mirror of
https://github.com/ParisNeo/lollms.git
synced 2024-12-18 20:27:58 +00:00
added diffusers_client
This commit is contained in:
Saifeddine ALOUI
parent
9d19668e9a
commit
d2b4036e57
@ -1,5 +1,5 @@
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# =================== Lord Of Large Language Multimodal Systems Configuration file ===========================
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version: 134
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version: 135
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binding_name: null
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model_name: null
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model_variant: null
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@ -102,7 +102,7 @@ copy_to_clipboard_add_all_details: false
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# -------------------- Services global configurations --------------------------
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# Select the active test to speach, text to image and speach to text services
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active_tts_service: "None" # xtts (offline), openai_tts (API key required), elevenlabs_tts (API key required)
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active_tti_service: "None" # autosd (offline), dall-e (online)
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active_tti_service: "None" # autosd (offline), diffusers (offline), diffusers_client (online), dall-e (online), midjourney (online)
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active_stt_service: "None" # whisper (offline), asr (offline or online), openai_whiosper (API key required)
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active_ttm_service: "None" # musicgen (offline)
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active_ttv_service: "None" # cog_video_x (offline)
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@ -183,9 +183,13 @@ sd_base_url: http://localhost:7860
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enable_fooocus_service: false
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fooocus_base_url: http://localhost:7860
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# diffuser
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# diffusers
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diffusers_offloading_mode: sequential_cpu_offload # sequential_cpu_offload
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diffusers_model: PixArt-alpha/PixArt-Sigma-XL-2-1024-MS
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diffusers_model: v2ray/stable-diffusion-3-medium-diffusers
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# diffusers client
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diffusers_client_base_url: http://localhost:8593
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# Dall e service key
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dall_e_key: ""
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@ -424,6 +424,9 @@ class LollmsApplication(LoLLMsCom):
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if self.config.active_tti_service == "diffusers":
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from lollms.services.tti.diffusers.lollms_diffusers import LollmsDiffusers
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self.tti = LollmsDiffusers(self)
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elif self.config.active_tti_service == "diffusers_client":
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from lollms.services.tti.diffusers_client.lollms_diffusers_client import LollmsDiffusersClient
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self.tti = LollmsDiffusersClient(self)
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elif self.config.active_tti_service == "autosd":
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if self.sd:
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self.tti = self.sd
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@ -526,6 +529,9 @@ class LollmsApplication(LoLLMsCom):
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if self.config.active_tti_service == "diffusers" and (self.tti is None or self.tti.name!="diffusers"):
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from lollms.services.tti.diffusers.lollms_diffusers import LollmsDiffusers
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self.tti = LollmsDiffusers(self)
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elif self.config.active_tti_service == "diffusers_client" and (self.tti is None or self.tti.name!="diffusers_client"):
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from lollms.services.tti.diffusers_client.lollms_diffusers_client import LollmsDiffusersClient
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self.tti = LollmsDiffusersClient(self)
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elif self.config.active_tti_service == "autosd" and (self.tti is None or self.tti.name!="stable_diffusion"):
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if self.sd:
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self.tti = self.sd
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@ -1,5 +1,5 @@
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# =================== Lord Of Large Language Multimodal Systems Configuration file ===========================
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version: 134
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version: 135
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binding_name: null
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model_name: null
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model_variant: null
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@ -102,7 +102,7 @@ copy_to_clipboard_add_all_details: false
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# -------------------- Services global configurations --------------------------
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# Select the active test to speach, text to image and speach to text services
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active_tts_service: "None" # xtts (offline), openai_tts (API key required), elevenlabs_tts (API key required)
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active_tti_service: "None" # autosd (offline), dall-e (online)
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active_tti_service: "None" # autosd (offline), diffusers (offline), diffusers_client (online), dall-e (online), midjourney (online)
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active_stt_service: "None" # whisper (offline), asr (offline or online), openai_whiosper (API key required)
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active_ttm_service: "None" # musicgen (offline)
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active_ttv_service: "None" # cog_video_x (offline)
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@ -183,9 +183,13 @@ sd_base_url: http://localhost:7860
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enable_fooocus_service: false
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fooocus_base_url: http://localhost:7860
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# diffuser
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# diffusers
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diffusers_offloading_mode: sequential_cpu_offload # sequential_cpu_offload
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diffusers_model: PixArt-alpha/PixArt-Sigma-XL-2-1024-MS
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diffusers_model: v2ray/stable-diffusion-3-medium-diffusers
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# diffusers client
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diffusers_client_base_url: http://localhost:8593
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# Dall e service key
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dall_e_key: ""
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216
lollms/services/tti/diffusers_client/lollms_diffusers_client.py
Normal file
216
lollms/services/tti/diffusers_client/lollms_diffusers_client.py
Normal file
@ -0,0 +1,216 @@
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# Title LollmsDiffusers
