Update tts_script.py

tts_script.py

@@ -2,361 +2,96 @@ import time
 import requests
 import pathlib
 from io import BytesIO
-from playsound import playsound
-from webscout import exceptions
-from webscout.AIbase import TTSProvider
-from webscout.litagent import LitAgent
+from flask import Flask, request, jsonify, send_file
 from concurrent.futures import ThreadPoolExecutor, as_completed
-"""
-Text processing utilities for TTS providers.
-"""
-from typing import List, Dict, Tuple, Set, Optional, Pattern
-import re
 
+# Flask App Setup
+app = Flask(__name__)
 
-class SentenceTokenizer:
-    """Advanced sentence tokenizer with support for complex cases and proper formatting."""
-    
-    def __init__(self) -> None:
-        # Common abbreviations by category
-        self.TITLES: Set[str] = {
-            'mr', 'mrs', 'ms', 'dr', 'prof', 'rev', 'sr', 'jr', 'esq',
-            'hon', 'pres', 'gov', 'atty', 'supt', 'det', 'rev', 'col','maj', 'gen', 'capt', 'cmdr',
-            'lt', 'sgt', 'cpl', 'pvt'
-        }
-        
-        self.ACADEMIC: Set[str] = {
-            'ph.d', 'phd', 'm.d', 'md', 'b.a', 'ba', 'm.a', 'ma', 'd.d.s', 'dds',
-            'm.b.a', 'mba', 'b.sc', 'bsc', 'm.sc', 'msc', 'llb', 'll.b', 'bl'
-        }
-        
-        self.ORGANIZATIONS: Set[str] = {
-            'inc', 'ltd', 'co', 'corp', 'llc', 'llp', 'assn', 'bros', 'plc', 'cos',
-            'intl', 'dept', 'est', 'dist', 'mfg', 'div'
-        }
-        
-        self.MONTHS: Set[str] = {
-            'jan', 'feb', 'mar', 'apr', 'jun', 'jul', 'aug', 'sep', 'oct', 'nov', 'dec'
-        }
-        
-        self.UNITS: Set[str] = {
-            'oz', 'pt', 'qt', 'gal', 'ml', 'cc', 'km', 'cm', 'mm', 'ft', 'in',
-            'kg', 'lb', 'lbs', 'hz', 'khz', 'mhz', 'ghz', 'kb', 'mb', 'gb', 'tb'
-        }
-        
-        self.TECHNOLOGY: Set[str] = {
-            'v', 'ver', 'app', 'sys', 'dir', 'exe', 'lib', 'api', 'sdk', 'url',
-            'cpu', 'gpu', 'ram', 'rom', 'hdd', 'ssd', 'lan', 'wan', 'sql', 'html'
-        }
-        
-        self.MISC: Set[str] = {
-            'vs', 'etc', 'ie', 'eg', 'no', 'al', 'ca', 'cf', 'pp', 'est', 'st',
-            'approx', 'appt', 'apt', 'dept', 'depts', 'min', 'max', 'avg'
-        }
+# ElevenLabs API Configuration
+ELEVENLABS_API_URL = "https://api.elevenlabs.io/v1/text-to-speech"
+HEADERS = {"User-Agent": "TTSApp"}
+CACHE_DIR = pathlib.Path("./audio_cache")
+CACHE_DIR.mkdir(exist_ok=True)
 
-        # Combine all abbreviations
-        self.all_abbreviations: Set[str] = (
-            self.TITLES | self.ACADEMIC | self.ORGANIZATIONS |
-            self.MONTHS | self.UNITS | self.TECHNOLOGY | self.MISC
-        )
+# Available Voices
+ALL_VOICES = {
+    "Brian": "nPczCjzI2devNBz1zQrb",
+    "Alice": "Xb7hH8MSUJpSbSDYk0k2",
+    "Will": "bIHbv24MWmeRgasZH58o",
+}
 
-        # Special patterns
-        self.ELLIPSIS: str = r'\.{2,}|…'
-        self.URL_PATTERN: str = (
-            r'(?:https?:\/\/|www\.)[\w\-\.]+\.[a-zA-Z]{2,}(?:\/[^\s]*)?'
-        )
-        self.EMAIL_PATTERN: str = r'[\w\.-]+@[\w\.-]+\.\w+'
-        self.NUMBER_PATTERN: str = (
-            r'\d+(?:\.\d+)?(?:%|°|km|cm|mm|m|kg|g|lb|ft|in|mph|kmh|hz|mhz|ghz)?'
-        )
-        
-        # Quote and bracket pairs
-        self.QUOTE_PAIRS: Dict[str, str] = {
-            '"': '"', "'": "'", '"': '"', "「": "」", "『": "』",
-            "«": "»", "‹": "›", "'": "'", "‚": "'"
-        }
-        
-        self.BRACKETS: Dict[str, str] = {
-            '(': ')', '[': ']', '{': '}', '⟨': '⟩', '「': '」',
-            '『': '』', '【': '】', '〖': '〗', '｢': '｣'
-        }
+# Split text into sentences (Basic)
+def split_sentences(text):
+    return text.split(". ")
 
