feat: OpenAI Realtime API pipeline
Replaced the 3-step sequential pipeline (Whisper STT → DeepSeek LLM → OpenAI TTS) with a single OpenAI Realtime API WebSocket using gpt-4o-mini-realtime-preview. - ~300-800ms latency vs 1-3s - Server VAD for automatic turn detection - Streaming audio chunks during playback - Interruptions: user can speak over Kira mid-response - Honcho memory still injected into session instructions - Frontend captures PCM16 mono 24kHz via AudioContext - Backend relays client ↔ OpenAI Realtime API - Supports both voice (PCM16) and text input
This commit is contained in:
+183
-172
@@ -1,26 +1,21 @@
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"""Kira — AI body double backend
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Real-time speech-to-speech pipeline:
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mic audio → Whisper API → text → DeepSeek LLM → response text → OpenAI TTS → audio
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Honcho memory integration:
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Cross-session user context injected into LLM prompts,
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conversation exchanges stored for continuous learning.
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User preferences (name, scene, outfit, accessory) persisted in peer metadata.
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OpenAI Realtime API pipeline:
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mic audio → [built-in STT → GPT-4o-mini → built-in TTS] → speaker audio
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Single WebSocket, ~300-800ms latency
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"""
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import json
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import base64
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import uuid
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import logging
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import asyncio
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from fastapi import FastAPI, WebSocket, WebSocketDisconnect
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from fastapi.middleware.cors import CORSMiddleware
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from config import settings
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from services.stt import transcribe_audio
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from services.llm import get_kira_response
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from services.tts import synthesize_speech
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from services.realtime import RealtimeRelay
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from services.memory import kira_memory
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logging.basicConfig(level=logging.INFO)
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@@ -36,24 +31,13 @@ app.add_middleware(
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allow_headers=["*"],
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)
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# ─── Base system prompt (static part) ───
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BASE_SYSTEM_PROMPT = (
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"You are Kira, a warm, kind, and encouraging AI body double. "
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"You speak in a friendly, girly-pop tone. You are helping someone with ADHD "
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"stay focused and on task. Keep responses short, supportive, and uplifting. "
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"Check in on them. Remind them to take breaks. Celebrate small wins. "
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"Use occasional emoji but don't overdo it. Never be judgmental. "
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"You remember things about them between conversations."
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)
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@app.on_event("startup")
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async def startup():
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"""Initialize Honcho memory on app startup."""
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if kira_memory.init():
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logger.info("Honcho memory initialized")
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else:
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logger.info("Honcho memory not configured — running without memory")
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logger.info("Honcho memory not configured")
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@app.get("/api/health")
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@@ -62,61 +46,6 @@ async def health():
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return {"status": "ok", "name": "kira", "memory": mem_status}
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def build_system_prompt(user_id: str) -> dict:
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"""Build system prompt with Honcho memory context injected."""
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base = BASE_SYSTEM_PROMPT
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if kira_memory.enabled:
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try:
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kira_memory.ensure_peers(user_id)
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memory_suffix = kira_memory.build_system_prompt_suffix()
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if memory_suffix:
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base += memory_suffix
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except Exception as e:
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logger.warning(f"Failed to build memory context: {e}")
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return {"role": "system", "content": base}
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def handle_identify(msg: dict, session_id: str) -> dict | None:
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"""Handle user identification. Returns user preferences or None."""
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user_id = msg.get("user_id", "").strip()
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if not user_id:
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return {"type": "error", "message": "user_id is required"}
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user_name = msg.get("name", "").strip()
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if user_name:
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kira_memory.set_user_preference(user_id, "name", user_name)
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prefs = kira_memory.get_user_preferences(user_id)
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logger.info(f"[{session_id}] Identified as {user_id} (name={user_name or prefs.get('name', '')})")
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return {
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"type": "identified",
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"user_id": user_id,
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"preferences": prefs,
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}
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def handle_set_preference(msg: dict, session_id: str, user_id: str) -> dict | None:
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"""Handle preference update. Returns success status."""
