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feat: Update visioncraft api with img2img support

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This commit is contained in:
Abhi
2024-09-19 16:40:24 +05:30
parent be73758102
commit 35c4889f37
1 changed files with 300 additions and 8 deletions
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308
modules/aiutils.py
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@@ -1,6 +1,27 @@
# Moon-Userbot - telegram userbot
# Copyright (C) 2020-present Moon Userbot Organization
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import os
import aiohttp
import base64
from pyrogram import Client, filters
from pyrogram.errors import MessageTooLong
from pyrogram.types import Message
@@ -52,6 +73,7 @@ async def vdxl(c: Client, message: Message):
await message.edit_text("<code>Please Wait...</code>")
try:
img2img = False
chat_id = message.chat.id
model_category = "SDXL-1.0"
models = await fetch_models(category=model_category)
@@ -68,7 +90,11 @@ async def vdxl(c: Client, message: Message):
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
elif message.reply_to_message and len(message.command) > 1:
elif (
message.reply_to_message
and len(message.command) > 1
and not message.reply_to_message.photo
):
model = message.text.split(maxsplit=1)[1]
print(model)
if model in models:
@@ -77,11 +103,45 @@ async def vdxl(c: Client, message: Message):
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
elif (
message.reply_to_message
and message.reply_to_message.photo
and len(message.command) > 1
):
img2img = True
model = message.text.split(maxsplit=1)[1]
if model in models:
prompt = message.reply_to_message.caption
image_path = await message.reply_to_message.download()
with open(image_path, "rb") as image_file:
image_data = base64.b64encode(image_file.read()).decode("utf-8")
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
data_img2img = {
"model": model,
"prompt": prompt,
"negative_prompt": "bad quality",
"token": vca_api_key,
"sampler": "Euler",
"steps": 30,
"width": 1024,
"height": 1024,
"cfg_scale": 7,
"loras": {},
"seed": -1,
"init_image": image_data if img2img else None,
"denoising_strength": 0.7,
"stream": False,
"nsfw_filter": False,
}
data = {
"model": model,
"prompt": prompt,
@@ -95,9 +155,10 @@ async def vdxl(c: Client, message: Message):
"loras": {},
"seed": -1,
"stream": False,
"nsfw_filter": False,
}
response = await generate_images(data)
response = await generate_images(data=data_img2img if img2img else data)
try:
image_url = response["image_url"]
async with aiohttp.ClientSession() as session:
@@ -111,6 +172,8 @@ async def vdxl(c: Client, message: Message):
caption=f"<b>Prompt: </b><code>{prompt}</code>\n<b>Model: </b><code>{model}</code>",
)
os.remove(filename)
if img2img:
os.remove(image_path)
await message.delete()
except KeyError:
try:
@@ -135,6 +198,7 @@ async def vdxl(c: Client, message: Message):
@Client.on_message(filters.command("vdxl2", prefix) & filters.me)
async def vdxl2(c: Client, message: Message):
"""Text to Image Generation Using SDXL"""
img2img = False
await message.edit_text("<code>Please Wait...</code>")
@@ -164,11 +228,45 @@ async def vdxl2(c: Client, message: Message):
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl2 [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
elif (
message.reply_to_message
and message.reply_to_message.photo
and len(message.command) > 1
):
img2img = True
model = message.text.split(maxsplit=1)[1]
if model in models:
prompt = message.reply_to_message.caption
image_path = await message.reply_to_message.download()
with open(image_path, "rb") as image_file:
image_data = base64.b64encode(image_file.read()).decode("utf-8")
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl2 [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl2 [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
data_img2img = {
"model": model,
"prompt": prompt,
"negative_prompt": "bad quality",
"token": vca_api_key,
"sampler": "Euler",
"steps": 30,
"width": 1024,
"height": 1024,
"cfg_scale": 7,
"loras": {},
"seed": -1,
"init_image": image_data if img2img else None,
"denoising_strength": 0.7,
"stream": False,
"nsfw_filter": False,
}
data = {
"model": model,
"prompt": prompt,
@@ -182,9 +280,10 @@ async def vdxl2(c: Client, message: Message):
"loras": {},
"seed": -1,
"stream": False,
"nsfw_filter": False,
}
response = await generate_images(data)
response = await generate_images(data_img2img if img2img else data)
try:
image_url = response["image_url"]
async with aiohttp.ClientSession() as session:
@@ -198,6 +297,8 @@ async def vdxl2(c: Client, message: Message):
caption=f"<b>Prompt: </b><code>{prompt}</code>\n<b>Model: </b><code>{model}</code>",
)
os.remove(filename)
if img2img:
os.remove(image_path)
await message.delete()
except KeyError:
try:
@@ -222,6 +323,7 @@ async def vdxl2(c: Client, message: Message):
@Client.on_message(filters.command("vdxl3", prefix) & filters.me)
async def vdxl3(c: Client, message: Message):