-        # Compile regex patterns
-        self._compile_patterns()
+# Generate TTS
+def generate_audio(text, voice):
+    if voice not in ALL_VOICES:
+        return {"error": f"Invalid voice '{voice}'"}
 
-    def _compile_patterns(self) -> None:
-        """Compile regex patterns for better performance."""
-        # Pattern for finding potential sentence boundaries
-        self.SENTENCE_END: Pattern = re.compile(
-            r'''
-            # Group for sentence endings
-            (?:
-                # Standard endings with optional quotes/brackets
-                (?<=[.!?])[\"\'\)\]\}»›」』\s]*
-                
-                # Ellipsis
-                |(?:\.{2,}|…)
-                
-                # Asian-style endings
-                |(?<=[。！？」』】\s])
-            )
-            
-            # Must be followed by whitespace and capital letter or number
-            (?=\s+(?:[A-Z0-9]|["'({[\[「『《‹〈][A-Z]))
-            ''',
-            re.VERBOSE
-        )
-
-        # Pattern for abbreviations
-        abbrev_pattern = '|'.join(re.escape(abbr) for abbr in self.all_abbreviations)
-        self.ABBREV_PATTERN: Pattern = re.compile(
-            fr'\b(?:{abbrev_pattern})\.?',
-            re.IGNORECASE
-        )
-
-    def _protect_special_cases(self, text: str) -> Tuple[str, Dict[str, str]]:
-        """Protect URLs, emails, and other special cases from being split."""
-        protected = text
-        placeholders: Dict[str, str] = {}
-        counter = 0
-
-        # Protect URLs and emails
-        for pattern in [self.URL_PATTERN, self.EMAIL_PATTERN]:
-            for match in re.finditer(pattern, protected):
-                placeholder = f'__PROTECTED_{counter}__'
-                placeholders[placeholder] = match.group()
-                protected = protected.replace(match.group(), placeholder)
-                counter += 1
-
-        # Protect quoted content
-        stack = []
-        protected_chars = list(protected)
-        i = 0
-        while i < len(protected_chars):
-            char = protected_chars[i]
-            if char in self.QUOTE_PAIRS:
-                stack.append((char, i))
-            elif stack and char == self.QUOTE_PAIRS[stack[-1][0]]:
-                start_quote, start_idx = stack.pop()
-                content = ''.join(protected_chars[start_idx:i + 1])
-                placeholder = f'__PROTECTED_{counter}__'
-                placeholders[placeholder] = content
-                protected_chars[start_idx:i + 1] = list(placeholder)
-                counter += 1
-            i += 1
-
-        return ''.join(protected_chars), placeholders
-
-    def _restore_special_cases(self, text: str, placeholders: Dict[str, str]) -> str:
-        """Restore protected content."""
-        restored = text
-        for placeholder, original in placeholders.items():
-            restored = restored.replace(placeholder, original)
-        return restored
-
-    def _handle_abbreviations(self, text: str) -> str:
-        """Handle abbreviations to prevent incorrect sentence splitting."""
-        def replace_abbrev(match: re.Match) -> str:
-            abbr = match.group().lower().rstrip('.')
-            if abbr in self.all_abbreviations:
-                return match.group().replace('.', '__DOT__')
-            return match.group()
-
-        return self.ABBREV_PATTERN.sub(replace_abbrev, text)
-
-    def _normalize_whitespace(self, text: str) -> str:
-        """Normalize whitespace while preserving paragraph breaks."""
-        # Replace multiple newlines with special marker
-        text = re.sub(r'\n\s*\n', ' __PARA__ ', text)
-        # Normalize remaining whitespace
-        text = re.sub(r'\s+', ' ', text)
-        return text.strip()
-
-    def _restore_formatting(self, sentences: List[str]) -> List[str]:
-        """Restore original formatting and clean up sentences."""
-        restored = []
-        for sentence in sentences:
-            # Restore dots in abbreviations
-            sentence = sentence.replace('__DOT__', '.')
-            
-            # Restore paragraph breaks
-            sentence = sentence.replace('__PARA__', '\n\n')
-            
-            # Clean up whitespace
-            sentence = re.sub(r'\s+', ' ', sentence).strip()
-            
-            # Capitalize first letter if it's lowercase and not an abbreviation
-            words = sentence.split()
-            if words and words[0].lower() not in self.all_abbreviations:
-                sentence = sentence[0].upper() + sentence[1:]
-            
-            if sentence:
-                restored.append(sentence)
-        
-        return restored
-
-    def tokenize(self, text: str) -> List[str]:
-        """
-        Split text into sentences while handling complex cases.
-        
-        Args:
-            text (str): Input text to split into sentences.
-            
-        Returns:
-            List[str]: List of properly formatted sentences.
-        """
-        if not text or not text.strip():
