custom models, text file as input and cache results

Author: daswer123

README.md

@@ -72,7 +72,7 @@ docker compose up # or with -d to run in background
 Use the `--deepspeed` flag to process the result fast ( 2-3x acceleration )
 
 ```
-usage: xtts_api_server [-h] [-hs HOST] [-p PORT] [-sf SPEAKER_FOLDER] [-o OUTPUT] [-t TUNNEL_URL] [-ms MODEL_SOURCE] [--lowvram] [--deepspeed] [--streaming-mode] [--stream-play-sync]
+usage: xtts_api_server [-h] [-hs HOST] [-p PORT] [-sf SPEAKER_FOLDER] [-o OUTPUT] [-t TUNNEL_URL] [-ms MODEL_SOURCE] [--use-cache] [--lowvram] [--deepspeed] [--streaming-mode] [--stream-play-sync]
 
 Run XTTSv2 within a FastAPI application
 
@@ -85,14 +85,19 @@ options:
   -o OUTPUT, --output Output folder
   -t TUNNEL_URL, --tunnel URL of tunnel used (e.g: ngrok, localtunnel)
   -ms MODEL_SOURCE, --model-source ["api","apiManual","local"]
-  -v MODEL_VERSION, --version You can choose any version of the model, keep in mind that if you choose model-source api, only the latest version will be loaded
+  -v MODEL_VERSION, --version You can download the official model or your own model, official version you can find [here](https://huggingface.co/coqui/XTTS-v2/tree/main)  the model version name is the same as the branch name [v2.0.2,v2.0.3, main] etc.
+  --use-cache Enables caching of results, your results will be saved and if there will be a repeated request, you will get a file instead of generation
   --lowvram The mode in which the model will be stored in RAM and when the processing will move to VRAM, the difference in speed is small
   --deepspeed allows you to speed up processing by several times, automatically downloads the necessary libraries
   --streaming-mode Enables streaming mode, currently has certain limitations, as described below.
   --streaming-mode-improve Enables streaming mode, includes an improved streaming mode that consumes 2gb more VRAM and uses a better tokenizer and more context.
   --stream-play-sync Additional flag for streaming mod that allows you to play all audio one at a time without interruption
 ```
 
+You can specify the path to the file as text, then the path counts and the file will be voiced
+
+You can load your own model, for this you need to create a folder in models and load the model with configs, note in the folder should be 3 files `config.json` `vocab.json` `model.pth`
+
 If you want your host to listen, use -hs 0.0.0.0
 
 The -t or --tunnel flag is needed so that when you get speakers via get you get the correct link to hear the preview. More info [here](https://imgur.com/a/MvpFT59)
@@ -103,7 +108,7 @@ Model-source defines in which format you want to use xtts:
 2. `apiManual` - loads version 2.0.2 by default, but you can specify the version via the -v flag, model saves into the models folder and uses the `tts_to_file` function from the TTS api
 3. `api` - will load the latest version of the model. The -v flag won't work.
 
-All versions of the XTTSv2 model can be found [here](https://huggingface.co/coqui/XTTS-v2/tree/v2.0.2) in the branches
+All versions of the XTTSv2 model can be found [here](https://huggingface.co/coqui/XTTS-v2/tree/main)  the model version name is the same as the branch name [v2.0.2,v2.0.3, main] etc.
 
 The first time you run or generate, you may need to confirm that you agree to use XTTS.
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "xtts-api-server"
-version = "0.6.8"
+version = "0.7.0"
 authors = [
   { name="daswer123", email="daswerq123@gmail.com" },
 ]

xtts_api_server/RealtimeTTS/engines/coqui_engine.py

@@ -1,3 +1,4 @@
+from xtts_api_server.tts_funcs import official_model_list
 from torch.multiprocessing import Process, Pipe, Event, set_start_method
 from .base_engine import BaseEngine
 from typing import Union, List
@@ -92,7 +93,16 @@ def __init__(self,
             ModelManager().download_model(model_name)
         else:
             logging.info(f"Local XTTS Model: \"{specific_model}\" specified")
-            self.local_model_path = self.download_model(specific_model, local_models_path)
+            is_official_model = False
+            for model in official_model_list:
+              if self.specific_model == model:
+                is_official_model = True
+                break
+
+            if is_official_model:
+              self.local_model_path = self.download_model(specific_model, local_models_path)
+            else:
+              self.local_model_path = os.path.join(local_models_path,specific_model)
 
