diff --git a/sijapi/__init__.py b/sijapi/__init__.py
index 973c55f..46ba33c 100644
--- a/sijapi/__init__.py
+++ b/sijapi/__init__.py
@@ -6,11 +6,11 @@ from dotenv import load_dotenv
from dateutil import tz
from pathlib import Path
from .logs import Logger
-from .classes import Database, Geocoder, APIConfig, Configuration, Dir
+from .classes import Database, Geocoder, APIConfig, Configuration, EmailConfiguration, Dir
### Initial initialization
API = APIConfig.load('api', 'secrets')
-Dir = Dir.load('dirs')
+Dir = Dir()
ENV_PATH = Dir.CONFIG / ".env"
LOGS_DIR = Dir.LOGS
L = Logger("Central", LOGS_DIR)
@@ -23,9 +23,11 @@ DB = Database.from_yaml('db.yaml')
ASR = Configuration.load('asr')
IMG = Configuration.load('img')
Cal = Configuration.load('cal', 'secrets')
-Email = Configuration.load('email', 'secrets')
+print(f"Cal configuration: {Cal.__dict__}")
+Email = EmailConfiguration.load('email', 'secrets')
LLM = Configuration.load('llm', 'secrets')
News = Configuration.load('news', 'secrets')
+Obsidian = Configuration.load('obsidian')
TTS = Configuration.load('tts', 'secrets')
CourtListener = Configuration.load('courtlistener', 'secrets')
Tailscale = Configuration.load('tailscale', 'secrets')
diff --git a/sijapi/classes.py b/sijapi/classes.py
index b1a9ad7..ba1acb8 100644
--- a/sijapi/classes.py
+++ b/sijapi/classes.py
@@ -207,7 +207,6 @@ class Configuration(BaseModel):
try:
with yaml_path.open('r') as file:
config_data = yaml.safe_load(file)
-
print(f"Loaded configuration data from {yaml_path}")
if secrets_path:
@@ -220,7 +219,6 @@ class Configuration(BaseModel):
instance._dir_config = dir_config or instance
resolved_data = instance.resolve_placeholders(config_data)
-
return cls._create_nested_config(resolved_data)
except Exception as e:
print(f"Error loading configuration: {str(e)}")
@@ -229,6 +227,8 @@ class Configuration(BaseModel):
@classmethod
def _create_nested_config(cls, data):
if isinstance(data, dict):
+ print(f"Creating nested config for: {cls.__name__}")
+ print(f"Data: {data}")
return cls(**{k: cls._create_nested_config(v) for k, v in data.items()})
elif isinstance(data, list):
return [cls._create_nested_config(item) for item in data]
@@ -267,15 +267,7 @@ class Configuration(BaseModel):
for match in matches:
parts = match.split('.')
- if len(parts) == 1: # Internal reference
- replacement = getattr(self._dir_config, parts[0], str(Path.home() / parts[0].lower()))
- elif len(parts) == 2 and parts[0] == 'Dir':
- replacement = getattr(self._dir_config, parts[1], str(Path.home() / parts[1].lower()))
- elif len(parts) == 2 and parts[0] == 'ENV':
- replacement = os.getenv(parts[1], '')
- else:
- replacement = value
-
+ replacement = self._resolve_nested_placeholder(parts)
value = value.replace('{{' + match + '}}', str(replacement))
# Convert to Path if it looks like a file path
@@ -283,6 +275,17 @@ class Configuration(BaseModel):
return Path(value).expanduser()
return value
+ def _resolve_nested_placeholder(self, parts: List[str]) -> Any:
+ current = self._dir_config
+ for part in parts:
+ if part == 'ENV':
