diff --git a/extensions/sd_api_pictures/README.MD b/extensions/sd_api_pictures/README.MD
new file mode 100644
index 0000000..f1fdb5c
--- /dev/null
+++ b/extensions/sd_api_pictures/README.MD
@@ -0,0 +1,78 @@
+## Description:
+TL;DR: Lets the bot answer you with a picture!
+
+Stable Diffusion API pictures for TextGen, v.1.1.0
+An extension to [oobabooga's textgen-webui](https://github.com/oobabooga/text-generation-webui) allowing you to receive pics generated by [Automatic1111's SD-WebUI API](https://github.com/AUTOMATIC1111/stable-diffusion-webui)
+
+
+Interface overview
+
+
+
+
+
+Load it in the `--chat` mode with `--extension sd_api_pictures` alongside `send_pictures` (it's not really required, but completes the picture, *pun intended*).
+
+The image generation is triggered either:
+- manually through the 'Force the picture response' button while in `Manual` or `Immersive/Interactive` modes OR
+- automatically in `Immersive/Interactive` mode if the words `'send|main|message|me'` are followed by `'image|pic|picture|photo|snap|snapshot|selfie|meme'` in the user's prompt
+- always on in Picturebook/Adventure mode (if not currently suppressed by 'Suppress the picture response')
+
+## Prerequisites
+
+One needs an available instance of Automatic1111's webui running with an `--api` flag. Ain't tested with a notebook / cloud hosted one but should be possible.
+To run it locally in parallel on the same machine, specify custom `--listen-port` for either Auto1111's or ooba's webUIs.
+
+## Features:
+- API detection (press enter in the API box)
+- VRAM management (model shuffling)
+- Three different operation modes (manual, interactive, always-on)
+- persistent settings via settings.json
+
+The model input is modified only in the interactive mode; other two are unaffected. The output pic description is presented differently for Picture-book / Adventure mode.
+
+Connection check (insert the Auto1111's address and press Enter):
+
+
+### Persistents settings
+
+Create or modify the `settings.json` in the `text-generation-webui` root directory to override the defaults
+present in script.py, ex:
+
+```json
+{
+ "sd_api_pictures-manage_VRAM": 1,
+ "sd_api_pictures-save_img": 1,
+ "sd_api_pictures-prompt_prefix": "(Masterpiece:1.1), detailed, intricate, colorful, (solo:1.1)",
+ "sd_api_pictures-sampler_name": "DPM++ 2M Karras"
+}
+```
+
+will automatically set the `Manage VRAM` & `Keep original images` checkboxes and change the texts in `Prompt Prefix` and `Sampler name` on load.
+
+---
+
+## Demonstrations:
+
+Those are examples of the version 1.0.0, but the core functionality is still the same
+
+
+Conversation 1
+
+
+
+
+
+
+
+
+
+
+Conversation 2
+
+
+
+
+
+
+
diff --git a/extensions/sd_api_pictures/script.py b/extensions/sd_api_pictures/script.py
index 80a6027..5eff143 100644
--- a/extensions/sd_api_pictures/script.py
+++ b/extensions/sd_api_pictures/script.py
@@ -1,34 +1,78 @@
import base64
import io
import re
+import time
+from datetime import date
from pathlib import Path
import gradio as gr
+import modules.shared as shared
import requests
import torch
+from modules.models import reload_model, unload_model
from PIL import Image
-from modules import chat, shared
-
torch._C._jit_set_profiling_mode(False)
# parameters which can be customized in settings.json of webui
params = {
- 'enable_SD_api': False,
'address': 'http://127.0.0.1:7860',
+ 'mode': 0, # modes of operation: 0 (Manual only), 1 (Immersive/Interactive - looks for words to trigger), 2 (Picturebook Adventure - Always on)
+ 'manage_VRAM': False,
'save_img': False,
- 'SD_model': 'NeverEndingDream', # not really used right now
- 'prompt_prefix': '(Masterpiece:1.1), (solo:1.3), detailed, intricate, colorful',
+ 'SD_model': 'NeverEndingDream', # not used right now
+ 'prompt_prefix': '(Masterpiece:1.1), detailed, intricate, colorful',
'negative_prompt': '(worst quality, low quality:1.3)',
- 'side_length': 512,
- 'restore_faces': False
+ 'width': 512,
+ 'height': 512,
+ 'restore_faces': False,
+ 'seed': -1,
+ 'sampler_name': 'DDIM',
+ 'steps': 32,
+ 'cfg_scale': 7
}
+
+def give_VRAM_priority(actor):
+ global shared, params
+
+ if actor == 'SD':
+ unload_model()
+ print("Requesting Auto1111 to re-load last checkpoint used...")