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# Licence: MIT
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# Author : Paris Neo
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# All rights are reserved
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from pathlib import Path
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import sys
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from lollms.app import LollmsApplication
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from lollms.utilities import PackageManager, check_and_install_torch, find_next_available_filename, install_cuda, check_torch_version
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import sys
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import requests
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from typing import List, Dict, Any
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from ascii_colors import ASCIIColors, trace_exception
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from lollms.paths import LollmsPaths
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from lollms.tti import LollmsTTI
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from lollms.utilities import git_pull
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from tqdm import tqdm
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from PIL import Image
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import threading
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import base64
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from PIL import Image
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import io
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import pipmaster as pm
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def adjust_dimensions(value: int) -> int:
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"""Adjusts the given value to be divisible by 8."""
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return (value // 8) * 8
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def download_file(url, folder_path, local_filename):
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# Make sure 'folder_path' exists
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folder_path.mkdir(parents=True, exist_ok=True)
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with requests.get(url, stream=True) as r:
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r.raise_for_status()
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total_size = int(r.headers.get('content-length', 0))
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progress_bar = tqdm(total=total_size, unit='B', unit_scale=True)
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with open(folder_path / local_filename, 'wb') as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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progress_bar.update(len(chunk))
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progress_bar.close()
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return local_filename
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def install_diffusers(lollms_app:LollmsApplication):
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root_dir = lollms_app.lollms_paths.personal_path
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shared_folder = root_dir/"shared"
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diffusers_folder = shared_folder / "diffusers"
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diffusers_folder.mkdir(exist_ok=True, parents=True)
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models_dir = diffusers_folder / "models"
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models_dir.mkdir(parents=True, exist_ok=True)
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PackageManager.reinstall("diffusers")
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PackageManager.reinstall("xformers")
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def upgrade_diffusers(lollms_app:LollmsApplication):
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PackageManager.install_or_update("diffusers")
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PackageManager.install_or_update("xformers")
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class LollmsDiffusersClient(LollmsTTI):
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has_controlnet = False
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def __init__(
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self,
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app:LollmsApplication,
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wm = "Artbot",
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base_url:str="http://localhost:8593"
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):
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super().__init__("diffusers_client",app)
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self.ready = False
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# Get the current directory
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lollms_paths = app.lollms_paths
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root_dir = lollms_paths.personal_path
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self.base_url = base_url
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self.wm = wm
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shared_folder = root_dir/"shared"
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self.diffusers_folder = shared_folder / "diffusers"
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self.output_dir = root_dir / "outputs/diffusers"
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self.models_dir = self.diffusers_folder / "models"
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self.output_dir.mkdir(parents=True, exist_ok=True)
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self.models_dir.mkdir(parents=True, exist_ok=True)
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ASCIIColors.green(" _ _ _ _ _ __ __ ")
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ASCIIColors.green(" | | | | | | (_)/ _|/ _| ")
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ASCIIColors.green(" | | ___ | | |_ __ ___ ___ __| |_| |_| |_ _ _ ___ ___ _ __ ___ ")
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ASCIIColors.green(" | | / _ \| | | '_ ` _ \/ __| / _` | | _| _| | | / __|/ _ \ '__/ __| ")
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ASCIIColors.green(" | |___| (_) | | | | | | | \__ \| (_| | | | | | | |_| \__ \ __/ | \__ \ ")
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ASCIIColors.green(" |______\___/|_|_|_| |_| |_|___/ \__,_|_|_| |_| \__,_|___/\___|_| |___/ ")
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ASCIIColors.green(" ______ ")
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ASCIIColors.green(" |______| ")
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@staticmethod
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def verify(app:LollmsApplication):
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# Clone repository
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root_dir = app.lollms_paths.personal_path
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shared_folder = root_dir/"shared"
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diffusers_folder = shared_folder / "diffusers"
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return diffusers_folder.exists()
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def get(app:LollmsApplication):
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root_dir = app.lollms_paths.personal_path
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shared_folder = root_dir/"shared"
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diffusers_folder = shared_folder / "diffusers"
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diffusers_script_path = diffusers_folder / "lollms_diffusers.py"
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git_pull(diffusers_folder)
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if diffusers_script_path.exists():
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ASCIIColors.success("lollms_diffusers found.")
