Upload 4 files
Browse files- constants.py +7 -7
- requirements-complete.txt +19 -0
- server.py +158 -36
constants.py
CHANGED
@@ -1,18 +1,18 @@
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# Constants
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# Also try: 'Salesforce/blip-image-captioning-base'
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DEFAULT_CAPTIONING_MODEL = "Salesforce/blip-image-captioning-large"
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DEFAULT_SD_MODEL = "sinkinai/MeinaHentai-v3-baked-vae"
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DEFAULT_EMBEDDING_MODEL = "sentence-transformers/all-mpnet-base-v2"
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DEFAULT_REMOTE_SD_HOST = "127.0.0.1"
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DEFAULT_REMOTE_SD_PORT = 7860
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DEFAULT_CHROMA_PORT = 8000
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SILERO_SAMPLES_PATH = "tts_samples"
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-
SILERO_SAMPLE_TEXT = "
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# ALL_MODULES = ['caption', 'summarize', 'classify', 'keywords', 'prompt', 'sd']
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DEFAULT_SUMMARIZE_PARAMS = {
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"temperature": 1.0,
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# Constants
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DEFAULT_CUDA_DEVICE = "cuda:0"
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# Also try: 'Qiliang/bart-large-cnn-samsum-ElectrifAi_v10'
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DEFAULT_SUMMARIZATION_MODEL = "Qiliang/bart-large-cnn-samsum-ChatGPT_v3"
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# Also try: 'joeddav/distilbert-base-uncased-go-emotions-student'
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DEFAULT_CLASSIFICATION_MODEL = "nateraw/bert-base-uncased-emotion"
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# Also try: 'Salesforce/blip-image-captioning-base'
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DEFAULT_CAPTIONING_MODEL = "Salesforce/blip-image-captioning-large"
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DEFAULT_SD_MODEL = "ckpt/anything-v4.5-vae-swapped"
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DEFAULT_EMBEDDING_MODEL = "sentence-transformers/all-mpnet-base-v2"
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DEFAULT_REMOTE_SD_HOST = "127.0.0.1"
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DEFAULT_REMOTE_SD_PORT = 7860
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DEFAULT_CHROMA_PORT = 8000
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SILERO_SAMPLES_PATH = "tts_samples"
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SILERO_SAMPLE_TEXT = "The quick brown fox jumps over the lazy dog"
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# ALL_MODULES = ['caption', 'summarize', 'classify', 'keywords', 'prompt', 'sd']
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DEFAULT_SUMMARIZE_PARAMS = {
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"temperature": 1.0,
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requirements-complete.txt
ADDED
@@ -0,0 +1,19 @@
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flask
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flask-cloudflared
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flask-cors
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flask-compress
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markdown
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Pillow
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colorama
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webuiapi
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--extra-index-url https://download.pytorch.org/whl/cu117
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torch==2.0.0+cu117
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torchvision==0.15.1
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torchaudio==2.0.1+cu117
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accelerate
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transformers==4.28.1
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diffusers==0.16.1
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silero-api-server
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chromadb
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sentence_transformers
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edge-tts
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server.py
CHANGED
@@ -21,6 +21,7 @@ import torch
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import time
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import os
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import gc
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import secrets
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from PIL import Image
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import base64
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colorama_init()
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class SplitArgs(argparse.Action):
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def __call__(self, parser, namespace, values, option_string=None):
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namespace, self.dest, values.replace('"', "").replace("'", "").split(",")
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)
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# Script arguments
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parser = argparse.ArgumentParser(
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parser.add_argument("--cpu", action="store_true", help="Run the models on the CPU")
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parser.add_argument("--cuda", action="store_false", dest="cpu", help="Run the models on the GPU")
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parser.set_defaults(cpu=True)
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parser.add_argument("--summarization-model", help="Load a custom summarization model")
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parser.add_argument(
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parser.add_argument("--chroma-host", help="Host IP for a remote ChromaDB instance")
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parser.add_argument("--chroma-port", help="HTTP port for a remote ChromaDB instance (defaults to 8000)")
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parser.add_argument("--chroma-folder", help="Path for chromadb persistence folder", default='.chroma_db')
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parser.add_argument('--chroma-persist', help="
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parser.add_argument(
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"--secure", action="store_true", help="Enforces the use of an API key"
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)
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sd_group = parser.add_mutually_exclusive_group()
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local_sd = sd_group.add_argument_group("sd-local")
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args = parser.parse_args()
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port =
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host = "0.0.0.0"
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summarization_model = (
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args.summarization_model
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if args.summarization_model
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@@ -142,12 +157,16 @@ if len(modules) == 0:
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print(f"Example: --enable-modules=caption,summarize{Style.RESET_ALL}")
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# Models init
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device = torch.device(device_string)
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torch_dtype = torch.float32 if device_string
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if not torch.cuda.is_available() and not args.cpu:
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print(f"{Fore.YELLOW}{Style.BRIGHT}torch-cuda is not supported on this device.