"""Text to Image Generation Using SDXL"""
img2img = False
await message.edit_text("<code>Please Wait...</code>")
@@ -251,11 +353,45 @@ async def vdxl3(c: Client, message: Message):
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl3 [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
elif (
message.reply_to_message
and message.reply_to_message.photo
and len(message.command) > 1
):
img2img = True
model = message.text.split(maxsplit=1)[1]
if model in models:
prompt = message.reply_to_message.caption
image_path = await message.reply_to_message.download()
with open(image_path, "rb") as image_file:
image_data = base64.b64encode(image_file.read()).decode("utf-8")
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl3 [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl3 [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
data_img2img = {
"model": model,
"prompt": prompt,
"negative_prompt": "bad quality",
"token": vca_api_key,
"sampler": "Euler",
"steps": 30,
"width": 1024,
"height": 1024,
"cfg_scale": 7,
"loras": {},
"seed": -1,
"init_image": image_data if img2img else None,
"denoising_strength": 0.7,
"stream": False,
"nsfw_filter": False,
}
data = {
"model": model,
"prompt": prompt,
@@ -269,9 +405,10 @@ async def vdxl3(c: Client, message: Message):
"loras": {},
"seed": -1,
"stream": False,
"nsfw_filter": False,
}
response = await generate_images(data)
response = await generate_images(data_img2img if img2img else data)
try:
image_url = response["image_url"]
async with aiohttp.ClientSession() as session:
@@ -285,6 +422,8 @@ async def vdxl3(c: Client, message: Message):
caption=f"<b>Prompt: </b><code>{prompt}</code>\n<b>Model: </b><code>{model}</code>",
)
os.remove(filename)
if img2img:
os.remove(image_path)
await message.delete()
except KeyError:
try:
@@ -309,6 +448,7 @@ async def vdxl3(c: Client, message: Message):
@Client.on_message(filters.command("vfxl", prefix) & filters.me)
async def vfxl(c: Client, message: Message):
"""Text to Image Generation Using SDXL"""
img2img = False
await message.edit_text("<code>Please Wait...</code>")
@@ -338,11 +478,45 @@ async def vfxl(c: Client, message: Message):
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vfxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
elif (
message.reply_to_message
and message.reply_to_message.photo
and len(message.command) > 1
):
img2img = True
model = message.text.split(maxsplit=1)[1]
if model in models:
prompt = message.reply_to_message.caption
image_path = await message.reply_to_message.download()
with open(image_path, "rb") as image_file:
image_data = base64.b64encode(image_file.read()).decode("utf-8")
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vdxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vfxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
data_img2img = {
"model": model,
"prompt": prompt,
"negative_prompt": "bad quality",
"token": vca_api_key,
"sampler": "Euler",
"steps": 30,
"width": 1024,
"height": 1024,
"cfg_scale": 7,
"loras": {},
"seed": -1,
"init_image": image_data if img2img else None,
"denoising_strength": 0.7,
"stream": False,
"nsfw_filter": False,
}
data = {
"model": model,
"prompt": prompt,
@@ -356,9 +530,10 @@ async def vfxl(c: Client, message: Message):
"loras": {},
"seed": -1,
"stream": False,
"nsfw_filter": False,
}
response = await generate_images(data)
response = await generate_images(data_img2img if img2img else data)
try:
image_url = response["image_url"]
async with aiohttp.ClientSession() as session:
@@ -372,6 +547,8 @@ async def vfxl(c: Client, message: Message):
caption=f"<b>Prompt: </b><code>{prompt}</code>\n<b>Model: </b><code>{model}</code>",
)
os.remove(filename)
if img2img:
os.remove(image_path)
await message.delete()
except KeyError:
try:
@@ -396,6 +573,7 @@ async def vfxl(c: Client, message: Message):
@Client.on_message(filters.command("vpxl", prefix) & filters.me)
async def vpxl(c: Client, message: Message):
"""Text to Image Generation Using SDXL"""
img2img = False
await message.edit_text("<code>Please Wait...</code>")
@@ -425,11 +603,45 @@ async def vpxl(c: Client, message: Message):
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vpxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
elif (
message.reply_to_message
and message.reply_to_message.photo
and len(message.command) > 1
):
img2img = True
model = message.text.split(maxsplit=1)[1]
if model in models:
prompt = message.reply_to_message.caption
image_path = await message.reply_to_message.download()
with open(image_path, "rb") as image_file:
image_data = base64.b64encode(image_file.read()).decode("utf-8")
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vpxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vpxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
data_img2img = {
"model": model,
"prompt": prompt,
"negative_prompt": "bad quality",
"token": vca_api_key,
"sampler": "Euler",
"steps": 30,
"width": 1024,
"height": 1024,
"cfg_scale": 7,
"loras": {},
