cnndabbler

Part 1/2 : Set up an OpenAI compatible CPU-based local LLM model

1. What is llama-cpp-python

   • llama-cpp-python offers a web server which aims to act as a drop-in replacement for the OpenAI API. This allows you to use llama.cpp compatible models with any OpenAI compatible client (language libraries, services, etc).
   • https://github.com/abetlen/llama-cpp-python

2. Installation

cnndabbler

"""
Movie Purchase System with Multi-Agent Orchestration

This script implements a sophisticated movie purchase system using OpenAI's Swarm framework
for multi-agent orchestration. The system handles the entire flow from movie selection to
shipping using specialized AI agents working in concert.

Key Components:
    - Supervisor Agent: Orchestrates the overall purchase flow
    - Buy Movie Agent: Handles pricing and purchase transactions

cnndabbler

from openai import OpenAI
from rich import print

client = OpenAI(base_url="http://localhost:11434/v1", api_key="ollama")

# model="qwq"
model="qwen2.5-coder:32b"

# TESTING INFERENCE

cnndabbler

from openai import OpenAI
from rich import print
from rich.console import Console
from rich.panel import Panel
from rich.prompt import Prompt
from rich.markdown import Markdown
from rich.text import Text
from rich.style import Style
from swarm import Swarm, Agent
from swarm.types import Response

cnndabbler

"""
Restaurant recommendation system demonstrating context features with multiple customers.
Shows how context helps personalize and improve recommendations over time.
"""

from typing import List, Optional, Dict, Literal
from pydantic import BaseModel, Field
import asyncio
from datetime import datetime
from pydantic_ai import Agent, RunContext

cnndabbler

# ---
# BENTOAI: 
# input as prompts_file: image_prompts.txt
# output-directory: "./flux/frame_XXXX.png"
# ---

# BENTOAI: This guide is based on  Modal excellent examples and tutorials: https://modal.com/docs/example


# In this guide, we'll run Flux to generate images from prompts using [Hugging Face's Diffusers](https://github.com/huggingface/diffusers).

cnndabbler

#!/usr/bin/env python3
from mcp.server import Server, NotificationOptions
from mcp.server.models import InitializationOptions
from mcp.server.fastmcp import FastMCP
import mcp.server.stdio
import mcp.types as types
from youtube_transcript_api import YouTubeTranscriptApi
from youtube_transcript_api._errors import NoTranscriptFound
from urllib.parse import urlparse, parse_qs
import logging

cnndabbler

#!/usr/bin/env python3
import asyncio
import logging
import sys
import os
from pathlib import Path
from contextlib import AsyncExitStack
from typing import Optional, List, Dict, Any

import gradio as gr