+ return os.getenv(parts[-1], '')
+ elif hasattr(current, part):
+ current = getattr(current, part)
+ else:
+ return str(Path.home() / part.lower())
+ return current
+
class APIConfig(BaseModel):
HOST: str
@@ -788,6 +791,31 @@ class EmailConfiguration(Configuration):
autoresponders: List[AutoResponder]
accounts: List[EmailAccount]
+ @classmethod
+ def _create_nested_config(cls, data):
+ if isinstance(data, dict):
+ if 'imaps' in data:
+ return cls(
+ imaps=[IMAPConfig(**imap) for imap in data['imaps']],
+ smtps=[SMTPConfig(**smtp) for smtp in data['smtps']],
+ autoresponders=[AutoResponder(**ar) for ar in data['autoresponders']],
+ accounts=[EmailAccount(**account) for account in data['accounts']],
+ **{k: v for k, v in data.items() if k not in ['imaps', 'smtps', 'autoresponders', 'accounts']}
+ )
+ else:
+ return data # Return the dict as-is for nested structures
+ elif isinstance(data, list):
+ return [cls._create_nested_config(item) for item in data]
+ else:
+ return data
+
+ @classmethod
+ def load(cls, yaml_path: Union[str, Path], secrets_path: Optional[Union[str, Path]] = None, dir_config: Optional['Configuration'] = None) -> 'EmailConfiguration':
+ config_data = super().load(yaml_path, secrets_path, dir_config)
+ return cls._create_nested_config(config_data)
+
+ # ... (rest of the methods remain the same)
+
def get_imap(self, username: str) -> Optional[IMAPConfig]:
return next((imap for imap in self.imaps if imap.username == username), None)
@@ -800,6 +828,9 @@ class EmailConfiguration(Configuration):
def get_account(self, name: str) -> Optional[EmailAccount]:
return next((account for account in self.accounts if account.name == name), None)
+ def get_email_accounts(self) -> List[EmailAccount]:
+ return self.accounts
+
class EmailContact(BaseModel):
email: str
name: Optional[str] = None
diff --git a/sijapi/config/dirs.yaml-example b/sijapi/config/dirs.yaml-example
deleted file mode 100644
index 1c6667f..0000000
--- a/sijapi/config/dirs.yaml-example
+++ /dev/null
@@ -1,16 +0,0 @@
-HOME: ~
-BASE: '{{ HOME }}/workshop/sijapi'
-SIJAPI: '{{ BASE }}/sijapi'
-CONFIG: '{{ SIJAPI }}/config'
-CONFIG.email: '{{ CONFIG }}/email.yaml'
-CONFIG.img: '{{ CONFIG }}/img.yaml'
-CONFIG.news: '{{ CONFIG }}/news.yaml'
-SECRETS: '{{ CONFIG }}/secrets.yaml'
-DATA: '{{ SIJAPI }}/data'
-DATA.ALERTS: '{{ DATA }}/alerts'
-DATA.ASR: '{{ DATA }}/asr'
-DATA.BASE: '{{ DATA }}/db'
-DATA.IMG: '{{ DATA }}/img'
-DATA.TTS: '{{ DATA }}/tts'
-TTS.VOICES: '{{ TTS }}/voices'
-LOGS: '{{ SIJAPI }}/logs'
\ No newline at end of file
diff --git a/sijapi/routers/cal.py b/sijapi/routers/cal.py
index c04ab05..eadadc2 100644
--- a/sijapi/routers/cal.py
+++ b/sijapi/routers/cal.py
@@ -23,7 +23,10 @@ cal = APIRouter()
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/token")
timeout = httpx.Timeout(12)
-print(f"Configuration MS365: {Cal.MS365}")
+print(f"Cal object: {Cal}")
+print(f"Cal.__dict__: {Cal.__dict__}")
+print(f"Cal.MS365: {Cal.MS365}")
+
if Cal.MS365.toggle == 'on':
L.CRIT(f"Visit https://api.sij.ai/MS365/login to obtain your Microsoft 365 authentication token.")
