diff --git a/.gitignore b/.gitignore
index af08bc6..351aee1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -54,6 +54,7 @@ examples/phoneme_examples/output/example_3.wav
 Kokoro-82M/
 ui/data/
 EXTERNAL_UV_DOCUMENTATION*
+app
 
 # Docker
 Dockerfile*
diff --git a/api/src/builds/kokoro.py b/api/src/builds/kokoro.py
deleted file mode 100644
index 4b6ff0c..0000000
--- a/api/src/builds/kokoro.py
+++ /dev/null
@@ -1,151 +0,0 @@
-import re
-
-import phonemizer
-import torch
-
-
-def split_num(num):
-    num = num.group()
-    if '.' in num:
-        return num
-    elif ':' in num:
-        h, m = [int(n) for n in num.split(':')]
-        if m == 0:
-            return f"{h} o'clock"
-        elif m < 10:
-            return f'{h} oh {m}'
-        return f'{h} {m}'
-    year = int(num[:4])
-    if year < 1100 or year % 1000 < 10:
-        return num
-    left, right = num[:2], int(num[2:4])
-    s = 's' if num.endswith('s') else ''
-    if 100 <= year % 1000 <= 999:
-        if right == 0:
-            return f'{left} hundred{s}'
-        elif right < 10:
-            return f'{left} oh {right}{s}'
-    return f'{left} {right}{s}'
-
-def flip_money(m):
-    m = m.group()
-    bill = 'dollar' if m[0] == '$' else 'pound'
-    if m[-1].isalpha():
-        return f'{m[1:]} {bill}s'
-    elif '.' not in m:
-        s = '' if m[1:] == '1' else 's'
-        return f'{m[1:]} {bill}{s}'
-    b, c = m[1:].split('.')
-    s = '' if b == '1' else 's'
-    c = int(c.ljust(2, '0'))
-    coins = f"cent{'' if c == 1 else 's'}" if m[0] == '$' else ('penny' if c == 1 else 'pence')
-    return f'{b} {bill}{s} and {c} {coins}'
-
-def point_num(num):
-    a, b = num.group().split('.')
-    return ' point '.join([a, ' '.join(b)])
-
-def normalize_text(text):
-    text = text.replace(chr(8216), "'").replace(chr(8217), "'")
-    text = text.replace('«', chr(8220)).replace('»', chr(8221))
-    text = text.replace(chr(8220), '"').replace(chr(8221), '"')
-    text = text.replace('(', '«').replace(')', '»')
-    for a, b in zip('、。！，：；？', ',.!,:;?'):
-        text = text.replace(a, b+' ')
-    text = re.sub(r'[^\S \n]', ' ', text)
-    text = re.sub(r'  +', ' ', text)
-    text = re.sub(r'(?<=\n) +(?=\n)', '', text)
-    text = re.sub(r'\bD[Rr]\.(?= [A-Z])', 'Doctor', text)
-    text = re.sub(r'\b(?:Mr\.|MR\.(?= [A-Z]))', 'Mister', text)
-    text = re.sub(r'\b(?:Ms\.|MS\.(?= [A-Z]))', 'Miss', text)
-    text = re.sub(r'\b(?:Mrs\.|MRS\.(?= [A-Z]))', 'Mrs', text)
-    text = re.sub(r'\betc\.(?! [A-Z])', 'etc', text)
-    text = re.sub(r'(?i)\b(y)eah?\b', r"\1e'a", text)
-    text = re.sub(r'\d*\.\d+|\b\d{4}s?\b|(?<!:)\b(?:[1-9]|1[0-2]):[0-5]\d\b(?!:)', split_num, text)
-    text = re.sub(r'(?<=\d),(?=\d)', '', text)
