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name: common-skills description: Best practices for the Common utilities package in LlamaFarm. Covers HuggingFace Hub integration, GGUF model management, and shared utilities. allowed-tools: Read, Grep, Glob user-invocable: false

Common Skills for LlamaFarm

Best practices and code review checklists for the common/ package - shared Python utilities used across all LlamaFarm services.

Component Overview

Purpose

The common/ package provides shared functionality that needs to be consistent across multiple Python services:

• Model file utilities (GGUF selection, quantization parsing)
• HuggingFace Hub integration (listing, downloading)
• Process management (PID files)

Shared Python Skills

This skill inherits all patterns from the shared Python skills:

Framework-Specific Checklists

Module Structure

Copycommon/
├── pyproject.toml           # UV-managed dependencies
├── llamafarm_common/
│   ├── __init__.py          # Public API exports
│   ├── model_utils.py       # GGUF file utilities
│   └── pidfile.py           # PID file management
└── tests/
    └── test_model_utils.py  # Unit tests with mocking

Public API

Model Utilities

Copyfrom llamafarm_common import (
    # Parse model:quantization syntax
    parse_model_with_quantization,
    # Extract quantization from filename
    parse_quantization_from_filename,
    # Select best GGUF file from list
    select_gguf_file,
    select_gguf_file_with_logging,
    # List GGUF files in HF repo
    list_gguf_files,
    # Download and get path to GGUF file
    get_gguf_file_path,
    # Default quantization preference order
    GGUF_QUANTIZATION_PREFERENCE_ORDER,
)

PID File Management

Copyfrom llamafarm_common.pidfile import write_pid, get_pid_file

Review Checklist Summary

When reviewing code in common/:

1. HuggingFace Integration (High priority)

   • Proper error handling for network failures
   • Authentication token passed correctly
   • High-speed transfer enabled appropriately

2. Model Selection (Medium priority)

   • Quantization preference order maintained
   • Case-insensitive matching
   • Graceful fallback when preferred not available

3. Testing (High priority)

   • HuggingFace API calls mocked
   • Network isolation in tests
   • Edge cases covered (empty lists, missing files)

4. Security (Medium priority)

   • No token exposure in logs
   • Safe file path handling
   • Environment variable protection

See huggingface.md for detailed HuggingFace-specific checklists.