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Example: LLM Wiki

docs/en/context-compilation/02-llm-wiki.md

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Example: LLM Wiki

Compile a set of heterogeneous sources into a Karpathy-style, evidence-grounded, interlinked LLM Wiki: every page has one clear retrieval purpose, opens with a direct summary, uses consistent terminology, makes relationships explicit, keeps evidence close to the claims it supports, and is fronted by an index.md navigation page.

The Skill picks the smallest page type that matches each page's retrieval purpose:

Page typeUse for
entityA named thing with a stable identity (person, organization, product, project, system, dataset, standard, event…)
conceptA reusable idea, mechanism, pattern, protocol, or mental model
methodA reusable procedure with prerequisites, ordered steps, and a verifiable outcome
comparisonTwo or more subjects evaluated side by side on explicit dimensions
analysisA cross-source conclusion tied to a clear question
summaryA faithful digest of one source (only when --reason explicitly asks for it)

entity and concept are the defaults; the others are promoted only when they pass their stricter tests. The result is a knowledge base, not a source-by-source pile of summaries.

Skill source: examples/compile/ov-compile-skills/llm-wiki · Visualization script: examples/compile/graph-show/llm-wiki

Step 1: Prepare the sources

If the material is not in OpenViking yet, import it. Use ov add-resource for directories, ov write for a single file:

bash
# Import a directory as a source
ov add-resource ./my-research --to viking://resources/research --wait

# Or write a single file
ov mkdir viking://resources/research
ov write viking://resources/research/notes.md \
  --from-file ./notes.md --mode create --wait

Confirm the source is in place:

bash
ov ls -r viking://resources/research

Step 2: Add the Skill

Install the LLM Wiki Skill. By default it lands in your user-private skills namespace; use -p viking://agent/skills to make it shared across the team:

bash
ov add-skill examples/compile/ov-compile-skills/llm-wiki --wait

Find the installed Skill URI:

bash
ov skills list
# → viking://agent/skills/llm-wiki  (or viking://user/<you>/skills/llm-wiki)

Step 3: Run compile

bash
ov compile \
  --from viking://resources/research \
  --to viking://resources/research-wiki \
  --skill viking://agent/skills/llm-wiki \
  --reason "Organize into a team-searchable Wiki, keeping the source of every claim" \
  --wait
  • --from can be repeated or comma-separated to pass multiple sources at once.
  • The --to directory is created automatically if it does not exist.
  • Add -o json for machine-readable output; drop --wait to avoid blocking and poll with the returned task_id:
bash
ov task status cmp_01abc      # progress and final result
ov task cancel cmp_01abc      # cooperative cancel

Step 4: Inspect the output

When compile finishes, the target directory holds a Markdown knowledge base. Read the navigation page first, then drill in:

bash
ov tree viking://resources/research-wiki
ov read viking://resources/research-wiki/index.md

Typical layout (page type maps to directory):

text
research-wiki/
├── index.md            # navigation entry, type index
├── entity/
│   └── <title>.md
├── concept/
│   └── <title>.md
├── method/…  comparison/…  analysis/…

Step 5: Visualize it as an interactive graph

wiki_graph.py connects directly to the OpenViking service to read the Wiki pages (no local download needed), colors pages by type, links them by their cross-references, and produces a standalone interactive HTML:

bash
python examples/compile/graph-show/llm-wiki/wiki_graph.py \
  viking://resources/research-wiki \
  -o research-wiki-graph.html \
  --title "Research Knowledge Base"

Open research-wiki-graph.html in a browser. Nodes are pages (colored by entity/concept/method…), edges are links between pages, and clicking a node shows its body.

Connection settings resolve the same way as ov: command-line arguments → OPENVIKING_* environment variables → ~/.openviking/ovcli.conf. Pass them explicitly for a remote service:

bash
python examples/compile/graph-show/llm-wiki/wiki_graph.py \
  viking://resources/research-wiki \
  --url https://openviking.example.com \
  --api-key "$OPENVIKING_API_KEY" \
  -o research-wiki-graph.html --title "Research Knowledge Base"

Pass multiple Wikis to draw them on the same graph for comparison:

bash
python examples/compile/graph-show/llm-wiki/wiki_graph.py \
  viking://resources/wiki-a viking://resources/wiki-b \
  -o combined.html --title "Two Knowledge Bases Side by Side"