By llama-farm
Complete toolkit for LlamaFarm AI applications: configuration generation, REST API integration, MCP server development, debugging, deployment, anomaly detection, text classification, OCR, NER, and streaming ML
Batch anomaly detection with 12+ backends. Train models, score data, detect outliers using isolation forests, autoencoders, and more.
Detect anomalies in data using batch or streaming ML models
REST API integration for LlamaFarm. Programmatic access to projects, chat, RAG, and datasets via HTTP endpoints.
Classify text using zero-shot or trained classification models
Generate LlamaFarm configurations from natural language. Activates for new projects, config creation, PDF/markdown/code patterns.
Uses power tools
Uses Bash, Write, or Edit tools
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Claude Code plugin for building LlamaFarm RAG and ML applications. Provides configuration generation, service management, anomaly detection, text classification, OCR, and more through slash commands and deep reference skills.
git clone https://github.com/llama-farm/claude-code-marketplace.git
cp -r claude-code-marketplace/plugins/llamafarm ~/.claude/plugins/
Or use the plugin directory directly:
claude --plugin-dir ./plugins/llamafarm
| Skill | Description |
|---|---|
/llamafarm:start | Start LlamaFarm services (server, RAG worker, runtime) |
/llamafarm:stop | Stop services gracefully |
/llamafarm:status | Check service health and component status |
/llamafarm:logs | View and filter service logs |
/llamafarm:ml-status | Check ML services health (anomaly, classify, buffers) |
/llamafarm:config | Generate or modify configuration from natural language |
/llamafarm:validate | Validate configuration against schema |
/llamafarm:example | Browse and scaffold from example projects |
/llamafarm:anomaly | Anomaly detection (fit, detect, stream) |
/llamafarm:classify | Text classification (zero-shot, train, predict) |
/llamafarm:ocr | Extract text from images and scanned documents |
| Skill | Description |
|---|---|
config-validation | Schema reference and validation patterns |
config-generation | Use-case patterns, multi-model setup |
rag-pipeline | Chunking, embeddings, retrieval strategies |
examples | Example project documentation |
api-integration | REST API programming, OpenAI compatibility |
mcp-development | Build MCP servers, inline tools |
debugging | Troubleshooting services, ingestion, retrieval |
deployment | Docker Compose, Kubernetes configuration |
anomaly-detection | Batch anomaly detection backends and tuning |
streaming-anomaly | Real-time streaming anomaly detection |
text-classification | Zero-shot and custom SetFit classification |
polars-buffers | Feature engineering with sliding windows |
ml-nlp | OCR, NER, and reranking capabilities |
ml-use-cases | End-to-end ML patterns (IoT, fraud, document intelligence) |
The plugin bundles an MCP server configuration that connects to running LlamaFarm services, providing tools for project management, chat, RAG queries, and dataset operations.
lf) installedllamafarm.yamllf runtime start)# Generate a configuration
/llamafarm:config I want to chat with my markdown documentation
# Validate and start
/llamafarm:validate
/llamafarm:start
# Create and process a dataset
lf datasets create -s markdown_processor -b main_db docs
lf datasets upload docs ./docs/*.md
lf datasets process docs
# Chat with your documents
lf chat "What are the main topics in my documentation?"
This plugin works with LlamaFarm.
Apache 2.0 - Same as LlamaFarm
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