Revert "Adds support for creating weighted voice combinations"

api/src/inference/voice_manager.py

@@ -182,106 +182,6 @@ class VoiceManager:
         except Exception:
             return False
 
-    async def create_weighted_voice(
-    self,
-    formula: str, 
-    normalize: bool = False,
-    device: str = "cpu",
-    ) -> str:
-        """
-        Parse the voice formula string (e.g. '0.3 * voiceA + 0.5 * voiceB')
-        and return a combined torch.Tensor representing the weighted sum
-        of the given voices.
-
-        Args:
-            formula: Weighted voice formula string.
-            voice_manager: A class that has a `load_voice(voice_name, device)` -> Tensor
-            device: 'cpu' or 'cuda' for the final tensor.
-            normalize: If True, divide the final result by the sum of the weights
-                    so the total "magnitude" remains consistent.
-
-        Returns:
-            A torch.Tensor containing the combined voice embedding.
-        """
-        pairs = self.parse_voice_formula(formula)  # [(weight, voiceName), (weight, voiceName), ...]
-        
-        # Validate the pairs
-        for weight, voice_name in pairs:
-            if weight <= 0:
-                raise ValueError(f"Invalid weight {weight} for voice {voice_name}.")
-
-        if not pairs:
-            raise ValueError("No valid weighted voices found in formula.")
-
-        # Keep track of total weight if we plan to normalize.
-        total_weight = 0.0
-        weighted_sum = None
-        combined_name = ""
-
-        for weight, voice_name in pairs:
-            # 1) Load each base voice from your manager/service
-            base_voice = await self.load_voice(voice_name, device=device)
-            
-            
-            # 3) Combine the base voices using the weights
-            if combined_name == "":
-                combined_name = voice_name
-            else:
-                combined_name += f"+{voice_name}"
-
-               
-        
-            
-            # 2) Multiply by weight and accumulate
-            if weighted_sum is None:
-                # Clone so we don't modify the base voice in memory
-                weighted_sum = base_voice.clone() * weight
-            else:
-                weighted_sum += (base_voice * weight)
-            
-            total_weight += weight
-
-        if weighted_sum is None:
-            raise ValueError("No voices were combined. Check the formula syntax.")
-
-        # Optional normalization
-        if normalize and total_weight != 0.0:
-            weighted_sum /= total_weight
-        
-        if settings.allow_local_voice_saving:
-            
-            # Save to disk
-            api_dir = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
-            voices_dir = os.path.join(api_dir, settings.voices_dir)
-            os.makedirs(voices_dir, exist_ok=True)
-            combined_path = os.path.join(voices_dir, f"{formula}.pt")
-            try:
-                torch.save(weighted_sum, combined_path)
-            except Exception as e:
-                logger.warning(f"Failed to save combined voice: {e}")
-                # Continue without saving - will be combined on-the-fly when needed
-
-        return combined_name
-        
-      
-    
-
-    def parse_voice_formula(self,formula: str) -> List[tuple[float, str]]:
-        """
-        Parse the voice formula string (e.g. '0.3 * voiceA + 0.5 * voiceB')
-        and return a list of (weight, voiceName) pairs.
-        Args:
-            formula: Weighted voice formula string.
-        Returns:
-            List of (weight, voiceName) pairs.
-        """
-        pairs = []
-        parts = formula.split('+')
-        for part in parts:
-            weight, voice_name = part.strip().split('*')
-            pairs.append((float(weight), voice_name.strip()))
-        return pairs
-
     @property
     def cache_info(self) -> Dict[str, int]:
         """Get cache statistics.

api/src/routers/openai_compatible.py

@@ -2,7 +2,7 @@ import json
 import os
 from typing import AsyncGenerator, Dict, List, Union
 
-from fastapi import APIRouter, Header, HTTPException, Request, Response
+from fastapi import APIRouter, Depends, Header, HTTPException, Request, Response
 from fastapi.responses import StreamingResponse
 from loguru import logger
 
@@ -112,17 +112,7 @@ async def stream_audio_chunks(
     client_request: Request
 ) -> AsyncGenerator[bytes, None]:
     """Stream audio chunks as they're generated with client disconnect handling"""
-    # Check if 'request.voice' is a weighted formula (contains '*')
+    voice_to_use = await process_voices(request.voice, tts_service)
-    if '*' in request.voice:
-         # Weighted formula path
-        voice_to_use = await tts_service._voice_manager.create_weighted_voice(
-                formula=request.voice,
-                normalize=True
-            )
-      
-    else:
-        # Normal single or multi-voice path
-        voice_to_use = await process_voices(request.voice, tts_service)
     
     try:
         async for chunk in tts_service.generate_audio_stream(
@@ -169,7 +159,10 @@ async def create_speech(
         # Get global service instance
         tts_service = await get_tts_service()
         
