Text Generation
GGUF
ONNX
English
conversational
text-to-speech
voice-cloning
offline
digital-twin
xtts
piper-tts
whisper
Instructions to use jlind456/jason-ai-twin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jlind456/jason-ai-twin with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf jlind456/jason-ai-twin # Run inference directly in the terminal: llama cli -hf jlind456/jason-ai-twin
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jlind456/jason-ai-twin # Run inference directly in the terminal: llama cli -hf jlind456/jason-ai-twin
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf jlind456/jason-ai-twin # Run inference directly in the terminal: ./llama-cli -hf jlind456/jason-ai-twin
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf jlind456/jason-ai-twin # Run inference directly in the terminal: ./build/bin/llama-cli -hf jlind456/jason-ai-twin
Use Docker
docker model run hf.co/jlind456/jason-ai-twin
- LM Studio
- Jan
- vLLM
How to use jlind456/jason-ai-twin with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jlind456/jason-ai-twin" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jlind456/jason-ai-twin", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jlind456/jason-ai-twin
- Ollama
How to use jlind456/jason-ai-twin with Ollama:
ollama run hf.co/jlind456/jason-ai-twin
- Unsloth Desktop
- Pi
How to use jlind456/jason-ai-twin with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jlind456/jason-ai-twin
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "jlind456/jason-ai-twin" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use jlind456/jason-ai-twin with Docker Model Runner:
docker model run hf.co/jlind456/jason-ai-twin
- Lemonade
How to use jlind456/jason-ai-twin with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jlind456/jason-ai-twin
Run and chat with the model
lemonade run user.jason-ai-twin-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use jlind456/jason-ai-twin with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jlind456/jason-ai-twin
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default jlind456/jason-ai-twin
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use jlind456/jason-ai-twin with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jlind456/jason-ai-twin
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "jlind456/jason-ai-twin" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Update AI Twin chat client to use cloned voice from /local-tts
Browse files- chat_twin.py +110 -54
chat_twin.py
CHANGED
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-
#!/
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import sys
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import os
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@@ -20,6 +20,7 @@ import subprocess
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import threading
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import queue
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import time
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import tempfile
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# --- ANSI Terminal Colors ---
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@@ -38,7 +39,7 @@ RECORD_FILE = "/tmp/chat_twin_record.wav"
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# Speech/TTS/STT Configuration
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tts_config = {
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"voice": "
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"rate": "0", # -100 to 100
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"pitch": "0", # -100 to 100
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"volume": "0", # -100 to 100
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@@ -46,6 +47,36 @@ tts_config = {
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"fallback_espeak": False
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}
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# --- Lazy-Loaded Speech-to-Text (STT) ---
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asr_pipeline = None
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@@ -90,9 +121,6 @@ def clean_markdown(text):
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text = re.sub(r'\s+', ' ', text)
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return text.strip()
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CLONED_SPEAKER_WAV = "/home/jason/local-tts/cloned_output.wav"
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TTS_CMD = "/home/jason/anaconda3/envs/tts-backend/bin/tts"
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def speak_text(text):
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"""Executes the TTS system commands to say the text using cloned voice."""
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if not tts_config["enabled"]:
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if not clean_text:
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return
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# Attempt
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if not tts_config["fallback_espeak"]:
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cmd = ["spd-say", "-w"] # -w waits until speaking is finished
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if tts_config["voice"]
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if tts_config["rate"]:
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cmd.extend(["-r", tts_config["rate"]])
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if tts_config["pitch"]:
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@@ -144,19 +185,22 @@ def speak_text(text):
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cmd.append(clean_text)
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try:
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subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
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except Exception:
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# Fallback to espeak-ng if spd-say fails
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tts_config["fallback_espeak"] = True
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speak_text(text)
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else:
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# Fallback to espeak-ng
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cmd = ["espeak-ng"]
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try:
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rate_val = int(tts_config["rate"])
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wpm = 175 + int(rate_val * 0.8)
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cmd.extend(["-s", str(wpm)])
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except:
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pass
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cmd.append(clean_text)
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try:
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print(f"\n{C_YELLOW}[TTS Error: {e}]{C_RESET}")
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def stop_speech():
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"""Cancels any ongoing speech and flushes the queue."""
