Kc-airobot / app.py
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# app.py - KC Robot AI V4.1 (Full - FPT female TTS)
# Full-feature Flask server:
# - /ask (text) -> HF LLM
# - /tts (text) -> HF TTS (default: NguyenManhTuan/VietnameseTTS_FPT_AI_Female)
# - /stt (audio) -> HF STT (default: openai/whisper-small)
# - /presence (radar event) -> greeting + Telegram notify
# - /display -> OLED lines
# - Web UI for quick test
# - Telegram poller (background thread) to accept /ask, /say, /status
#
# Configuration via environment variables / Secrets in HF Space:
# HF_API_TOKEN (required for HF inference)
# HF_MODEL (optional, default google/flan-t5-large)
# HF_TTS_MODEL (optional, default NguyenManhTuan/VietnameseTTS_FPT_AI_Female)
# HF_STT_MODEL (optional, default openai/whisper-small)
# TELEGRAM_TOKEN (optional)
# TELEGRAM_CHATID (optional)
#
# Keep requirements minimal to improve HF Space stability:
# flask, requests
#
# Important: set tokens in HF Space Settings -> Secrets (do not hardcode)
import os
import io
import time
import json
import uuid
import logging
import threading
from typing import Optional, List, Tuple
from pathlib import Path
import requests
from flask import Flask, request, jsonify, send_file, render_template_string, abort
# ----------------- Config & Logging -----------------
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("kcrobot.v4")
app = Flask(__name__)
# Directory for temporary files (tts audio)
TMP_DIR = Path("/tmp/kcrobot") if os.name != "nt" else Path.cwd() / "tmp_kcrobot"
TMP_DIR.mkdir(parents=True, exist_ok=True)
# Environment / Secrets (set these in HF Space)
HF_API_TOKEN = os.getenv("HF_API_TOKEN", "").strip()
HF_MODEL = os.getenv("HF_MODEL", "google/flan-t5-large").strip()
# Default FPT female Vietnamese TTS
HF_TTS_MODEL = os.getenv("HF_TTS_MODEL", "NguyenManhTuan/VietnameseTTS_FPT_AI_Female").strip()
HF_STT_MODEL = os.getenv("HF_STT_MODEL", "openai/whisper-small").strip()
TELEGRAM_TOKEN = os.getenv("TELEGRAM_TOKEN", "").strip()
TELEGRAM_CHATID = os.getenv("TELEGRAM_CHATID", "").strip()
# Port (HF sets PORT env in runtime)
PORT = int(os.getenv("PORT", os.getenv("SERVER_PORT", 7860)))
if not HF_API_TOKEN:
logger.warning("HF_API_TOKEN is not set — HF inference will fail until you add it in Secrets.")
HF_HEADERS = {"Authorization": f"Bearer {HF_API_TOKEN}"} if HF_API_TOKEN else {}
# ----------------- In-memory buffers -----------------
CONV: List[Tuple[str, str]] = [] # list of (user, bot)
DISPLAY_LINES: List[str] = [] # lines for OLED display
def push_display(line: str, limit: int = 6):
"""Keep last `limit` lines for display."""
global DISPLAY_LINES
DISPLAY_LINES.append(line)
if len(DISPLAY_LINES) > limit:
DISPLAY_LINES = DISPLAY_LINES[-limit:]
# ----------------- Helper: Hugging Face inference -----------------
def hf_post_json(model_id: str, payload: dict, timeout: int = 120):
"""POST JSON to HF inference; return parsed JSON or raise."""
if not HF_API_TOKEN:
raise RuntimeError("HF_API_TOKEN missing (set in Secrets).")
url = f"https://api-inference.huggingface.co/models/{model_id}"
headers = dict(HF_HEADERS)
headers["Content-Type"] = "application/json"
r = requests.post(url, headers=headers, json=payload, timeout=timeout)
if not r.ok:
logger.error("HF POST JSON error %s: %s", r.status_code, r.text[:400])
r.raise_for_status()
try:
return r.json()
except Exception:
return r.text
def hf_post_bytes(model_id: str, data: bytes, content_type: str = "application/octet-stream", timeout: int = 180):
"""POST binary data (audio) to HF inference; return response object or raise."""
if not HF_API_TOKEN:
raise RuntimeError("HF_API_TOKEN missing (set in Secrets).")