diff --git a/sijapi/routers/email.py b/sijapi/routers/email.py
index 6752c97..93b741f 100644
--- a/sijapi/routers/email.py
+++ b/sijapi/routers/email.py
@@ -363,7 +363,7 @@ async def save_processed_uid(filename: Path, account_name: str, uid: str):
async def process_all_accounts():
- email_accounts = load_email_accounts(EMAIL_CONFIG)
+ email_accounts = Email.get_email_accounts()
summarization_tasks = [asyncio.create_task(process_account_archival(account)) for account in email_accounts]
autoresponding_tasks = [asyncio.create_task(process_account_autoresponding(account)) for account in email_accounts]
await asyncio.gather(*summarization_tasks, *autoresponding_tasks)
@@ -371,4 +371,4 @@ async def process_all_accounts():
@email.on_event("startup")
async def startup_event():
await asyncio.sleep(5)
- asyncio.create_task(process_all_accounts())
+ asyncio.create_task(process_all_accounts())
\ No newline at end of file
diff --git a/sijapi/routers/llm.py b/sijapi/routers/llm.py
index 5ad02f1..60432c8 100644
--- a/sijapi/routers/llm.py
+++ b/sijapi/routers/llm.py
@@ -26,7 +26,7 @@ import tempfile
import shutil
import html2text
import markdown
-from sijapi import L, Dir, API, LLM, TTS
+from sijapi import L, Dir, API, LLM, TTS, Obsidian
from sijapi.utilities import convert_to_unix_time, sanitize_filename, ocr_pdf, clean_text, should_use_ocr, extract_text_from_pdf, extract_text_from_docx, read_text_file, str_to_bool, get_extension
from sijapi.routers import tts
from sijapi.routers.asr import transcribe_audio
@@ -49,7 +49,7 @@ def read_markdown_files(folder: Path):
return documents, file_paths
# Read markdown files and generate embeddings
-documents, file_paths = read_markdown_files(DOC_DIR)
+documents, file_paths = read_markdown_files(Obsidian.docs)
for i, doc in enumerate(documents):
response = ollama.embeddings(model="mxbai-embed-large", prompt=doc)
embedding = response["embedding"]
@@ -83,7 +83,7 @@ async def generate_response(prompt: str):
return {"response": output['response']}
-async def query_ollama(usr: str, sys: str = LLM_SYS_MSG, model: str = DEFAULT_LLM, max_tokens: int = 200):
+async def query_ollama(usr: str, sys: str = LLM.chat.sys, model: str = LLM.chat.model, max_tokens: int = LLM.chat.max_tokens):
messages = [{"role": "system", "content": sys},
{"role": "user", "content": usr}]
LLM = Ollama()
@@ -100,8 +100,8 @@ async def query_ollama(usr: str, sys: str = LLM_SYS_MSG, model: str = DEFAULT_LL
async def query_ollama_multishot(
message_list: List[str],
- sys: str = LLM_SYS_MSG,
- model: str = DEFAULT_LLM,
+ sys: str = LLM.chat.sys,
+ model: str = LLM.chat.model,
max_tokens: int = 200
):
if len(message_list) % 2 == 0:
@@ -130,7 +130,7 @@ async def chat_completions(request: Request):
body = await request.json()
timestamp = dt_datetime.now().strftime("%Y%m%d_%H%M%S%f")
- filename = REQUESTS_DIR / f"request_{timestamp}.json"
+ filename = Dir.logs.requests / f"request_{timestamp}.json"
async with aiofiles.open(filename, mode='w') as file:
await file.write(json.dumps(body, indent=4))
@@ -227,9 +227,9 @@ async def stream_messages_with_vision(message: dict, model: str, num_predict: in
def get_appropriate_model(requested_model):
if requested_model == "gpt-4-vision-preview":
- return DEFAULT_VISION
+ return LLM.vision.model
elif not is_model_available(requested_model):
- return DEFAULT_LLM
+ return LLM.chat.model
else:
return requested_model
@@ -310,7 +310,7 @@ async def chat_completions_options(request: Request):
],
"created": int(time.time()),
"id": str(uuid.uuid4()),
- "model": DEFAULT_LLM,
+ "model": LLM.chat.model,
"object": "chat.completion.chunk",
},
status_code=200,
@@ -431,7 +431,7 @@ def llava(image_base64, prompt):
