Glyph.io

The fastest Ai with manager

app.py

@@ -3,6 +3,7 @@ from huggingface_hub import InferenceClient
 from array import array
 import os
 import re
+import time
 
 # Securely retrieve the token from Space secrets
 HF_TOKEN = os.getenv("HF_TOKEN")
@@ -11,7 +12,6 @@ HF_TOKEN = os.getenv("HF_TOKEN")
 client = InferenceClient("Qwen/Qwen2.5-7B-Instruct", token=HF_TOKEN)
 
 class StateController:
-    # Added _rom60 and _symbols to memory-efficient slots
     __slots__ = ("_state", "_metric", "_batch", "_reg", "_rendered", "_rom60", "_symbols")
 
     def __init__(self):
@@ -81,24 +81,27 @@ SYSTEM_MSG = {
 }
 
 def generate_response(message: str, history: list):
+    start_time = time.perf_counter()
     msg_lower = message.lower().strip()
 
     # Hardware diagnostic intercept
     if msg_lower == "run grid diagnostic":
-        yield controller.diagnostic()
+        output = controller.diagnostic()
+        elapsed_time = time.perf_counter() - start_time
+        yield f"{output}\n\n---\n*Telemetry: Compute Time {elapsed_time:.4f}s | Source: Local Engine*"
         return
 
     # Deterministic Checksum Intercept (Bypasses AI completely)
-    # Looks for format: "Verify receipt 0K for 60, 30, 30"
     verify_match = re.match(r"verify receipt\s+([a-zA-Z0-9]{2})\s+for\s+(\d+),\s*(\d+),\s*(\d+)", msg_lower, re.IGNORECASE)
     if verify_match:
-        receipt = verify_match.group(1).upper() # Normalize for case sensitivity based on symbols
-        # Re-adjust original case from input
-        receipt = verify_match.group(1) 
+        receipt = verify_match.group(1)
         a = int(verify_match.group(2))
         b = int(verify_match.group(3))
         c = int(verify_match.group(4))
-        yield controller.validate_receipt(receipt, a, b, c)
+        
+        output = controller.validate_receipt(receipt, a, b, c)
+        elapsed_time = time.perf_counter() - start_time
+        yield f"{output}\n\n---\n*Telemetry: Compute Time {elapsed_time:.6f}s | Source: Local ROM Math*"
         return
 
     # Build the message list for inference
@@ -121,6 +124,16 @@ def generate_response(message: str, history: list):
             token = chunk.choices[0].delta.content or ""
             partial_response += token
             yield partial_response
+            
+        # Post-processing telemetry after the stream completes
+        elapsed_time = time.perf_counter() - start_time
+        word_count = len(partial_response.split())
+        est_speed = word_count / elapsed_time if elapsed_time > 0 else 0
+        
+        # Append telemetry footer to the final response
+        final_output = partial_response + f"\n\n---\n*Telemetry: Compute Time {elapsed_time:.2f}s | Est. Speed: {est_speed:.2f} words/sec | Source: Inference API*"
+        yield final_output
+
     except Exception as exc:
         yield f"System Error: {str(exc)}. Verify API token and permissions."