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ui/sidebar.py
──────────────────────────────────────────────────────────────────────────────
VoiceVerse Pro — Configuration Sidebar
"""
from __future__ import annotations
import os
import streamlit as st
from modules.llm_backbone import SUPPORTED_MODELS
from modules.tts_engine import TTSBackend
from ui.state import SidebarConfig, OutputMode
def render(current_stage: int) -> SidebarConfig:
with st.sidebar:
st.markdown("### ⚙️ Configuration")
st.divider()
# ── Auth ──────────────────────────────────────────────────────────────
st.markdown("**🔑 Hugging Face API Token**")
hf_token = st.text_input(
"HF Token",
value=os.getenv("HUGGINGFACEHUB_API_TOKEN", ""),
type="password",
label_visibility="collapsed",
placeholder="hf_…",
)
if hf_token:
os.environ["HUGGINGFACEHUB_API_TOKEN"] = hf_token
st.divider()
# ── Output Mode ───────────────────────────────────────────────────────
st.markdown("**🎭 Output Mode**")
# Read current value from session state (set by main-area toggle)
current_mode = st.session_state.get("output_mode", "Audio Transcript")
mode_options = [m.value for m in OutputMode]
mode_index = mode_options.index(current_mode) if current_mode in mode_options else 0
mode_label = st.radio(
"Output Mode",
options=mode_options,
index=mode_index,
label_visibility="collapsed",
help=(
"Also controllable via the main toggle above the pipeline. "
"Both controls are in sync."
),
)
# Write back to session state so main-area toggle reflects sidebar change
st.session_state["output_mode"] = mode_label
output_mode = OutputMode(mode_label)
st.divider()
# ── RAG ───────────────────────────────────────────────────────────────
st.markdown("**🔍 RAG Parameters**")
top_k = st.slider("Top-K Chunks", 1, 8, 4)
chunk_size = st.slider("Chunk Size", 400, 2000, 1000, step=100)
chunk_overlap = st.slider("Chunk Overlap", 0, 300, 100, step=50)
st.divider()
# ── LLM ───────────────────────────────────────────────────────────────
st.markdown("**🧠 LLM Settings**")
model_id = st.selectbox("Model", options=SUPPORTED_MODELS, index=0)
temperature = st.slider("Temperature", 0.1, 1.2, 0.65, step=0.05)
max_tokens = st.slider("Max New Tokens", 256, 2048, 1024, step=128)
target_words = st.slider("Target Script Words", 100, 800, 400, step=50)
st.divider()
# ── TTS ───────────────────────────────────────────────────────────────
st.markdown("**🔊 TTS Backend**")
tts_label = st.selectbox(
"TTS Engine",
options=[b.value for b in TTSBackend],
index=0,
label_visibility="collapsed",
)
tts_backend = TTSBackend(tts_label)
speaker_id = 7306
female_speaker_id = 1580
male_speaker_id = 7306
if tts_backend == TTSBackend.SPEECHT5:
if output_mode == OutputMode.TRANSCRIPT:
speaker_id = st.slider(
"Speaker ID (xvector)", 0, 7500, 7306, step=100,
help="CMU Arctic speaker index for the narrator voice.",
)
else:
st.markdown("*Podcast voices (CMU Arctic xvectors):*")
female_speaker_id = st.slider(
"🎙️ HOST — Female Voice ID", 0, 7500, 1580, step=100,
help="Speaker embedding for the female host.",
)
male_speaker_id = st.slider(
"🎙️ GUEST — Male Voice ID", 0, 7500, 7306, step=100,
help="Speaker embedding for the male guest.",
)
st.divider()
_stage_icons = ["⭕", "🔵", "🟡", "🟠", "🟢"]
st.markdown(f"**Pipeline:** {_stage_icons[current_stage]} Stage {current_stage}/4")
st.markdown(
"<small style='color:#555'>VoiceVerse Pro · 2026 Stable</small>",
unsafe_allow_html=True,
)
return SidebarConfig(
hf_token=hf_token,
output_mode=output_mode,
top_k=top_k,
chunk_size=chunk_size,
chunk_overlap=chunk_overlap,
model_id=model_id,
temperature=temperature,
max_tokens=max_tokens,
target_words=target_words,
tts_backend=tts_backend,
speaker_id=speaker_id,
female_speaker_id=female_speaker_id,
male_speaker_id=male_speaker_id,
) |