Metadata-Version: 2.4
Name: kogwistar-llm-wiki
Version: 0.2.0
Summary: LLM-Wiki: a continuously-learning knowledge system built on Kogwistar
License: MIT
Keywords: knowledge-graph,llm,obsidian,kogwistar,wiki
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Text Processing :: Indexing
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Provides-Extra: chromadb
Requires-Dist: chromadb>=0.6; extra == "chromadb"
Provides-Extra: test
Requires-Dist: pytest>=8.0; extra == "test"
Requires-Dist: pytest-anyio; extra == "test"
Provides-Extra: dev
Requires-Dist: kogwistar-llm-wiki[chromadb,test]; extra == "dev"

# Kogwistar LLM-Wiki

A **continuously-learning knowledge system** built on [Kogwistar](https://github.com/humblemat810/kogwistar).

Feed it documents. It extracts entities, promotes knowledge, distills wisdom, and projects an interlinked Obsidian vault — automatically, in the background.

```
raw sources → kg-doc-parser → conversation graph → promote → knowledge graph → Obsidian vault
                                                                               → wisdom engine
```

---

## What it is

| Layer | Role |
|---|---|
| **conversation** | Working memory — parsed artifacts, candidate links, maintenance jobs |
| **knowledge graph** | Stabilized, promoted truth |
| **wisdom engine** | Reusable patterns derived from execution history |
| **Obsidian vault** | Human-facing projection (markdown + canvas) |

> It is **not** a chatbot, a note app, or a RAG wrapper.

---

## Installation

### Option A — Local development (recommended)

```bash
bash scripts/bootstrap-dev.sh
```

The script:
1. Clones `kogwistar`, `kogwistar-obsidian-sink`, `kg-doc-parser` from GitHub if not already present locally
2. Installs all three as **editable** from the local checkout
3. Installs this package last

After running, the venv always uses local editable sources — re-running is safe (existing checkouts are kept).

### Option B — GitHub-only (CI / no local edits needed)

```bash
pip install git+https://github.com/humblemat810/kogwistar.git
pip install git+https://github.com/humblemat810/kogwistar-obsidian-sink.git
pip install git+https://github.com/humblemat810/kg-doc-parser.git
pip install -e ".[dev]"
```

> `kogwistar` and `kogwistar-obsidian-sink` are **not on PyPI** — both options install them from source.

> **Windows**: Run the bootstrap from Git Bash or WSL.

---

## Quick demo

```bash
# 1. Bootstrap (first time only)
bash scripts/bootstrap-dev.sh

# 2. Ingest a document
python -c "
from kogwistar_llm_wiki.ingest_pipeline import IngestPipeline
p = IngestPipeline(workspace_id='demo')
p.run('my_document.md')
"

# 3. Run the background workers
llm-wiki daemon maintenance --workspace demo
llm-wiki daemon projection  --workspace demo --vault ~/obsidian/wiki
```

See [QUICKSTART.md](QUICKSTART.md) for the full step-by-step tutorial.

---

## CLI reference

```
llm-wiki daemon projection  --workspace <id> --vault <path> [--interval <s>]
llm-wiki daemon maintenance --workspace <id>                [--interval <s>]
```

Full reference: [doc/cli_reference.md](doc/cli_reference.md)

---

## Docs

### System Documentation

| Document | Purpose |
|---|---|
| [QUICKSTART.md](QUICKSTART.md) | Step-by-step tutorial |
| [doc/cli_reference.md](doc/cli_reference.md) | CLI cheatsheet |
| [doc/diagrams.md](doc/diagrams.md) | CLI spider map, pipeline, algorithm & data-flow diagrams |
| [doc/architecture.md](doc/architecture.md) | System design |
| [doc/core_workflows.md](doc/core_workflows.md) | Workflow graph designs |
| [doc/lane_namespace_convention.md](doc/lane_namespace_convention.md) | Namespace/lane conventions |
| [doc/maintenance_job_taxonomy.md](doc/maintenance_job_taxonomy.md) | Maintenance job types |
| [doc/glossary.md](doc/glossary.md) | Term definitions |
| [doc/distillation_core_migration.md](doc/distillation_core_migration.md) | Notes on migrating distillation to kogwistar core |
| [STATUS.md](STATUS.md) | Implementation status |

### Ecosystem Analysis

| Document | Purpose |
|---|---|
| [doc/engineering_assessment.md](doc/engineering_assessment.md) | Engineering-level assessment of the author and ecosystem |
| [doc/ai_os_gap_analysis.md](doc/ai_os_gap_analysis.md) | Gap analysis: what is missing to become a genuine AI-native OS |
| [doc/ai_os_roadmap.md](doc/ai_os_roadmap.md) | Executable plan: polish to production + AI OS build order |

---

## Development

```bash
pytest tests/unit/          # fast unit tests (in-memory, no services)
pytest -m integration       # Obsidian vault + other on-disk integration checks
pytest -m manual            # opt-in smoke tests requiring local services
```

After a successful ingest/projection run, the most useful manual checks are:
- maintenance jobs in the durable meta-store should be `DONE`
- projection jobs in the durable meta-store should be `DONE`
- the projection manifest row should be `ready`
- the Obsidian vault should contain the expected `.md` files