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print(f"{Fore.GREEN}{Style.BRIGHT}Using torch device: {device_string}{Style.RESET_ALL}")
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@@ -184,12 +203,10 @@ if "sd" in modules and not sd_use_remote:
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from diffusers import StableDiffusionPipeline
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from diffusers import EulerAncestralDiscreteScheduler
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print("Initializing Stable Diffusion pipeline")
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sd_device_string = (
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"cuda" if torch.cuda.is_available() and not args.sd_cpu else "cpu"
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)
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sd_device = torch.device(sd_device_string)
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sd_torch_dtype = torch.float32 if sd_device_string
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sd_pipe = StableDiffusionPipeline.from_pretrained(
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sd_model, custom_pipeline="lpw_stable_diffusion", torch_dtype=sd_torch_dtype
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).to(sd_device)
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@@ -252,26 +269,19 @@ if "chromadb" in modules:
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posthog.capture = lambda *args, **kwargs: None
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if args.chroma_host is None:
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if args.chroma_persist:
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chromadb_client = chromadb.
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print(f"ChromaDB is running in-memory with persistence. Persistence is stored in {args.chroma_folder}. Can be cleared by deleting the folder or purging db.")
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else:
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chromadb_client = chromadb.
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print(f"ChromaDB is running in-memory without persistence.")
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else:
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chroma_port=(
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args.chroma_port if args.chroma_port else DEFAULT_CHROMA_PORT
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)
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chromadb_client = chromadb.
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Settings(
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anonymized_telemetry=False,
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chroma_api_impl="rest",
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chroma_server_host=args.chroma_host,
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chroma_server_http_port=chroma_port
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)
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)
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print(f"ChromaDB is remotely configured at {args.chroma_host}:{chroma_port}")
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chromadb_embedder = SentenceTransformer(embedding_model)
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chromadb_embed_fn = lambda *args, **kwargs: chromadb_embedder.encode(*args, **kwargs).tolist()
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# Check if the db is connected and running, otherwise tell the user
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@@ -405,10 +415,24 @@ def image_to_base64(image: Image, quality: int = 75) -> str:
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image.save(buffer, format="JPEG", quality=quality)
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img_str = base64.b64encode(buffer.getvalue()).decode("utf-8")
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return img_str
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ignore_auth = []
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-
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def is_authorize_ignored(request):
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view_func = app.view_functions.get(request.endpoint)
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return True
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return False
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@app.before_request
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def before_request():
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# Request time measuring
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# Checks if an API key is present and valid, otherwise return unauthorized
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# The options check is required so CORS doesn't get angry
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try:
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if request.method != 'OPTIONS' and is_authorize_ignored(request) == False and getattr(request.authorization, 'token', '') != api_key:
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print(f"WARNING: Unauthorized API key access from {request.remote_addr}")
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response = jsonify({ 'error': '401: Invalid API key' })
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response.status_code = 401
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return
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except Exception as e:
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print(f"API key check error: {e}")
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return "
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@app.after_request
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]
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return jsonify(voices)
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@app.route("/api/tts/generate", methods=["POST"])
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@require_module("silero-tts")
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def tts_generate():
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# Remove asterisks
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voice["text"] = voice["text"].replace("*", "")
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try:
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audio = tts_service.generate(voice["speaker"], voice["text"])
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except Exception as e:
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print(e)
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abort(500, voice["speaker"])
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count = collection.count()
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collection.delete()
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#Write deletion to persistent folder
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chromadb_client.persist()
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print("ChromaDB embeddings deleted", count)
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return 'Ok', 200
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@@ -768,6 +798,11 @@ def chromadb_query():
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name=f"chat-{chat_id_md5}", embedding_function=chromadb_embed_fn
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)
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n_results = min(collection.count(), n_results)
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query_result = collection.query(
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query_texts=[data["query"]],
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return jsonify(messages)
