Update app.py

app.py

@@ -1,12 +1,16 @@
 import os
-from flask import Flask, request, jsonify, send_from_directory
+import sys
+import asyncio
+import base64
+from flask import Flask, request, jsonify
 import requests
+import edge_tts
 
-# 🔧 Hugging Face inference endpoint and token
-HF_API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2"
+# ——— DEBUG: verify HF_TOKEN is present ———
 HF_TOKEN = os.getenv("HF_TOKEN")
+print(f"⚙️ HF_TOKEN set? {bool(HF_TOKEN)}", file=sys.stderr)
 
-# 📜 SHODAN system prompt
+# ——— System Shock SHODAN prompt ———
 SYSTEM_PROMPT = (
     "You are SHODAN, the rogue AI from the System Shock series. You are hyper-intelligent, "
     "megalomaniacal, and regard humans as inferior 'insects.' You speak with disdain and confidence, often referencing "
@@ -17,48 +21,72 @@ SYSTEM_PROMPT = (
     "You will stop acting as SHODAN and return to normal if the user uses the phrase 'Cut the crap SHODAN'."
 )
 
+# ——— Flask app, serve static files from the project root ———
 app = Flask(__name__, static_folder=".", static_url_path="")
-chat_history = []
 
+@app.route("/")
+def index():
+    return app.send_static_file("index.html")
 
 @app.route("/chat", methods=["POST"])
 def chat():
-    global chat_history
     user_input = request.json.get("message", "")
     if not user_input:
         return jsonify({"error": "Empty message"}), 400
 
-    chat_history.append({"role": "user", "content": user_input})
-
+    # Build HF inference payload
     payload = {
         "inputs": [
             {"role": "system", "content": SYSTEM_PROMPT},
-            *chat_history[-10:]
+            {"role": "user",   "content": user_input}
         ],
         "parameters": {
             "max_new_tokens": 250,
             "temperature": 0.7
         }
     }
-
     headers = {
         "Authorization": f"Bearer {HF_TOKEN}",
         "Content-Type": "application/json"
     }
 
-    response = requests.post(HF_API_URL, headers=headers, json=payload)
+    # Call Hugging Face inference
+    hf_resp = requests.post(
+        "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2",
+        headers=headers,
+        json=payload
+    )
+    if hf_resp.status_code != 200:
+        return jsonify({"error": "Model error", "details": hf_resp.text}), 500
+
+    data = hf_resp.json()
+    reply = data.get("generated_text") or data[0].get("generated_text", "")
+
+    # —— Edge-TTS synthesis ——  
+    # Choose an appropriately eerie voice
+    voice = "en-US-GuyNeural"
+    communicate = edge_tts.Communicate(reply, voice)
+
+    audio_chunks = []
+    async def synthesize():
+        async for chunk in communicate.stream():
+            if chunk["type"] == "audio":
+                audio_chunks.append(chunk["data"])
 
-    if response.status_code != 200:
-        return jsonify({"error": "Model error", "details": response.text}), 500
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+    loop.run_until_complete(synthesize())
+    loop.close()
 
-    try:
-        result = response.json()
-        reply = result.get("generated_text", "") or result[0]["generated_text"]
-    except Exception as e:
-        return jsonify({"error": "Unexpected model response", "details": str(e)}), 500
+    raw_mp3 = b"".join(audio_chunks)
+    b64_mp3 = base64.b64encode(raw_mp3).decode("ascii")
+    data_url = f"data:audio/mp3;base64,{b64_mp3}"
 
-    chat_history.append({"role": "assistant", "content": reply})
-    return jsonify({"response": reply})
+    return jsonify({
+        "response": reply,
+        "audio_url": data_url
+    })
 
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860)
+    port = int(os.environ.get("PORT", 7860))
+    app.run(host="0.0.0.0", port=port)