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Showing content from https://python.langchain.com/docs/integrations/tools/google_imagen/ below:

Google Imagen | 🦜️🔗 LangChain

Imagen on Vertex AI brings Google's state of the art image generative AI capabilities to application developers. With Imagen on Vertex AI, application developers can build next-generation AI products that transform their user's imagination into high quality visual assets using AI generation, in seconds.

With Imagen on Langchain , You can do the following tasks

• VertexAIImageGeneratorChat : Generate novel images using only a text prompt (text-to-image AI generation).
• VertexAIImageEditorChat : Edit an entire uploaded or generated image with a text prompt.
• VertexAIImageCaptioning : Get text descriptions of images with visual captioning.
• VertexAIVisualQnAChat : Get answers to a question about an image with Visual Question Answering (VQA).
  • NOTE : Currently we support only single-turn chat for Visual QnA (VQA)

Generate novel images using only a text prompt (text-to-image AI generation)

from langchain_core.messages import AIMessage, HumanMessage
from langchain_google_vertexai.vision_models import VertexAIImageGeneratorChat

generator = VertexAIImageGeneratorChat()

messages = [HumanMessage(content=["a cat at the beach"])]
response = generator.invoke(messages)

generated_image = response.content[0]

import base64
import io

from PIL import Image


img_base64 = generated_image["image_url"]["url"].split(",")[-1]


img = Image.open(io.BytesIO(base64.decodebytes(bytes(img_base64, "utf-8"))))


img

Edit an entire uploaded or generated image with a text prompt.

from langchain_core.messages import AIMessage, HumanMessage
from langchain_google_vertexai.vision_models import (
    VertexAIImageEditorChat,
    VertexAIImageGeneratorChat,
)

generator = VertexAIImageGeneratorChat()


messages = [HumanMessage(content=["a cat at the beach"])]


response = generator.invoke(messages)


generated_image = response.content[0]

editor = VertexAIImageEditorChat()

messages = [HumanMessage(content=[generated_image, "a dog at the beach "])]


editor_response = editor.invoke(messages)

import base64
import io

from PIL import Image


edited_img_base64 = editor_response.content[0]["image_url"]["url"].split(",")[-1]


edited_img = Image.open(
    io.BytesIO(base64.decodebytes(bytes(edited_img_base64, "utf-8")))
)


edited_img

from langchain_google_vertexai import VertexAIImageCaptioning


model = VertexAIImageCaptioning()

NOTE : we're using generated image in Image Generation Section

img_base64 = generated_image["image_url"]["url"]
response = model.invoke(img_base64)
print(f"Generated Caption : {response}")


img = Image.open(
    io.BytesIO(base64.decodebytes(bytes(img_base64.split(",")[-1], "utf-8")))
)


img

Generated Cpation : a cat sitting on the beach looking at the camera

from langchain_google_vertexai import VertexAIVisualQnAChat

model = VertexAIVisualQnAChat()

NOTE : we're using generated image in Image Generation Section

question = "What animal is shown in the image?"
response = model.invoke(
    input=[
        HumanMessage(
            content=[
                {"type": "image_url", "image_url": {"url": img_base64}},
                question,
            ]
        )
    ]
)

print(f"question : {question}\nanswer : {response.content}")


img = Image.open(
    io.BytesIO(base64.decodebytes(bytes(img_base64.split(",")[-1], "utf-8")))
)


img

question : What animal is shown in the image?
answer : cat

• Tool conceptual guide
• Tool how-to guides

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