return "" if "pass" in response["response"].lower() else response["response"]
def gpt4v(image_base64, prompt_sys: str, prompt_usr: str, max_tokens: int = 150):
- VISION_LLM = OpenAI(api_key=OPENAI_API_KEY)
+ VISION_LLM = OpenAI(api_key=LLM.OPENAI_API_KEY)
response_1 = VISION_LLM.chat.completions.create(
model="gpt-4-vision-preview",
messages=[
@@ -512,12 +512,12 @@ def gpt4v(image_base64, prompt_sys: str, prompt_usr: str, max_tokens: int = 150)
@llm.get("/summarize")
-async def summarize_get(text: str = Form(None), instruction: str = Form(SUMMARY_INSTRUCT)):
+async def summarize_get(text: str = Form(None), instruction: str = Form(LLM.summary.instruct)):
summarized_text = await summarize_text(text, instruction)
return summarized_text
@llm.post("/summarize")
-async def summarize_post(file: Optional[UploadFile] = File(None), text: Optional[str] = Form(None), instruction: str = Form(SUMMARY_INSTRUCT)):
+async def summarize_post(file: Optional[UploadFile] = File(None), text: Optional[str] = Form(None), instruction: str = Form(LLM.summary.instruct)):
text_content = text if text else await extract_text(file)
summarized_text = await summarize_text(text_content, instruction)
return summarized_text
@@ -526,10 +526,10 @@ async def summarize_post(file: Optional[UploadFile] = File(None), text: Optional
@llm.post("/speaksummary")
async def summarize_tts_endpoint(
bg_tasks: BackgroundTasks,
- instruction: str = Form(SUMMARY_INSTRUCT),
+ instruction: str = Form(LLM.summary.instruct),
file: Optional[UploadFile] = File(None),
text: Optional[str] = Form(None),
- voice: Optional[str] = Form(DEFAULT_VOICE),
+ voice: Optional[str] = Form(TTS.xtts.voice),
speed: Optional[float] = Form(1.2),
podcast: Union[bool, str] = Form(False)
):
@@ -572,8 +572,8 @@ async def summarize_tts_endpoint(
async def summarize_tts(
text: str,
- instruction: str = SUMMARY_INSTRUCT,
- voice: Optional[str] = DEFAULT_VOICE,
+ instruction: str = LLM.summary.instruct,
+ voice: Optional[str] = TTS.xtts.voice,
speed: float = 1.1,
podcast: bool = False,
LLM: Ollama = None
@@ -605,9 +605,9 @@ def split_text_into_chunks(text: str) -> List[str]:
sentences = re.split(r'(?<=[.!?])\s+', text)
words = text.split()
total_words = len(words)
- L.DEBUG(f"Total words: {total_words}. SUMMARY_CHUNK_SIZE: {SUMMARY_CHUNK_SIZE}. SUMMARY_TPW: {SUMMARY_TPW}.")
+ L.DEBUG(f"Total words: {total_words}. LLM.summary.chunk_size: {LLM.summary.chunk_size}. LLM.tpw: {LLM.tpw}.")
- max_words_per_chunk = int(SUMMARY_CHUNK_SIZE / SUMMARY_TPW)
+ max_words_per_chunk = int(LLM.summary.chunk_size / LLM.tpw)
L.DEBUG(f"Maximum words per chunk: {max_words_per_chunk}")
chunks = []
@@ -633,8 +633,8 @@ def split_text_into_chunks(text: str) -> List[str]:
def calculate_max_tokens(text: str) -> int:
- tokens_count = max(1, int(len(text.split()) * SUMMARY_TPW)) # Ensure at least 1
- return min(tokens_count // 4, SUMMARY_CHUNK_SIZE)
+ tokens_count = max(1, int(len(text.split()) * LLM.tpw)) # Ensure at least 1
+ return min(tokens_count // 4, LLM.summary.chunk_size)
@@ -694,7 +694,7 @@ async def extract_text(file: Union[UploadFile, bytes, bytearray, str, Path], bg_
raise ValueError(f"Error extracting text: {str(e)}")
-async def summarize_text(text: str, instruction: str = SUMMARY_INSTRUCT, length_override: int = None, length_quotient: float = SUMMARY_LENGTH_RATIO, LLM: Ollama = None):
+async def summarize_text(text: str, instruction: str = LLM.summary.instruct, length_override: int = None, length_quotient: float = LLM.summary.length_ratio, LLM: Ollama = None):
LLM = LLM if LLM else Ollama()
chunked_text = split_text_into_chunks(text)
@@ -703,12 +703,12 @@ async def summarize_text(text: str, instruction: str = SUMMARY_INSTRUCT, length_
total_words_count = sum(len(chunk.split()) for chunk in chunked_text)