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@app.route("/api/chromadb/export", methods=["POST"])
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@require_module("chromadb")
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@@ -802,9 +900,14 @@ def chromadb_export():
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abort(400, '"chat_id" is required')
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chat_id_md5 = hashlib.md5(data["chat_id"].encode()).hexdigest()
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-
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collection_content = collection.get()
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documents = collection_content.get('documents', [])
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ids = collection_content.get('ids', [])
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@@ -847,8 +950,27 @@ def chromadb_import():
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collection.upsert(documents=documents, metadatas=metadatas, ids=ids)
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return jsonify({"count": len(ids)})
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ignore_auth.append(tts_play_sample)
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app.run(host=host, port=port)
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import time
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import os
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import gc
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import sys
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import secrets
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from PIL import Image
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import base64
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colorama_init()
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if sys.hexversion < 0x030b0000:
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print(f"{Fore.BLUE}{Style.BRIGHT}Python 3.11 or newer is recommended to run this program.{Style.RESET_ALL}")
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time.sleep(2)
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class SplitArgs(argparse.Action):
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def __call__(self, parser, namespace, values, option_string=None):
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namespace, self.dest, values.replace('"', "").replace("'", "").split(",")
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)
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#Setting Root Folders for Silero Generations so it is compatible with STSL, should not effect regular runs. - Rolyat
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parent_dir = os.path.dirname(os.path.abspath(__file__))
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SILERO_SAMPLES_PATH = os.path.join(parent_dir, "tts_samples")
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SILERO_SAMPLE_TEXT = os.path.join(parent_dir)
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# Create directories if they don't exist
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if not os.path.exists(SILERO_SAMPLES_PATH):
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os.makedirs(SILERO_SAMPLES_PATH)
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if not os.path.exists(SILERO_SAMPLE_TEXT):
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os.makedirs(SILERO_SAMPLE_TEXT)
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# Script arguments
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parser = argparse.ArgumentParser(
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)
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parser.add_argument("--cpu", action="store_true", help="Run the models on the CPU")
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parser.add_argument("--cuda", action="store_false", dest="cpu", help="Run the models on the GPU")
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parser.add_argument("--cuda-device", help="Specify the CUDA device to use")
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parser.add_argument("--mps", "--apple", "--m1", "--m2", action="store_false", dest="cpu", help="Run the models on Apple Silicon")
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parser.set_defaults(cpu=True)
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parser.add_argument("--summarization-model", help="Load a custom summarization model")
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parser.add_argument(
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parser.add_argument("--chroma-host", help="Host IP for a remote ChromaDB instance")
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parser.add_argument("--chroma-port", help="HTTP port for a remote ChromaDB instance (defaults to 8000)")
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parser.add_argument("--chroma-folder", help="Path for chromadb persistence folder", default='.chroma_db')
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parser.add_argument('--chroma-persist', help="ChromaDB persistence", default=True, action=argparse.BooleanOptionalAction)
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parser.add_argument(
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"--secure", action="store_true", help="Enforces the use of an API key"
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)
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sd_group = parser.add_mutually_exclusive_group()
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local_sd = sd_group.add_argument_group("sd-local")
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args = parser.parse_args()
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port = args.port if args.port else 5100
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host = "0.0.0.0" if args.listen else "localhost"
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summarization_model = (
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args.summarization_model
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if args.summarization_model
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print(f"Example: --enable-modules=caption,summarize{Style.RESET_ALL}")
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# Models init
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cuda_device = DEFAULT_CUDA_DEVICE if not args.cuda_device else args.cuda_device
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device_string = cuda_device if torch.cuda.is_available() and not args.cpu else 'mps' if torch.backends.mps.is_available() and not args.cpu else 'cpu'
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device = torch.device(device_string)
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+
torch_dtype = torch.float32 if device_string != cuda_device else torch.float16
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if not torch.cuda.is_available() and not args.cpu:
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print(f"{Fore.YELLOW}{Style.BRIGHT}torch-cuda is not supported on this device.{Style.RESET_ALL}")
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if not torch.backends.mps.is_available() and not args.cpu:
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print(f"{Fore.YELLOW}{Style.BRIGHT}torch-mps is not supported on this device.{Style.RESET_ALL}")
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+
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print(f"{Fore.GREEN}{Style.BRIGHT}Using torch device: {device_string}{Style.RESET_ALL}")
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from diffusers import StableDiffusionPipeline
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from diffusers import EulerAncestralDiscreteScheduler
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print("Initializing Stable Diffusion pipeline...")
