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Introducing LlamaFarm - Config-Based AI for Everyone

· 3 min read
LlamaFarm Team
LlamaFarm Team
Building the future of decentralized AI

Today, we're excited to announce LlamaFarm - an open-source framework that makes deploying AI as simple as writing a YAML file. Run any model, anywhere, with just configuration.

The Vision​

Remember when deploying a web app meant manually configuring servers, installing dependencies, and writing deployment scripts? Then came tools like Docker and Kubernetes that changed everything with declarative configuration.

We're bringing that same revolution to AI.

What is LlamaFarm?​

LlamaFarm is a configuration-based AI deployment framework that lets you:

  • 🏠 Run models locally on your hardware
  • ☁️ Deploy to any cloud (AWS, Azure, GCP, or your own)
  • 🔄 Switch models instantly with config changes
  • 🛡️ Keep data private with local-first processing
  • 📊 Scale seamlessly from laptop to cluster

Simple as YAML​

Here's all it takes to deploy a multi-model AI pipeline:

# llamafarm.yaml
models:
  - name: local-llama
    type: llama2-7b
    device: cuda

  - name: embeddings
    type: sentence-transformers
    model: all-MiniLM-L6-v2

pipeline:
  - embed:
      model: embeddings
      input: documents
  - generate:
      model: local-llama
      prompt: 'Summarize: {context}'

deploy:
  local: true
  replicas: 2

Run it with:

llamafarm up

That's it. LlamaFarm handles model downloading, optimization, serving, and scaling.

Key Features​

1. Model Agnostic​

Support for all major models:

  • Llama 2 & 3
  • GPT (via OpenAI API)
  • Claude (via Anthropic API)
  • Mistral
  • Custom models

2. Deploy Anywhere​

One configuration, multiple targets:

  • Local machines
  • Kubernetes clusters
  • AWS EC2/Lambda
  • Azure Container Instances
  • Edge devices

3. Production Ready​

Built-in features for real applications:

  • Auto-scaling
  • Load balancing
  • Health checks
  • Metrics & monitoring
  • A/B testing

4. Developer Friendly​

  • Hot reload configuration
  • Simple CLI
  • REST & gRPC APIs
  • SDK for Python, Node.js, Go

Real-World Use Cases​

Secure Document Processing​

models:
  - name: doc-analyzer
    type: llama2-13b
    quantization: int8

pipeline:
  - extract:
      type: pdf
      path: /secure/documents
  - analyze:
      model: doc-analyzer
      keep_local: true # Never send to cloud

Multi-Cloud Deployment​

deploy:
  targets:
    - aws:
        region: us-east-1
        instance: g4dn.xlarge
    - azure:
        region: westus2
        sku: Standard_NC6s_v3
    - local:
        when: development

Edge AI​

models:
  - name: edge-vision
    type: mobilenet
    optimize: edge

deploy:
  edge:
    devices:
      - raspberry-pi-cluster
      - nvidia-jetson
    sync: true

Getting Started​

  1. Install LlamaFarm:
pip install llamafarm
# or
brew install llamafarm
  1. Create your config:
llamafarm init my-ai-app
cd my-ai-app
  1. Deploy:
llamafarm up
  1. Use your AI:
curl localhost:8080/generate \
  -d '{"prompt": "Hello, LlamaFarm!"}'

Open Source & Community Driven​

LlamaFarm is 100% open source under the Apache 2.0 license. We believe AI infrastructure should be:

  • Transparent - See exactly how your AI runs
  • Extensible - Add your own models and deployments
  • Community-owned - No vendor lock-in

What's Next?​

This is just the beginning. Our roadmap includes:

  • 🔌 Plugin system for custom processors
  • 🎯 Fine-tuning workflows built-in
  • 📱 Mobile SDKs for iOS/Android
  • 🌐 Distributed training support
  • 🤖 AutoML capabilities

Join Us!​

We're building LlamaFarm in the open and would love your help:

Thank You​

To the open-source AI community - thank you for inspiring us. To everyone who's been locked out of AI due to cost or complexity - this is for you.

Let's farm some llamas! 🦙

Ready to take control of your AI infrastructure? Get started with LlamaFarm today and join us in democratizing AI.