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ASCIIColors.success("Loading source file...",end="")
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# use importlib to load the module from the file path
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from lollms.services.tti.diffusers.lollms_diffusers import LollmsDiffusers
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ASCIIColors.success("ok")
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return LollmsDiffusers
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def paint(
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self,
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positive_prompt,
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negative_prompt="",
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sampler_name="",
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seed=-1,
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scale=7.5,
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steps=20,
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img2img_denoising_strength=0.9,
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width=512,
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height=512,
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restore_faces=True,
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output_path=None
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):
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url = f"{self.base_url}/generate-image"
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payload = {
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"positive_prompt": positive_prompt,
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"negative_prompt": negative_prompt,
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"sampler_name": sampler_name,
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"seed": seed,
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"scale": scale,
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"steps": steps,
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"width": width,
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"height": height,
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"restore_faces": restore_faces
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}
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try:
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response = requests.post(url, json=payload)
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response.raise_for_status()
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result = response.json()
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# Assuming the server returns the image path
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server_image_path = result['image_path']
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# If output_path is not provided, use the server's image path
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if output_path is None:
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output_path = server_image_path
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else:
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# Copy the image from server path to output_path
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# This part needs to be implemented based on how you want to handle file transfer
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pass
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return {
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"image_path": output_path,
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"prompt": result['prompt'],
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"negative_prompt": result['negative_prompt']
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}
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except requests.exceptions.RequestException as e:
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print(f"An error occurred: {e}")
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return None
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def save_image(self, image_data, output_path):
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image = Image.open(io.BytesIO(base64.b64decode(image_data)))
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image.save(output_path)
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print(f"Image saved to {output_path}")
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def paint_from_images(self, positive_prompt: str,
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images: List[str],
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negative_prompt: str = "",
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sampler_name="",
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seed=-1,
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scale=7.5,
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steps=20,
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img2img_denoising_strength=0.9,
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width=512,
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height=512,
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restore_faces=True,
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output_path=None
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) -> List[Dict[str, str]]:
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import torch
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if sampler_name!="":
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sc = self.get_scheduler_by_name(sampler_name)
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if sc:
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self.model.scheduler = sc
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if output_path is None:
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output_path = self.output_dir
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if seed!=-1:
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generator = torch.Generator("cuda").manual_seed(seed)
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image = self.model(positive_prompt, negative_prompt=negative_prompt, height=height, width=width, guidance_scale=scale, num_inference_steps=steps, generator=generator).images[0]
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else:
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image = self.model(positive_prompt, negative_prompt=negative_prompt, height=height, width=width, guidance_scale=scale, num_inference_steps=steps).images[0]
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output_path = Path(output_path)
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fn = find_next_available_filename(output_path,"diff_img_")
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# Save the image
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image.save(fn)
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return fn, {"prompt":positive_prompt, "negative_prompt":negative_prompt}
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