-            return []
-
-        # Step 1: Protect special cases
-        protected_text, placeholders = self._protect_special_cases(text)
-        
-        # Step 2: Normalize whitespace
-        protected_text = self._normalize_whitespace(protected_text)
-        
-        # Step 3: Handle abbreviations
-        protected_text = self._handle_abbreviations(protected_text)
-        
-        # Step 4: Split into potential sentences
-        potential_sentences = self.SENTENCE_END.split(protected_text)
-        
-        # Step 5: Process and restore formatting
-        sentences = self._restore_formatting(potential_sentences)
-        
-        # Step 6: Restore special cases
-        sentences = [self._restore_special_cases(s, placeholders) for s in sentences]
-        
-        # Step 7: Post-process sentences
-        final_sentences = []
-        current_sentence = []
-        
-        for sentence in sentences:
-            # Skip empty sentences
-            if not sentence.strip():
-                continue
-                
-            # Check if sentence might be continuation of previous
-            if current_sentence and sentence[0].islower():
-                current_sentence.append(sentence)
-            else:
-                if current_sentence:
-                    final_sentences.append(' '.join(current_sentence))
-                current_sentence = [sentence]
-        
-        # Add last sentence if exists
-        if current_sentence:
-            final_sentences.append(' '.join(current_sentence))
-        
-        return final_sentences
-
-
-def split_sentences(text: str) -> List[str]:
-    """
-    Convenience function to split text into sentences using SentenceTokenizer.
-    
-    Args:
-        text (str): Input text to split into sentences.
-    
-    Returns:
-        List[str]: List of properly formatted sentences.
-    """
-    tokenizer = SentenceTokenizer()
-    return tokenizer.tokenize(text)
-
-
-class ElevenlabsTTS(TTSProvider): 
-    """
-    Text-to-speech provider using the ElevenlabsTTS API.
-    """
-    # Request headers
-    headers: dict[str, str] = {
-        "User-Agent": LitAgent().random()
-    }
-    cache_dir = pathlib.Path("./audio_cache")
-    all_voices: dict[str, str] = {"Brian": "nPczCjzI2devNBz1zQrb", "Alice":"Xb7hH8MSUJpSbSDYk0k2", "Bill":"pqHfZKP75CvOlQylNhV4", "Callum":"N2lVS1w4EtoT3dr4eOWO", "Charlie":"IKne3meq5aSn9XLyUdCD", "Charlotte":"XB0fDUnXU5powFXDhCwa", "Chris":"iP95p4xoKVk53GoZ742B", "Daniel":"onwK4e9ZLuTAKqWW03F9", "Eric":"cjVigY5qzO86Huf0OWal", "George":"JBFqnCBsd6RMkjVDRZzb", "Jessica":"cgSgspJ2msm6clMCkdW9", "Laura":"FGY2WhTYpPnrIDTdsKH5", "Liam":"TX3LPaxmHKxFdv7VOQHJ", "Lily":"pFZP5JQG7iQjIQuC4Bku", "Matilda":"XrExE9yKIg1WjnnlVkGX", "Sarah":"EXAVITQu4vr4xnSDxMaL", "Will":"bIHbv24MWmeRgasZH58o", "Neal":"Zp1aWhL05Pi5BkhizFC3"}
-
-    def __init__(self, timeout: int = 20, proxies: dict = None):
-        """Initializes the ElevenlabsTTS TTS client."""
-        self.session = requests.Session()
-        self.session.headers.update(self.headers)
-        if proxies:
-            self.session.proxies.update(proxies)
-        self.timeout = timeout
-        self.params = {'allow_unauthenticated': '1'}
-
-    def tts(self, text: str, voice: str = "Brian", verbose:bool = True) -> str:
-        """
-        Converts text to speech using the ElevenlabsTTS API and saves it to a file.
-        """
-        assert (
-            voice in self.all_voices
-        ), f"Voice '{voice}' not one of [{', '.join(self.all_voices.keys())}]"
-
-        filename = self.cache_dir / f"{int(time.time())}.mp3"  
-
-        # Split text into sentences
-        sentences = split_sentences(text)
-
-        # Function to request audio for each chunk
-        def generate_audio_for_chunk(part_text: str, part_number: int):
-            while True:
-                try:
-                    json_data = {'text': part_text, 'model_id': 'eleven_multilingual_v2'}
-                    response = self.session.post(f'https://api.elevenlabs.io/v1/text-to-speech/{self.all_voices[voice]}',params=self.params, headers=self.headers, json=json_data, timeout=self.timeout)
-                    response.raise_for_status()
-
-                    # Create the audio_cache directory if it doesn't exist
-                    self.cache_dir.mkdir(parents=True, exist_ok=True) 
-
-                    # Check if the request was successful
-                    if response.ok and response.status_code == 200:
-                        return part_number, response.content
-                    else:
-                        raise exceptions.FailedToGenerateResponseError(
-                            f"Failed to generate audio for chunk {part_number}: {response.status_code}"
-                        )
-                except requests.RequestException as e:
-                    time.sleep(1)
-                    continue
+    filename = CACHE_DIR / f"{int(time.time())}.mp3"
+    sentences = split_sentences(text)
 
