/config-skills
Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.
$ npx -y skills add llama-farm/llamafarm --skill config-skills --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/config-skills
Context preview
The summary Claude sees to decide when to auto-load this skill.
Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.
SKILL.md
config-skills.SKILL.mdname: config-skills
description: Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.
allowed-tools: Read, Grep, Glob
user-invocable: false
Config Skills for LlamaFarm
Specialized patterns and best practices for the LlamaFarm configuration module (`config/`).
Module Overview
The config module provides YAML/TOML/JSON configuration loading with JSONSchema validation:
| File | Purpose | |------|---------| | `datamodel.py` | Generated Pydantic v2 models from JSONSchema | | `schema.yaml` | Source JSONSchema with `$ref` references | | `compile_schema.py` | Dereferences `$ref` to create `schema.deref.yaml` | | `generate_types.py` | Generates Python types via `datamodel-codegen` | | `validators.py` | Custom validators beyond JSONSchema capabilities | | `helpers/loader.py` | Config loading, saving, and format detection | | `helpers/generator.py` | Template-based config generation |
Links to Shared Skills
This module follows Python conventions from the shared skills:
| Topic | Link | Key Relevance | |-------|------|---------------| | Patterns | [python-skills/patterns.md](../python-skills/patterns.md) | Pydantic v2, dataclasses | | Typing | [python-skills/typing.md](../python-skills/typing.md) | Type hints, constrained types | | Testing | [python-skills/testing.md](../python-skills/testing.md) | Pytest fixtures, temp files | | Errors | [python-skills/error-handling.md](../python-skills/error-handling.md) | Custom exceptions | | Security | [python-skills/security.md](../python-skills/security.md) | Path traversal prevention |
Framework-Specific Checklists
| Checklist | Description | |-----------|-------------| | [pydantic.md](pydantic.md) | Pydantic v2 configuration patterns, nested models, constraints | | [jsonschema.md](jsonschema.md) | JSONSchema generation, dereferencing, validation |
Tech Stack
- **Python**: 3.11+
- **Pydantic**: v2 with `ConfigDict`, `Field`, constrained types
- **JSONSchema**: Draft-07 with `$ref` dereferencing via `jsonref`
- **YAML**: `ruamel.yaml` for comment-preserving read/write
- **Code Generation**: `datamodel-codegen` for schema-to-Pydantic
Key Patterns
Generated Pydantic Models
The `datamodel.py` file is auto-generated from JSONSchema:
# Generated by datamodel-codegen from schema.deref.yaml
from pydantic import BaseModel, ConfigDict, Field, conint, constr
class Database(BaseModel):
model_config = ConfigDict(extra="forbid")
name: constr(pattern=r"^[a-z][a-z0-9_]*$", min_length=1, max_length=50)
type: Type
config: dict[str, Any] | None = Field(None, description="Database-specific configuration")Custom Validators for Cross-Field Constraints
JSONSchema draft-07 cannot express all constraints. Custom validators extend validation:
def validate_llamafarm_config(config_dict: dict[str, Any]) -> None:
"""Validate constraints beyond JSONSchema (uniqueness, references)."""
# Check for duplicate prompt names
prompt_names = [p.get("name") for p in config_dict.get("prompts", [])]
duplicates = [name for name in prompt_names if prompt_names.count(name) > 1]
if duplicates:
raise ValueError(f"Duplicate prompt set names: {', '.join(set(duplicates))}")Comment-Preserving YAML with ruamel.yaml
Configuration files preserve user comments when modified:
from ruamel.yaml import YAML
from ruamel.yaml.comments import CommentedMap
def _get_ruamel_yaml() -> YAML:
yaml_instance = YAML()
yaml_instance.preserve_quotes = True
yaml_instance.indent(mapping=2, sequence=4, offset=2)
return yaml_instanceDirectory Structure
config/
├── pyproject.toml # UV-managed dependencies
├── schema.yaml # Source JSONSchema with $ref
├── schema.deref.yaml # Dereferenced schema (generated)
├── datamodel.py # Pydantic models (generated)
├── compile_schema.py # Schema compilation script
├── generate_types.py # Type generation script
├── validators.py # Custom validation beyond JSONSchema
├── validate_config.py # CLI validation wrapper
├── __init__.py # Public API exports
├── helpers/
│ ├── loader.py # Config loading/saving
│ └── generator.py # Template-based generation
├── templates/
│ └── default.yaml # Default config template
└── tests/
├── conftest.py # Shared fixtures
└── test_*.py # Test modulesWorkflow: Schema Changes
When modifying the configuration schema:
1. **Edit** `schema.yaml` (or referenced schemas like `../rag/schema.yaml`) 2. **Run** `nx run generate-types` to compile and generate types 3. **Update** `validators.py` if new cross-field constraints are needed 4. **Test** with `uv run pytest config/tests/`
Common Commands
# Generate types from schema
nx run generate-types
# Validate a config file
uv run python config/validate_config.py path/to/llamafarm.yaml --verbose
# Run tests
uv run pytest config/tests/ -v
# Lint and format
ruff check config/ --fix
ruff format config/
Read more
name: config-skills description: Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation. allowed-tools: Read, Grep, Glob user-invocable: false
Config Skills for LlamaFarm
Specialized patterns and best practices for the LlamaFarm configuration module (`config/`).