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sd_device_string = cuda_device if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu'
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sd_device = torch.device(sd_device_string)
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sd_torch_dtype = torch.float32 if sd_device_string != cuda_device else torch.float16
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sd_pipe = StableDiffusionPipeline.from_pretrained(
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sd_model, custom_pipeline="lpw_stable_diffusion", torch_dtype=sd_torch_dtype
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).to(sd_device)
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posthog.capture = lambda *args, **kwargs: None
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if args.chroma_host is None:
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if args.chroma_persist:
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chromadb_client = chromadb.PersistentClient(path=args.chroma_folder, settings=Settings(anonymized_telemetry=False))
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print(f"ChromaDB is running in-memory with persistence. Persistence is stored in {args.chroma_folder}. Can be cleared by deleting the folder or purging db.")
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else:
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275 |
+
chromadb_client = chromadb.EphemeralClient(Settings(anonymized_telemetry=False))
|
276 |
print(f"ChromaDB is running in-memory without persistence.")
|
277 |
else:
|
278 |
chroma_port=(
|
279 |
args.chroma_port if args.chroma_port else DEFAULT_CHROMA_PORT
|
280 |
)
|
281 |
+
chromadb_client = chromadb.HttpClient(host=args.chroma_host, port=chroma_port, settings=Settings(anonymized_telemetry=False))
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
282 |
print(f"ChromaDB is remotely configured at {args.chroma_host}:{chroma_port}")
|
283 |
|
284 |
+
chromadb_embedder = SentenceTransformer(embedding_model, device=device_string)
|
285 |
chromadb_embed_fn = lambda *args, **kwargs: chromadb_embedder.encode(*args, **kwargs).tolist()
|
286 |
|
287 |
# Check if the db is connected and running, otherwise tell the user
|
|
|
415 |
image.save(buffer, format="JPEG", quality=quality)
|
416 |
img_str = base64.b64encode(buffer.getvalue()).decode("utf-8")
|
417 |
return img_str
|
|
|
|
|
418 |
|
419 |
+
ignore_auth = []
|
420 |
+
# Reads an API key from an already existing file. If that file doesn't exist, create it.
|
421 |
+
if args.secure:
|
422 |
+
try:
|
423 |
+
with open("api_key.txt", "r") as txt:
|
424 |
+
api_key = txt.read().replace('\n', '')
|
425 |
+
except:
|
426 |
+
api_key = secrets.token_hex(5)
|
427 |
+
with open("api_key.txt", "w") as txt:
|
428 |
+
txt.write(api_key)
|
429 |
+
|
430 |
+
print(f"Your API key is {api_key}")
|
431 |
+
elif args.share and args.secure != True:
|
432 |
+
print("WARNING: This instance is publicly exposed without an API key! It is highly recommended to restart with the \"--secure\" argument!")
|
433 |
+
else:
|
434 |
+
print("No API key given because you are running locally.")