         self.synthesize_process = Process(target=CoquiEngine._synthesize_worker, args=(child_synthesize_pipe, model_name, cloning_reference_wav, language, self.main_synthesize_ready_event, level, self.speed, thread_count, stream_chunk_size, full_sentences, overlap_wav_len, temperature, length_penalty, repetition_penalty, top_k, top_p, enable_text_splitting, use_mps, self.local_model_path, use_deepspeed, self.voices_path))
         self.synthesize_process.start()
@@ -540,28 +550,29 @@ def download_file(url, destination):
         progress_bar.close()
 
     @staticmethod
-    def download_model(model_name = "2.0.2", local_models_path = None):
+    def download_model(model_name = "v2.0.2", local_models_path = None):
 
         # Creating a unique folder for each model version
         if local_models_path and len(local_models_path) > 0:
-            model_folder = os.path.join(local_models_path, f'v{model_name}')
+            model_folder = os.path.join(local_models_path, f'{model_name}')
             logging.info(f"Local models path: \"{model_folder}\"")
         else:
-            model_folder = os.path.join(os.getcwd(), 'models', f'v{model_name}')
+            model_folder = os.path.join(os.getcwd(), 'models', f'{model_name}')
             logging.info(f"Checking for models within application directory: \"{model_folder}\"")
 
         os.makedirs(model_folder, exist_ok=True)
+        print(model_name)
 
         files = {
-            "config.json": f"https://huggingface.co/coqui/XTTS-v2/raw/v{model_name}/config.json",
-            "model.pth": f"https://huggingface.co/coqui/XTTS-v2/resolve/v{model_name}/model.pth?download=true",
-            "vocab.json": f"https://huggingface.co/coqui/XTTS-v2/raw/v{model_name}/vocab.json"
+         "config.json": f"https://huggingface.co/coqui/XTTS-v2/raw/{model_name}/config.json",
+         "model.pth": f"https://huggingface.co/coqui/XTTS-v2/resolve/{model_name}/model.pth?download=true",
+         "vocab.json": f"https://huggingface.co/coqui/XTTS-v2/raw/{model_name}/vocab.json"
         }
 
         for file_name, url in files.items():
             file_path = os.path.join(model_folder, file_name)
             if not os.path.exists(file_path):
-                logger.info(f"Downloading {file_name} for Model v{model_name}...")
+                logger.info(f"Downloading {file_name} for Model {model_name}...")
                 CoquiEngine.download_file(url, file_path)
                 # r = requests.get(url, allow_redirects=True)
                 # with open(file_path, 'wb') as f:

xtts_api_server/__main__.py

@@ -11,9 +11,10 @@
 parser.add_argument("-t", "--tunnel", default="", type=str, help="URL of tunnel used (e.g: ngrok, localtunnel)")
 parser.add_argument("-ms", "--model-source", default="local", choices=["api","apiManual", "local"],
                     help="Define the model source: 'api' for latest version from repository, apiManual for 2.0.2 model and api inference or 'local' for using local inference and model v2.0.2.")
-parser.add_argument("-v", "--version", default="2.0.2", type=str, help="You can specify which version of xtts to use,This version will be used everywhere in local, api and apiManual.")
+parser.add_argument("-v", "--version", default="v2.0.2", type=str, help="You can specify which version of xtts to use,This version will be used everywhere in local, api and apiManual.")
 parser.add_argument("--lowvram", action='store_true', help="Enable low vram mode which switches the model to RAM when not actively processing.")
 parser.add_argument("--deepspeed", action='store_true', help="Enables deepspeed mode, speeds up processing by several times.")
+parser.add_argument("--use-cache", action='store_true', help="Enables caching of results, your results will be saved and if there will be a repeated request, you will get a file instead of generation.")
 parser.add_argument("--streaming-mode", action='store_true', help="Enables streaming mode, currently needs a lot of work.")
 parser.add_argument("--streaming-mode-improve", action='store_true', help="Includes an improved streaming mode that consumes 2gb more VRAM and uses a better tokenizer, good for languages such as Chinese")
 parser.add_argument("--stream-play-sync", action='store_true', help="Additional flag for streaming mod that allows you to play all audio one at a time without interruption")
@@ -27,6 +28,7 @@
 os.environ['TUNNEL_URL'] = args.tunnel  # it is necessary to correctly return correct previews in list of speakers
 os.environ['MODEL_SOURCE'] = args.model_source  # Set environment variable for the model source
 os.environ["MODEL_VERSION"] = args.version # Specify version of XTTS model
+os.environ["USE_CACHE"] = str(args.use_cache).lower() # Set lowvram mode
 os.environ["DEEPSPEED"] = str(args.deepspeed).lower() # Set lowvram mode
 os.environ["LOWVRAM_MODE"] = str(args.lowvram).lower() # Set lowvram mode
 os.environ["STREAM_MODE"] = str(args.streaming_mode).lower() # Enable Streaming mode