+ response = requests.post(url=f'{params["address"]}/sdapi/v1/reload-checkpoint', json='')
+ response.raise_for_status()
+
+ elif actor == 'LLM':
+ print("Requesting Auto1111 to vacate VRAM...")
+ response = requests.post(url=f'{params["address"]}/sdapi/v1/unload-checkpoint', json='')
+ response.raise_for_status()
+ reload_model()
+
+ elif actor == 'set':
+ print("VRAM mangement activated -- requesting Auto1111 to vacate VRAM...")
+ response = requests.post(url=f'{params["address"]}/sdapi/v1/unload-checkpoint', json='')
+ response.raise_for_status()
+
+ elif actor == 'reset':
+ print("VRAM mangement deactivated -- requesting Auto1111 to reload checkpoint")
+ response = requests.post(url=f'{params["address"]}/sdapi/v1/reload-checkpoint', json='')
+ response.raise_for_status()
+
+ else:
+ raise RuntimeError(f'Managing VRAM: "{actor}" is not a known state!')
+
+ response.raise_for_status()
+ del response
+
+
+if params['manage_VRAM']:
+ give_VRAM_priority('set')
+
+samplers = ['DDIM', 'DPM++ 2M Karras'] # TODO: get the availible samplers with http://{address}}/sdapi/v1/samplers
SD_models = ['NeverEndingDream'] # TODO: get with http://{address}}/sdapi/v1/sd-models and allow user to select
streaming_state = shared.args.no_stream # remember if chat streaming was enabled
picture_response = False # specifies if the next model response should appear as a picture
-pic_id = 0
def remove_surrounded_chars(string):
@@ -36,7 +80,13 @@ def remove_surrounded_chars(string):
# 'as few symbols as possible (0 upwards) between an asterisk and the end of the string'
return re.sub('\*[^\*]*?(\*|$)', '', string)
-# I don't even need input_hijack for this as visible text will be commited to history as the unmodified string
+
+def triggers_are_in(string):
+ string = remove_surrounded_chars(string)
+ # regex searches for send|main|message|me (at the end of the word) followed by
+ # a whole word of image|pic|picture|photo|snap|snapshot|selfie|meme(s),
+ # (?aims) are regex parser flags
+ return bool(re.search('(?aims)(send|mail|message|me)\\b.+?\\b(image|pic(ture)?|photo|snap(shot)?|selfie|meme)s?\\b', string))
def input_modifier(string):
@@ -44,75 +94,80 @@ def input_modifier(string):
This function is applied to your text inputs before
they are fed into the model.
"""
- global params, picture_response
- if not params['enable_SD_api']:
+
+ global params
+
+ if not params['mode'] == 1: # if not in immersive/interactive mode, do nothing
return string
- commands = ['send', 'mail', 'me']
- mediums = ['image', 'pic', 'picture', 'photo']
- subjects = ['yourself', 'own']
- lowstr = string.lower()
-
- # TODO: refactor out to separate handler and also replace detection with a regexp
- if any(command in lowstr for command in commands) and any(case in lowstr for case in mediums): # trigger the generation if a command signature and a medium signature is found
- picture_response = True
- shared.args.no_stream = True # Disable streaming cause otherwise the SD-generated picture would return as a dud
- shared.processing_message = "*Is sending a picture...*"
- string = "Please provide a detailed description of your surroundings, how you look and the situation you're in and what you are doing right now"
- if any(target in lowstr for target in subjects): # the focus of the image should be on the sending character
- string = "Please provide a detailed and vivid description of how you look and what you are wearing"
+ if triggers_are_in(string): # if we're in it, check for trigger words
+ toggle_generation(True)
+ string = string.lower()
+ if "of" in string:
+ subject = string.split('of', 1)[1] # subdivide the string once by the first 'of' instance and get what's coming after it
+ string = "Please provide a detailed and vivid description of " + subject
+ else:
+ string = "Please provide a detailed description of your appearance, your surroundings and what you are doing right now"
return string
# Get and save the Stable Diffusion-generated picture
-
-
def get_SD_pictures(description):
- global params, pic_id
+ global params
+
+ if params['manage_VRAM']:
+ give_VRAM_priority('SD')
payload = {
"prompt": params['prompt_prefix'] + description,
- "seed": -1,
- "sampler_name": "DPM++ 2M Karras",
- "steps": 32,
- "cfg_scale": 7,
- "width": params['side_length'],
- "height": params['side_length'],
+ "seed": params['seed'],
+ "sampler_name": params['sampler_name'],
+ "steps": params['steps'],
+ "cfg_scale": params['cfg_scale'],
+ "width": params['width'],
+ "height": params['height'],
"restore_faces": params['restore_faces'],
"negative_prompt": params['negative_prompt']
}
+ print(f'Prompting the image generator via the API on {params["address"]}...')
