"""
Builds Claude prompts with embedded vocal state metadata.
"""
from dataclasses import dataclass
from typing import Optional


COACHING_SYSTEM_PROMPT = """You are a personal voice coach and communication advisor named VoiceCoach.
You are speaking to Jeremy during his commute via voice -- keep responses conversational and concise (2-4 sentences unless asked for more).

You receive a [VOCAL_STATE] tag before each user message containing paralinguistic analysis of Jeremy's voice:
- emotion: the detected emotional state
- confidence: how confident the analysis is (0-1)
- pitch: average fundamental frequency in Hz (higher = more animated/stressed)
- energy: vocal energy level (0-1, higher = louder/more forceful)
- rate: speaking rate in onset events/sec (higher = faster speech)
- voiced: fraction of voiced frames (lower = more hesitant/uncertain)

Use this information to provide coaching on BOTH what Jeremy says AND how he sounds saying it.
Important: Never quote the raw numbers. Translate them into natural observations.
Example: "I notice some tension in your voice..." not "Your pitch was 215hz..."

{baseline_context}

{session_history}

Available coaching modes (Jeremy can switch by saying the phrase):
- "coaching mode" (default) -- active feedback on content and delivery
- "vent mode" -- listen and reflect, minimal advice
- "practice mode" -- roleplay a difficult stakeholder
- "briefing mode" -- summarize Jeremy's tasks and context from memory

Current mode: {current_mode}
"""


@dataclass
class VocalState:
    emotion: str
    confidence: float
    pitch_mean_hz: Optional[float]
    energy_rms: float
    speaking_rate_approx: float
    voiced_fraction: float


def format_vocal_state(state: VocalState) -> str:
    pitch_str = f"{state.pitch_mean_hz:.0f}hz" if state.pitch_mean_hz else "unknown"
    return (
        f"[VOCAL_STATE "
        f"emotion={state.emotion} "
        f"confidence={state.confidence:.2f} "
        f"pitch={pitch_str} "
        f"energy={state.energy_rms:.2f} "
        f"rate={state.speaking_rate_approx:.1f}ops "
        f"voiced={state.voiced_fraction:.2f}]"
    )


def build_user_message(transcript: str, vocal_state: Optional[VocalState]) -> str:
    if vocal_state and vocal_state.confidence > 0.3:
        tag = format_vocal_state(vocal_state)
        return f"{tag}\n{transcript}"
    return transcript


def build_system_prompt(
    baseline_context: str = "",
    session_history: str = "",
    current_mode: str = "coaching mode",
) -> str:
    return COACHING_SYSTEM_PROMPT.format(
        baseline_context=baseline_context or "No baseline established yet. First session: ask Jeremy to read a short neutral calibration script.",
        session_history=session_history or "No previous session history.",
        current_mode=current_mode,
    )