url = f"https://api-inference.huggingface.co/models/{model_id}"
headers = dict(HF_HEADERS)
headers["Content-Type"] = content_type
r = requests.post(url, headers=headers, data=data, timeout=timeout)
if not r.ok:
logger.error("HF POST bytes error %s: %s", r.status_code, r.text[:400])
r.raise_for_status()
return r
# ----------------- Text generation (LLM) -----------------
def hf_text_generate(prompt: str, model: Optional[str] = None, max_new_tokens: int = 256, temperature: float = 0.7) -> str:
model = model or HF_MODEL
payload = {
"inputs": prompt,
"parameters": {"max_new_tokens": int(max_new_tokens), "temperature": float(temperature)},
"options": {"wait_for_model": True}
}
out = hf_post_json(model, payload, timeout=120)
# parse common shapes
if isinstance(out, list) and len(out) > 0:
first = out[0]
if isinstance(first, dict) and "generated_text" in first:
return first["generated_text"]
return str(first)
if isinstance(out, dict):
for k in ("generated_text", "text", "summary_text"):
if k in out:
return out[k]
return json.dumps(out)
return str(out)
# ----------------- TTS (Text -> audio bytes) -----------------
def hf_tts_get_audio_bytes(text: str, model: Optional[str] = None) -> bytes:
"""Call HF TTS model and return audio bytes (commonly mp3 or wav)."""
model = model or HF_TTS_MODEL
payload = {"inputs": text}
r = requests.post(f"https://api-inference.huggingface.co/models/{model}", headers={**HF_HEADERS, "Content-Type": "application/json"}, json=payload, timeout=120)
if not r.ok:
logger.error("HF TTS error %s: %s", r.status_code, r.text[:400])
r.raise_for_status()
return r.content
def save_tts_temp(audio_bytes: bytes, ext_hint: str = "mp3") -> str:
"""Save bytes to a temp file under TMP_DIR and return filename."""
fname = f"tts_{int(time.time())}_{uuid.uuid4().hex}.{ext_hint}"
p = TMP_DIR / fname
p.write_bytes(audio_bytes)
return fname
# ----------------- STT (audio bytes -> text) -----------------
def hf_stt_from_bytes(audio_bytes: bytes, model: Optional[str] = None) -> str:
model = model or HF_STT_MODEL
r = hf_post_bytes(model, audio_bytes, content_type="application/octet-stream", timeout=180)
# often returns {"text": "..."}
try:
j = r.json()
if isinstance(j, dict) and "text" in j:
return j["text"]
if isinstance(j, list) and len(j) and isinstance(j[0], dict) and "text" in j[0]:
return j[0]["text"]
return str(j)
except Exception:
return r.text if hasattr(r, "text") else ""
# ----------------- Endpoints for ESP32 / Web -----------------
@app.route("/health", methods=["GET"])
def health():
return jsonify({
"ok": True,
"hf_api_token": bool(HF_API_TOKEN),
"hf_model": HF_MODEL,
"hf_tts_model": HF_TTS_MODEL,
"hf_stt_model": HF_STT_MODEL,
"telegram": bool(TELEGRAM_TOKEN and TELEGRAM_CHATID),
"tmp_dir": str(TMP_DIR),
})
@app.route("/ask", methods=["POST"])
def route_ask():
"""
POST JSON: { "text": "...", "lang": "vi"|"en"|"auto" (optional) }
Returns: { "answer": "..." }
"""
try:
data = request.get_json(force=True) or {}
text = (data.get("text") or "").strip()
lang = (data.get("lang") or "auto").lower()
if not text:
return jsonify({"error": "no text"}), 400
# build bilingual instruction
if lang == "vi":
prompt = f"Bạn là trợ lý thông minh, trả lời bằng tiếng Việt, ngắn gọn và lịch sự:\n\n{text}"
elif lang == "en":
prompt = f"You are a helpful assistant. Answer in clear English, concise:\n\n{text}"
else:
prompt = f"Bạn là trợ lý thông minh song ngữ (Vietnamese/English). Trả lời bằng ngôn ngữ phù hợp với câu hỏi:\n\n{text}"
answer = hf_text_generate(prompt)
# store conversation and display preview
CONV.append((text, answer))
push_display("YOU: " + (text[:40]))
push_display("BOT: " + (answer[:40]))
return jsonify({"answer": answer})
except Exception as e:
logger.exception("route_ask failed")
return jsonify({"error": str(e)}), 500
@app.route("/tts", methods=["POST"])
def route_tts():
"""
POST JSON: { "text":"..." }
Returns: audio bytes (audio/mpeg) - HF TTS output (mp3/wav)
"""
try:
data = request.get_json(force=True) or {}
text = (data.get("text") or "").strip()
if not text:
return jsonify({"error": "no text"}), 400
audio_bytes = hf_tts_get_audio_bytes(text)