-         # Set content type based on format
+        # Process voice combination and validate
+        voice_to_use = await process_voices(request.voice, tts_service)
+
+        # Set content type based on format
         content_type = {
             "mp3": "audio/mpeg",
             "opus": "audio/opus",
@@ -216,27 +209,13 @@ async def create_speech(
                 },
             )
         else:
-                # Check if 'request.voice' is a weighted formula (contains '*')
+            # Generate complete audio using public interface
-            if '*' in request.voice:
+            audio, _ = await tts_service.generate_audio(
-                # Weighted formula path
+                text=request.input,
-                print("Weighted formula path")
+                voice=voice_to_use,
-                voice_to_use = await tts_service._voice_manager.create_weighted_voice(
+                speed=request.speed,
-                    formula=request.voice,
+                stitch_long_output=True
-                    normalize=True
+            )
-                )
-                print(voice_to_use)
-            else:
-                # Normal single or multi-voice path
-                print("Normal single or multi-voice path")
-                # Otherwise, handle normal single or multi-voice logic
-                voice_to_use = await process_voices(request.voice, tts_service)
-                # Generate complete audio using public interface
-                audio, _ = await tts_service.generate_audio(
-                    text=request.input,
-                    voice=voice_to_use,
-                    speed=request.speed,
-                    stitch_long_output=True
-                )
 
             # Convert to requested format
             content = await AudioService.convert_audio(

docker/gpu/docker-compose.yml

@@ -1,6 +1,7 @@
-name: InstaVoice
+name: kokoro-tts
 services:
- server1:
+  kokoro-tts:
+    # image: ghcr.io/remsky/kokoro-fastapi-gpu:v0.1.0
     build:
       context: ../..
       dockerfile: docker/gpu/Dockerfile
@@ -18,59 +19,23 @@ services:
         reservations:
           devices:
             - driver: nvidia
-              count: all
+              count: 1
               capabilities: [gpu]
 
- server2:
+  # # Gradio UI service
-    build:
+  # gradio-ui:
-      context: ../..
+  #   image: ghcr.io/remsky/kokoro-fastapi-ui:v0.1.0
-      dockerfile: docker/gpu/Dockerfile
+  #   # Uncomment below to build from source instead of using the released image
-    volumes:
+  #   # build:
-      - ../../api:/app/api
+  #     # context: ../../ui
-    ports:
+  #   ports:
-      - "8880:8880"
+  #     - "7860:7860"
-    environment:
+  #   volumes:
-      - PYTHONPATH=/app:/app/api
+  #     - ../../ui/data:/app/ui/data
-      - USE_GPU=true
+  #     - ../../ui/app.py:/app/app.py  # Mount app.py for hot reload
-      - USE_ONNX=false
+  #   environment:
-      - PYTHONUNBUFFERED=1
+  #     - GRADIO_WATCH=1  # Enable hot reloading
-    deploy:
+  #     - PYTHONUNBUFFERED=1  # Ensure Python output is not buffered
-      resources:
+  #     - DISABLE_LOCAL_SAVING=false  # Set to 'true' to disable local saving and hide file view
-        reservations:
+  #     - API_HOST=kokoro-tts  # Set TTS service URL
-          devices:
+  #     - API_PORT=8880  # Set TTS service PORT
-            - driver: nvidia
-              count: all
-              capabilities: [gpu]
-
- server3:
-    build:
-      context: ../..
-      dockerfile: docker/gpu/Dockerfile
-    volumes:
-      - ../../api:/app/api
-    ports:
-      - "8880:8880"
-    environment:
-      - PYTHONPATH=/app:/app/api
-      - USE_GPU=true
-      - USE_ONNX=false
-      - PYTHONUNBUFFERED=1
-    deploy:
-      resources:
-        reservations:
-          devices:
-            - driver: nvidia
-              count: all
-              capabilities: [gpu]
-
- 
-nginx:
-    image: nginx:alpine
-    ports:
-      - "80:80" # Expose port 80 on the host machine
-    volumes:
-      - ./nginx.conf:/etc/nginx/nginx.conf # Load custom NGINX configuration
-    depends_on:
-      - server3
-      - server1
-      - server2