-    text = re.sub(r'(?i)[$£]\d+(?:\.\d+)?(?: hundred| thousand| (?:[bm]|tr)illion)*\b|[$£]\d+\.\d\d?\b', flip_money, text)
-    text = re.sub(r'\d*\.\d+', point_num, text)
-    text = re.sub(r'(?<=\d)-(?=\d)', ' to ', text)
-    text = re.sub(r'(?<=\d)S', ' S', text)
-    text = re.sub(r"(?<=[BCDFGHJ-NP-TV-Z])'?s\b", "'S", text)
-    text = re.sub(r"(?<=X')S\b", 's', text)
-    text = re.sub(r'(?:[A-Za-z]\.){2,} [a-z]', lambda m: m.group().replace('.', '-'), text)
-    text = re.sub(r'(?i)(?<=[A-Z])\.(?=[A-Z])', '-', text)
-    return text.strip()
-
-def get_vocab():
-    _pad = "$"
-    _punctuation = ';:,.!?¡¿—…"«»“” '
-    _letters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
-    _letters_ipa = "ɑɐɒæɓʙβɔɕçɗɖðʤəɘɚɛɜɝɞɟʄɡɠɢʛɦɧħɥʜɨɪʝɭɬɫɮʟɱɯɰŋɳɲɴøɵɸθœɶʘɹɺɾɻʀʁɽʂʃʈʧʉʊʋⱱʌɣɤʍχʎʏʑʐʒʔʡʕʢǀǁǂǃˈˌːˑʼʴʰʱʲʷˠˤ˞↓↑→↗↘'̩'ᵻ"
-    symbols = [_pad] + list(_punctuation) + list(_letters) + list(_letters_ipa)
-    dicts = {}
-    for i in range(len((symbols))):
-        dicts[symbols[i]] = i
-    return dicts
-
-VOCAB = get_vocab()
-def tokenize(ps):
-    return [i for i in map(VOCAB.get, ps) if i is not None]
-
-phonemizers = dict(
-    a=phonemizer.backend.EspeakBackend(language='en-us', preserve_punctuation=True, with_stress=True),
-    b=phonemizer.backend.EspeakBackend(language='en-gb', preserve_punctuation=True, with_stress=True),
-)
-def phonemize(text, lang, norm=True):
-    if norm:
-        text = normalize_text(text)
-    ps = phonemizers[lang].phonemize([text])
-    ps = ps[0] if ps else ''
-    # https://en.wiktionary.org/wiki/kokoro#English
-    ps = ps.replace('kəkˈoːɹoʊ', 'kˈoʊkəɹoʊ').replace('kəkˈɔːɹəʊ', 'kˈəʊkəɹəʊ')
-    ps = ps.replace('ʲ', 'j').replace('r', 'ɹ').replace('x', 'k').replace('ɬ', 'l')
-    ps = re.sub(r'(?<=[a-zɹː])(?=hˈʌndɹɪd)', ' ', ps)
-    ps = re.sub(r' z(?=[;:,.!?¡¿—…"«»“” ]|$)', 'z', ps)
-    if lang == 'a':
-        ps = re.sub(r'(?<=nˈaɪn)ti(?!ː)', 'di', ps)
-    ps = ''.join(filter(lambda p: p in VOCAB, ps))
-    return ps.strip()
-
-def length_to_mask(lengths):
-    mask = torch.arange(lengths.max()).unsqueeze(0).expand(lengths.shape[0], -1).type_as(lengths)
-    mask = torch.gt(mask+1, lengths.unsqueeze(1))
-    return mask
-
-@torch.no_grad()
-def forward(model, tokens, ref_s, speed):
-    device = ref_s.device
-    tokens = torch.LongTensor([[0, *tokens, 0]]).to(device)
-    input_lengths = torch.LongTensor([tokens.shape[-1]]).to(device)
-    text_mask = length_to_mask(input_lengths).to(device)
-    bert_dur = model.bert(tokens, attention_mask=(~text_mask).int())
-    d_en = model.bert_encoder(bert_dur).transpose(-1, -2)
-    s = ref_s[:, 128:]
-    d = model.predictor.text_encoder(d_en, s, input_lengths, text_mask)
