🦙 Ollama Self-Learning System
Master Local LLM Deployment with Ollama — a structured 7-stage journey from Unknown to Proven.
🌍 Real Unknown→
🌳 Environment→
🌌 Simulation→
📐 Formula→
🔣 Symbols→
🌀 Semblance→
🧪 Testing Known
🗺️
The 7-Stage Journey
Each stage transforms uncertainty into validated knowledge
Stage 1 — The Why
🌍
Real Unknown
Problem definitions, OKRs, and the core questions we're answering. Master Local LLM deployment goals and key results.
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Stage 2 — The Context
🌳
Environment
Roadmaps, constraints, and setup guides for Windows, Mac, Linux, and AI clients (Ollama + Qdrant).
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Stage 3 — The Vision
🌌
Simulation
UI mockups, concepts, and a dynamic image carousel of what the end-result looks like.
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Stage 4 — The Recipe
📐
Formula
Step-by-step installation guides, prerequisites, feature references, and the logic behind the build.
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Stage 5 — The Reality
🔣
Symbols
Core source code, implementation snippets, and PrismJS-highlighted examples in action.
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Stage 6 — The Scars
🌀
Semblance
Error logs, near-misses, workarounds, and the gap between what was planned and what actually happened.
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Stage 7 — The Proof
🧪
Testing Known
Validation against Stage 1 objectives, testing checklists, and confirmed outcomes that prove it works.
Explore →
Tool
📝
Markdown Renderer
View any markdown file in the project with full syntax highlighting via PrismJS and clean rendering.
Open →
🤖
AI Stack
Local AI infrastructure powering this project
🦙
Ollama
Run large language models locally. Powers inference, chat, and embedding generation without cloud dependencies.
Local
Open Source
🗄️
Qdrant
Vector database for semantic search. Uses
nomic-embed-text with 4096-dimension embeddings for fast similarity search.
4096 dims
Containerized
🧠
nomic-embed-text
Embedding model for semantic understanding. Powers Qdrant population and Obsidian shortcut title generation via local Ollama.
Embeddings
Local Inference
🔗
Connect & Contribute