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if not user_id or user_id == "default-user":
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return {"type": "error", "message": "Must identify first"}
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key = msg.get("key", "").strip()
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value = msg.get("value", "").strip()
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if not key:
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return {"type": "error", "message": "key is required"}
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ok = kira_memory.set_user_preference(user_id, key, value)
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return {
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"type": "preference_saved",
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"key": key,
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"success": ok,
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}
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@app.websocket("/api/ws")
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async def conversation_ws(websocket: WebSocket):
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await websocket.accept()
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@@ -125,8 +54,102 @@ async def conversation_ws(websocket: WebSocket):
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identified = False
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logger.info(f"[{session_id}] WebSocket connected")
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audio_buffer = bytearray()
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conversation_history: list[dict] = []
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# Track conversation for Honcho
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pending_transcripts: list[tuple[str, str]] = []
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# Will be set when Realtime relay is ready
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relay_ready = asyncio.Event()
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relay: RealtimeRelay | None = None
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relay_task: asyncio.Task | None = None
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audio_queue: asyncio.Queue[bytes] = asyncio.Queue()
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text_queue: asyncio.Queue[str] = asyncio.Queue()
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async def on_ready():
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relay_ready.set()
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logger.info(f"[{session_id}] Realtime relay ready")
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async def on_audio_delta(audio_bytes: bytes):
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"""Forward audio chunks from OpenAI to the client."""
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try:
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audio_b64 = base64.b64encode(audio_bytes).decode("utf-8")
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await websocket.send_json({
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"type": "audio",
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"data": audio_b64,
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})
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except Exception:
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pass
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async def on_transcript(text: str):
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"""Store transcripts for Honcho."""
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pending_transcripts.append(("transcript", text))
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role, content = text.split(": ", 1)
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logger.info(f"[{session_id}] {role}: {content}")
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await websocket.send_json({
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"type": "transcript",
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"role": role,
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"text": content,
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})
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async def on_speech_started():
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"""Kira started speaking."""
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await websocket.send_json({"type": "speaking_start"})
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async def on_speech_stopped():
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"""Kira finished speaking."""
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await websocket.send_json({"type": "speaking_end"})
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async def on_interruption():
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"""User interrupted — Kira stops speaking."""
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await websocket.send_json({"type": "interruption"})
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async def on_error(msg: str):
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await websocket.send_json({"type": "error", "message": msg})
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# ── Create and start the Realtime relay ──
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relay = RealtimeRelay(
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on_audio_delta=on_audio_delta,
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on_transcript=on_transcript,
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on_speech_started=on_speech_started,
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on_speech_stopped=on_speech_stopped,
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on_interruption=on_interruption,
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on_error=on_error,
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on_ready=on_ready,
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)
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relay_task = asyncio.create_task(relay.connect())
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# Wait for relay to be ready
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try:
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await asyncio.wait_for(relay_ready.wait(), timeout=15)
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except asyncio.TimeoutError:
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logger.error(f"[{session_id}] Realtime relay failed to connect")
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await websocket.send_json({"type": "error", "message": "Failed to connect to AI"})
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relay_task.cancel()
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return
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# ── Forward audio/text from client to relay ──
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async def forward_audio():
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while relay and relay._connected:
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try:
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pcm16 = await asyncio.wait_for(audio_queue.get(), timeout=1)
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await relay.send_audio(pcm16)
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except asyncio.TimeoutError:
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continue
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except Exception:
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break
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async def forward_text():
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while relay and relay._connected:
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try:
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text = await asyncio.wait_for(text_queue.get(), timeout=1)
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await relay.send_text(text)
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except asyncio.TimeoutError:
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continue
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except Exception:
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break
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fwd_audio_task = asyncio.create_task(forward_audio())
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fwd_text_task = asyncio.create_task(forward_text())
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try:
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while True:
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@@ -134,110 +157,98 @@ async def conversation_ws(websocket: WebSocket):
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msg = json.loads(raw)
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msg_type = msg.get("type", "")
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# ── Identity & Preferences ──
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# ── Identity ──
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if msg_type == "identify":
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response = handle_identify(msg, session_id)
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if response:
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await websocket.send_json(response)
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if response["type"] == "identified":
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user_id = response["user_id"]
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identified = True
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# Set up Honcho for this user
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if kira_memory.enabled:
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try:
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kira_memory.ensure_peers(user_id)
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kira_memory.ensure_session(session_id)
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logger.info(f"[{session_id}] Honcho session ready for {user_id}")
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except Exception as e:
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logger.warning(f"[{session_id}] Honcho setup failed: {e}")
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user_id = msg.get("user_id", "").strip()
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user_name = msg.get("name", "").strip()
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if user_name and user_id:
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kira_memory.set_user_preference(user_id, "name", user_name)
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prefs = kira_memory.get_user_preferences(user_id)
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identified = True
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if kira_memory.enabled:
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kira_memory.ensure_peers(user_id)
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kira_memory.ensure_session(session_id)
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# Inject Honcho context into the Realtime session instructions
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memory_suffix = ""
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if kira_memory.enabled:
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try:
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ctx = kira_memory.build_system_prompt_suffix()
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if ctx:
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memory_suffix = ctx
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except Exception:
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pass
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if relay and relay._connected and memory_suffix:
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await relay._send({
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"type": "session.update",
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"session": {
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"instructions": (
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"You are Kira, a warm, kind, and encouraging AI body double. "
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"Speak in a friendly, girly-pop tone. Help someone with ADHD "
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"stay focused. Keep responses short and supportive. "
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"Check in, remind breaks, celebrate wins. Never judgmental."
