Update app.py

app.py

@@ -1,179 +1,24 @@
-import os, requests, streamlit as st
-from audio_recorder_streamlit import audio_recorder
+import streamlit as st
 
-# ----- Config (set secrets in Space → Settings → Secrets) -----
-HF_TOKEN   = os.getenv("HF_TOKEN", "").strip()
-HF_API_BASE= os.getenv("HF_API_BASE", "https://api-inference.huggingface.co").rstrip("/")
-CHAT_MODEL = os.getenv("HF_MODEL", "google/gemma-2-2b-it").strip()
-SYSTEM_PROMPT = os.getenv("SYSTEM_PROMPT", "You are EDGE AI, a concise helpful assistant.")
+st.set_page_config(page_title="EDGE", page_icon="🤖", layout="centered")
 
-# Voice defaults (you can also move these to Secrets if you want)
-ASR_MODEL  = os.getenv("ASR_MODEL",  "openai/whisper-small").strip()
-TTS_MODEL  = os.getenv("TTS_MODEL",  "parler-tts/parler-tts-mini-v1").strip()
-
-HEADERS = {"Authorization": f"Bearer {HF_TOKEN}", "Accept": "application/json"} if HF_TOKEN else {}
-
-# ----- Page UI -----
-st.set_page_config(page_title="EDGE AI", page_icon="🤖", layout="centered")
-
-# Show your logo if present
-if os.path.exists("logo.png"):
+# show your logo if present
+try:
     st.image("logo.png", width=220)
-else:
-    st.markdown("<h1 style='text-align:center;margin:0'>🤖 EDGE AI</h1>", unsafe_allow_html=True)
-
-st.caption("Streamlit chatbot • text + voice")
-
-with st.sidebar:
-    st.subheader("Models")
-    chat_model = st.selectbox(
-        "Chat model",
-        ["google/gemma-2-2b-it", "HuggingFaceH4/zephyr-7b-beta", "mistralai/Mistral-7B-Instruct-v0.2"],
-        index=0 if CHAT_MODEL.startswith("google/gemma-2-2b-it") else (1 if "zephyr" in CHAT_MODEL else 2),
-    )
-    asr_model = st.text_input("ASR model (speech→text)", ASR_MODEL)               # Whisper family is good
-    tts_model = st.text_input("TTS model (text→speech)", TTS_MODEL)                # parler-tts works well
-    use_tts   = st.checkbox("Speak assistant replies", value=True)
-    system_prompt = st.text_area("System prompt", SYSTEM_PROMPT, height=100)
-    clear = st.button("Clear chat")
-    st.write("HF token:", "✅ set" if HF_TOKEN else "❌ missing")
-
-if not HF_TOKEN:
-    st.error("HF_TOKEN is missing. Add it in **Space → Settings → Secrets**.")
-    st.stop()
-
-# ----- State -----
-if "messages" not in st.session_state or clear:
-    st.session_state.messages = [{"role": "system", "content": system_prompt}]
-else:
-    st.session_state.messages[0]["content"] = system_prompt  # keep in sync if edited
-
-# Render history
-for m in st.session_state.messages:
-    if m["role"] in ("user", "assistant"):
-        with st.chat_message(m["role"]):
-            st.markdown(m["content"])
-
-# ----- HF helpers -----
-def call_v1_chat(messages, model):
-    url = f"{HF_API_BASE}/v1/chat/completions"
-    payload = {"model": model, "messages": messages, "max_tokens": 300, "temperature": 0.7}
-    return requests.post(url, headers=HEADERS, json=payload, timeout=90)
-
-def call_legacy_chat(messages, model):
-    parts = []
-    for m in messages:
-        if m["role"] == "system":
-            parts.append(f"<|system|>\n{m['content']}</s>\n")
-        else:
-            role = "assistant" if m["role"] == "assistant" else "user"
-            parts.append(f"<|{role}|>\n{m['content']}</s>\n")
-    parts.append("<|assistant|>\n")
-    prompt = "".join(parts)
-    url = f"{HF_API_BASE}/models/{model}"
-    payload = {"inputs": prompt, "parameters": {"max_new_tokens": 256, "return_full_text": False},
-               "options": {"wait_for_model": True}}
-    return requests.post(url, headers=HEADERS, json=payload, timeout=90)
-
-def chat_reply(messages, model):
-    # v1 first
-    try:
-        r = call_v1_chat(messages, model)
-        if r.status_code == 200:
-            data = r.json()
-            return data["choices"][0]["message"]["content"].strip(), "v1"
-    except Exception:
-        pass
-    # legacy fallback
-    r2 = call_legacy_chat(messages, model)
-    r2.raise_for_status()
-    data2 = r2.json()
-    return (data2[0]["generated_text"] or "").strip(), "legacy"
-
-def transcribe_audio(audio_bytes, model):
-    """Send audio bytes to HF ASR model; returns text."""
-    url = f"{HF_API_BASE}/models/{model}"
-    headers = HEADERS.copy()
