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Notebooks

Interactive Jupyter notebook examples demonstrating how to use the MicroDC client library. These notebooks show how to leverage MicroDC's distributed computing platform to run AI applications on any computer, regardless of hardware capabilities.

Available Notebooks

01 - Basic Usage

Introduction to the MicroDC client library:

  • Simple LLM calls
  • Callback-based async processing
  • Embedding generation
  • Multi-turn conversations
  • Job management
  • Context manager patterns

02 - Simple RAG

Complete RAG (Retrieval-Augmented Generation) implementation:

  • PDF text extraction and chunking
  • Embedding generation using MicroDC
  • Vector store creation and similarity search
  • Question-answering with retrieved context
  • Interactive Q&A sessions

03 - Batch Processing

Efficient batch processing patterns:

  • Batch text classification
  • Large-scale embedding generation
  • Multi-document summarization
  • Progress tracking with metadata
  • Error handling and retry logic
  • Performance metrics and optimization

Running the Notebooks

# Set your API key
export MICRODC_API_KEY="mDC_..."

# Install Jupyter
pip install jupyter

# Launch
jupyter notebook notebooks/