z zlatent

Here is how to set up and run the LiteLLM Proxy with Apple Foundation Models using uv.

Run these commands in your terminal to create a dedicated environment and install the necessary dependencies:

# Create a new project directory
mkdir my-apple-proxy && cd my-apple-proxy

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duckdb -cmd "CREATE VIEW view_name AS FROM 'filename.csv';" -ui

	import networkx as nx
	import real_ladybug
	import csv
	import tempfile
	import os

	def nx_to_ladybug_bulk(G: nx.Graph, db_path: str = "./ladybug_db"):
	"""
	Convert a NetworkX graph to LadybugDB using bulk COPY FROM CSV.
	Much faster than row-by-row inserts for large graphs.

	function uvt --description 'Manage tools in a shared global uv-env'
	set -l global_env "$HOME/.local/share/uv-env"
	set -l cmd $argv[1]
	set -l args $argv[2..-1]

	# 1. Show Help / Usage
	if test (count $argv) -eq 0; or contains -- -h $argv; or contains -- --help $argv
	echo "uvt: uv tool manager for a single shared environment"
	echo "Usage: uvt <command> [args]"
	echo ""


	import re

	def camel_to_snake(input_string):
	"""
	Convert camelCase or PascalCase strings to snake_case.

	Args:
	input_string (str): The input string in camelCase or PascalCase

	from sqlalchemy.dialects import registry
	from sqlalchemy.dialects.postgresql.psycopg2 import PGDialect_psycopg2
	class RedshiftPostgresDialect(PGDialect_psycopg2):
	def _set_backslash_escapes(self, connection):
	self._backslash_escapes = "off"
	registry.register("redshift_custom", __name__, "RedshiftPostgresDialect")

	from sqlalchemy import create_engine
	db = create_engine("redshift_custom://user:password@redshifthost:5439/dev")