|
435 |
+
|
436 |
|
437 |
def is_authorize_ignored(request):
|
438 |
view_func = app.view_functions.get(request.endpoint)
|
|
|
442 |
return True
|
443 |
return False
|
444 |
|
445 |
+
|
446 |
@app.before_request
|
447 |
def before_request():
|
448 |
# Request time measuring
|
|
|
451 |
# Checks if an API key is present and valid, otherwise return unauthorized
|
452 |
# The options check is required so CORS doesn't get angry
|
453 |
try:
|
454 |
+
if request.method != 'OPTIONS' and args.secure and is_authorize_ignored(request) == False and getattr(request.authorization, 'token', '') != api_key:
|
455 |
print(f"WARNING: Unauthorized API key access from {request.remote_addr}")
|
456 |
response = jsonify({ 'error': '401: Invalid API key' })
|
457 |
response.status_code = 401
|
458 |
+
return response
|
459 |
except Exception as e:
|
460 |
print(f"API key check error: {e}")
|
461 |
+
return "401 Unauthorized\n{}\n\n".format(e), 401
|
462 |
|
463 |
|
464 |
@app.after_request
|
|
|
670 |
]
|
671 |
return jsonify(voices)
|
672 |
|
673 |
+
# Added fix for Silero not working as new files were unable to be created if one already existed. - Rolyat 7/7/23
|
674 |
@app.route("/api/tts/generate", methods=["POST"])
|
675 |
@require_module("silero-tts")
|
676 |
def tts_generate():
|
|
|
682 |
# Remove asterisks
|
683 |
voice["text"] = voice["text"].replace("*", "")
|
684 |
try:
|
685 |
+
# Remove the destination file if it already exists
|
686 |
+
if os.path.exists('test.wav'):
|
687 |
+
os.remove('test.wav')
|
688 |
+
|
689 |
audio = tts_service.generate(voice["speaker"], voice["text"])
|
690 |
+
audio_file_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), os.path.basename(audio))
|
691 |
+
|
692 |
+
os.rename(audio, audio_file_path)
|
693 |
+
return send_file(audio_file_path, mimetype="audio/x-wav")
|
694 |
except Exception as e:
|
695 |
print(e)
|
696 |
abort(500, voice["speaker"])
|
|
|
775 |
|
776 |
count = collection.count()
|
777 |
collection.delete()
|
|
|
|
|
778 |
print("ChromaDB embeddings deleted", count)
|
779 |
return 'Ok', 200
|
780 |
|
|
|
798 |
name=f"chat-{chat_id_md5}", embedding_function=chromadb_embed_fn
|
799 |
)
|
800 |
|
801 |
+
if collection.count() == 0:
|
802 |
+
print(f"Queried empty/missing collection for {repr(data['chat_id'])}.")
|
803 |
+
return jsonify([])
|
804 |
+
|
805 |
+
|
806 |
n_results = min(collection.count(), n_results)
|
807 |
query_result = collection.query(
|
808 |
query_texts=[data["query"]],
|
|
|
828 |
|
829 |
return jsonify(messages)
|
830 |
|
831 |
+
@app.route("/api/chromadb/multiquery", methods=["POST"])
|
832 |
+
@require_module("chromadb")
|
833 |
+
def chromadb_multiquery():
|
834 |
+
data = request.get_json()
|
835 |
+
if "chat_list" not in data or not isinstance(data["chat_list"], list):
|
836 |
+
abort(400, '"chat_list" is required and should be a list')
|
837 |
+
if "query" not in data or not isinstance(data["query"], str):
|
838 |
+
abort(400, '"query" is required')
|
839 |
+
|
840 |
+
if "n_results" not in data or not isinstance(data["n_results"], int):
|
841 |
+
n_results = 1
|
842 |
+
else:
|
843 |
+
n_results = data["n_results"]
|
844 |
+
|
845 |
+
messages = []
|
846 |
+
|
847 |
+