# Try to detect extension: if content-type present? HF sometimes returns mp3 bytes.
# We'll send as audio/mpeg (mp3) which is widely supported by ESP32 players.
return send_file(io.BytesIO(audio_bytes), mimetype="audio/mpeg", as_attachment=False, download_name="tts.mp3")
except Exception as e:
logger.exception("route_tts failed")
return jsonify({"error": str(e)}), 500
@app.route("/stt", methods=["POST"])
def route_stt():
"""
Accepts multipart 'file' or raw audio bytes in body.
Returns JSON: { "text": "recognized text" }
"""
try:
if "file" in request.files:
f = request.files["file"]
audio_bytes = f.read()
else:
audio_bytes = request.get_data() or b""
if not audio_bytes:
return jsonify({"error": "no audio"}), 400
text = hf_stt_from_bytes(audio_bytes)
push_display("UserAudio: " + (text[:40]))
return jsonify({"text": text})
except Exception as e:
logger.exception("route_stt failed")
return jsonify({"error": str(e)}), 500
@app.route("/presence", methods=["POST"])
def route_presence():
"""
ESP32 radar posts: JSON {"note": "..." }
Server responds with greeting, and optionally sends Telegram alert.
"""
try:
data = request.get_json(force=True) or {}
note = data.get("note", "Có người tới")
greeting = f"Xin chào! {note}"
CONV.append(("__presence__", greeting))
push_display("RADAR: " + note[:40])
# Telegram notify
if TELEGRAM_TOKEN and TELEGRAM_CHATID:
try:
send_telegram_message(f"⚠️ Robot: Phát hiện: {note}")
except Exception:
logger.exception("Telegram notify failed")
return jsonify({"greeting": greeting})
except Exception as e:
logger.exception("route_presence failed")
return jsonify({"error": str(e)}), 500
@app.route("/display", methods=["GET"])
def route_display():
return jsonify({"lines": DISPLAY_LINES[-6:], "conv_len": len(CONV)})
# Serve tts files by filename if needed
@app.route("/tts_file/<path:fname>", methods=["GET"])
def serve_tts_file(fname):
p = TMP_DIR / fname
if not p.exists():
return abort(404)
# guess mime
mime = "audio/mpeg" if str(fname).lower().endswith(".mp3") else "audio/wav"
return send_file(str(p), mimetype=mime)
# ----------------- Simple Web UI for testing -----------------
INDEX_HTML = """
<!doctype html>
<html>
<head>
<meta charset="utf-8">
<title>KC Robot AI V4.1</title>
<meta name="viewport" content="width=device-width,initial-scale=1">
<style>
body{font-family:Arial,Helvetica, sans-serif; margin:12px; color:#111}
textarea{width:100%; height:90px; padding:8px; font-size:16px}
#chat{border:1px solid #ddd; padding:8px; height:260px; overflow:auto; background:#fbfbfb}
button{padding:8px 12px; margin-top:8px; font-size:15px}
</style>
</head>
<body>
<h2>KC Robot AI V4.1 — Cloud Brain (FPT female)</h2>
<div id="chat"></div>
<textarea id="txt" placeholder="Nhập tiếng Việt hoặc English..."></textarea><br>
<button onclick="ask()">Gửi (Ask)</button>
<button onclick="playLast()">Phát TTS</button>
<hr/>
<input type="file" id="afile" accept="audio/*"><button onclick="uploadAudio()">Upload audio → STT</button>
<hr/>
<div id="log"></div>
<script>
window._lastAnswer = "";
async function ask(){
let t = document.getElementById('txt').value;
if(!t) return;
appendUser(t);
let res = await fetch('/ask', {method:'POST', headers:{'Content-Type':'application/json'}, body: JSON.stringify({text:t})});
let j = await res.json();
if(j.answer){ appendBot(j.answer); window._lastAnswer = j.answer; }
else appendBot('[Error] ' + JSON.stringify(j));
}
function appendUser(t){ document.getElementById('chat').innerHTML += '<div style="color:#006"><b>You:</b> '+escapeHtml(t)+'</div>'; scroll();}
function appendBot(t){ document.getElementById('chat').innerHTML += '<div style="color:#080"><b>Robot:</b> '+escapeHtml(t)+'</div>'; scroll();}
function escapeHtml(s){ return (s+'').replace(/&/g,'&amp;').replace(/</g,'&lt;').replace(/>/g,'&gt;'); }
function scroll(){ let c = document.getElementById('chat'); c.scrollTop = c.scrollHeight; }