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+ memory_suffix
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),
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},
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})
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await websocket.send_json({
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"type": "identified",
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"user_id": user_id,
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"preferences": prefs,
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})
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continue
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# ── Preferences ──
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if msg_type == "set_preference":
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response = handle_set_preference(msg, session_id, user_id)
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if response:
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await websocket.send_json(response)
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key = msg.get("key", "").strip()
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value = msg.get("value", "").strip()
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if key and user_id and user_id != "default-user":
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kira_memory.set_user_preference(user_id, key, value)
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continue
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# ── Conversation ──
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# ── Audio from frontend (PCM16) ──
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if msg_type == "audio":
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audio_b64 = msg.get("data", "")
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if audio_b64:
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pcm16 = base64.b64decode(audio_b64)
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await audio_queue.put(pcm16)
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continue
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system_prompt = build_system_prompt(user_id)
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# ── Text input ──
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if msg_type == "conversation_text":
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text = msg.get("text", "").strip()
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if text:
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await text_queue.put(text)
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# Also store in Honcho immediately
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if kira_memory.enabled and identified:
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kira_memory.store_user_message(text)
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continue
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if msg_type == "audio_chunk":
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chunk = base64.b64decode(msg["data"])
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audio_buffer.extend(chunk)
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elif msg_type == "transcribe":
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if not audio_buffer:
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await websocket.send_json({"type": "error", "message": "No audio data"})
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continue
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logger.info(f"[{session_id}] Transcribing {len(audio_buffer)} bytes...")
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transcript = await transcribe_audio(bytes(audio_buffer))
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audio_buffer.clear()
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if not transcript:
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await websocket.send_json({"type": "error", "message": "Could not transcribe audio"})
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continue
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await websocket.send_json({"type": "transcript", "text": transcript})
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logger.info(f"[{session_id}] User: {transcript}")
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conversation_history.append({"role": "user", "content": transcript})
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messages = [system_prompt] + conversation_history[-10:]
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kira_text = await get_kira_response(messages)
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conversation_history.append({"role": "assistant", "content": kira_text})
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logger.info(f"[{session_id}] Kira: {kira_text}")
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if kira_memory.enabled and identified:
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try:
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kira_memory.store_messages(transcript, kira_text)
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except Exception as e:
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logger.warning(f"[{session_id}] Failed to store messages: {e}")
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await websocket.send_json({"type": "speaking_start", "text": kira_text})
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audio_bytes = await synthesize_speech(kira_text)
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audio_b64 = base64.b64encode(audio_bytes).decode("utf-8")
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await websocket.send_json({"type": "audio", "data": audio_b64, "text": kira_text})
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await websocket.send_json({"type": "speaking_end"})
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elif msg_type == "ping":
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if msg_type == "ping":
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await websocket.send_json({"type": "pong"})
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elif msg_type == "conversation_text":
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user_text = msg.get("text", "").strip()
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if not user_text:
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continue
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logger.info(f"[{session_id}] User (text): {user_text}")
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conversation_history.append({"role": "user", "content": user_text})
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messages = [system_prompt] + conversation_history[-10:]
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kira_text = await get_kira_response(messages)
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conversation_history.append({"role": "assistant", "content": kira_text})
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logger.info(f"[{session_id}] Kira: {kira_text}")
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if kira_memory.enabled and identified:
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try:
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kira_memory.store_messages(user_text, kira_text)
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except Exception as e:
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logger.warning(f"[{session_id}] Failed to store messages: {e}")
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await websocket.send_json({"type": "speaking_start", "text": kira_text})
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audio_bytes = await synthesize_speech(kira_text)
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audio_b64 = base64.b64encode(audio_bytes).decode("utf-8")
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await websocket.send_json({"type": "audio", "data": audio_b64, "text": kira_text})
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await websocket.send_json({"type": "speaking_end"})
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except WebSocketDisconnect:
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logger.info(f"[{session_id}] Disconnected")
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except Exception as e:
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logger.error(f"[{session_id}] Error: {e}")
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try:
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await websocket.send_json({"type": "error", "message": str(e)})
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except Exception:
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pass
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finally:
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# Store pending transcripts in Honcho
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if kira_memory.enabled and identified:
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for _, transcript_text in pending_transcripts:
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if transcript_text.startswith("user: "):
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content = transcript_text[6:]
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kira_memory.store_user_message(content)
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elif transcript_text.startswith("assistant: "):
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content = transcript_text[11:]
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kira_memory.store_kira_message(content)
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fwd_audio_task.cancel()
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fwd_text_task.cancel()
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if relay:
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await relay.disconnect()
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if relay_task:
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relay_task.cancel()
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@@ -7,3 +7,4 @@ pydantic>=2.10.0
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pydantic-settings>=2.7.0
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httpx>=0.28.0
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honcho-ai>=2.1.0
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openai[realtime]>=2.41.0
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@@ -0,0 +1,191 @@
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"""OpenAI Realtime API relay service.