+    def fetch_audio(sentence, part_number):
         try:
-            # Using ThreadPoolExecutor to handle requests concurrently
-            with ThreadPoolExecutor() as executor:
-                futures = {executor.submit(generate_audio_for_chunk, sentence.strip(), chunk_num): chunk_num 
-                        for chunk_num, sentence in enumerate(sentences, start=1)}
-                
-                # Dictionary to store results with order preserved
-                audio_chunks = {}
-
-                for future in as_completed(futures):
-                    chunk_num = futures[future]
-                    try:
-                        part_number, audio_data = future.result()
-                        audio_chunks[part_number] = audio_data
-                    except Exception as e:
-                        raise exceptions.FailedToGenerateResponseError(
-                            f"Failed to generate audio for chunk {chunk_num}: {e}"
-                        )
-
-            # Combine audio chunks in the correct sequence
-            combined_audio = BytesIO()
-            for part_number in sorted(audio_chunks.keys()):
-                combined_audio.write(audio_chunks[part_number])
-
-            # Save the combined audio data to a single file
-            with open(filename, 'wb') as f:
-                f.write(combined_audio.getvalue())
-            return filename.as_posix()
-
-        except requests.exceptions.RequestException as e:
-            raise exceptions.FailedToGenerateResponseError(
-                f"Failed to perform the operation: {e}"
+            response = requests.post(
+                f"{ELEVENLABS_API_URL}/{ALL_VOICES[voice]}",
+                headers=HEADERS,
+                json={"text": sentence, "model_id": "eleven_multilingual_v2"},
+                timeout=20
             )
-        
+            response.raise_for_status()
+            return part_number, response.content
+        except requests.RequestException:
+            return part_number, None
+
+    audio_chunks = {}
+    with ThreadPoolExecutor() as executor:
+        futures = {executor.submit(fetch_audio, sentence.strip(), i): i for i, sentence in enumerate(sentences)}
+
+        for future in as_completed(futures):
+            part_number, audio_data = future.result()
+            if audio_data:
+                audio_chunks[part_number] = audio_data
+
+    combined_audio = BytesIO()
+    for part_number in sorted(audio_chunks.keys()):
+        combined_audio.write(audio_chunks[part_number])
+
+    with open(filename, "wb") as f:
+        f.write(combined_audio.getvalue())
+
+    return filename.as_posix()
+
+# Flask Routes
+@app.route("/")
+def home():
+    return '''
+    <h1>Text-to-Speech API</h1>
+    <form action="/tts" method="post">
+        <label>Text:</label>
+        <input type="text" name="text" required>
+        <label>Voice:</label>
+        <select name="voice">
+            <option value="Brian">Brian</option>
+            <option value="Alice">Alice</option>
+            <option value="Will">Will</option>
+        </select>
+        <button type="submit">Generate</button>
+    </form>
+    '''
+
+@app.route("/tts", methods=["POST"])
+def tts():
+    text = request.form.get("text")
+    voice = request.form.get("voice", "Brian")
+
+    if not text:
+        return jsonify({"error": "Text is required!"})
+
+    audio_file = generate_audio(text, voice)
+    return send_file(audio_file, as_attachment=True)
 
-# Example usage
 if __name__ == "__main__":
-    elevenlabs = ElevenlabsTTS()
-    text = "This is a test of the ElevenlabsTTS text-to-speech API. It supports multiple sentences and advanced logging."
-
-    audio_file = elevenlabs.tts(text, voice="Brian") 
+    app.run(debug=True, host="0.0.0.0", port=5000)