L.DEBUG(f"Total words count: {total_words_count}")
- total_tokens_count = max(1, int(total_words_count * SUMMARY_TPW))
+ total_tokens_count = max(1, int(total_words_count * LLM.tpw))
L.DEBUG(f"Total tokens count: {total_tokens_count}")
total_summary_length = length_override if length_override else total_tokens_count // length_quotient
L.DEBUG(f"Total summary length: {total_summary_length}")
- corrected_total_summary_length = min(total_summary_length, SUMMARY_TOKEN_LIMIT)
+ corrected_total_summary_length = min(total_summary_length, LLM.summary.max_tokens)
L.DEBUG(f"Corrected total summary length: {corrected_total_summary_length}")
summaries = await asyncio.gather(*[
@@ -738,11 +738,11 @@ async def process_chunk(instruction: str, text: str, part: int, total_parts: int
LLM = LLM if LLM else Ollama()
words_count = len(text.split())
- tokens_count = max(1, int(words_count * SUMMARY_TPW))
+ tokens_count = max(1, int(words_count * LLM.tpw))
- summary_length_ratio = length_ratio if length_ratio else SUMMARY_LENGTH_RATIO
- max_tokens = min(tokens_count // summary_length_ratio, SUMMARY_CHUNK_SIZE)
- max_tokens = max(max_tokens, SUMMARY_MIN_LENGTH)
+ summary_length_ratio = length_ratio if length_ratio else LLM.summary.length_ratio
+ max_tokens = min(tokens_count // summary_length_ratio, LLM.summary.chunk_size)
+ max_tokens = max(max_tokens, LLM.summary.min_length)
L.DEBUG(f"Processing part {part} of {total_parts}: Words: {words_count}, Estimated tokens: {tokens_count}, Max output tokens: {max_tokens}")
@@ -753,7 +753,7 @@ async def process_chunk(instruction: str, text: str, part: int, total_parts: int
L.DEBUG(f"Starting LLM.generate for part {part} of {total_parts}")
response = await LLM.generate(
- model=SUMMARY_MODEL,
+ model=LLM.summary.model,
prompt=prompt,
stream=False,
options={'num_predict': max_tokens, 'temperature': 0.5}
diff --git a/sijapi/routers/tts.py b/sijapi/routers/tts.py
index 2972607..e1141d4 100644
--- a/sijapi/routers/tts.py
+++ b/sijapi/routers/tts.py
@@ -12,7 +12,7 @@ import asyncio
from pydantic import BaseModel
from typing import Optional, Union, List
from pydub import AudioSegment
-from TTS.api import TTS
+from TTS.api import TTS as XTTSv2
from pathlib import Path
from datetime import datetime as dt_datetime
from time import time
@@ -25,7 +25,7 @@ import tempfile
import random
import re
import os
-from sijapi import L, DEFAULT_VOICE, TTS_SEGMENTS_DIR, VOICE_DIR, PODCAST_DIR, TTS_OUTPUT_DIR, ELEVENLABS_API_KEY
+from sijapi import L, Dir, API, TTS
from sijapi.utilities import sanitize_filename
@@ -39,14 +39,14 @@ MODEL_NAME = "tts_models/multilingual/multi-dataset/xtts_v2"
@tts.get("/tts/local_voices", response_model=List[str])
async def list_wav_files():
- wav_files = [file.split('.')[0] for file in os.listdir(VOICE_DIR) if file.endswith(".wav")]
+ wav_files = [file.split('.')[0] for file in os.listdir(Dir.data.tts.voices) if file.endswith(".wav")]
return wav_files
@tts.get("/tts/elevenlabs_voices")
async def list_11l_voices():
formatted_list = ""
url = "https://api.elevenlabs.io/v1/voices"
- headers = {"xi-api-key": ELEVENLABS_API_KEY}
+ headers = {"xi-api-key": TTS.elevenlabs.api_key}
async with httpx.AsyncClient() as client:
try:
response = await client.get(url, headers=headers)
@@ -71,10 +71,10 @@ async def select_voice(voice_name: str) -> str:
# Case Insensitive comparison
voice_name_lower = voice_name.lower()
L.DEBUG(f"Looking for {voice_name_lower}")
- for item in VOICE_DIR.iterdir():
+ for item in Dir.data.tts.voices.iterdir():
L.DEBUG(f"Checking {item.name.lower()}")
if item.name.lower() == f"{voice_name_lower}.wav":
- L.DEBUG(f"select_voice received query to use voice: {voice_name}. Found {item} inside {VOICE_DIR}.")