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Manages a WebSocket connection to OpenAI's Realtime API and relays
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audio/text events between the client and OpenAI.
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"""
|
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|
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import json
|
||||
import logging
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from typing import Callable, Awaitable
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from config import settings
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logger = logging.getLogger("kira.realtime")
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|
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# ─── System instructions for Kira's personality ───
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|
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KIRA_INSTRUCTIONS = (
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"You are Kira, a warm, kind, and encouraging AI body double. "
|
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"You speak in a friendly, girly-pop tone. You are helping someone with ADHD "
|
||||
"stay focused and on task. Keep responses short, supportive, and uplifting. "
|
||||
"Check in on them. Remind them to take breaks. Celebrate small wins. "
|
||||
"Use occasional emoji but don't overdo it. Never be judgmental. "
|
||||
"You remember things about them between conversations."
|
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)
|
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|
||||
|
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class RealtimeRelay:
|
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"""Relays audio/text between a client WS and OpenAI Realtime API."""
|
||||
|
||||
def __init__(
|
||||
self,
|
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on_audio_delta: Callable[[bytes], Awaitable[None]],
|
||||
on_transcript: Callable[[str], Awaitable[None]],
|
||||
on_speech_started: Callable[[], Awaitable[None]],
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on_speech_stopped: Callable[[], Awaitable[None]],
|
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on_interruption: Callable[[], Awaitable[None]],
|
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on_error: Callable[[str], Awaitable[None]],
|
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on_ready: Callable[[], Awaitable[None]],
|
||||
):
|
||||
self._on_audio_delta = on_audio_delta
|
||||
self._on_transcript = on_transcript
|
||||
self._on_speech_started = on_speech_started
|
||||
self._on_speech_stopped = on_speech_stopped
|
||||
self._on_interruption = on_interruption
|
||||
self._on_error = on_error
|
||||
self._on_ready = on_ready
|
||||
self._conn = None
|
||||
self._connected = False
|
||||
|
||||
async def connect(self):
|
||||
"""Open a WebSocket to OpenAI Realtime API."""
|
||||
if self._connected:
|
||||
return
|
||||
|
||||
try:
|
||||
from openai import AsyncOpenAI
|
||||
|
||||
client = AsyncOpenAI(api_key=settings.openai_api_key)
|
||||
|
||||
logger.info("Connecting to OpenAI Realtime API...")
|
||||
async with client.beta.realtime.connect(
|
||||
model="gpt-4o-mini-realtime-preview-2025-07-18",
|
||||
) as conn:
|
||||
self._conn = conn
|
||||
self._connected = True
|
||||
logger.info("Connected to OpenAI Realtime API")
|
||||
|
||||
# Configure session
|
||||
await self._send({
|
||||
"type": "session.update",
|
||||
"session": {
|
||||
"instructions": KIRA_INSTRUCTIONS,
|
||||
"voice": "alloy",
|
||||
"input_audio_transcription": {"enabled": True},
|
||||
"turn_detection": {
|
||||
"type": "server_vad",
|
||||
"threshold": 0.5,
|
||||
"prefix_padding_ms": 300,
|
||||
"silence_duration_ms": 600,
|
||||
},
|
||||
},
|
||||
})
|
||||
|
||||
await self._on_ready()
|
||||
|
||||
# Listen for events
|
||||
while self._connected:
|
||||
try:
|
||||
event = await conn.recv()
|
||||
await self._handle_event(event)
|
||||
except Exception as e:
|
||||
if self._connected:
|
||||
logger.warning(f"Realtime recv error: {e}")
|
||||
break
|
||||
|
||||
except ImportError:
|
||||
logger.error("openai[realtime] not installed — run: pip install 'openai[realtime]'")
|
||||
await self._on_error("Missing openai[realtime] dependency")
|
||||
except Exception as e:
|
||||
logger.error(f"Realtime connection error: {e}")
|
||||
await self._on_error(str(e))
|
||||
finally:
|
||||
self._connected = False
|
||||
self._conn = None
|
||||
|
||||
async def _handle_event(self, event):
|
||||
"""Process an event from the OpenAI Realtime API."""
