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Update conver.py
Browse files
conver.py
CHANGED
@@ -1,7 +1,6 @@
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from dataclasses import dataclass
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from typing import List, Tuple, Dict
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import os
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import re
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import httpx
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import json
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from openai import OpenAI
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@@ -19,10 +18,17 @@ class ConversationConfig:
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model_name: str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"
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class URLToAudioConverter:
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def __init__(self, config: ConversationConfig, llm_api_key: str):
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self.config = config
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self.llm_client = OpenAI(api_key=llm_api_key, base_url="https://api.together.xyz/v1")
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self.llm_out = None
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def fetch_text(self, url: str) -> str:
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if not url:
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@@ -46,44 +52,49 @@ class URLToAudioConverter:
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f"between two experts. Return ONLY a JSON object with the following structure:\n"
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'{"conversation": [{"speaker": "Speaker1", "text": "..."}, {"speaker": "Speaker2", "text": "..."}]}'
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)
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-
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chat_completion = self.llm_client.chat.completions.create(
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messages=[{"role": "user", "content": prompt}],
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model=self.config.model_name,
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response_format={"type": "json_object"}
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)
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-
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response_content = chat_completion.choices[0].message.content
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json_str = response_content.strip()
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-
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if not json_str.startswith('{'):
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start = json_str.find('{')
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if start != -1:
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json_str = json_str[start:]
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-
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if not json_str.endswith('}'):
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end = json_str.rfind('}')
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if end != -1:
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json_str = json_str[:end+1]
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return json.loads(json_str)
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except Exception as e:
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print(f"Error en extract_conversation: {str(e)}")
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raise RuntimeError(f"Failed to extract conversation: {str(e)}")
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async def text_to_speech(self, conversation_json: Dict, voice_1: str, voice_2: str) -> Tuple[List[str], str]:
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output_dir = self._create_output_directory()
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filenames = []
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try:
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for i, turn in enumerate(conversation_json["conversation"]):
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filename =
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voice = voice_1 if i % 2 == 0 else voice_2
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tmp_path, error = await self._generate_audio(turn["text"], voice)
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if error:
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raise RuntimeError(f"Text-to-speech failed: {error}")
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os.rename(tmp_path, filename)
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filenames.append(filename)
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except Exception as e:
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raise RuntimeError(f"Failed to convert text to speech: {e}")
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@@ -92,75 +103,108 @@ class URLToAudioConverter:
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return None, "Text cannot be empty"
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if not voice:
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return None, "Voice cannot be empty"
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voice_short_name = voice.split(" - ")[0]
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rate_str = f"{rate:+d}%"
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pitch_str = f"{pitch:+d}Hz"
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communicate = edge_tts.Communicate(text, voice_short_name, rate=rate_str, pitch=pitch_str)
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with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
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tmp_path = tmp_file.name
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await communicate.save(tmp_path)
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return tmp_path, None
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def _create_output_directory(self) -> str:
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file_path = os.path.join(directory, filename)
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if file_path.endswith(".mp3"):
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file_age = now - os.path.getmtime(file_path)
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if file_age > max_age_seconds:
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os.remove(file_path)
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def combine_audio_files(self, filenames: List[str], output_file: str) -> None:
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if not filenames:
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raise ValueError("No input files provided")
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try:
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combined = AudioSegment.empty()
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for filename in filenames:
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combined.export(output_file, format="mp3")
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except Exception as e:
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raise RuntimeError(f"Failed to combine audio files: {e}")
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async def url_to_audio(self, url: str, voice_1: str, voice_2: str) -> Tuple[str, str]:
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self.clean_old_files()
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text = self.fetch_text(url)
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words = text.split()
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if len(words) > self.config.max_words:
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text = " ".join(words[:self.config.max_words])
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conversation_json = self.extract_conversation(text)
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conversation_text = "\n".join(
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f"{turn['speaker']}: {turn['text']}" for turn in conversation_json["conversation"]
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)
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self.llm_out = conversation_json
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audio_files,
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async def text_to_audio(self, text: str, voice_1: str, voice_2: str) -> Tuple[str, str]:
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conversation_json = self.extract_conversation(text)
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conversation_text = "\n".join(
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f"{turn['speaker']}: {turn['text']}" for turn in conversation_json["conversation"]
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)
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audio_files,
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-
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async def raw_text_to_audio(self, text: str, voice_1: str, voice_2: str) -> Tuple[str, str]:
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conversation = {
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"conversation": [
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{"speaker": "Host", "text": text},
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{"speaker": "Co-host", "text": "(Continuación del tema)"}
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]
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}
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audio_files,
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output_file = os.path.join(
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self.combine_audio_files(audio_files, output_file)
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return text, output_file
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from dataclasses import dataclass
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from typing import List, Tuple, Dict
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import os
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import httpx
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import json
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from openai import OpenAI
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model_name: str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"
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class URLToAudioConverter:
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BASE_OUTPUT_DIR = "outputs"
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def __init__(self, config: ConversationConfig, llm_api_key: str):
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self.config = config
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self.llm_client = OpenAI(api_key=llm_api_key, base_url="https://api.together.xyz/v1")
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self.llm_out = None
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self._ensure_base_output_dir()
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def _ensure_base_output_dir(self):
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if not os.path.exists(self.BASE_OUTPUT_DIR):
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os.makedirs(self.BASE_OUTPUT_DIR, exist_ok=True)
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def fetch_text(self, url: str) -> str:
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if not url:
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f"between two experts. Return ONLY a JSON object with the following structure:\n"
