added diffusers_client

configs/config.yaml

@@ -1,5 +1,5 @@
 # =================== Lord Of Large Language Multimodal Systems Configuration file =========================== 
-version: 134
+version: 135
 binding_name: null
 model_name: null
 model_variant: null
@@ -102,7 +102,7 @@ copy_to_clipboard_add_all_details: false
 # -------------------- Services global configurations --------------------------
 # Select the active test to speach, text to image and speach to text services
 active_tts_service: "None" # xtts (offline), openai_tts (API key required), elevenlabs_tts (API key required)
-active_tti_service: "None" # autosd (offline), dall-e (online)
+active_tti_service: "None" # autosd (offline), diffusers (offline), diffusers_client (online), dall-e (online), midjourney (online)
 active_stt_service: "None" # whisper (offline), asr (offline or online), openai_whiosper (API key required)
 active_ttm_service: "None" # musicgen (offline)
 active_ttv_service: "None" # cog_video_x (offline)
@@ -183,9 +183,13 @@ sd_base_url: http://localhost:7860
 enable_fooocus_service: false
 fooocus_base_url: http://localhost:7860
 
-# diffuser
+# diffusers
 diffusers_offloading_mode: sequential_cpu_offload # sequential_cpu_offload
-diffusers_model: PixArt-alpha/PixArt-Sigma-XL-2-1024-MS
+diffusers_model: v2ray/stable-diffusion-3-medium-diffusers
+
+# diffusers client
+diffusers_client_base_url: http://localhost:8593
+
 
 # Dall e service key
 dall_e_key: ""

lollms/app.py

@@ -424,6 +424,9 @@ class LollmsApplication(LoLLMsCom):
             if self.config.active_tti_service == "diffusers":
                 from lollms.services.tti.diffusers.lollms_diffusers import LollmsDiffusers
                 self.tti = LollmsDiffusers(self)
+            elif self.config.active_tti_service == "diffusers_client":
+                from lollms.services.tti.diffusers_client.lollms_diffusers_client import LollmsDiffusersClient
+                self.tti = LollmsDiffusersClient(self)
             elif self.config.active_tti_service == "autosd":
                 if self.sd:
                     self.tti = self.sd
@@ -526,6 +529,9 @@ class LollmsApplication(LoLLMsCom):
             if self.config.active_tti_service == "diffusers" and (self.tti is None or self.tti.name!="diffusers"):
                 from lollms.services.tti.diffusers.lollms_diffusers import LollmsDiffusers
                 self.tti = LollmsDiffusers(self)
+            elif self.config.active_tti_service == "diffusers_client" and (self.tti is None or self.tti.name!="diffusers_client"):
+                from lollms.services.tti.diffusers_client.lollms_diffusers_client import LollmsDiffusersClient
+                self.tti = LollmsDiffusersClient(self)
             elif self.config.active_tti_service == "autosd" and (self.tti is None or self.tti.name!="stable_diffusion"):
                 if self.sd:
                     self.tti = self.sd

lollms/configs/config.yaml

@@ -1,5 +1,5 @@
 # =================== Lord Of Large Language Multimodal Systems Configuration file =========================== 
-version: 134
+version: 135
 binding_name: null
 model_name: null
 model_variant: null
@@ -102,7 +102,7 @@ copy_to_clipboard_add_all_details: false
 # -------------------- Services global configurations --------------------------
 # Select the active test to speach, text to image and speach to text services
 active_tts_service: "None" # xtts (offline), openai_tts (API key required), elevenlabs_tts (API key required)
-active_tti_service: "None" # autosd (offline), dall-e (online)
+active_tti_service: "None" # autosd (offline), diffusers (offline), diffusers_client (online), dall-e (online), midjourney (online)
 active_stt_service: "None" # whisper (offline), asr (offline or online), openai_whiosper (API key required)
 active_ttm_service: "None" # musicgen (offline)
 active_ttv_service: "None" # cog_video_x (offline)
@@ -183,9 +183,13 @@ sd_base_url: http://localhost:7860
 enable_fooocus_service: false
 fooocus_base_url: http://localhost:7860
 