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# Clear the queue
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while not tts_queue.empty():
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try:
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except queue.Empty:
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break
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# Send cancel to speech dispatcher
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try:
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subprocess.run(["spd-say", "-C"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
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except:
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pass
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# Terminate any running espeak-ng processes
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try:
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subprocess.run(["pkill", "-x", "espeak-ng"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
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except:
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pass
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def tts_worker():
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def print_help():
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print(f"\n{C_MAGENTA}{C_BOLD}--- Digital Twin Help Menu ---{C_RESET}")
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print(f" {C_BOLD}/stop{C_RESET} or {C_BOLD}/s{C_RESET} : Stop current speaking immediately.")
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print(f" {C_BOLD}/voice <type>{C_RESET} : Set voice (male1, male2, male3, female1, female2, female3, child_male, child_female).")
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print(f" {C_BOLD}/rate <value>{C_RESET} : Set speech rate (-100 to 100, e.g. -20, 0, 20).")
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print(f" {C_BOLD}/clear{C_RESET} or {C_BOLD}/c{C_RESET} : Clear screen and reset conversation history.")
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print(f" {C_BOLD}/tts <on|off>{C_RESET} : Enable or disable Text-to-Speech.")
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return
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print(f"Twin model '{C_BOLD}{MODEL_NAME}{C_RESET}' loaded.")
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print(f"Two-Way Voice active. Type text OR press {C_BOLD}[ENTER]{C_RESET} to speak. (Type {C_BOLD}/help{C_RESET} for commands)\n")
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start_tts_system()
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# If input is empty, enter Voice Input Mode
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if not user_input:
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subprocess.run(["aplay", "-q", "/home/jason/coral/mic_active.wav"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
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print(f"{C_YELLOW}[🎙️ Mic Active - Recording... Press ENTER to stop recording]{C_RESET}", end="", flush=True)
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# Start recording
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record_proc = record_audio()
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elif cmd == "/voice":
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if len(cmd_parts) > 1:
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new_voice = cmd_parts[1].lower()
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valid_voices = ["male1", "male2", "male3", "female1", "female2", "female3", "child_male", "child_female"]
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if new_voice in valid_voices:
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tts_config["voice"] = new_voice
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else:
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print(f"{C_YELLOW}Invalid voice. Select from: {', '.join(valid_voices)}{C_RESET}")
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else:
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-
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continue
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elif cmd == "/rate":
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if len(cmd_parts) > 1:
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#!/usr/bin/env python3
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import sys
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import os
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import threading
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import queue
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import time
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import shutil
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import tempfile
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# --- ANSI Terminal Colors ---
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# Speech/TTS/STT Configuration
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tts_config = {
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"voice": "cloned", # Options: cloned, male1, male2, male3, female1, female2, female3, child_male, child_female
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"rate": "0", # -100 to 100
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"pitch": "0", # -100 to 100
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"volume": "0", # -100 to 100
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"fallback_espeak": False
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}
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# Voice Cloning & Cloned Speaker Paths (/local-tts)
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CLONED_VOICE_CANDIDATES = [
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"/home/jason/local-tts/cloned_output.wav",
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"/home/jason/local-tts/my_voice_clean.wav",
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os.path.join(os.path.dirname(os.path.abspath(__file__)), "cloned_output.wav"),
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os.path.join(os.path.dirname(os.path.abspath(__file__)), "my_voice_clean.wav"),
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]
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def get_cloned_voice_path():
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"""Locate the cloned speaker reference audio file."""
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for p in CLONED_VOICE_CANDIDATES:
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if os.path.exists(p) and os.path.getsize(p) > 1000:
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return p
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return None
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TTS_CMD_CANDIDATES = [
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"/home/jason/miniconda3/envs/env_twin/bin/tts",
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"/home/jason/.local/bin/tts",
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"/home/jason/local-tts/tts-env/bin/tts",
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"/home/jason/local-tts/bin/tts",
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]
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def get_tts_cmd():
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"""Locate the TTS binary for voice cloning synthesis."""