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'{"conversation": [{"speaker": "Speaker1", "text": "..."}, {"speaker": "Speaker2", "text": "..."}]}'
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)
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chat_completion = self.llm_client.chat.completions.create(
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messages=[{"role": "user", "content": prompt}],
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model=self.config.model_name,
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response_format={"type": "json_object"}
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)
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response_content = chat_completion.choices[0].message.content
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json_str = response_content.strip()
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if not json_str.startswith('{'):
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start = json_str.find('{')
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if start != -1:
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json_str = json_str[start:]
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if not json_str.endswith('}'):
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end = json_str.rfind('}')
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if end != -1:
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json_str = json_str[:end+1]
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return json.loads(json_str)
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except Exception as e:
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print(f"Error en extract_conversation: {str(e)}")
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print(f"Respuesta del modelo: {response_content}")
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raise RuntimeError(f"Failed to extract conversation: {str(e)}")
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async def text_to_speech(self, conversation_json: Dict, voice_1: str, voice_2: str) -> Tuple[List[str], str]:
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output_dir = Path(self._create_output_directory())
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filenames = []
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try:
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for i, turn in enumerate(conversation_json["conversation"]):
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filename = output_dir / f"output_{i}.mp3"
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voice = voice_1 if i % 2 == 0 else voice_2
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tmp_path, error = await self._generate_audio(turn["text"], voice)
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if error:
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raise RuntimeError(f"Text-to-speech failed: {error}")
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os.rename(tmp_path, filename)
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filenames.append(str(filename))
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return filenames, str(output_dir)
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except Exception as e:
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raise RuntimeError(f"Failed to convert text to speech: {e}")
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return None, "Text cannot be empty"
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if not voice:
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return None, "Voice cannot be empty"
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voice_short_name = voice.split(" - ")[0]
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rate_str = f"{rate:+d}%"
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pitch_str = f"{pitch:+d}Hz"
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communicate = edge_tts.Communicate(text, voice_short_name, rate=rate_str, pitch=pitch_str)
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with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
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tmp_path = tmp_file.name
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await communicate.save(tmp_path)
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return tmp_path, None
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def _create_output_directory(self) -> str:
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# Crear carpeta única dentro de outputs/
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random_bytes = os.urandom(8)
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folder_name = base64.urlsafe_b64encode(random_bytes).decode("utf-8").rstrip("=")
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full_path = os.path.join(self.BASE_OUTPUT_DIR, f"podcast_{folder_name}")
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os.makedirs(full_path, exist_ok=True)
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return full_path
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def combine_audio_files(self, filenames: List[str], output_file: str) -> None:
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if not filenames:
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raise ValueError("No input files provided")
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try:
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combined = AudioSegment.empty()
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for filename in filenames:
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audio_segment = AudioSegment.from_file(filename, format="mp3")
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combined += audio_segment
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combined.export(output_file, format="mp3")
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# NO eliminar archivos aquí. Solo en limpieza periódica.
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except Exception as e:
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raise RuntimeError(f"Failed to combine audio files: {e}")
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async def url_to_audio(self, url: str, voice_1: str, voice_2: str) -> Tuple[str, str]:
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text = self.fetch_text(url)
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words = text.split()
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if len(words) > self.config.max_words:
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text = " ".join(words[:self.config.max_words])
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conversation_json = self.extract_conversation(text)
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conversation_text = "\n".join(
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f"{turn['speaker']}: {turn['text']}" for turn in conversation_json["conversation"]
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)
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self.llm_out = conversation_json
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audio_files, folder_name = await self.text_to_speech(
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conversation_json, voice_1, voice_2
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)
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final_output = os.path.join(folder_name, "combined_output.mp3")
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self.combine_audio_files(audio_files, final_output)
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return final_output, conversation_text
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async def text_to_audio(self, text: str, voice_1: str, voice_2: str) -> Tuple[str, str]:
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"""Procesamiento normal con LLM"""
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conversation_json = self.extract_conversation(text)
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conversation_text = "\n".join(
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f"{turn['speaker']}: {turn['text']}" for turn in conversation_json["conversation"]
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)
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audio_files, folder_name = await self.text_to_speech(
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conversation_json, voice_1, voice_2
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)
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final_output = os.path.join(folder_name, "combined_output.mp3")
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self.combine_audio_files(audio_files, final_output)
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return final_output, conversation_text
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async def raw_text_to_audio(self, text: str, voice_1: str, voice_2: str) -> Tuple[str, str]:
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"""Modo sin LLM (texto directo)"""
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conversation = {
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"conversation": [
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{"speaker": "Host", "text": text},
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{"speaker": "Co-host", "text": "(Continuación del tema)"}
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]
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}
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audio_files, folder_name = await self.text_to_speech(conversation, voice_1, voice_2)
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output_file = os.path.join(folder_name, "raw_podcast.mp3")
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self.combine_audio_files(audio_files, output_file)
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return text, output_file
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def clean_old_files(self, max_age_seconds=86400):
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"""
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Borra carpetas y archivos en BASE_OUTPUT_DIR que tengan más de max_age_seconds (por defecto 24h)
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"""
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if not os.path.exists(self.BASE_OUTPUT_DIR):
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return
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now = time.time()
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for folder in os.listdir(self.BASE_OUTPUT_DIR):
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folder_path = os.path.join(self.BASE_OUTPUT_DIR, folder)
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if os.path.isdir(folder_path):
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try:
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mtime = os.path.getmtime(folder_path)
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if now - mtime > max_age_seconds:
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# Borramos carpeta completa
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for root, dirs, files in os.walk(folder_path, topdown=False):
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for name in files:
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os.remove(os.path.join(root, name))
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for name in dirs:
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os.rmdir(os.path.join(root, name))
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os.rmdir(folder_path)
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except Exception:
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pass
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