-    headers["Content-Type"] = "audio/wav"          # component returns WAV
-    r = requests.post(url, headers=headers, data=audio_bytes, timeout=90)
-    r.raise_for_status()
-    data = r.json()
-    # Most ASR models return {"text": "..."}
-    if isinstance(data, dict) and "text" in data:
-        return data["text"]
-    # Fallback shapes
-    if isinstance(data, list) and data and isinstance(data[0], dict) and "text" in data[0]:
-        return data[0]["text"]
-    return ""
-
-def tts_audio(text, model):
-    """Return WAV bytes from HF TTS model; many TTS models honor Accept: audio/wav."""
-    url = f"{HF_API_BASE}/models/{model}"
-    headers = HEADERS.copy()
-    headers["Accept"] = "audio/wav"
-    # For most TTS models, JSON with {"inputs": text} works. Parler-TTS also supports this on serverless.
-    r = requests.post(url, headers=headers, json={"inputs": text}, timeout=120)
-    r.raise_for_status()
-    return r.content  # raw wav bytes
-
-# ----- Text chat input -----
-user_text = st.chat_input("Type your message…")
-if user_text:
-    st.session_state.messages.append({"role": "user", "content": user_text})
-    with st.chat_message("user"): st.markdown(user_text)
-
-    with st.chat_message("assistant"):
-        with st.spinner("Thinking…"):
-            try:
-                reply, mode = chat_reply(st.session_state.messages, chat_model)
-            except Exception as e:
-                reply, mode = f"_HF error:_ {e}", "error"
-            st.markdown(reply or "_no reply_")
-            st.caption(f"• mode: {mode} • model: {chat_model}")
-            # optional TTS
-            if use_tts and reply and mode != "error":
-                try:
-                    wav = tts_audio(reply, tts_model)
-                    st.audio(wav, format="audio/wav")
-                except Exception as e:
-                    st.info(f"TTS failed: {e}")
-    if reply:
-        st.session_state.messages.append({"role": "assistant", "content": reply})
-
-# ----- Voice recorder -----
-st.divider()
-st.subheader("🎙️ Voice chat")
-st.caption("Click to record, then release to transcribe and chat.")
-audio_bytes = audio_recorder(
-    pause_threshold=1.0, sample_rate=16000, energy_threshold=(-1.0, 1.0), text="Record / Stop", icon_size="2x"
-)
-
-if audio_bytes:
-    with st.spinner("Transcribing…"):
-        try:
-            text_from_audio = transcribe_audio(audio_bytes, asr_model).strip()
-        except Exception as e:
-            text_from_audio = ""
-            st.error(f"ASR failed: {e}")
-
-    if text_from_audio:
-        # push as a user message and run the normal chat path
-        st.session_state.messages.append({"role": "user", "content": text_from_audio})
-        with st.chat_message("user"): st.markdown(text_from_audio)
-
-        with st.chat_message("assistant"):
-            with st.spinner("Thinking…"):
-                try:
-                    reply, mode = chat_reply(st.session_state.messages, chat_model)
-                except Exception as e:
-                    reply, mode = f"_HF error:_ {e}", "error"
-                st.markdown(reply or "_no reply_")
-                st.caption(f"• mode: {mode} • model: {chat_model}")
-                if use_tts and reply and mode != "error":
-                    try:
-                        wav = tts_audio(reply, tts_model)
-                        st.audio(wav, format="audio/wav")
-                    except Exception as e:
-                        st.info(f"TTS failed: {e}")
-        if reply:
-            st.session_state.messages.append({"role": "assistant", "content": reply})
+except Exception:
+    st.title("EDGE")
+
+st.success("✅ Frontend is alive. Type below to interact.")
+
+# tiny chat echo so you can interact
+if "chat" not in st.session_state: st.session_state.chat = []
+for role, text in st.session_state.chat:
+    with st.chat_message(role): st.markdown(text)
+
+msg = st.chat_input("Say something…")
+if msg:
+    st.session_state.chat.append(("user", msg))
+    with st.chat_message("user"): st.markdown(msg)
+    reply = f"You said: **{msg}**"
+    st.session_state.chat.append(("assistant", reply))
+    with st.chat_message("assistant"): st.markdown(reply)