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for c in TTS_CMD_CANDIDATES:
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if c and os.path.exists(c):
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return c
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return shutil.which("tts")
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# --- Lazy-Loaded Speech-to-Text (STT) ---
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asr_pipeline = None
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text = re.sub(r'\s+', ' ', text)
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return text.strip()
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def speak_text(text):
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"""Executes the TTS system commands to say the text using cloned voice."""
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if not tts_config["enabled"]:
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if not clean_text:
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return
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# 1. Attempt Voice-Cloned TTS using XTTS v2 and cloned audio from /local-tts
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if tts_config["voice"] == "cloned" and not tts_config.get("fallback_espeak", False):
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cloned_wav = get_cloned_voice_path()
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tts_cmd = get_tts_cmd()
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if tts_cmd and cloned_wav:
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tmp_wav = None
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try:
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_file:
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tmp_wav = tmp_file.name
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cmd = [
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tts_cmd,
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"--model_name", "tts_models/multilingual/multi-dataset/xtts_v2",
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"--text", clean_text,
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"--speaker_wav", cloned_wav,
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"--language_idx", "en",
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"--out_path", tmp_wav,
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"--use_cuda", "true"
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]
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env = os.environ.copy()
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env["COQUI_TOS_AGREED"] = "1"
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res = subprocess.run(cmd, env=env, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=45)
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if res.returncode == 0 and os.path.exists(tmp_wav) and os.path.getsize(tmp_wav) > 1000:
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play_res = subprocess.run(["paplay", tmp_wav], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
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if play_res.returncode != 0:
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subprocess.run(["aplay", "-q", tmp_wav], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
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try:
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os.remove(tmp_wav)
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except Exception:
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pass
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return
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except Exception:
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pass
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finally:
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if tmp_wav and os.path.exists(tmp_wav):
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try:
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os.remove(tmp_wav)
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except Exception:
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pass
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# 2. Prepare command for spd-say (standard voice fallback)
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if not tts_config["fallback_espeak"]:
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cmd = ["spd-say", "-w"] # -w waits until speaking is finished
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voice_target = tts_config["voice"] if tts_config["voice"] != "cloned" else "male1"
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if voice_target:
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cmd.extend(["-t", voice_target])
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if tts_config["rate"]:
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cmd.extend(["-r", tts_config["rate"]])
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if tts_config["pitch"]:
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cmd.append(clean_text)
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try:
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res = subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
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if res.returncode == 0:
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return
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except Exception:
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# Fallback to espeak-ng if spd-say fails
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tts_config["fallback_espeak"] = True
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speak_text(text)
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return
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else:
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# 3. Fallback to espeak-ng
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cmd = ["espeak-ng"]
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try:
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rate_val = int(tts_config["rate"])
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wpm = 175 + int(rate_val * 0.8)
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| 202 |
cmd.extend(["-s", str(wpm)])
|
| 203 |
+
except Exception:
|
| 204 |
pass
|
| 205 |
cmd.append(clean_text)
|
| 206 |
try:
|
|
|
|
| 209 |
print(f"\n{C_YELLOW}[TTS Error: {e}]{C_RESET}")
|
| 210 |
|
| 211 |
def stop_speech():
|
| 212 |
+
"""Cancels any ongoing speech, terminates playback processes, and flushes the queue."""
|
| 213 |
# Clear the queue
|
| 214 |
while not tts_queue.empty():
|
| 215 |
try:
|
|
|
|
| 218 |
except queue.Empty:
|
| 219 |
break
|
| 220 |
|
| 221 |
+
# Kill any audio players or ongoing tts synthesis processes
|
| 222 |
+
for proc in ["paplay", "aplay", "tts", "espeak-ng"]:
|
| 223 |
+
try:
|
| 224 |
+
subprocess.run(["pkill", "-x", proc], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
|
| 225 |
+
except Exception:
|
| 226 |
+
pass
|
| 227 |
+
|
| 228 |
# Send cancel to speech dispatcher
|
| 229 |
try:
|
| 230 |
subprocess.run(["spd-say", "-C"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
|
| 231 |
+
except Exception:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 232 |
pass
|
| 233 |
|
| 234 |
def tts_worker():
|
|
|
|
| 299 |
def print_help():
|
| 300 |
print(f"\n{C_MAGENTA}{C_BOLD}--- Digital Twin Help Menu ---{C_RESET}")
|
| 301 |
print(f" {C_BOLD}/stop{C_RESET} or {C_BOLD}/s{C_RESET} : Stop current speaking immediately.")
