Kjdragan

from pydantic import BaseModel, Field
from typing import List

class Product(BaseModel):
    name: str
    price: float
    quantity: int

    @property
    def total_value(self) -> float:

Kjdragan

# --------------------------------------------------------------
# Customer Support Ticket Classification System
# --------------------------------------------------------------

import instructor
from pydantic import BaseModel, Field
from openai import OpenAI
from enum import Enum
from typing import List

Kjdragan

Kjdragan

from PIL import Image
import matplotlib.pyplot as plt
import os

image_paths = []
for img_path in os.listdir("./input_images"):
    image_paths.append(str(os.path.join("./input_images", img_path)))


def plot_images(image_paths):

Kjdragan

from llama_index.multi_modal_llms.openai import OpenAIMultiModal
from llama_index.core import SimpleDirectoryReader

# put your local directore here
image_documents = SimpleDirectoryReader("./input_images").load_data()

openai_mm_llm = OpenAIMultiModal(
    model="gpt-4o", api_key=OPENAI_API_KEY, max_new_tokens=1500
)

Kjdragan

Kjdragan

import requests
import os

url = "https://www.dropbox.com/scl/fi/mlaymdy1ni1ovyeykhhuk/tesla_2021_10k.htm?rlkey=qf9k4zn0ejrbm716j0gg7r802&dl=1"
save_path = "./mixed_wiki/tesla_2021_10k.htm"

# Ensure the directory exists
os.makedirs(os.path.dirname(save_path), exist_ok=True)

# Download the file

Kjdragan

from rembg import remove

input_path = 'input.png'
output_path = 'output.png'

with open(input_path, 'rb') as i:
    with open(output_path, 'wb') as o:
        input = i.read()
        output = remove(input)
        o.write(output)

Kjdragan

# SET CONFIG
video_url = "https://www.youtube.com/watch?v=d_qvLDhkg00"
output_video_path = "./video_data/"
output_folder = "./mixed_data/"
output_audio_path = "./mixed_data/output_audio.wav"

filepath = output_video_path + "input_vid.mp4"
Path(output_folder).mkdir(parents=True, exist_ok=True)

Kjdragan

# We need to now extract multimodal content — Images, Text(via Audio). I extracted 1 frame every 5 seconds of the video (~160 frames) using moviepy .

def video_to_images(video_path, output_folder):
    """
    Convert a video to a sequence of images and save them to the output folder.

    Parameters:
    video_path (str): The path to the video file.
    output_folder (str): The path to the folder to save the images to.