response = requests.post(url=f'{params["address"]}/sdapi/v1/txt2img', json=payload)
+ response.raise_for_status()
r = response.json()
visible_result = ""
for img_str in r['images']:
image = Image.open(io.BytesIO(base64.b64decode(img_str.split(",", 1)[0])))
if params['save_img']:
- output_file = Path(f'extensions/sd_api_pictures/outputs/{pic_id:06d}.png')
+ variadic = f'{date.today().strftime("%Y_%m_%d")}/{shared.character}_{int(time.time())}'
+ output_file = Path(f'extensions/sd_api_pictures/outputs/{variadic}.png')
+ output_file.parent.mkdir(parents=True, exist_ok=True)
image.save(output_file.as_posix())
- pic_id += 1
- # lower the resolution of received images for the chat, otherwise the log size gets out of control quickly with all the base64 values in visible history
- image.thumbnail((300, 300))
- buffered = io.BytesIO()
- image.save(buffered, format="JPEG")
- buffered.seek(0)
- image_bytes = buffered.getvalue()
- img_str = "data:image/jpeg;base64," + base64.b64encode(image_bytes).decode()
- visible_result = visible_result + f'
\n'
+ visible_result = visible_result + f'
\n'
+ else:
+ # lower the resolution of received images for the chat, otherwise the log size gets out of control quickly with all the base64 values in visible history
+ image.thumbnail((300, 300))
+ buffered = io.BytesIO()
+ image.save(buffered, format="JPEG")
+ buffered.seek(0)
+ image_bytes = buffered.getvalue()
+ img_str = "data:image/jpeg;base64," + base64.b64encode(image_bytes).decode()
+ visible_result = visible_result + f'\n'
+
+ if params['manage_VRAM']:
+ give_VRAM_priority('LLM')
return visible_result
# TODO: how do I make the UI history ignore the resulting pictures (I don't want HTML to appear in history)
# and replace it with 'text' for the purposes of logging?
-
-
def output_modifier(string):
"""
This function is applied to the model outputs.
"""
- global pic_id, picture_response, streaming_state
+
+ global picture_response, params
if not picture_response:
return string
@@ -125,17 +180,18 @@ def output_modifier(string):
if string == '':
string = 'no viable description in reply, try regenerating'
+ return string
- # I can't for the love of all that's holy get the name from shared.gradio['name1'], so for now it will be like this
- text = f'*Description: "{string}"*'
+ text = ""
+ if (params['mode'] < 2):
+ toggle_generation(False)
+ text = f'*Sends a picture which portrays: “{string}”*'
+ else:
+ text = string
- image = get_SD_pictures(string)
+ string = get_SD_pictures(string) + "\n" + text
- picture_response = False
-
- shared.processing_message = "*Is typing...*"
- shared.args.no_stream = streaming_state
- return image + "\n" + text
+ return string
def bot_prefix_modifier(string):
@@ -148,42 +204,91 @@ def bot_prefix_modifier(string):
return string
-def force_pic():
- global picture_response
- picture_response = True
+def toggle_generation(*args):
+ global picture_response, shared, streaming_state
+
+ if not args:
+ picture_response = not picture_response
+ else:
+ picture_response = args[0]
+
+ shared.args.no_stream = True if picture_response else streaming_state # Disable streaming cause otherwise the SD-generated picture would return as a dud
+ shared.processing_message = "*Is sending a picture...*" if picture_response else "*Is typing...*"
+
+
+def filter_address(address):
+ address = address.strip()
+ # address = re.sub('http(s)?:\/\/|\/$','',address) # remove starting http:// OR https:// OR trailing slash
+ address = re.sub('\/$', '', address) # remove trailing /s
+ if not address.startswith('http'):
+ address = 'http://' + address
+ return address
+
+
+def SD_api_address_update(address):
+
+ global params
+
+ msg = "✔️ SD API is found on:"
+ address = filter_address(address)
+ params.update({"address": address})
+ try:
+ response = requests.get(url=f'{params["address"]}/sdapi/v1/sd-models')
+ response.raise_for_status()
+ # r = response.json()
+ except:
+ msg = "❌ No SD API endpoint on:"