Module Overview
The config module provides YAML/TOML/JSON configuration loading with JSONSchema validation:
| File | Purpose | |------|---------| | `datamodel.py` | Generated Pydantic v2 models from JSONSchema | | `schema.yaml` | Source JSONSchema with `$ref` references | | `compile_schema.py` | Dereferences `$ref` to create `schema.deref.yaml` | | `generate_types.py` | Generates Python types via `datamodel-codegen` | | `validators.py` | Custom validators beyond JSONSchema capabilities | | `helpers/loader.py` | Config loading, saving, and format detection | | `helpers/generator.py` | Template-based config generation |
Links to Shared Skills
This module follows Python conventions from the shared skills:
| Topic | Link | Key Relevance | |-------|------|---------------| | Patterns | [python-skills/patterns.md](../python-skills/patterns.md) | Pydantic v2, dataclasses | | Typing | [python-skills/typing.md](../python-skills/typing.md) | Type hints, constrained types | | Testing | [python-skills/testing.md](../python-skills/testing.md) | Pytest fixtures, temp files | | Errors | [python-skills/error-handling.md](../python-skills/error-handling.md) | Custom exceptions | | Security | [python-skills/security.md](../python-skills/security.md) | Path traversal prevention |
Framework-Specific Checklists
| Checklist | Description | |-----------|-------------| | [pydantic.md](pydantic.md) | Pydantic v2 configuration patterns, nested models, constraints | | [jsonschema.md](jsonschema.md) | JSONSchema generation, dereferencing, validation |
Tech Stack
- **Python**: 3.11+
- **Pydantic**: v2 with `ConfigDict`, `Field`, constrained types
- **JSONSchema**: Draft-07 with `$ref` dereferencing via `jsonref`
- **YAML**: `ruamel.yaml` for comment-preserving read/write
- **Code Generation**: `datamodel-codegen` for schema-to-Pydantic
Key Patterns
Generated Pydantic Models
The `datamodel.py` file is auto-generated from JSONSchema:
# Generated by datamodel-codegen from schema.deref.yaml
from pydantic import BaseModel, ConfigDict, Field, conint, constr
class Database(BaseModel):
model_config = ConfigDict(extra="forbid")
name: constr(pattern=r"^[a-z][a-z0-9_]*$", min_length=1, max_length=50)
type: Type
config: dict[str, Any] | None = Field(None, description="Database-specific configuration")Custom Validators for Cross-Field Constraints
JSONSchema draft-07 cannot express all constraints. Custom validators extend validation:
def validate_llamafarm_config(config_dict: dict[str, Any]) -> None:
"""Validate constraints beyond JSONSchema (uniqueness, references)."""
# Check for duplicate prompt names
prompt_names = [p.get("name") for p in config_dict.get("prompts", [])]
duplicates = [name for name in prompt_names if prompt_names.count(name) > 1]
if duplicates:
raise ValueError(f"Duplicate prompt set names: {', '.join(set(duplicates))}")Comment-Preserving YAML with ruamel.yaml
Configuration files preserve user comments when modified:
from ruamel.yaml import YAML
from ruamel.yaml.comments import CommentedMap
def _get_ruamel_yaml() -> YAML:
yaml_instance = YAML()
yaml_instance.preserve_quotes = True
yaml_instance.indent(mapping=2, sequence=4, offset=2)
return yaml_instanceDirectory Structure
config/
├── pyproject.toml # UV-managed dependencies
├── schema.yaml # Source JSONSchema with $ref
├── schema.deref.yaml # Dereferenced schema (generated)
├── datamodel.py # Pydantic models (generated)
├── compile_schema.py # Schema compilation script
├── generate_types.py # Type generation script
├── validators.py # Custom validation beyond JSONSchema
├── validate_config.py # CLI validation wrapper
├── __init__.py # Public API exports
├── helpers/
│ ├── loader.py # Config loading/saving
│ └── generator.py # Template-based generation
├── templates/
│ └── default.yaml # Default config template
└── tests/
├── conftest.py # Shared fixtures
└── test_*.py # Test modulesWorkflow: Schema Changes
When modifying the configuration schema:
1. **Edit** `schema.yaml` (or referenced schemas like `../rag/schema.yaml`) 2. **Run** `nx run generate-types` to compile and generate types 3. **Update** `validators.py` if new cross-field constraints are needed 4. **Test** with `uv run pytest config/tests/`
Common Commands
# Generate types from schema nx run generate-types # Validate a config file uv run python config/validate_config.py path/to/llamafarm.yaml --verbose # Run tests uv run pytest config/tests/ -v # Lint and format ruff check config/ --fix ruff format config/
Enterprise AI capabilities on your own hardware. No cloud required. LlamaFarm is an open-source AI platform that runs entirely on your hardware.
Repo: llama-farm/llamafarm
Other skills on llamafarm.
- /cli-skills
CLI best practices for LlamaFarm. Covers Cobra, Bubbletea, Lipgloss patterns for Go CLI development.
Open skill - /code-review
Comprehensive code review for diffs. Analyzes changed code for security vulnerabilities, anti-patterns, and quality issues. Auto-detects domain (frontend/backend) from file paths.
Open skill - /commit-push-pr
Commit changes, push to GitHub, and open a PR. Includes quality checks (security, patterns, simplification). Use --quick to skip checks.
Open skill - /common-skills
Best practices for the Common utilities package in LlamaFarm. Covers HuggingFace Hub integration, GGUF model management, and shared utilities.
Open skill - /designer-skills
Designer subsystem patterns for LlamaFarm. Covers React 18, TanStack Query, TailwindCSS, and Radix UI.
Open skill - /electron-skills
Electron patterns for LlamaFarm Desktop. Covers main/renderer processes, IPC, security, and packaging.
Open skill