docker/gpu/nginx.conf

@@ -1,78 +0,0 @@
-user nginx;
-worker_processes auto; # Automatically adjust worker processes based on available CPUs
-
-events {
-    worker_connections 1024; # Maximum simultaneous connections per worker
-    use epoll;               # Use efficient event handling for Linux
-}
-
-http {
-    # Basic security headers
-    add_header X-Frame-Options SAMEORIGIN always;  # Prevent clickjacking
-    add_header X-Content-Type-Options nosniff always;  # Prevent MIME-type sniffing
-    add_header X-XSS-Protection "1; mode=block" always; # Enable XSS protection in browsers
-    add_header Strict-Transport-Security "max-age=31536000; includeSubDomains" always; # Enforce HTTPS
-    add_header Content-Security-Policy "default-src 'self';" always; # Restrict resource loading to same origin
-
-    # Timeouts
-    sendfile on;                      # Enable sendfile for efficient file serving
-    tcp_nopush on;                    # Reduce packet overhead
-    tcp_nodelay on;                   # Minimize latency
-    keepalive_timeout 65;             # Keep connections alive for 65 seconds
-    client_max_body_size 10m;         # Limit request body size to 10MB
-    client_body_timeout 12;           # Timeout for client body read
-    client_header_timeout 12;         # Timeout for client header read
-
-    # Compression
-    gzip on;                          # Enable gzip compression
-    gzip_disable "msie6";             # Disable gzip for old browsers
-    gzip_vary on;                     # Add "Vary: Accept-Encoding" header
-    gzip_proxied any;                 # Enable gzip for proxied requests
-    gzip_comp_level 6;                # Compression level
-    gzip_types text/plain text/css application/json application/javascript text/xml application/xml application/xml+rss text/javascript;
-
-    # Load balancing upstream
-    upstream backend {
-        least_conn; # Use least connections load balancing strategy
-        server server1:8880 max_fails=3 fail_timeout=5s; # Add health check for backend servers
-        # Uncomment additional servers for scaling:
-        server server2:8880 max_fails=3 fail_timeout=5s;
-        server server3:8880 max_fails=3 fail_timeout=5s;
-    }
-
-    server {
-        listen 80;
-
-        # Redirect HTTP to HTTPS (optional)
-        # Uncomment the lines below if SSL is configured:
-        # listen 443 ssl;
-        # ssl_certificate /path/to/certificate.crt;
-        # ssl_certificate_key /path/to/private.key;
-
-        location / {
-            proxy_pass http://backend;              # Proxy traffic to the backend servers
-            proxy_http_version 1.1;                # Use HTTP/1.1 for persistent connections
-            proxy_set_header Upgrade $http_upgrade;
-            proxy_set_header Connection "upgrade";
-            proxy_set_header Host $host;
-            proxy_set_header X-Forwarded-For $remote_addr; # Forward client IP
-            proxy_cache_bypass $http_upgrade;
-            proxy_read_timeout 60s;                # Adjust read timeout for backend
-            proxy_connect_timeout 60s;            # Adjust connection timeout for backend
-            proxy_send_timeout 60s;               # Adjust send timeout for backend
-        }
-
-        # Custom error pages
-        error_page 502 503 504 /50x.html;
-        location = /50x.html {
-            root /usr/share/nginx/html;
-        }
-
-        # Deny access to hidden files (e.g., .git)
-        location ~ /\. {
-            deny all;
-            access_log off;
-            log_not_found off;
-        }
-    }
-}

examples/openai_streaming_audio.py

@@ -31,7 +31,7 @@ def stream_to_speakers() -> None:
 
     with openai.audio.speech.with_streaming_response.create(
         model="kokoro",
-        voice="0.100 * af + 0.300 * am_adam + 0.400 * am_michael + 0.100 * bf_emma + 0.100 * bm_lewis ",
+        voice="af_bella",
         response_format="pcm",  # similar to WAV, but without a header chunk at the start.
         input="""I see skies of blue and clouds of white
                 The bright blessed days, the dark sacred nights

setup.sh

@@ -1,31 +0,0 @@
-#!/bin/bash
-
-# Ensure models directory exists
-mkdir -p api/src/models
-
-# Function to download a file
-download_file() {
-    local url="$1"
-    local filename=$(basename "$url")
-    echo "Downloading $filename..."
-    curl -L "$url" -o "api/src/models/$filename"
-}
-
-# Default PTH model if no arguments provided
-DEFAULT_MODELS=(
-    "https://github.com/remsky/Kokoro-FastAPI/releases/download/v0.1.0/kokoro-v0_19.pth"
-)
-
-# Use provided models or default
-if [ $# -gt 0 ]; then
-    MODELS=("$@")
-else
-    MODELS=("${DEFAULT_MODELS[@]}")
-fi
-
-# Download all models
-for model in "${MODELS[@]}"; do
-    download_file "$model"
-done
-
-echo "PyTorch model download complete!"