-    x, _ = model.predictor.lstm(d)
-    duration = model.predictor.duration_proj(x)
-    duration = torch.sigmoid(duration).sum(axis=-1) / speed
-    pred_dur = torch.round(duration).clamp(min=1).long()
-    pred_aln_trg = torch.zeros(input_lengths, pred_dur.sum().item())
-    c_frame = 0
-    for i in range(pred_aln_trg.size(0)):
-        pred_aln_trg[i, c_frame:c_frame + pred_dur[0,i].item()] = 1
-        c_frame += pred_dur[0,i].item()
-    en = d.transpose(-1, -2) @ pred_aln_trg.unsqueeze(0).to(device)
-    F0_pred, N_pred = model.predictor.F0Ntrain(en, s)
-    t_en = model.text_encoder(tokens, input_lengths, text_mask)
-    asr = t_en @ pred_aln_trg.unsqueeze(0).to(device)
-    return model.decoder(asr, F0_pred, N_pred, ref_s[:, :128]).squeeze().cpu().numpy()
-
-def generate(model, text, voicepack, lang='a', speed=1, ps=None):
-    ps = ps or phonemize(text, lang)
-    tokens = tokenize(ps)
-    if not tokens:
-        return None
-    elif len(tokens) > 510:
-        tokens = tokens[:510]
-        print('Truncated to 510 tokens')
-    ref_s = voicepack[len(tokens)]
-    out = forward(model, tokens, ref_s, speed)
-    ps = ''.join(next(k for k, v in VOCAB.items() if i == v) for i in tokens)
-    return out, ps
diff --git a/api/src/core/kokoro.py b/api/src/core/kokoro.py
deleted file mode 100644
index 8b65b9b..0000000
--- a/api/src/core/kokoro.py
+++ /dev/null
@@ -1,185 +0,0 @@
-import re
-
-import phonemizer
-import torch
-
-
-def split_num(num):
-    num = num.group()
-    if "." in num:
-        return num
-    elif ":" in num:
-        h, m = [int(n) for n in num.split(":")]
-        if m == 0:
-            return f"{h} o'clock"
-        elif m < 10:
-            return f"{h} oh {m}"
-        return f"{h} {m}"
-    year = int(num[:4])
-    if year < 1100 or year % 1000 < 10:
-        return num
-    left, right = num[:2], int(num[2:4])
-    s = "s" if num.endswith("s") else ""
-    if 100 <= year % 1000 <= 999:
-        if right == 0:
-            return f"{left} hundred{s}"
-        elif right < 10:
-            return f"{left} oh {right}{s}"
-    return f"{left} {right}{s}"
-
-
-def flip_money(m):
-    m = m.group()
-    bill = "dollar" if m[0] == "$" else "pound"
-    if m[-1].isalpha():
-        return f"{m[1:]} {bill}s"
-    elif "." not in m:
-        s = "" if m[1:] == "1" else "s"
-        return f"{m[1:]} {bill}{s}"
-    b, c = m[1:].split(".")
-    s = "" if b == "1" else "s"
-    c = int(c.ljust(2, "0"))
-    coins = (
-        f"cent{'' if c == 1 else 's'}"
-        if m[0] == "$"
-        else ("penny" if c == 1 else "pence")
-    )
-    return f"{b} {bill}{s} and {c} {coins}"
-
-
-def point_num(num):
-    a, b = num.group().split(".")