for chat_id in data["chat_list"]:
|
848 |
+
if not isinstance(chat_id, str):
|
849 |
+
continue
|
850 |
+
|
851 |
+
try:
|
852 |
+
chat_id_md5 = hashlib.md5(chat_id.encode()).hexdigest()
|
853 |
+
collection = chromadb_client.get_collection(
|
854 |
+
name=f"chat-{chat_id_md5}", embedding_function=chromadb_embed_fn
|
855 |
+
)
|
856 |
+
|
857 |
+
# Skip this chat if the collection is empty
|
858 |
+
if collection.count() == 0:
|
859 |
+
continue
|
860 |
+
|
861 |
+
n_results_per_chat = min(collection.count(), n_results)
|
862 |
+
query_result = collection.query(
|
863 |
+
query_texts=[data["query"]],
|
864 |
+
n_results=n_results_per_chat,
|
865 |
+
)
|
866 |
+
documents = query_result["documents"][0]
|
867 |
+
ids = query_result["ids"][0]
|
868 |
+
metadatas = query_result["metadatas"][0]
|
869 |
+
distances = query_result["distances"][0]
|
870 |
+
|
871 |
+
chat_messages = [
|
872 |
+
{
|
873 |
+
"id": ids[i],
|
874 |
+
"date": metadatas[i]["date"],
|
875 |
+
"role": metadatas[i]["role"],
|
876 |
+
"meta": metadatas[i]["meta"],
|
877 |
+
"content": documents[i],
|
878 |
+
"distance": distances[i],
|
879 |
+
}
|
880 |
+
for i in range(len(ids))
|
881 |
+
]
|
882 |
+
|
883 |
+
messages.extend(chat_messages)
|
884 |
+
except Exception as e:
|
885 |
+
print(e)
|
886 |
+
|
887 |
+
#remove duplicate msgs, filter down to the right number
|
888 |
+
seen = set()
|
889 |
+
messages = [d for d in messages if not (d['content'] in seen or seen.add(d['content']))]
|
890 |
+
messages = sorted(messages, key=lambda x: x['distance'])[0:n_results]
|
891 |
+
|
892 |
+
return jsonify(messages)
|
893 |
+
|
894 |
|
895 |
@app.route("/api/chromadb/export", methods=["POST"])
|
896 |
@require_module("chromadb")
|
|
|
900 |
abort(400, '"chat_id" is required')
|
901 |
|
902 |
chat_id_md5 = hashlib.md5(data["chat_id"].encode()).hexdigest()
|
903 |
+
try:
|
904 |
+
collection = chromadb_client.get_collection(
|
905 |
+
name=f"chat-{chat_id_md5}", embedding_function=chromadb_embed_fn
|
906 |
+
)
|
907 |
+
except Exception as e:
|
908 |
+
print(e)
|
909 |
+
abort(400, "Chat collection not found in chromadb")
|
910 |
+
|
911 |
collection_content = collection.get()
|
912 |
documents = collection_content.get('documents', [])
|
913 |
ids = collection_content.get('ids', [])
|
|
|
950 |
|
951 |
|
952 |
collection.upsert(documents=documents, metadatas=metadatas, ids=ids)
|
953 |
+
print(f"Imported {len(ids)} (total {collection.count()}) content entries into {repr(data['chat_id'])}")
|
954 |
|
955 |
return jsonify({"count": len(ids)})
|
956 |
|
957 |
+
|
958 |
+
if args.share:
|
959 |
+
from flask_cloudflared import _run_cloudflared
|
960 |
+
import inspect
|
961 |
+
|
962 |
+
sig = inspect.signature(_run_cloudflared)
|
963 |
+
sum = sum(
|
964 |
+
1
|
965 |
+
for param in sig.parameters.values()
|
966 |
+
if param.kind == param.POSITIONAL_OR_KEYWORD
|
967 |
+
)
|
968 |
+
if sum > 1:
|
969 |
+
metrics_port = randint(8100, 9000)
|
970 |
+
cloudflare = _run_cloudflared(port, metrics_port)
|
971 |
+
else:
|
972 |
+
cloudflare = _run_cloudflared(port)
|
973 |
+
print("Running on", cloudflare)
|
974 |
+
|
975 |
ignore_auth.append(tts_play_sample)
|
976 |
app.run(host=host, port=port)
|