"""
title: Google Gemini 2.0 Flash Experimental Image Generation
author: Justin Miller
author_url: https://github.com/millerjl1980
funding_url: https://buymeacoffee.com/justinmillerdev
git_url: https://github.com/millerjl1980/webui-toolkit-gemini-imagegen
version: 0.1
required_open_webui_version: 0.5.3
requirements: google-genai, google-generativeai, Pillow
"""
import base64
from datetime import datetime
# Open WebUI imports
from fastapi import Request
from pydantic import BaseModel, Field
from open_webui.routers.images import upload_image, load_b64_image_data
from open_webui.models.users import Users
# Google Gemini 2.0 Flash Experimental imports
from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
class Tools:
"""Container class for Open WebUI tools."""
class Valves(BaseModel):
"""User-configurable settings for the tool."""
api_key: str = Field(default="", description="Your Google AI API key here")
# Check Gemini docs for models supporting multi-modal output if 2.0 flash is deprecated
model_name: str = Field(
default="gemini-2.0-flash-exp-image-generation",
description="The specific Google AI model name for image generation"
)
# Supported Pillow formats for image
image_format: str = Field(
default="png",
description="The format of the generated image (PNG, GIF, JPEG)",
enum=["png", "gif", "jpeg"]
)
def __init__(self):
"""Initialize the Tool."""
self.valves = self.Valves()
# Ensure Pillow is installed for image processing
try:
from PIL import Image
except ImportError:
raise ImportError("Pillow library is required for image processing. Please install it: pip install Pillow")
async def gemini_generate_image(
self, prompt: str, __request__: Request, __user__: dict, __event_emitter__=None
) -> str:
"""
Generates an image based on a prompt using a Google AI model.
The model might also return accompanying text. Both the image (if generated)
and text (if generated) are sent directly to the UI via events.
This function returns a string confirming the outcome for the LLM.
:param prompt: The text prompt to use for image generation.
:param __event_emitter__: (Internal) Used by Open WebUI to send updates/results to the UI.
:return: A string message summarizing the operation's result for the LLM.
"""
if not self.valves.api_key:
return "Error: API key is missing. Please configure it in the tool settings."
await __event_emitter__(
{
"type": "status",
"data": {"description": "Generating an image", "done": False},
}
)
try:
# https://ai.google.dev/gemini-api/docs/image-generation#gemini
client = genai.Client(api_key=self.valves.api_key)
response = client.models.generate_content(
model=self.valves.model_name,
contents=prompt,
config=types.GenerateContentConfig(
response_modalities=['Text', 'Image']
)
)
generated_text = None
image = None
for part in response.candidates[0].content.parts:
# In case multiple parts, emit both text and image once it is received
if part.text:
generated_text = part.text
await __event_emitter__(
{
"type": "status",
"data": {"description": "Received text with image:.", "done": False},
}
)
await __event_emitter__(
{
"type": "message",
"data": {"content": generated_text},
}
)
else:
generated_text = None
if part.inline_data is not None:
image = Image.open(BytesIO((part.inline_data.data)))
buffered = BytesIO()
image.save(buffered, format=self.valves.image_format)
mime_type = f"image/{self.valves.image_format.lower()}"
data = {
"instances": {"prompt": prompt},
"parameters": {
"sampleCount": 1,
"outputOptions": {"mimeType": mime_type},
},
}
header = f"{mime_type};base64,"
img_str = header + base64.b64encode(buffered.getvalue()).decode()
image_data, content_type = load_b64_image_data(img_str)
url = upload_image(__request__, data, image_data, content_type, user=Users.get_user_by_id(__user__["id"]))
await __event_emitter__(
{
"type": "status",
"data": {"description": "Generated an image", "done": True},
}
)
await __event_emitter__(
{
"type": "message",
"data": {"content": f""},
}
)
else:
image = None
if image is not None:
return f"Notify the user that the image has been successfully generated"
else:
return f"Notify the user that the image has not been generated"
except Exception as err:
await __event_emitter__(
{
"type": "status",
"data": {"description": f"An error occurred: {err}", "done": True},
}
)
return f"Tell the user: {err}"