-    return " point ".join([a, " ".join(b)])
-
-
-def normalize_text(text):
-    text = text.replace(chr(8216), "'").replace(chr(8217), "'")
-    text = text.replace("«", chr(8220)).replace("»", chr(8221))
-    text = text.replace(chr(8220), '"').replace(chr(8221), '"')
-    text = text.replace("(", "«").replace(")", "»")
-    for a, b in zip("、。！，：；？", ",.!,:;?"):
-        text = text.replace(a, b + " ")
-    text = re.sub(r"[^\S \n]", " ", text)
-    text = re.sub(r"  +", " ", text)
-    text = re.sub(r"(?<=\n) +(?=\n)", "", text)
-    text = re.sub(r"\bD[Rr]\.(?= [A-Z])", "Doctor", text)
-    text = re.sub(r"\b(?:Mr\.|MR\.(?= [A-Z]))", "Mister", text)
-    text = re.sub(r"\b(?:Ms\.|MS\.(?= [A-Z]))", "Miss", text)
-    text = re.sub(r"\b(?:Mrs\.|MRS\.(?= [A-Z]))", "Mrs", text)
-    text = re.sub(r"\betc\.(?! [A-Z])", "etc", text)
-    text = re.sub(r"(?i)\b(y)eah?\b", r"\1e'a", text)
-    text = re.sub(
-        r"\d*\.\d+|\b\d{4}s?\b|(?<!:)\b(?:[1-9]|1[0-2]):[0-5]\d\b(?!:)", split_num, text
-    )
-    text = re.sub(r"(?<=\d),(?=\d)", "", text)
-    text = re.sub(
-        r"(?i)[$£]\d+(?:\.\d+)?(?: hundred| thousand| (?:[bm]|tr)illion)*\b|[$£]\d+\.\d\d?\b",
-        flip_money,
-        text,
-    )
-    text = re.sub(r"\d*\.\d+", point_num, text)
-    text = re.sub(r"(?<=\d)-(?=\d)", " to ", text)
-    text = re.sub(r"(?<=\d)S", " S", text)
-    text = re.sub(r"(?<=[BCDFGHJ-NP-TV-Z])'?s\b", "'S", text)
-    text = re.sub(r"(?<=X')S\b", "s", text)
-    text = re.sub(
-        r"(?:[A-Za-z]\.){2,} [a-z]", lambda m: m.group().replace(".", "-"), text
-    )
-    text = re.sub(r"(?i)(?<=[A-Z])\.(?=[A-Z])", "-", text)
-    return text.strip()
-
-
-def get_vocab():
-    _pad = "$"
-    _punctuation = ';:,.!?¡¿—…"«»“” '
-    _letters = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"
-    _letters_ipa = "ɑɐɒæɓʙβɔɕçɗɖðʤəɘɚɛɜɝɞɟʄɡɠɢʛɦɧħɥʜɨɪʝɭɬɫɮʟɱɯɰŋɳɲɴøɵɸθœɶʘɹɺɾɻʀʁɽʂʃʈʧʉʊʋⱱʌɣɤʍχʎʏʑʐʒʔʡʕʢǀǁǂǃˈˌːˑʼʴʰʱʲʷˠˤ˞↓↑→↗↘'̩'ᵻ"
-    symbols = [_pad] + list(_punctuation) + list(_letters) + list(_letters_ipa)
-    dicts = {}
-    for i in range(len((symbols))):
-        dicts[symbols[i]] = i
-    return dicts
-
-
-VOCAB = get_vocab()
-
-
-def tokenize(ps):
-    return [i for i in map(VOCAB.get, ps) if i is not None]
-
-
-phonemizers = dict(
-    a=phonemizer.backend.EspeakBackend(
-        language="en-us", preserve_punctuation=True, with_stress=True
-    ),
-    b=phonemizer.backend.EspeakBackend(
-        language="en-gb", preserve_punctuation=True, with_stress=True
-    ),
-)
-
-
-def phonemize(text, lang, norm=True):
-    if norm:
-        text = normalize_text(text)
-    ps = phonemizers[lang].phonemize([text])
-    ps = ps[0] if ps else ""
-    # https://en.wiktionary.org/wiki/kokoro#English
-    ps = ps.replace("kəkˈoːɹoʊ", "kˈoʊkəɹoʊ").replace("kəkˈɔːɹəʊ", "kˈəʊkəɹəʊ")
-    ps = ps.replace("ʲ", "j").replace("r", "ɹ").replace("x", "k").replace("ɬ", "l")
-    ps = re.sub(r"(?<=[a-zɹː])(?=hˈʌndɹɪd)", " ", ps)