+
+ return gr.Textbox.update(label=msg)
def ui():
# Gradio elements
- with gr.Accordion("Stable Diffusion api integration", open=True):
+ # gr.Markdown('### Stable Diffusion API Pictures') # Currently the name of extension is shown as the title
+ with gr.Accordion("Parameters", open=True):
with gr.Row():
- with gr.Column():
- enable = gr.Checkbox(value=params['enable_SD_api'], label='Activate SD Api integration')
- save_img = gr.Checkbox(value=params['save_img'], label='Keep original received images in the outputs subdir')
- with gr.Column():
- address = gr.Textbox(placeholder=params['address'], value=params['address'], label='Stable Diffusion host address')
+ address = gr.Textbox(placeholder=params['address'], value=params['address'], label='Auto1111\'s WebUI address')
+ mode = gr.Dropdown(["Manual", "Immersive/Interactive", "Picturebook/Adventure"], value="Manual", label="Mode of operation", type="index")
+ with gr.Column(scale=1, min_width=300):
+ manage_VRAM = gr.Checkbox(value=params['manage_VRAM'], label='Manage VRAM')
+ save_img = gr.Checkbox(value=params['save_img'], label='Keep original images and use them in chat')
- with gr.Row():
- force_btn = gr.Button("Force the next response to be a picture")
- generate_now_btn = gr.Button("Generate an image response to the input")
+ force_pic = gr.Button("Force the picture response")
+ suppr_pic = gr.Button("Suppress the picture response")
with gr.Accordion("Generation parameters", open=False):
prompt_prefix = gr.Textbox(placeholder=params['prompt_prefix'], value=params['prompt_prefix'], label='Prompt Prefix (best used to describe the look of the character)')
with gr.Row():
- negative_prompt = gr.Textbox(placeholder=params['negative_prompt'], value=params['negative_prompt'], label='Negative Prompt')
- dimensions = gr.Slider(256, 702, value=params['side_length'], step=64, label='Image dimensions')
- # model = gr.Dropdown(value=SD_models[0], choices=SD_models, label='Model')
+ with gr.Column():
+ negative_prompt = gr.Textbox(placeholder=params['negative_prompt'], value=params['negative_prompt'], label='Negative Prompt')
+ sampler_name = gr.Textbox(placeholder=params['sampler_name'], value=params['sampler_name'], label='Sampler')
+ with gr.Column():
+ width = gr.Slider(256, 768, value=params['width'], step=64, label='Width')
+ height = gr.Slider(256, 768, value=params['height'], step=64, label='Height')
+ with gr.Row():
+ steps = gr.Number(label="Steps:", value=params['steps'])
+ seed = gr.Number(label="Seed:", value=params['seed'])
+ cfg_scale = gr.Number(label="CFG Scale:", value=params['cfg_scale'])
# Event functions to update the parameters in the backend
- enable.change(lambda x: params.update({"enable_SD_api": x}), enable, None)
+ address.change(lambda x: params.update({"address": filter_address(x)}), address, None)
+ mode.select(lambda x: params.update({"mode": x}), mode, None)
+ mode.select(lambda x: toggle_generation(x > 1), inputs=mode, outputs=None)
+ manage_VRAM.change(lambda x: params.update({"manage_VRAM": x}), manage_VRAM, None)
+ manage_VRAM.change(lambda x: give_VRAM_priority('set' if x else 'reset'), inputs=manage_VRAM, outputs=None)
save_img.change(lambda x: params.update({"save_img": x}), save_img, None)
- address.change(lambda x: params.update({"address": x}), address, None)
+
+ address.submit(fn=SD_api_address_update, inputs=address, outputs=address)
prompt_prefix.change(lambda x: params.update({"prompt_prefix": x}), prompt_prefix, None)
negative_prompt.change(lambda x: params.update({"negative_prompt": x}), negative_prompt, None)
- dimensions.change(lambda x: params.update({"side_length": x}), dimensions, None)
- # model.change(lambda x: params.update({"SD_model": x}), model, None)
+ width.change(lambda x: params.update({"width": x}), width, None)
+ height.change(lambda x: params.update({"height": x}), height, None)
- force_btn.click(force_pic)
- generate_now_btn.click(force_pic)
