o 4à“iÌ7ã @sœdZddlZddlZddlZddlmZmZmZddl Z ddl m Z m Z ddl mZddlmZe  e¡Zdd ed ed ed edef dd„ZGdd„dƒZdS)u Long Text Processing Service Handles text chunking and audio stitching for long text inputs. Why This Approach: - Text-based chunking: Preserves semantic meaning - SNAC token sliding window: Separate layer for smooth audio - Crossfade stitching: Seamless audio transitions between chunks - Unlimited text: Can process any length text Architecture: 1. Long text → IndicSentenceChunker → Text chunks 2. Each text chunk → TTS Model → Audio chunk 3. All audio chunks → Crossfade stitching → Final audio éN)ÚListÚOptionalÚAsyncGenerator)ÚIndicSentenceChunkerÚcrossfade_audio)ÚVeena3SlidingWindowPipeline)ÚSparkTTSPipelineéÀ]ééÚ data_sizeÚ sample_rateÚchannelsÚbits_per_sampleÚreturnc Csd|||d}||d}t ddd|d¡}|t dddd |||||¡ 7}|t d d |¡7}|S) a Create WAV file header for PCM data. Args: data_size: Size of PCM data in bytes sample_rate: Sample rate (Hz) channels: Number of channels bits_per_sample: Bits per sample Returns: WAV header bytes (44 bytes) éz<4sI4ssRIFFé$sWAVEz <4sIHHIIHHsfmt r r z<4sIsdata)ÚstructÚpack)r r rrÚ byte_rateÚ block_alignÚheader©rúE/home/ubuntu/veenaModal/veena3modal/processing/long_text_processor.pyÚcreate_wav_headers  rc@seZdZdZdZdZdZdZ d&dede e fd d „Z d e d e fd d„Zd e d efdd„Z       d'd e de dededededede eded e efdd„Z  d(d eeded!ed efd"d#„Z    d)d e de dededede ed eedffd$d%„ZdS)*ÚLongTextProcessoru/ Process long texts by chunking, generating audio, and stitching. Features: - Intelligent text chunking (respects sentence boundaries, Indic languages) - Parallel audio generation (if desired) - Crossfade stitching for seamless audio - Memory efficient (processes chunks sequentially by default) Why text chunking, not token chunking: - Text maintains semantic meaning - Natural sentence boundaries = better prosody - Simpler implementation - Model handles tokenization internally - SNAC token sliding window is separate (already implemented) Max Input Length Reference (post-normalization): "इसके निरà¥à¤®à¤¾à¤£ में मà¥à¤–à¥à¤¯ वासà¥à¤¤à¥à¤•à¤¾à¤° उसà¥à¤¤à¤¾à¤¦ अहमद लाहौरी के नेतृतà¥à¤µ में लगभग 20,000 कारीगरों और शिलà¥à¤ªà¤•à¤¾à¤°à¥‹à¤‚ ने दिन-रात मेहनत की थी। इमारत के सामने बना 'चारबाग' शैली का उदà¥à¤¯à¤¾à¤¨ और पानी की नहरें इसकी सà¥à¤‚दरता में चार चाà¤à¤¦ लगा देते हैं।" = ~232 characters after normalization (numbers expanded to words) éæéÜéªé2NÚpipelineÚstreaming_pipelinecCs>||_||_t|jd|_tjd|j|j|j|j dœddS)zÊ Initialize long text processor. Args: pipeline: Non-streaming TTS pipeline streaming_pipeline: Optional streaming pipeline (for streaming mode) )Úmax_chunk_lengthzLongTextProcessor initialized)Úmax_model_input_lengthÚchunking_thresholdÚ chunk_sizeÚ crossfade_ms©ÚextraN) r r!rÚ CHUNK_SIZEÚchunkerÚloggerÚinfoÚMAX_MODEL_INPUT_LENGTHÚCHUNKING_THRESHOLDÚ CROSSFADE_MS)Úselfr r!rrrÚ__init__`s ü þzLongTextProcessor.__init__ÚtextrcCst|ƒ|jkS)z$Determine if text should be chunked.)Úlenr.©r0r2rrrÚ should_chunkzszLongTextProcessor.should_chunkcCs |j |¡S)a@ Chunk text using the internal chunker. Delegates to self.chunker.chunk_text() for actual chunking logic. This method is used by _stream_chunked_text in tts_runtime. Args: text: Text to chunk Returns: List of text chunks )r*Ú chunk_textr4rrrr6~s zLongTextProcessor.chunk_textçš™™™™™Ù?çÍÌÌÌÌÌì?éçÍÌÌÌÌÌð?