+ L.DEBUG(f"select_voice received query to use voice: {voice_name}. Found {item} inside {Dir.data.tts.voices}.")
return str(item)
L.ERR(f"Voice file not found")
@@ -131,7 +131,7 @@ async def generate_speech(
title: str = None,
output_dir = None
) -> str:
- output_dir = Path(output_dir) if output_dir else TTS_OUTPUT_DIR
+ output_dir = Path(output_dir) if output_dir else TTS.data.tts.outputs
if not output_dir.exists():
output_dir.mkdir(parents=True)
@@ -149,7 +149,7 @@ async def generate_speech(
# raise HTTPException(status_code=400, detail="Invalid model specified")
if podcast == True:
- podcast_path = Path(PODCAST_DIR) / audio_file_path.name
+ podcast_path = TTS.podcast_dir / audio_file_path.name
L.DEBUG(f"Podcast path: {podcast_path}")
shutil.copy(str(audio_file_path), str(podcast_path))
bg_tasks.add_task(os.remove, str(audio_file_path))
@@ -196,7 +196,7 @@ async def determine_voice_id(voice_name: str) -> str:
L.DEBUG(f"Requested voice not among the hardcoded options.. checking with 11L next.")
url = "https://api.elevenlabs.io/v1/voices"
- headers = {"xi-api-key": ELEVENLABS_API_KEY}
+ headers = {"xi-api-key": TTS.elevenlabs.api_key}
async with httpx.AsyncClient() as client:
try:
response = await client.get(url, headers=headers)
@@ -222,10 +222,10 @@ async def elevenlabs_tts(model: str, input_text: str, voice: str, title: str = N
"text": input_text,
"model_id": model
}
- headers = {"Content-Type": "application/json", "xi-api-key": ELEVENLABS_API_KEY}
+ headers = {"Content-Type": "application/json", "xi-api-key": TTS.elevenlabs.api_key}
async with httpx.AsyncClient(timeout=httpx.Timeout(300.0)) as client: # 5 minutes timeout
response = await client.post(url, json=payload, headers=headers)
- output_dir = output_dir if output_dir else TTS_OUTPUT_DIR
+ output_dir = output_dir if output_dir else TTS.podcast_dir
title = title if title else dt_datetime.now().strftime("%Y%m%d%H%M%S")
filename = f"{sanitize_filename(title)}.mp3"
file_path = Path(output_dir) / filename
@@ -236,9 +236,6 @@ async def elevenlabs_tts(model: str, input_text: str, voice: str, title: str = N
else:
raise HTTPException(status_code=response.status_code, detail="Error from ElevenLabs API")
-
-
-
async def get_text_content(text: Optional[str], file: Optional[UploadFile]) -> str:
if file:
return (await file.read()).decode("utf-8").strip()
@@ -247,20 +244,17 @@ async def get_text_content(text: Optional[str], file: Optional[UploadFile]) -> s
else:
raise HTTPException(status_code=400, detail="No text provided")
-
-
async def get_voice_file_path(voice: str = None, voice_file: UploadFile = None) -> str:
if voice:
L.DEBUG(f"Looking for voice: {voice}")
- selected_voice = await select_voice(voice)
+ selected_voice = await select_voice(voice)
return selected_voice
elif voice_file and isinstance(voice_file, UploadFile):
- VOICE_DIR.mkdir(exist_ok=True)
-
+ Dir.data.tts.voices.mkdir(exist_ok=True)
content = await voice_file.read()
checksum = hashlib.md5(content).hexdigest()
- existing_file = VOICE_DIR / voice_file.filename
+ existing_file = Dir.data.tts.voices / voice_file.filename
if existing_file.is_file():
with open(existing_file, 'rb') as f:
existing_checksum = hashlib.md5(f.read()).hexdigest()
@@ -272,7 +266,7 @@ async def get_voice_file_path(voice: str = None, voice_file: UploadFile = None)
counter = 1
