Kjarni CLI Commands

Model Management

List available models

# List all models
kjarni model list

# Filter by architecture
kjarni model list --arch encoder
kjarni model list --arch decoder
kjarni model list --arch encoder-decoder
kjarni model list --arch cross-encoder

Download a model

kjarni model download llama-3.2-1b
kjarni model download minilm-l6-v2

Show model info

kjarni model info llama-3.2-1b

Search for models

kjarni model search llama
kjarni model search summarize

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Text Generation

Basic generation

kjarni generate "Once upon a time"

With options

kjarni generate "The meaning of life is" \
  --model llama-3.2-3b \
  --max-tokens 200 \
  --temperature 0.8

Greedy decoding (deterministic)

kjarni generate "The capital of France is" --greedy

Creative writing

kjarni generate "Write a poem about" \
  --temperature 1.0 \
  --top-p 0.95 \
  --max-tokens 200

From file

kjarni generate prompt.txt --max-tokens 500

GPU acceleration

kjarni generate "Hello" --gpu

Quiet mode (for piping)

echo "Explain quantum computing:" | kjarni generate -q

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Chat

Interactive chat

kjarni chat

With custom model

kjarni chat --model llama-3-8b-instruct

With system prompt

kjarni chat --system "You are a pirate. Respond in pirate speak."

Chat commands

> /help           Show available commands
> /quit           Exit chat
> /clear          Clear conversation history
> /system         Show current system prompt
> /system <text>  Set new system prompt
> /history        Show conversation history

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Summarization

Basic summarization

kjarni summarize article.txt

From stdin

cat long_document.txt | kjarni summarize

With options

kjarni summarize article.txt \
  --max-length 100 \
  --min-length 30 \
  --num-beams 6

GPU acceleration

kjarni summarize large_doc.txt --model bart-large-cnn --gpu

Quiet mode for scripting

cat article.txt | kjarni summarize -q > summary.txt

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Text Encoding (Embeddings)

Encode text

kjarni encode "Hello world"

Encode from file

kjarni encode document.txt

Batch encoding from stdin

echo -e "First text\nSecond text\nThird text" | kjarni encode

Output formats

kjarni encode "text" --format json    # Full JSON with metadata
kjarni encode "text" --format jsonl   # JSON lines
kjarni encode "text" --format raw     # Space-separated floats

Custom pooling and normalization

kjarni encode "text" --pooling cls --normalize false
kjarni encode "text" --pooling mean --normalize true

Different model

kjarni encode "text" --model mpnet-base-v2

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Semantic Similarity

Compare two texts

kjarni similarity "The cat sat on the mat" "A feline was sitting on a rug"

Compare files

kjarni similarity doc1.txt doc2.txt

Quiet mode (output score only)

kjarni similarity "text1" "text2" -q
# Output: 0.8234

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Reranking

Rerank documents

kjarni rerank "machine learning" doc1.txt doc2.txt doc3.txt

From stdin (one document per line)

echo -e "Python is great\nRust is fast\nJava is verbose" | \
  kjarni rerank "systems programming"

Top-K results

kjarni rerank "query" doc1.txt doc2.txt doc3.txt --top-k 2

Output formats

kjarni rerank "query" docs/*.txt --format json
kjarni rerank "query" docs/*.txt --format text
kjarni rerank "query" docs/*.txt --format docs  # Just documents, for piping

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Indexing

Create an index

kjarni index create ./docs.idx ./documents/

Index multiple paths

kjarni index create ./code.idx src/ lib/ tests/

Custom chunking

kjarni index create ./large.idx ./books/ \
  --chunk-size 2000 \
  --chunk-overlap 400

Add to existing index

kjarni index add ./docs.idx ./new-documents/

Show index info

kjarni index info ./docs.idx

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Search

Hybrid search (default)

kjarni search ./docs.idx "how to deploy kubernetes"

Keyword-only (BM25)

kjarni search ./docs.idx "deployment error" --mode keyword

Semantic search

kjarni search ./docs.idx "container orchestration" --mode semantic

Limit results

kjarni search ./docs.idx "query" --top-k 5

Output formats

kjarni search ./docs.idx "query" --format json
kjarni search ./docs.idx "query" --format docs  # Just text, for piping

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Advanced Pipelines

Semantic grep (find relevant lines)

cat README.md | kjarni rerank "installation" -k 3 --format docs

RAG pipeline

# Search, rerank, then generate
kjarni search ./knowledge.idx "deployment" -k 10 --format docs | \
  kjarni rerank "kubernetes deployment" -k 3 -q --format docs | \
  kjarni generate "Based on this context, explain:" -q

Multi-document summarization

for f in articles/*.txt; do
  kjarni summarize "$f" -q
done | kjarni rerank "key findings" -k 1 --format docs

Build embeddings for external use

cat texts.txt | kjarni encode --format raw > embeddings.txt

Zero-shot classification via reranking

echo -e "positive sentiment\nnegative sentiment\nneutral" | \
  kjarni rerank "This product is amazing!" -k 1 --format docs
# Output: positive sentiment

Find similar content

kjarni search ./docs.idx "$(cat target.txt)" --mode semantic -k 5

Batch processing

# Summarize all articles
find articles/ -name "*.txt" -exec sh -c \
  'kjarni summarize "$1" -q > summaries/$(basename "$1")' _ {} \;

Full RAG with chat

CONTEXT=$(kjarni search ./brain.idx "$QUERY" -k 3 -q --format docs)
kjarni chat --system "Answer using only this context: $CONTEXT"

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Global Options

Option	Description
--gpu	Use GPU acceleration (WGPU)
-q, --quiet	Suppress status messages
-m, --model	Specify model name
--model-path	Use local model directory

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Environment Variables

Variable	Description
KJARNI_CACHE_DIR	Model cache directory (default: ~/.cache/kjarni/)
RUST_LOG	Logging level (e.g., info, debug)