-# diffuser
+# diffusers
 diffusers_offloading_mode: sequential_cpu_offload # sequential_cpu_offload
-diffusers_model: PixArt-alpha/PixArt-Sigma-XL-2-1024-MS
+diffusers_model: v2ray/stable-diffusion-3-medium-diffusers
+
+# diffusers client
+diffusers_client_base_url: http://localhost:8593
+
 
 # Dall e service key
 dall_e_key: ""

lollms/services/tti/diffusers_client/lollms_diffusers_client.py

@@ -0,0 +1,216 @@
+# Title LollmsDiffusers
+# Licence: MIT
+# Author : Paris Neo
+    # All rights are reserved
+
+from pathlib import Path
+import sys
+from lollms.app import LollmsApplication
+from lollms.utilities import PackageManager, check_and_install_torch, find_next_available_filename, install_cuda, check_torch_version
+
+import sys
+import requests
+from typing import List, Dict, Any
+
+from ascii_colors import ASCIIColors, trace_exception
+from lollms.paths import LollmsPaths
+from lollms.tti import LollmsTTI
+from lollms.utilities import git_pull
+from tqdm import tqdm
+from PIL import Image
+import threading
+import base64
+from PIL import Image
+import io
+import pipmaster as pm
+
+
+def adjust_dimensions(value: int) -> int:
+    """Adjusts the given value to be divisible by 8."""
+    return (value // 8) * 8
+
+def download_file(url, folder_path, local_filename):
+    # Make sure 'folder_path' exists
+    folder_path.mkdir(parents=True, exist_ok=True)
+
+    with requests.get(url, stream=True) as r:
+        r.raise_for_status()
+        total_size = int(r.headers.get('content-length', 0))
+        progress_bar = tqdm(total=total_size, unit='B', unit_scale=True)
+        with open(folder_path / local_filename, 'wb') as f:
+            for chunk in r.iter_content(chunk_size=8192): 
+                f.write(chunk)
+                progress_bar.update(len(chunk))
+        progress_bar.close()
+
+    return local_filename
+
+
+def install_diffusers(lollms_app:LollmsApplication):
+    root_dir = lollms_app.lollms_paths.personal_path
+    shared_folder = root_dir/"shared"
+    diffusers_folder = shared_folder / "diffusers"
+    diffusers_folder.mkdir(exist_ok=True, parents=True)
+    models_dir = diffusers_folder / "models"
+    models_dir.mkdir(parents=True, exist_ok=True)
+
+    PackageManager.reinstall("diffusers")
+    PackageManager.reinstall("xformers")
+        
+
+
+
+def upgrade_diffusers(lollms_app:LollmsApplication):
+    PackageManager.install_or_update("diffusers")
+    PackageManager.install_or_update("xformers")
+
+
+class LollmsDiffusersClient(LollmsTTI):
+    has_controlnet = False
+    def __init__(
+                    self, 
+                    app:LollmsApplication, 
+                    wm = "Artbot", 
+                    base_url:str="http://localhost:8593"
+                    ):
+        super().__init__("diffusers_client",app)
+        self.ready = False
+        # Get the current directory
+        lollms_paths = app.lollms_paths
+        root_dir = lollms_paths.personal_path
+
+        self.base_url = base_url
+        
+        self.wm = wm
+
+        shared_folder = root_dir/"shared"
+        self.diffusers_folder = shared_folder / "diffusers"
+        self.output_dir = root_dir / "outputs/diffusers"
+        self.models_dir = self.diffusers_folder / "models"
+        self.output_dir.mkdir(parents=True, exist_ok=True)
+        self.models_dir.mkdir(parents=True, exist_ok=True)
+
+       
+        ASCIIColors.green("   _           _ _                    _ _  __  __                          ")
+        ASCIIColors.green("  | |         | | |                  | (_)/ _|/ _|                         ")
+        ASCIIColors.green("  | |     ___ | | |_ __ ___  ___   __| |_| |_| |_ _   _ ___  ___ _ __ ___  ")
+        ASCIIColors.green("  | |    / _ \| | | '_ ` _ \/ __| / _` | |  _|  _| | | / __|/ _ \ '__/ __| ")
+        ASCIIColors.green("  | |___| (_) | | | | | | | \__ \| (_| | | | | | | |_| \__ \  __/ |  \__ \ ")
+        ASCIIColors.green("  |______\___/|_|_|_| |_| |_|___/ \__,_|_|_| |_|  \__,_|___/\___|_|  |___/ ")
+        ASCIIColors.green("                              ______                                       ")
+        ASCIIColors.green("                             |______|                                      ")
+
+
+    @staticmethod
+    def verify(app:LollmsApplication):
+        # Clone repository
+        root_dir = app.lollms_paths.personal_path