xtts_api_server/modeldownloader.py

@@ -120,13 +120,13 @@ def check_stream2sentence_version():
 def download_model(this_dir,model_version):
     # Define paths
     base_path = this_dir / 'models'
-    model_path = base_path / f'v{model_version}'
+    model_path = base_path / f'{model_version}'
 
     # Define files and their corresponding URLs
     files_to_download = {
-         "config.json": f"https://huggingface.co/coqui/XTTS-v2/raw/v{model_version}/config.json",
-         "model.pth": f"https://huggingface.co/coqui/XTTS-v2/resolve/v{model_version}/model.pth?download=true",
-         "vocab.json": f"https://huggingface.co/coqui/XTTS-v2/raw/v{model_version}/vocab.json"
+         "config.json": f"https://huggingface.co/coqui/XTTS-v2/raw/{model_version}/config.json",
+         "model.pth": f"https://huggingface.co/coqui/XTTS-v2/resolve/{model_version}/model.pth?download=true",
+         "vocab.json": f"https://huggingface.co/coqui/XTTS-v2/raw/{model_version}/vocab.json"
     }
 
     # Check and create directories

xtts_api_server/server.py

@@ -24,9 +24,11 @@
 SPEAKER_FOLDER = os.getenv('SPEAKER', 'speakers')
 BASE_URL = os.getenv('BASE_URL', '127.0.0.1:8020')
 MODEL_SOURCE = os.getenv("MODEL_SOURCE", "local")
-MODEL_VERSION = os.getenv("MODEL_VERSION","2.0.2")
+MODEL_VERSION = os.getenv("MODEL_VERSION","v2.0.2")
 LOWVRAM_MODE = os.getenv("LOWVRAM_MODE") == 'true'
 DEEPSPEED = os.getenv("DEEPSPEED") == 'true'
+USE_CACHE = os.getenv("USE_CACHE") == 'true'
+
 # STREAMING VARS
 STREAM_MODE = os.getenv("STREAM_MODE") == 'true'
 STREAM_MODE_IMPROVE = os.getenv("STREAM_MODE_IMPROVE") == 'true'
@@ -41,17 +43,14 @@
 
 # Create an instance of the TTSWrapper class and server
 app = FastAPI()
-XTTS = TTSWrapper(OUTPUT_FOLDER,SPEAKER_FOLDER,LOWVRAM_MODE,MODEL_SOURCE,MODEL_VERSION,DEVICE,DEEPSPEED)
+XTTS = TTSWrapper(OUTPUT_FOLDER,SPEAKER_FOLDER,LOWVRAM_MODE,MODEL_SOURCE,MODEL_VERSION,DEVICE,DEEPSPEED,USE_CACHE)
 
 # Create version string
 version_string = ""
-if MODEL_SOURCE == "api":
+if MODEL_SOURCE == "api" or MODEL_VERSION == "main":
     version_string = "lastest"
 else:
-    version_string = "v"+MODEL_VERSION
-
-if MODEL_SOURCE == "api" and MODEL_SOURCE != "2.0.2":
-    logger.warning("Attention you have specified flag -v but you have selected --model-source api, please change --model-souce to apiManual or local to use the specified version, otherwise the latest version of the model will be loaded.")
+    version_string = MODEL_VERSION
 
 # Load model
 # logger.info(f"The model {version_string} starts to load,wait until it loads")
@@ -74,6 +73,9 @@
 else:
   XTTS.load_model() 
 
+if USE_CACHE:
+    logger.info("You have enabled caching, this option enables caching of results, your results will be saved and if there is a repeat request, you will get a file instead of generation")
+
 # Add CORS middleware 
 origins = ["*"]
 app.add_middleware(