-style summaries (stretch goal)
+- **Processing Status** — see what's being ingested, progress, errors
+- **Refinement Tools** — correct the agent, add context, mark important sections
+
+This is how users continuously evolve their expert after initial deployment.
+
+## Deployment Flow
+
+```
+1. Builder UI collects: source list + LLM config + persona
+2. Builder spins up AgentZero container (docker run)
+3. Builder injects into container:
+   a. Source manifest (URLs, file paths) — NOT processed data
+   b. System prompt with persona + data processing instructions
+   c. LLM config (API keys, endpoints)
+   d. Pre-installed tools for: yt-dlp, PDF parsing, web scraping, Whisper transcription
+   e. NotebookLM frontend (served on a separate port or path)
+4. AgentZero boot sequence:
+   a. Reads source manifest
+   b. Downloads/processes each source autonomously
+   c. Chunks and embeds into local RAG
+   d. Reports status via NotebookLM frontend
+5. Container is ready — user accesses:
+   - AgentZero chat UI (port 50001)
+   - NotebookLM knowledge manager (port 50002 or /notebook path)
+```
+
+## What Builder Must Ensure at Deploy Time
+
+The Builder is responsible for making sure each AgentZero instance can consume all data formats:
+- **yt-dlp** installed in container for YouTube downloads
+- **Whisper** available (local model or remote endpoint to GPU box)
+- **PDF parser** installed (pdftotext, pdf-parse, or similar)
+- **Web scraper** available (requests + beautifulsoup or similar)
+- **Embedding model** configured (Ollama nomic-embed-text or similar)
+- **Vector DB** running inside container (ChromaDB or similar)
+- **System prompt** includes instructions for processing the source manifest on first boot
+- **Processing tools** as AgentZero custom tools in python/tools/
+
+## NotebookLM Frontend Requirements
+
+**Tech Stack:** Next.js 15 + Tailwind v4 + ShadCN UI + Lucide + TypeScript (matches Builder)
+
+**Pages/Features:**
+1. **Dashboard** — overview of knowledge base (source count, chunk count, last updated)
+2. **Sources** — list all sources, add new ones, see processing status, remove sources
+3. **Chat** — conversational interface with source citations in responses
+4. **Browse** — explore indexed content, search within knowledge base
+5. **Settings** — LLM config, embedding model, persona settings
+
+**Key Behaviors:**
+- Adding a new source triggers AgentZero to process it (same pipeline as initial deploy)
+- Chat responses include citations linking back to source chunks
+- Processing is async — user sees real-time status updates
+
+## Tech Stack
+- **Builder UI:** Next.js 15 + Tailwind v4 + Framer Motion + ShadCN UI + Lucide + TypeScript
+- **NotebookLM Frontend:** Same stack (bundled into container)
+- **Generated Containers:** AgentZero (Python, Docker)
+- **Transcription:** Faster Whisper (inside container or remote GPU endpoint)
+- **Embeddings:** nomic-embed-text via Ollama (inside container or remote)
+- **Vector DB:** ChromaDB (inside container)
+- **Container Runtime:** Docker
+
+## Infrastructure
+- Builder runs on VM (192.168.86.45:3001)
+- Docker on VM for spinning up AgentZero containers
+- GPU box (192.168.86.40) available as remote Whisper endpoint
+- Generated containers are portable — run anywhere with Docker
+
+## What We Already Have
+- ✅ Builder UI scaffolded (Next.js 16, running at :3001, systemd service)
+- ✅ Onboarding flow (project create, source input)
+- ✅ Docker installed on VM
+- ✅ AgentZero Docker image available
+- ✅ yt-dlp working
+- ✅ Faster Whisper on GPU box
+- ✅ ChromaDB infrastructure
+- ✅ Ollama + nomic-embed-text
+
+## What Needs Building
+- [ ] **Refactor Builder** — remove all processing logic, make it a pure launcher
+- [ ] **Container deployment engine** — spin up AgentZero, inject config + source manifest
+- [ ] **AgentZero boot processor** — custom tool that reads source manifest and processes on startup
+- [ ] **Data format tools for AgentZero** — YouTube downloader, PDF parser, web scraper, transcription
+- [ ] **NotebookLM frontend** — full knowledge management UI (sources, chat, browse, settings)
+- [ ] **Bundle NotebookLM frontend into container** — served alongside AgentZero
+- [ ] **Container management UI in Builder** — list running agents, start/stop, access links
+- [ ] **Unit tests** — pipeline tools, API routes, deployment engine
+- [ ] **E2E tests** — full flow: create project → add sources → deploy → verify agent processes data → chat works
+
+## Pricing Target
+| Tier | Price | Includes |
+|------|-------|----------|
+| Free | $0 | 1 agent, 50 docs, local LLM only |
+| Personal | $12/mo | 5 agents, 500 docs, cloud LLM |
+| Pro | $25/mo | Unlimited agents, API access, priority processing |
+| Self-Hosted | Free (open core) | Full feature set, BYOLLM |
+| Enterprise | Custom | SSO, audit logs, dedicated support |