+        shared_folder = root_dir/"shared"
+        diffusers_folder = shared_folder / "diffusers"
+        return diffusers_folder.exists()
+    
+    def get(app:LollmsApplication):
+        root_dir = app.lollms_paths.personal_path
+        shared_folder = root_dir/"shared"
+        diffusers_folder = shared_folder / "diffusers"
+        diffusers_script_path = diffusers_folder / "lollms_diffusers.py"
+        git_pull(diffusers_folder)
+        
+        if diffusers_script_path.exists():
+            ASCIIColors.success("lollms_diffusers found.")
+            ASCIIColors.success("Loading source file...",end="")
+            # use importlib to load the module from the file path
+            from lollms.services.tti.diffusers.lollms_diffusers import LollmsDiffusers
+            ASCIIColors.success("ok")
+            return LollmsDiffusers
+    def paint(
+        self,
+        positive_prompt,
+        negative_prompt="",
+        sampler_name="",
+        seed=-1,
+        scale=7.5,
+        steps=20,
+        img2img_denoising_strength=0.9,
+        width=512,
+        height=512,
+        restore_faces=True,
+        output_path=None
+    ):
+        url = f"{self.base_url}/generate-image"
+        
+        payload = {
+            "positive_prompt": positive_prompt,
+            "negative_prompt": negative_prompt,
+            "sampler_name": sampler_name,
+            "seed": seed,
+            "scale": scale,
+            "steps": steps,
+            "width": width,
+            "height": height,
+            "restore_faces": restore_faces
+        }
+
+        try:
+            response = requests.post(url, json=payload)
+            response.raise_for_status()
+            result = response.json()
+
+            # Assuming the server returns the image path
+            server_image_path = result['image_path']
+            
+            # If output_path is not provided, use the server's image path
+            if output_path is None:
+                output_path = server_image_path
+            else:
+                # Copy the image from server path to output_path
+                # This part needs to be implemented based on how you want to handle file transfer
+                pass
+
+            return {
+                "image_path": output_path,
+                "prompt": result['prompt'],
+                "negative_prompt": result['negative_prompt']
+            }
+
+        except requests.exceptions.RequestException as e:
+            print(f"An error occurred: {e}")
+            return None
+
+    def save_image(self, image_data, output_path):
+        image = Image.open(io.BytesIO(base64.b64decode(image_data)))
+        image.save(output_path)
+        print(f"Image saved to {output_path}")
+    
+    def paint_from_images(self, positive_prompt: str, 
+                            images: List[str], 
+                            negative_prompt: str = "",
+                            sampler_name="",
+                            seed=-1,
+                            scale=7.5,
+                            steps=20,
+                            img2img_denoising_strength=0.9,
+                            width=512,
+                            height=512,
+                            restore_faces=True,
+                            output_path=None
+                            ) -> List[Dict[str, str]]:
+        import torch
+        if sampler_name!="":
+            sc = self.get_scheduler_by_name(sampler_name)
+            if sc:
+                self.model.scheduler = sc
+
+        if output_path is None:
+            output_path = self.output_dir
+        if seed!=-1:
+            generator = torch.Generator("cuda").manual_seed(seed)
+            image = self.model(positive_prompt, negative_prompt=negative_prompt, height=height, width=width, guidance_scale=scale, num_inference_steps=steps, generator=generator).images[0]
+        else:
+            image = self.model(positive_prompt, negative_prompt=negative_prompt, height=height, width=width, guidance_scale=scale, num_inference_steps=steps).images[0]
+        output_path = Path(output_path)
+        fn = find_next_available_filename(output_path,"diff_img_")
+        # Save the image
+        image.save(fn)
+        return fn, {"prompt":positive_prompt, "negative_prompt":negative_prompt}
+