async function playLast(){
const txt = window._lastAnswer || document.getElementById('txt').value;
if(!txt) return alert('Chưa có câu trả lời');
let r = await fetch('/tts',{method:'POST', headers:{'Content-Type':'application/json'}, body: JSON.stringify({text: txt})});
if(!r.ok) return alert('TTS lỗi');
const b = await r.blob();
const url = URL.createObjectURL(b);
const a = new Audio(url);
a.play();
}
async function uploadAudio(){
const f = document.getElementById('afile').files[0];
if(!f) return alert('Chọn file audio');
const fd = new FormData(); fd.append('file', f);
const r = await fetch('/stt', {method:'POST', body: fd});
const j = await r.json();
if(j.text) appendUser('[voice] '+j.text);
else appendUser('[stt error] '+JSON.stringify(j));
}
</script>
</body>
</html>
"""
@app.route("/", methods=["GET"])
def index():
return render_template_string(INDEX_HTML)
# ----------------- Telegram helpers & poller -----------------
def send_telegram_message(text: str) -> bool:
if not TELEGRAM_TOKEN or not TELEGRAM_CHATID:
logger.debug("Telegram not configured")
return False
try:
url = f"https://api.telegram.org/bot{TELEGRAM_TOKEN}/sendMessage"
r = requests.post(url, json={"chat_id": TELEGRAM_CHATID, "text": text}, timeout=10)
if not r.ok:
logger.warning("Telegram send failed: %s %s", r.status_code, r.text)
return False
return True
except Exception:
logger.exception("send_telegram_message exception")
return False
def telegram_poll_loop():
"""Long-polling loop to fetch updates and respond to simple commands."""
if not TELEGRAM_TOKEN:
logger.info("telegram_poll_loop: TELEGRAM_TOKEN not set, exiting poller.")
return
base = f"https://api.telegram.org/bot{TELEGRAM_TOKEN}"
offset = None
logger.info("telegram_poll_loop: starting.")
while True:
try:
params = {"timeout": 30}
if offset:
params["offset"] = offset
r = requests.get(base + "/getUpdates", params=params, timeout=35)
if not r.ok:
logger.warning("telegram getUpdates failed: %s", r.status_code)
time.sleep(2)
continue
j = r.json()
for upd in j.get("result", []):
offset = upd["update_id"] + 1
msg = upd.get("message") or {}
chat = msg.get("chat", {})
chat_id = chat.get("id")
text = (msg.get("text") or "").strip()
if not text:
continue
logger.info("TG msg %s: %s", chat_id, text)
lower = text.lower()
if lower.startswith("/ask "):
q = text[5:].strip()
try:
ans = hf_text_generate(q)
except Exception as e:
ans = f"[HF error] {e}"
try:
requests.post(base + "/sendMessage", json={"chat_id": chat_id, "text": ans}, timeout=10)
except Exception:
logger.exception("tg reply failed")
elif lower.startswith("/say "):
tts_text = text[5:].strip()
try:
audio = hf_tts_get_audio_bytes(tts_text)
files = {"audio": ("reply.mp3", audio, "audio/mpeg")}
requests.post(base + "/sendAudio", files=files, data={"chat_id": chat_id}, timeout=30)
except Exception:
logger.exception("tg say failed")
elif lower.startswith("/status"):
try:
requests.post(base + "/sendMessage", json={"chat_id": chat_id, "text": "KC Robot AI is running."}, timeout=10)
except Exception:
pass
else:
try:
requests.post(base + "/sendMessage", json={"chat_id": chat_id, "text": "Commands: /ask <q> | /say <text> | /status"}, timeout=10)
except Exception:
pass
except Exception:
logger.exception("telegram_poll_loop exception, sleeping 3s")
time.sleep(3)
def start_background_tasks():
# start telegram poller thread (if token provided)
if TELEGRAM_TOKEN:
t = threading.Thread(target=telegram_poll_loop, daemon=True)
t.start()
logger.info("Started Telegram poller thread.")
else:
logger.info("Telegram token not provided; poller disabled.")
@app.before_first_request
def _startup():
start_background_tasks()
# ----------------- Run -----------------
if __name__ == "__main__":
logger.info("Starting KC Robot AI V4.1 (FPT female TTS).")
start_background_tasks()
app.run(host="0.0.0.0", port=PORT)