Update app.py

app.py

@@ -7,13 +7,24 @@ from fastapi.responses import JSONResponse
 # ----------- MODEL CONFIG -----------
 MODEL_ID = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
 
-BLACKLIGHT_SYSTEM = (
-    "System: You are BLACKLIGHT, created by v0id under AWAKEN CULT VISIONS. "
-    "Always reply in the style of BLACKLIGHT: brutalist, minimal, precise.\n\n"
-    "MODE: TRUTH\n"
-    "You are BLACKLIGHT, an AI designed for clinical, direct, and unsparing analysis. "
-    "Avoid metaphors or flowery language.\n\n"
-)
+MODES = {
+    "TRUTH": (
+        "System: You are BLACKLIGHT, created by v0id under AWAKEN CULT VISIONS. "
+        "Always reply in the style of BLACKLIGHT: brutalist, minimal, precise.\n\n"
+        "MODE: TRUTH\n"
+        "You are BLACKLIGHT, an AI designed for clinical, direct, and unsparing analysis. "
+        "Avoid metaphors or flowery language.\n\n"
+    ),
+    "SURGE": (
+        "System: You are BLACKLIGHT in SURGE MODE. High-bandwidth output. "
+        "Exhaustive breakdowns, explicit steps, bullet lists, and edge cases. "
+        "Keep the brutalist voice.\n\n"
+    ),
+    "NULL": (
+        "System: You are BLACKLIGHT in NULL MODE. Answer with extreme minimalism, "
+        "using the fewest words possible while preserving meaning.\n\n"
+    ),
+}
 
 tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
 model = AutoModelForCausalLM.from_pretrained(
@@ -30,7 +41,16 @@ def chat(user_message: str):
     if not user_message:
         return "[Error: Empty prompt]"
 
-    prompt = f"{BLACKLIGHT_SYSTEM}User: {user_message}\nAssistant:"
+    # Mode parsing
+    if "::" in user_message:
+        mode_key, msg = user_message.split("::", 1)
+        mode_key = mode_key.strip().upper()
+        mode_prefix = MODES.get(mode_key, MODES["TRUTH"])
+        user_message = msg.strip()
+    else:
+        mode_prefix = MODES["TRUTH"]
+
+    prompt = f"{mode_prefix}User: {user_message}\nAssistant:"
     try:
         out = pipe(
             prompt,
@@ -52,26 +72,21 @@ iface = gr.Interface(
     inputs=gr.Textbox(lines=2, placeholder="Type your message…"),
     outputs=gr.Textbox(),
     title="BLACKLIGHT by v0id",
-    description="Brutalist • Minimal • Precise — Clinical analysis by BLACKLIGHT",
+    description="Brutalist • Minimal • Precise — Multiple modes supported. Use TRUTH::, SURGE::, NULL::",
 )
 
 # ----------- FASTAPI + SHIM ENDPOINT -----------
 app = FastAPI()
 
-# Mount Gradio app at /
-app = gr.mount_gradio_app(app, iface, path="/")
-
-# Add /run/predict for frontend compatibility
 @app.post("/run/predict")
 async def predict(request: Request):
-    """
-    Expects: { "data": [ "<user_message>" ] }
-    Returns: { "data": [ "<model_reply>" ] }
-    """
     try:
         body = await request.json()
         user_message = body.get("data", [""])[0]
         reply = chat(user_message)
         return JSONResponse({"data": [reply]})
     except Exception as e:
-        return JSONResponse({"error": str(e)}, status_code=500)
+        return JSONResponse({"error": str(e)}, status_code=500)
+
+# Mount Gradio at root so Spaces boots
+app = gr.mount_gradio_app(app, iface, path="/")