new_file = existing_file
while new_file.is_file():
- new_file = VOICE_DIR / f"{base_name}{counter:02}.wav"
+ new_file = Dir.data.tts.voices / f"{base_name}{counter:02}.wav"
counter += 1
with open(new_file, 'wb') as f:
@@ -280,8 +274,8 @@ async def get_voice_file_path(voice: str = None, voice_file: UploadFile = None)
return str(new_file)
else:
- L.DEBUG(f"{dt_datetime.now().strftime('%Y%m%d%H%M%S')}: No voice specified or file provided, using default voice: {DEFAULT_VOICE}")
- selected_voice = await select_voice(DEFAULT_VOICE)
+ L.DEBUG(f"{dt_datetime.now().strftime('%Y%m%d%H%M%S')}: No voice specified or file provided, using default voice: {TTS.xtts.voice}")
+ selected_voice = await select_voice(TTS.xtts.voice)
return selected_voice
@@ -302,7 +296,7 @@ async def local_tts(
datetime_str = dt_datetime.now().strftime("%Y%m%d%H%M%S")
title = sanitize_filename(title) if title else "Audio"
filename = f"{datetime_str}_{title}.wav"
- file_path = TTS_OUTPUT_DIR / filename
+ file_path = Dir.data.tts.outputs / filename
# Ensure the parent directory exists
file_path.parent.mkdir(parents=True, exist_ok=True)
@@ -310,14 +304,14 @@ async def local_tts(
voice_file_path = await get_voice_file_path(voice, voice_file)
# Initialize TTS model in a separate thread
- XTTS = await asyncio.to_thread(TTS, model_name=MODEL_NAME)
+ XTTS = await asyncio.to_thread(XTTSv2, model_name=MODEL_NAME)
await asyncio.to_thread(XTTS.to, DEVICE)
segments = split_text(text_content)
combined_audio = AudioSegment.silent(duration=0)
for i, segment in enumerate(segments):
- segment_file_path = TTS_SEGMENTS_DIR / f"segment_{i}.wav"
+ segment_file_path = Dir.data.tts.segments / f"segment_{i}.wav"
L.DEBUG(f"Segment file path: {segment_file_path}")
# Run TTS in a separate thread
@@ -340,7 +334,7 @@ async def local_tts(
# Export the combined audio in a separate thread
if podcast:
- podcast_file_path = Path(PODCAST_DIR) / file_path.name
+ podcast_file_path = Path(TTS.podcast_dir) / file_path.name
await asyncio.to_thread(combined_audio.export, podcast_file_path, format="wav")
await asyncio.to_thread(combined_audio.export, file_path, format="wav")
@@ -368,7 +362,7 @@ async def stream_tts(text_content: str, speed: float, voice: str, voice_file) ->
async def generate_tts(text: str, speed: float, voice_file_path: str) -> str:
output_dir = tempfile.mktemp(suffix=".wav", dir=tempfile.gettempdir())
- XTTS = TTS(model_name=MODEL_NAME).to(DEVICE)
+ XTTS = XTTSv2(model_name=MODEL_NAME).to(DEVICE)
XTTS.tts_to_file(text=text, speed=speed, file_path=output_dir, speaker_wav=[voice_file_path], language="en")
return output_dir
@@ -381,7 +375,7 @@ async def get_audio_stream(model: str, input_text: str, voice: str):
"text": input_text,
"model_id": "eleven_turbo_v2"
}
- headers = {"Content-Type": "application/json", "xi-api-key": ELEVENLABS_API_KEY}
+ headers = {"Content-Type": "application/json", "xi-api-key": TTS.elevenlabs.api_key}
response = requests.post(url, json=payload, headers=headers)
if response.status_code == 200:
@@ -434,7 +428,7 @@ def copy_to_podcast_dir(file_path):
file_name = Path(file_path).name
# Construct the destination path in the PODCAST_DIR
- destination_path = Path(PODCAST_DIR) / file_name
+ destination_path = TTS.podcast_dir / file_name
# Copy the file to the PODCAST_DIR
shutil.copy(file_path, destination_path)