Update

app.py

@@ -1,102 +1,443 @@
 
-# KC Robot AI V4.1 (FPT Female Voice, HuggingFace Cloud Brain)
-import os, io, time, threading, requests, logging
-from flask import Flask, request, jsonify, send_file, render_template_string
+# 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)
 
-app = Flask(__name__)
+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.ai")
+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()
 
-# ========== CONFIG ==========
-HF_API_TOKEN = os.getenv("HF_API_TOKEN", "")
-HF_MODEL = os.getenv("HF_MODEL", "google/flan-t5-large")
-HF_TTS_MODEL = os.getenv("HF_TTS_MODEL", "NguyenManhTuan/VietnameseTTS_FPT_AI_Female")
-HF_STT_MODEL = os.getenv("HF_STT_MODEL", "openai/whisper-small")
-TELEGRAM_TOKEN = os.getenv("TELEGRAM_TOKEN", "")
-TELEGRAM_CHATID = os.getenv("TELEGRAM_CHATID", "")
-HF_HEADERS = {"Authorization": f"Bearer {HF_API_TOKEN}"}
+# Port (HF sets PORT env in runtime)
+PORT = int(os.getenv("PORT", os.getenv("SERVER_PORT", 7860)))
 
-CONV = []
-DISPLAY_LINES = []
+if not HF_API_TOKEN:
+    logger.warning("HF_API_TOKEN is not set — HF inference will fail until you add it in Secrets.")
 
-def push_display(line, limit=6):
+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:]
-
-# ========== HF HELPERS ==========
-def hf_text_generate(prompt):
-    url = f"https://api-inference.huggingface.co/models/{HF_MODEL}"
-    r = requests.post(url, headers=HF_HEADERS, json={"inputs": prompt, "parameters":{"max_new_tokens":256}})
-    return r.json()[0].get("generated_text", "Lỗi HF model") if r.ok else f"HF Error {r.status_code}"
-
-def hf_tts_get_mp3(text):
-    url = f"https://api-inference.huggingface.co/models/{HF_TTS_MODEL}"
-    r = requests.post(url, headers=HF_HEADERS, json={"inputs": text})
-    return r.content if r.ok else b""
-
-def hf_stt_from_bytes(audio_bytes):
-    url = f"https://api-inference.huggingface.co/models/{HF_STT_MODEL}"
-    r = requests.post(url, headers={**HF_HEADERS,"Content-Type":"application/octet-stream"}, data=audio_bytes)
-    j = r.json()
-    return j.get("text","") if isinstance(j,dict) else str(j)
-
-# ========== ROUTES ==========
+        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 ask():
-    data = request.get_json(force=True)
-    text = data.get("text","")
-    lang = "vi" if any(ch in "ăâêôơưđáàạảãấầẩậẫéèẻẹẽíìỉịĩóòỏõọúùủụũ" for ch in text.lower()) else "en"
-    prompt = f"Bạn là trợ lý AI song ngữ. Trả lời bằng {('tiếng Việt' if lang=='vi' else 'English')}:\n{text}"
-    ans = hf_text_generate(prompt)
-    CONV.append((text, ans)); push_display(f"YOU:{text[:40]}"); push_display(f"BOT:{ans[:40]}")
-    return jsonify({"answer": ans})
+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 tts():
-    data = request.get_json(force=True)
-    text = data.get("text","")
-    audio = hf_tts_get_mp3(text)
-    return send_file(io.BytesIO(audio), mimetype="audio/mpeg", as_attachment=False)
+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 stt():
-    f = request.files.get("file")
-    audio_bytes = f.read() if f else request.get_data()
-    text = hf_stt_from_bytes(audio_bytes)
-    push_display("UserAudio: " + text[:40])
-    return jsonify({"text": text})
+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 presence():
-    note = request.json.get("note","Có người tới")
-    greeting = f"Xin chào! {note}"
-    if TELEGRAM_TOKEN and TELEGRAM_CHATID:
-        try:
-            requests.post(f"https://api.telegram.org/bot{TELEGRAM_TOKEN}/sendMessage",
-                json={"chat_id": TELEGRAM_CHATID, "text": f"⚠️ Robot phát hiện: {note}"})
-        except Exception as e: logger.warning(f"Telegram error: {e}")
-    return jsonify({"greeting": greeting})
-
-@app.route("/display")
-def display(): return jsonify({"lines": DISPLAY_LINES})
-
-# ========== WEB CHAT ==========
-HTML = """
-<!doctype html><html><head><meta charset="utf-8"><title>KC Robot AI</title></head>
-<body><h3>KC Robot AI V4.1 🤖</h3>
-<textarea id='q' rows=3 cols=80 placeholder='Nhập tiếng Việt hoặc English...'></textarea><br>
-<button onclick='ask()'>Gửi</button><pre id='out'></pre>
-<script>
-async function ask(){
- let q=document.getElementById('q').value;
- let r=await fetch('/ask',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({text:q})});
- let j=await r.json();document.getElementById('out').innerText=j.answer;
-}
-</script></body></html>
+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("/") 
-def home(): return 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__":
-    app.run(host="0.0.0.0", port=int(os.getenv("PORT", 7860)))
+    logger.info("Starting KC Robot AI V4.1 (FPT female TTS).")
+    start_background_tasks()
+    app.run(host="0.0.0.0", port=PORT)