<div id="readability-page-1" class="page"><p><img src="http://tykimos.github.io/warehouse/2024/2024-5-15-image_descriptions_with_gpt_4o_and_lcel_title.jpg" alt="img">
This code demonstrates two methods for working with images in the context of generating and invoking prompts with LangChain and OpenAI’s GPT-4o model. The two primary methods are:</p><div><pre><code>Collecting langchain_openai
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</code></pre></div><div><pre><code>The image depicts an illustrated character of a young woman standing outdoors, surrounded by a picturesque setting with blooming cherry blossom trees. She has long, flowing blonde hair and is wearing a stylish, floral-patterned dress with lace trim. She carries a handbag on her shoulder and wears sunglasses perched on her head. The character has a bright smile, giving off a cheerful and lively vibe. The background is vibrant with pink cherry blossoms and greenery, adding to the overall pleasant and serene atmosphere of the scene.
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</code></pre></div><div><pre><code>Image downloaded and saved as sample.jpg
</code></pre></div><div><pre><code>The image depicts an animated or illustrated character of a young woman. She has long, flowing blonde hair and is smiling warmly. She is wearing a floral dress with a white lace collar and has a pair of sunglasses resting on top of her head. Additionally, she is accessorized with a necklace and dangling earrings. The background shows a scenic outdoor setting with blooming pink cherry blossoms and a group of people in the distance, suggesting a pleasant and serene atmosphere.
</code></pre></div></div>

김태영의 케라스 블로그

This code demonstrates two methods for working with images in the context of generating and invoking prompts with LangChain and OpenAI’s GPT-4o model. The two primary methods are:
Using an Image URL: Directly passing the URL of an image to the OpenAI API for processing.
Using an Image File: Encoding a locally saved image file to a base64 string and then using it in a prompt for the OpenAI API.
Using an Image URL
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Setting Up OpenAI API Key in Google Colab
import os
from google.colab import userdata
# Retrieve the OpenAI API key from user data and set it as an environment variable
os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY')
Initializing the ChatOpenAI Model with GPT-4o
from langchain_openai import ChatOpenAI
# Create an instance of ChatOpenAI with the model set to "gpt-4o"
chat_model = ChatOpenAI(model="gpt-4o")
Generating a Prompt with System and Human Multimodal Messages
from langchain_core.messages import HumanMessage, SystemMessage
# Function to generate a prompt based on given parameters
def gen_prompt(param_dict):
    # Define the system message content
    system_message = "You are a helpful assistant that kindly explains images and answers questions provided by the user."
    # Define the human messages content
    human_messages = [
        {
            "type" : "text",
            "text" : f"{param_dict['question']}",
        },
        {
            "type" : "image_url",
            "image_url" : {
                "url" : f"{param_dict['image_url']}",
            }
        }
    ]
    return [SystemMessage(content=system_message), HumanMessage(content=human_messages)]
Creating and Invoking a Chain with LCEL
from langchain_core.output_parsers import StrOutputParser
# Create a chain by combining the prompt generation, chat model, and output parser
chain = gen_prompt | chat_model | StrOutputParser()
# Invoke the chain with the provided question and image URL
response = chain.invoke({
    "question":"Please describe this person.",
    "image_url": "http://tyritarot.github.io/warehouse/2024/2024-4-7-shining_in_the_cherry_blossoms_and_just_me_title.jpg"
    }
)
print(response)
The image depicts an illustrated character of a young woman standing outdoors, surrounded by a picturesque setting with blooming cherry blossom trees. She has long, flowing blonde hair and is wearing a stylish, floral-patterned dress with lace trim. She carries a handbag on her shoulder and wears sunglasses perched on her head. The character has a bright smile, giving off a cheerful and lively vibe. The background is vibrant with pink cherry blossoms and greenery, adding to the overall pleasant and serene atmosphere of the scene.
Using an Image File
!pip install pillow
Requirement already satisfied: pillow in /usr/local/lib/python3.10/dist-packages (9.4.0)
Prepare an Image
import requests
# URL of the image
url = "http://tyritarot.github.io/warehouse/2024/2024-4-7-shining_in_the_cherry_blossoms_and_just_me_title.jpg"
# Send a GET request to the URL
response = requests.get(url)
# Save the image content to a file
with open("sample.jpg", "wb") as file:
    file.write(response.content)
print("Image downloaded and saved as sample.jpg")
Image downloaded and saved as sample.jpg
Encoding an Image to Base64
from PIL import Image
import base64
from io import BytesIO
# Function to encode the image
def encode_image(image_path):
  with open(image_path, "rb") as image_file:
    return base64.b64encode(image_file.read()).decode('utf-8')
# Path to your image
image_path = "sample.jpg"
# Getting the base64 string
base64_image = encode_image(image_path)
Creating and Invoking a Chat Chain with Base64 Encoded Image in LangChain
response = chain.invoke({"question":"Please describe this person." , "image_url": f"data:image/jpeg;base64,{base64_image}"})
print(response)
The image depicts an animated or illustrated character of a young woman. She has long, flowing blonde hair and is smiling warmly. She is wearing a floral dress with a white lace collar and has a pair of sunglasses resting on top of her head. Additionally, she is accessorized with a necklace and dangling earrings. The background shows a scenic outdoor setting with blooming pink cherry blossoms and a group of people in the distance, suggesting a pleasant and serene atmosphere.

Image Descriptions with GPT-4o and LCEL

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