-    ps = re.sub(r' z(?=[;:,.!?¡¿—…"«»“” ]|$)', "z", ps)
-    if lang == "a":
-        ps = re.sub(r"(?<=nˈaɪn)ti(?!ː)", "di", ps)
-    ps = "".join(filter(lambda p: p in VOCAB, ps))
-    return ps.strip()
-
-
-def length_to_mask(lengths):
-    mask = (
-        torch.arange(lengths.max())
-        .unsqueeze(0)
-        .expand(lengths.shape[0], -1)
-        .type_as(lengths)
-    )
-    mask = torch.gt(mask + 1, lengths.unsqueeze(1))
-    return mask
-
-
-@torch.no_grad()
-def forward(model, tokens, ref_s, speed):
-    device = ref_s.device
-    tokens = torch.LongTensor([[0, *tokens, 0]]).to(device)
-    input_lengths = torch.LongTensor([tokens.shape[-1]]).to(device)
-    text_mask = length_to_mask(input_lengths).to(device)
-    bert_dur = model.bert(tokens, attention_mask=(~text_mask).int())
-    d_en = model.bert_encoder(bert_dur).transpose(-1, -2)
-    s = ref_s[:, 128:]
-    d = model.predictor.text_encoder(d_en, s, input_lengths, text_mask)
-    x, _ = model.predictor.lstm(d)
-    duration = model.predictor.duration_proj(x)
-    duration = torch.sigmoid(duration).sum(axis=-1) / speed
-    pred_dur = torch.round(duration).clamp(min=1).long()
-    pred_aln_trg = torch.zeros(input_lengths, pred_dur.sum().item())
-    c_frame = 0
-    for i in range(pred_aln_trg.size(0)):
-        pred_aln_trg[i, c_frame : c_frame + pred_dur[0, i].item()] = 1
-        c_frame += pred_dur[0, i].item()
-    en = d.transpose(-1, -2) @ pred_aln_trg.unsqueeze(0).to(device)
-    F0_pred, N_pred = model.predictor.F0Ntrain(en, s)
-    t_en = model.text_encoder(tokens, input_lengths, text_mask)
-    asr = t_en @ pred_aln_trg.unsqueeze(0).to(device)
-    return model.decoder(asr, F0_pred, N_pred, ref_s[:, :128]).squeeze().cpu().numpy()
-
-
-def generate(model, text, voicepack, lang="a", speed=1):
-    ps = phonemize(text, lang)
-    tokens = tokenize(ps)
-    if not tokens:
-        return None
-    elif len(tokens) > 510:
-        tokens = tokens[:510]
-        print("Truncated to 510 tokens")
-    ref_s = voicepack[len(tokens)]
-    out = forward(model, tokens, ref_s, speed)
-    ps = "".join(next(k for k, v in VOCAB.items() if i == v) for i in tokens)
-    return out, ps
diff --git a/pyproject.toml b/pyproject.toml
index 68434e1..7f91bce 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -40,7 +40,7 @@ gpu = [
     "torch==2.5.1+cu121",
 ]
 cpu = [
-    "torch==2.5.1+cpu",
+    "torch==2.5.1",
 ]
 test = [
     "pytest==8.0.0",
diff --git a/ui/lib/config.py b/ui/lib/config.py
index 406cdf0..1e6cfe8 100644
--- a/ui/lib/config.py
+++ b/ui/lib/config.py
@@ -6,10 +6,11 @@ API_PORT = os.getenv("API_PORT", "8880")
 API_URL = f"http://{API_HOST}:{API_PORT}"
 
 # File paths
-INPUTS_DIR = "/app/ui/data/inputs"
-OUTPUTS_DIR = "/app/ui/data/outputs"
+INPUTS_DIR = "app/ui/data/inputs"
+OUTPUTS_DIR = "app/ui/data/outputs"
 
 # Create directories if they don't exist
+
 os.makedirs(INPUTS_DIR, exist_ok=True)
 os.makedirs(OUTPUTS_DIR, exist_ok=True)