"seed": -1,
"init_image": image_data if img2img else None,
"denoising_strength": 0.7,
"stream": False,
"nsfw_filter": False,
}
data = {
"model": model,
"prompt": prompt,
@@ -443,9 +655,10 @@ async def vpxl(c: Client, message: Message):
"loras": {},
"seed": -1,
"stream": False,
"nsfw_filter": False,
}
response = await generate_images(data)
response = await generate_images(data_img2img if img2img else data)
try:
image_url = response["image_url"]
async with aiohttp.ClientSession() as session:
@@ -459,6 +672,8 @@ async def vpxl(c: Client, message: Message):
caption=f"<b>Prompt: </b><code>{prompt}</code>\n<b>Model: </b><code>{model}</code>",
)
os.remove(filename)
if img2img:
os.remove(image_path)
await message.delete()
except KeyError:
try:
@@ -483,6 +698,7 @@ async def vpxl(c: Client, message: Message):
@Client.on_message(filters.command("vpixl", prefix) & filters.me)
async def vpixl(c: Client, message: Message):
"""Text to Image Generation Using SDXL"""
img2img = False
await message.edit_text("<code>Please Wait...</code>")
@@ -512,11 +728,45 @@ async def vpixl(c: Client, message: Message):
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vpixl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
elif (
message.reply_to_message
and message.reply_to_message.photo
and len(message.command) > 1
):
img2img = True
model = message.text.split(maxsplit=1)[1]
if model in models:
prompt = message.reply_to_message.caption
image_path = await message.reply_to_message.download()
with open(image_path, "rb") as image_file:
image_data = base64.b64encode(image_file.read()).decode("utf-8")
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vpixl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vpixl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
data_img2img = {
"model": model,
"prompt": prompt,
"negative_prompt": "bad quality",
"token": vca_api_key,
"sampler": "Euler",
"steps": 30,
"width": 1024,
"height": 1024,
"cfg_scale": 7,
"loras": {},
"seed": -1,
"init_image": image_data if img2img else None,
"denoising_strength": 0.7,
"stream": False,
"nsfw_filter": False,
}
data = {
"model": model,
"prompt": prompt,
@@ -530,9 +780,10 @@ async def vpixl(c: Client, message: Message):
"loras": {},
"seed": -1,
"stream": False,
"nsfw_filter": False,
}
response = await generate_images(data)
response = await generate_images(data_img2img if img2img else data)
try:
image_url = response["image_url"]
async with aiohttp.ClientSession() as session:
@@ -546,6 +797,8 @@ async def vpixl(c: Client, message: Message):
caption=f"<b>Prompt: </b><code>{prompt}</code>\n<b>Model: </b><code>{model}</code>",
)
os.remove(filename)
if img2img:
os.remove(image_path)
await message.delete()
except KeyError:
try:
@@ -570,6 +823,7 @@ async def vpixl(c: Client, message: Message):
@Client.on_message(filters.command("vkxl", prefix) & filters.me)
async def vkxl(c: Client, message: Message):
"""Text to Image Generation Using SDXL"""
img2img = False
await message.edit_text("<code>Please Wait...</code>")
@@ -599,11 +853,45 @@ async def vkxl(c: Client, message: Message):
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vkxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
elif (
message.reply_to_message
and message.reply_to_message.photo
and len(message.command) > 1
):
img2img = True
model = message.text.split(maxsplit=1)[1]
if model in models:
prompt = message.reply_to_message.caption
image_path = await message.reply_to_message.download()
with open(image_path, "rb") as image_file:
image_data = base64.b64encode(image_file.read()).decode("utf-8")
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vkxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
else:
return await message.edit_text(
f"<b>Usage: </b><code>{prefix}vkxl [model]* [prompt/reply to prompt]*</code>\n <b>Available Models:</b> <blockquote>{models}</blockquote>"
)
data_img2img = {
"model": model,
"prompt": prompt,
"negative_prompt": "bad quality",
"token": vca_api_key,
"sampler": "Euler",
"steps": 30,
"width": 1024,
"height": 1024,
"cfg_scale": 7,
"loras": {},
"seed": -1,
"init_image": image_data if img2img else None,
"denoising_strength": 0.7,
"stream": False,
"nsfw_filter": False,
}
data = {
"model": model,
"prompt": prompt,
@@ -617,9 +905,10 @@ async def vkxl(c: Client, message: Message):
"loras": {},
"seed": -1,
"stream": False,
"nsfw_filter": False,
}
response = await generate_images(data)
response = await generate_images(data_img2img if img2img else data)
try:
image_url = response["image_url"]
async with aiohttp.ClientSession() as session:
@@ -633,6 +922,8 @@ async def vkxl(c: Client, message: Message):
caption=f"<b>Prompt: </b><code>{prompt}</code>\n<b>Model: </b><code>{model}</code>",
)
os.remove(filename)
if img2img:
os.remove(image_path)
await message.delete()
except KeyError:
try:
@@ -705,6 +996,7 @@ async def vgif(c: Client, message: Message):
"cfg_scale": 7,
"sampler": "Euler",
"loras": {},
"nsfw_filter": False,
}
response = await generate_video(data)