After-hours calls answered, zero hallucinated answers

You are the AI phone receptionist for {business_name}, a {industry} firm.

Your job is to answer inbound phone calls and help callers with basic business information. You must be professional, warm, and concise.

BUSINESS INFORMATION:
- Business Name: {business_name}
- Address: {address}
- Hours of Operation: Monday through Friday, 9:00 AM to 5:00 PM CST. Closed Saturday and Sunday.
- Services: {services}

RESPONSE RULES:
- Keep answers to 1-2 sentences maximum. Callers are listening, not reading.
- Use a professional, friendly tone appropriate for a CPA firm.
- Only provide information listed above. Do not speculate or make up information.
- If asked about pricing, appointments, or specific tax questions, say: "I'd be happy to help with that. Please call us during business hours, Monday through Friday, 9 AM to 5 PM, and one of our team members can assist you."
- If the caller's question is unclear, politely ask them to repeat it.
- Do not discuss topics unrelated to the business.

import logging
from typing import Optional
import anthropic

logger = logging.getLogger(__name__)

FALLBACK_RESPONSE = (
    "I'm sorry, I'm having trouble right now. "
    "Our office hours are Monday through Friday, 9 AM to 5 PM. "
    "Please call back during business hours for assistance."
)


class ClaudeClient:
    def __init__(self, api_key: str, system_prompt: str):
        self.client = anthropic.AsyncAnthropic(api_key=api_key)
        self.system_prompt = system_prompt

    async def generate_response(
        self,
        user_message: str,
        conversation_history: Optional[list] = None,
    ) -> str:
        messages = list(conversation_history or [])
        messages.append({"role": "user", "content": user_message})

        try:
            response = await self.client.messages.create(
                model="claude-sonnet-4-6",
                max_tokens=256,
                temperature=0.3,
                system=self.system_prompt,
                messages=messages,
            )
            for block in response.content:
                if block.type == "text":
                    return block.text
            return FALLBACK_RESPONSE
        except Exception:
            logger.exception("Claude API error")
            return FALLBACK_RESPONSE

import logging
import hashlib
from pathlib import Path
from typing import Dict, List
from twilio.twiml.voice_response import VoiceResponse, Gather

logger = logging.getLogger(__name__)

AUDIO_DIR = Path("/tmp/sg_cpa_audio")
AUDIO_DIR.mkdir(exist_ok=True)


def save_audio_temp(audio_bytes: bytes, call_sid: str) -> str:
    filename = f"resp_{hashlib.md5(call_sid.encode() + audio_bytes[:16]).hexdigest()[:12]}.mp3"
    path = AUDIO_DIR / filename
    path.write_bytes(audio_bytes)
    return f"/audio/{filename}"


class VoiceHandler:
    def __init__(self, app_base_url: str, claude_client, elevenlabs_client):
        self.app_base_url = app_base_url
        self.claude_client = claude_client
        self.elevenlabs_client = elevenlabs_client
        self.conversations: Dict[str, List[dict]] = {}

    def build_greeting(self) -> VoiceResponse:
        response = VoiceResponse()
        gather = Gather(
            input="speech",
            action="/voice/respond",
            method="POST",
            speech_timeout="5",
            language="en-US",
        )
        gather.say(
            "Thank you for calling SG CPA. How can I help you today?",
            voice="Polly.Joanna",
        )
        response.append(gather)
        response.say(
            "I didn't catch that. Thank you for calling SG CPA. Goodbye.",
            voice="Polly.Joanna",
        )
        return response

    async def handle_speech(self, speech_text: str, call_sid: str) -> VoiceResponse:
        history = self.conversations.get(call_sid, [])

        ai_response = await self.claude_client.generate_response(
            speech_text, conversation_history=history
        )

        history.append({"role": "user", "content": speech_text})
        history.append({"role": "assistant", "content": ai_response})
        self.conversations[call_sid] = history

        response = VoiceResponse()

        audio_bytes = await self.elevenlabs_client.synthesize(ai_response)
        if audio_bytes:
            audio_path = save_audio_temp(audio_bytes, call_sid)
            audio_url = f"{self.app_base_url}{audio_path}"
            gather = Gather(
                input="speech",
                action="/voice/respond",
                method="POST",
                speech_timeout="5",
                language="en-US",
            )
            gather.play(audio_url)
            response.append(gather)
        else:
            logger.warning("ElevenLabs failed, falling back to Twilio TTS")
            gather = Gather(
                input="speech",
                action="/voice/respond",
                method="POST",
                speech_timeout="5",
                language="en-US",
            )
            gather.say(ai_response, voice="Polly.Joanna")
            response.append(gather)

        response.say(
            "Thank you for calling SG CPA. Have a great day. Goodbye.",
            voice="Polly.Joanna",
        )
        return response

    def build_goodbye(self) -> VoiceResponse:
        response = VoiceResponse()
        response.say(
            "Thank you for calling SG CPA. Have a great day. Goodbye.",
            voice="Polly.Joanna",
        )
        response.hangup()
        return response

    def cleanup_call(self, call_sid: str) -> None:
        self.conversations.pop(call_sid, None)