from __future__ import annotations import numpy as np import gradio as gr from typing import Annotated from app import _log_call_end, _log_call_start, _truncate_for_log from ._docstrings import autodoc try: import torch # type: ignore except Exception: # pragma: no cover torch = None # type: ignore try: from kokoro import KModel, KPipeline # type: ignore except Exception: # pragma: no cover KModel = None # type: ignore KPipeline = None # type: ignore _KOKORO_STATE = { "initialized": False, "device": "cpu", "model": None, "pipelines": {}, } def get_kokoro_voices() -> list[str]: try: from huggingface_hub import list_repo_files files = list_repo_files("hexgrad/Kokoro-82M") voice_files = [file for file in files if file.endswith(".pt") and file.startswith("voices/")] voices = [file.replace("voices/", "").replace(".pt", "") for file in voice_files] return sorted(voices) if voices else _get_fallback_voices() except Exception: return _get_fallback_voices() def _get_fallback_voices() -> list[str]: return [ "af_alloy", "af_aoede", "af_bella", "af_heart", "af_jessica", "af_kore", "af_nicole", "af_nova", "af_river", "af_sarah", "af_sky", "am_adam", "am_echo", "am_eric", "am_fenrir", "am_liam", "am_michael", "am_onyx", "am_puck", "am_santa", "bf_alice", "bf_emma", "bf_isabella", "bf_lily", "bm_daniel", "bm_fable", "bm_george", "bm_lewis", "ef_dora", "em_alex", "em_santa", "ff_siwis", "hf_alpha", "hf_beta", "hm_omega", "hm_psi", "if_sara", "im_nicola", "jf_alpha", "jf_gongitsune", "jf_nezumi", "jf_tebukuro", "jm_kumo", "pf_dora", "pm_alex", "pm_santa", "zf_xiaobei", "zf_xiaoni", "zf_xiaoxiao", "zf_xiaoyi", "zm_yunjian", "zm_yunxi", "zm_yunxia", "zm_yunyang", ] def _init_kokoro() -> None: if _KOKORO_STATE["initialized"]: return if KModel is None or KPipeline is None: raise RuntimeError("Kokoro is not installed. Please install the 'kokoro' package (>=0.9.4).") device = "cpu" if torch is not None: try: if torch.cuda.is_available(): device = "cuda" except Exception: device = "cpu" model = KModel().to(device).eval() pipelines = {"a": KPipeline(lang_code="a", model=False)} try: pipelines["a"].g2p.lexicon.golds["kokoro"] = "kˈOkəɹO" except Exception: pass _KOKORO_STATE.update({"initialized": True, "device": device, "model": model, "pipelines": pipelines}) def List_Kokoro_Voices() -> list[str]: return get_kokoro_voices() # Single source of truth for the LLM-facing tool description TOOL_SUMMARY = ( "Synthesize speech from text using Kokoro-82M; choose voice and speed; returns (sample_rate, waveform). " "Return the generated media to the user in this format `![Alt text](URL)`." ) @autodoc( summary=TOOL_SUMMARY, ) def Generate_Speech( text: Annotated[str, "The text to synthesize (English)."], speed: Annotated[float, "Speech speed multiplier in 0.5–2.0; 1.0 = normal speed."] = 1.25, voice: Annotated[ str, ( "Voice identifier from 54 available options. " "Voice Legend: af=American female, am=American male, bf=British female, bm=British male, ef=European female, " "em=European male, hf=Hindi female, hm=Hindi male, if=Italian female, im=Italian male, jf=Japanese female, " "jm=Japanese male, pf=Portuguese female, pm=Portuguese male, zf=Chinese female, zm=Chinese male, ff=French female. " "All Voices: af_alloy, af_aoede, af_bella, af_heart, af_jessica, af_kore, af_nicole, af_nova, af_river, af_sarah, af_sky, " "am_adam, am_echo, am_eric, am_fenrir, am_liam, am_michael, am_onyx, am_puck, am_santa, bf_alice, bf_emma, bf_isabella, " "bf_lily, bm_daniel, bm_fable, bm_george, bm_lewis, ef_dora, em_alex, em_santa, ff_siwis, hf_alpha, hf_beta, hm_omega, hm_psi, " "if_sara, im_nicola, jf_alpha, jf_gongitsune, jf_nezumi, jf_tebukuro, jm_kumo, pf_dora, pm_alex, pm_santa, zf_xiaobei, " "zf_xiaoni, zf_xiaoxiao, zf_xiaoyi, zm_yunjian, zm_yunxi, zm_yunxia, zm_yunyang." ), ] = "af_heart", ) -> tuple[int, np.ndarray]: _log_call_start("Generate_Speech", text=_truncate_for_log(text, 200), speed=speed, voice=voice) if not text or not text.strip(): try: _log_call_end("Generate_Speech", "error=empty text") finally: pass raise gr.Error("Please provide non-empty text to synthesize.") _init_kokoro() model = _KOKORO_STATE["model"] pipelines = _KOKORO_STATE["pipelines"] pipeline = pipelines.get("a") if pipeline is None: raise gr.Error("Kokoro English pipeline not initialized.") audio_segments = [] pack = pipeline.load_voice(voice) try: segments = list(pipeline(text, voice, speed)) total_segments = len(segments) for segment_idx, (text_chunk, ps, _) in enumerate(segments): ref_s = pack[len(ps) - 1] try: audio = model(ps, ref_s, float(speed)) audio_segments.append(audio.detach().cpu().numpy()) if total_segments > 10 and (segment_idx + 1) % 5 == 0: print(f"Progress: Generated {segment_idx + 1}/{total_segments} segments...") except Exception as exc: raise gr.Error(f"Error generating audio for segment {segment_idx + 1}: {exc}") if not audio_segments: raise gr.Error("No audio was generated (empty synthesis result).") if len(audio_segments) == 1: final_audio = audio_segments[0] else: final_audio = np.concatenate(audio_segments, axis=0) if total_segments > 1: duration = len(final_audio) / 24_000 print(f"Completed: {total_segments} segments concatenated into {duration:.1f} seconds of audio") _log_call_end("Generate_Speech", f"samples={final_audio.shape[0]} duration_sec={len(final_audio)/24_000:.2f}") return 24_000, final_audio except gr.Error as exc: _log_call_end("Generate_Speech", f"gr_error={str(exc)}") raise except Exception as exc: # pylint: disable=broad-except _log_call_end("Generate_Speech", f"error={str(exc)[:120]}") raise gr.Error(f"Error during speech generation: {exc}") def build_interface() -> gr.Interface: available_voices = get_kokoro_voices() return gr.Interface( fn=Generate_Speech, inputs=[ gr.Textbox(label="Text", placeholder="Type text to synthesize…", lines=4), gr.Slider(minimum=0.5, maximum=2.0, value=1.25, step=0.1, label="Speed"), gr.Dropdown( label="Voice", choices=available_voices, value="af_heart", info="Select from 54 available voices across multiple languages and accents", ), ], outputs=gr.Audio(label="Audio", type="numpy", format="wav", show_download_button=True), title="Generate Speech", description=( "
Generate speech with Kokoro-82M. Supports multiple languages and accents. Runs on CPU or CUDA if available.
" ), api_description=TOOL_SUMMARY, flagging_mode="never", ) __all__ = ["Generate_Speech", "List_Kokoro_Voices", "build_interface"]