é€>ÚspeakerÚ temperatureÚtop_kÚtop_pÚ max_tokensÚrepetition_penaltyÚseedr c  ÃsÜ|j |¡} tjdt|ƒ| d| |dœd|j |¡} tjdt| ƒ›dt| ƒdd„| Dƒd œdg} tjd t| ƒ›d t|ƒ›d t| ƒt|ƒ|d œdt| ƒD]]\} }ttt|ƒdƒdƒ}t |dƒ}|j j ||||||||dIdH}|duržtj d| d›dt| ƒ›| t|ƒ|dd…t| ƒdœddSt|ƒdkrª|dd…n|}|   |¡qT|j| | |jd}tt|ƒ| ddd}||}t|ƒ| d}tjdt| ƒ›d|d›d t| ƒ|t|ƒd!d"œd|S)#a­ Generate audio for long text with chunking and stitching. Process: 1. Chunk text at natural boundaries 2. Generate audio for each chunk 3. Stitch audio with crossfade Args: text: Long text to synthesize speaker: Speaker name (lipakshi, reet, etc.) temperature: Sampling temperature top_p: Nucleus sampling max_tokens: Max tokens per chunk seed: Random seed (same seed = same voice across chunks) sample_rate: Audio sample rate Returns: Stitched audio bytes (int16 PCM) or None if generation fails z"Processing long text with chunkingÚprimary)Ú text_lengthÚprimary_languageÚlang_mixr<r'zText chunked into ú chunkscSsg|]}t|ƒ‘qSr)r3)Ú.0ÚchunkrrrÚ Ász.)Ú num_chunksÚ chunk_sizesu🎵 Generating z chunks for z chars)Ú total_chunksÚ total_charsr<ér9éd)r<r2r=r>r?r@rArBNu'⌠Failed to generate audio for chunk r ú/é–)Ú chunk_indexÚ chunk_lengthÚchunk_text_previewrMé,)r r&r )r r rréu✅ Generated u chunks → z.1fzs audioi)rMÚaudio_durationÚ audio_size_mb)r*Údetect_language_mixr+r,r3r6Ú enumerateÚminÚintÚmaxr Úgenerate_speech_indicÚerrorÚappendÚstitch_audio_chunksr/r)r0r2r<r=r>r?r@rArBr Ú lang_infoÚ text_chunksÚ audio_chunksÚirIÚchunk_max_tokensÚ audio_bytesÚpcm_dataÚ stitched_pcmÚ wav_headerÚ final_audioÚtotal_audio_durationrrrÚgenerate_with_chunkings”€ !üþ  þþ ýþ þ  ø  üþ  ýü ýþ z(LongTextProcessor.generate_with_chunkingrer&cCs‚|sdSt|ƒdkr|dSt|d|ƒ}|d}tdt|ƒƒD]}t|||||d}tjd|d›|t|ƒdœdq!|S) aà Stitch multiple audio chunks with crossfade transitions. Why crossfade: - Prevents pops/clicks at chunk boundaries - Smooth transitions between chunks - Professional audio quality Args: audio_chunks: List of audio bytes (int16 PCM) sample_rate: Sample rate (Hz) crossfade_ms: Crossfade duration (milliseconds) Returns: Stitched audio bytes ór rg@@)Úcrossfade_samplesr zCrossfaded chunk )rSÚcurrent_length_bytesr')r3r]Úrangerr+Údebug)r0rer r&rpÚresultrfrrrrbs( ü þþz%LongTextProcessor.stitch_audio_chunksc Cs¤|jdur tdƒ‚|j |¡}tjdt|ƒ›ddt|ƒidt|ƒD]*\}} t d|d›d t|ƒ›¡|jj|| ||||d 2z 3dHW} | VqD6q%dS) a² Generate audio for long text with streaming (experimental). Note: Streaming long texts is more complex: - Need to stream each chunk - Need to buffer for crossfade - Adds latency for stitching For now, recommend using non-streaming for long texts. Args: text: Long text to synthesize speaker: Speaker name temperature: Sampling temperature top_p: Nucleus sampling max_tokens: Max tokens per chunk repetition_penalty: Repetition penalty seed: Random seed Yields: Audio bytes (in chunks) Nz Streaming pipeline not availablezStreaming long text with rGrKr'zStreaming chunk r rQ)r<r2r=r?r@rB) r!Ú ValueErrorr*r6r+r,r3r[Úgenerate_speech_stream_indic) r0r2r<r=r?r@rBrdrfrIrhrrrÚ generate_with_chunking_streamingLs*€   þúøüz2LongTextProcessor.generate_with_chunking_streaming)N)r7rr8r9r:Nr;)r;r)r7r8r9N)Ú__name__Ú __module__Ú __qualname__Ú__doc__r-r.r)r/rrrr1ÚstrÚboolr5Úlistr6Úfloatr]Úbytesrnrrbrrwrrrrr6s’ýþ ýöþýüûúùø ÷ ö õüþýü û9ùþýüûúù ør)r r r )r{ÚasyncioÚnumpyÚnprÚtypingrrrÚloggingÚ#veena3modal.processing.text_chunkerrrÚ#veena3modal.core.streaming_pipelinerÚveena3modal.core.pipelinerÚ getLoggerrxr+r]r€rrrrrrÚs