- generate_now_btn.click(chat.cai_chatbot_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream)
+ sampler_name.change(lambda x: params.update({"sampler_name": x}), sampler_name, None)
+ steps.change(lambda x: params.update({"steps": x}), steps, None)
+ seed.change(lambda x: params.update({"seed": x}), seed, None)
+ cfg_scale.change(lambda x: params.update({"cfg_scale": x}), cfg_scale, None)
+
+ force_pic.click(lambda x: toggle_generation(True), inputs=force_pic, outputs=None)
+ suppr_pic.click(lambda x: toggle_generation(False), inputs=suppr_pic, outputs=None)
diff --git a/modules/LoRA.py b/modules/LoRA.py
index 17dd722..0cf379e 100644
--- a/modules/LoRA.py
+++ b/modules/LoRA.py
@@ -4,14 +4,7 @@ import torch
from peft import PeftModel
import modules.shared as shared
-from modules.models import load_model
-from modules.text_generation import clear_torch_cache
-
-
-def reload_model():
- shared.model = shared.tokenizer = None
- clear_torch_cache()
- shared.model, shared.tokenizer = load_model(shared.model_name)
+from modules.models import reload_model
def add_lora_to_model(lora_name):
diff --git a/modules/models.py b/modules/models.py
index 5e2b098..6fa7dbb 100644
--- a/modules/models.py
+++ b/modules/models.py
@@ -1,3 +1,4 @@
+import gc
import json
import os
import re
@@ -16,11 +17,10 @@ import modules.shared as shared
transformers.logging.set_verbosity_error()
-local_rank = None
-
if shared.args.flexgen:
from flexgen.flex_opt import CompressionConfig, ExecutionEnv, OptLM, Policy
+local_rank = None
if shared.args.deepspeed:
import deepspeed
from transformers.deepspeed import (HfDeepSpeedConfig,
@@ -182,6 +182,23 @@ def load_model(model_name):
return model, tokenizer
+def clear_torch_cache():
+ gc.collect()
+ if not shared.args.cpu:
+ torch.cuda.empty_cache()
+
+
+def unload_model():
+ shared.model = shared.tokenizer = None
+ clear_torch_cache()
+
+
+def reload_model():
+ shared.model = shared.tokenizer = None
+ clear_torch_cache()
+ shared.model, shared.tokenizer = load_model(shared.model_name)
+
+
def load_soft_prompt(name):
if name == 'None':
shared.soft_prompt = False
diff --git a/modules/text_generation.py b/modules/text_generation.py
index 9719c5a..80bb34d 100644
--- a/modules/text_generation.py
+++ b/modules/text_generation.py
@@ -1,4 +1,3 @@
-import gc
import re
import time
import traceback
@@ -12,7 +11,7 @@ from modules.callbacks import (Iteratorize, Stream,
_SentinelTokenStoppingCriteria)
from modules.extensions import apply_extensions
from modules.html_generator import generate_4chan_html, generate_basic_html
-from modules.models import local_rank
+from modules.models import clear_torch_cache, local_rank
def get_max_prompt_length(tokens):
@@ -101,12 +100,6 @@ def formatted_outputs(reply, model_name):
return reply
-def clear_torch_cache():
- gc.collect()
- if not shared.args.cpu:
- torch.cuda.empty_cache()
-
-
def set_manual_seed(seed):
if seed != -1:
torch.manual_seed(seed)
diff --git a/server.py b/server.py
index 1436f9f..48fea6e 100644
--- a/server.py
+++ b/server.py
@@ -18,9 +18,8 @@ import modules.extensions as extensions_module
from modules import api, chat, shared, training, ui
from modules.html_generator import chat_html_wrapper
from modules.LoRA import add_lora_to_model
-from modules.models import load_model, load_soft_prompt
-from modules.text_generation import (clear_torch_cache, generate_reply,
- stop_everything_event)
+from modules.models import load_model, load_soft_prompt, unload_model
+from modules.text_generation import generate_reply, stop_everything_event
# Loading custom settings
settings_file = None
@@ -79,11 +78,6 @@ def get_available_loras():
return ['None'] + sorted([item.name for item in list(Path(shared.args.lora_dir).glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
-def unload_model():
- shared.model = shared.tokenizer = None
- clear_torch_cache()
-
-
def load_model_wrapper(selected_model):
if selected_model != shared.model_name:
shared.model_name = selected_model