|
| 302 |
+
print(f" {C_BOLD}/voice <type>{C_RESET} : Set voice (cloned [from /local-tts], male1, male2, male3, female1, female2, female3, child_male, child_female).")
|
| 303 |
print(f" {C_BOLD}/rate <value>{C_RESET} : Set speech rate (-100 to 100, e.g. -20, 0, 20).")
|
| 304 |
print(f" {C_BOLD}/clear{C_RESET} or {C_BOLD}/c{C_RESET} : Clear screen and reset conversation history.")
|
| 305 |
print(f" {C_BOLD}/tts <on|off>{C_RESET} : Enable or disable Text-to-Speech.")
|
|
|
|
| 353 |
return
|
| 354 |
|
| 355 |
print(f"Twin model '{C_BOLD}{MODEL_NAME}{C_RESET}' loaded.")
|
| 356 |
+
cloned_path = get_cloned_voice_path()
|
| 357 |
+
if cloned_path and tts_config["voice"] == "cloned":
|
| 358 |
+
print(f"Voice Profile: {C_BOLD}{C_GREEN}Jason's Cloned Voice ({cloned_path}){C_RESET}")
|
| 359 |
+
else:
|
| 360 |
+
print(f"Voice Profile: {C_BOLD}{C_MAGENTA}{tts_config['voice']}{C_RESET}")
|
| 361 |
print(f"Two-Way Voice active. Type text OR press {C_BOLD}[ENTER]{C_RESET} to speak. (Type {C_BOLD}/help{C_RESET} for commands)\n")
|
| 362 |
|
| 363 |
start_tts_system()
|
|
|
|
| 375 |
|
| 376 |
# If input is empty, enter Voice Input Mode
|
| 377 |
if not user_input:
|
| 378 |
+
print(f"{C_YELLOW}[Recording... Press ENTER to stop recording]{C_RESET}", end="", flush=True)
|
|
|
|
|
|
|
| 379 |
|
| 380 |
# Start recording
|
| 381 |
record_proc = record_audio()
|
|
|
|
| 432 |
elif cmd == "/voice":
|
| 433 |
if len(cmd_parts) > 1:
|
| 434 |
new_voice = cmd_parts[1].lower()
|
| 435 |
+
valid_voices = ["cloned", "male1", "male2", "male3", "female1", "female2", "female3", "child_male", "child_female"]
|
| 436 |
if new_voice in valid_voices:
|
| 437 |
tts_config["voice"] = new_voice
|
| 438 |
+
if new_voice == "cloned":
|
| 439 |
+
p = get_cloned_voice_path()
|
| 440 |
+
print(f"{C_MAGENTA}Voice updated to: Jason's Cloned Voice ({p}){C_RESET}")
|
| 441 |
+
else:
|
| 442 |
+
print(f"{C_MAGENTA}Voice updated to: {new_voice}{C_RESET}")
|
| 443 |
else:
|
| 444 |
print(f"{C_YELLOW}Invalid voice. Select from: {', '.join(valid_voices)}{C_RESET}")
|
| 445 |
else:
|
| 446 |
+
if tts_config['voice'] == 'cloned':
|
| 447 |
+
p = get_cloned_voice_path()
|
| 448 |
+
print(f"{C_MAGENTA}Current voice: Jason's Cloned Voice ({p}){C_RESET}")
|
| 449 |
+
else:
|
| 450 |
+
print(f"{C_MAGENTA}Current voice: {tts_config['voice']}{C_RESET}")
|
| 451 |
continue
|
| 452 |
elif cmd == "/rate":
|
| 453 |
if len(cmd_parts) > 1:
|