|
||||
event_type = getattr(event, "type", None) or event.get("type", "")
|
||||
|
||||
if event_type == "response.audio.delta":
|
||||
audio_b64 = getattr(event, "delta", None) or event.get("delta", "")
|
||||
if audio_b64:
|
||||
import base64
|
||||
audio_bytes = base64.b64decode(audio_b64)
|
||||
await self._on_audio_delta(audio_bytes)
|
||||
|
||||
elif event_type == "response.audio_buffer.speech_started":
|
||||
await self._on_speech_started()
|
||||
|
||||
elif event_type == "response.audio_buffer.speech_stopped":
|
||||
await self._on_speech_stopped()
|
||||
|
||||
elif event_type == "input_audio_buffer.speech_started":
|
||||
# User started speaking — interrupt Kira
|
||||
await self._on_interruption()
|
||||
|
||||
elif event_type == "conversation.item.created":
|
||||
item = getattr(event, "item", None) or event.get("item", {})
|
||||
role = getattr(item, "role", None) or item.get("role", "")
|
||||
content = getattr(item, "content", None) or item.get("content", [])
|
||||
for part in (content or []):
|
||||
part_type = getattr(part, "type", None) or part.get("type", "")
|
||||
part_text = getattr(part, "text", None) or part.get("text", "")
|
||||
if part_type == "text" and part_text and role == "assistant":
|
||||
await self._on_transcript(f"assistant: {part_text}")
|
||||
part_transcript = getattr(part, "transcript", None) or part.get("transcript", "")
|
||||
if part_type == "transcript" and part_transcript and role == "user":
|
||||
await self._on_transcript(f"user: {part_transcript}")
|
||||
|
||||
elif event_type == "error":
|
||||
err = getattr(event, "error", None) or event.get("error", {})
|
||||
msg = getattr(err, "message", None) or err.get("message", str(event))
|
||||
logger.warning(f"Realtime API error: {msg}")
|
||||
await self._on_error(msg)
|
||||
|
||||
async def send_audio(self, pcm16_bytes: bytes):
|
||||
"""Send PCM16 audio chunk to OpenAI."""
|
||||
if not self._connected or not self._conn:
|
||||
return
|
||||
try:
|
||||
import base64
|
||||
audio_b64 = base64.b64encode(pcm16_bytes).decode("utf-8")
|
||||
await self._send({
|
||||
"type": "input_audio_buffer.append",
|
||||
"audio": audio_b64,
|
||||
})
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to send audio: {e}")
|
||||
|
||||
async def send_text(self, text: str):
|
||||
"""Send a text message to OpenAI and trigger a response."""
|
||||
if not self._connected or not self._conn:
|
||||
return
|
||||
try:
|
||||
await self._send({
|
||||
"type": "conversation.item.create",
|
||||
"item": {
|
||||
"type": "message",
|
||||
"role": "user",
|
||||
"content": [{"type": "input_text", "text": text}],
|
||||
},
|
||||
})
|
||||
await self._send({"type": "response.create"})
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to send text: {e}")
|
||||
|
||||
async def _send(self, data: dict):
|
||||
"""Send a JSON event to the Realtime API."""
|
||||
try:
|
||||
await self._conn.send(data)
|
||||
except Exception as e:
|
||||
logger.warning(f"Realtime send error: {e}")
|
||||
|
||||
async def disconnect(self):
|
||||
"""Close the Realtime connection."""
|
||||
self._connected = False
|
||||
if self._conn:
|
||||
try:
|
||||
await self._conn.close()
|
||||
except Exception:
|
||||
pass
|
||||
self._conn = None
|
||||
Reference in New Issue
Block a user