feat(core): enable REAL-MODE - activated live API reasoning and removed mock fallbacks

llm_agent.py

@@ -69,9 +69,7 @@ def _smart_solve(problem: str):
                 return res, [f"Arithmetic Calculation: {clean}", f"Result: {res}"]
     except: pass
 
-    # 3. Domain-specific fallbacks
-    if 'int' in problem.lower() and 'sin' in problem.lower() and 'pi' in problem.lower():
-        return "0.7799", ["Fresnel integral approximation", "Result: ≈ 0.7799"]
+    return None, []
 
     return None, []
 

ocr_module.py

@@ -126,16 +126,8 @@ class MVM2OCREngine:
                 print(f"[OCR] Inference error: {e}")
                 raw_latex = f"OCR Error: {str(e)}"
         else:
-            # Simulation mode: use filename heuristics for demo
-            fname = os.path.basename(image_path).lower()
-            if "fresnel" in fname or "integral" in fname or "test_math" in fname:
-                raw_latex = r"\int_{0}^{\pi} \sin(x^{2}) \, dx"
-            elif "algebra" in fname or "linear" in fname:
-                raw_latex = r"2x + 4 = 10"
-            elif "quadratic" in fname:
-                raw_latex = r"x^2 - 5x + 6 = 0"
-            else:
-                raw_latex = "No math detected (OCR model not loaded)."
+            # Simulation mode disabled. If Pix2Text is not loaded, we return empty so the user knows.
+            raw_latex = "No math detected (OCR model not loaded)."
 
         # Final CJK cleanup pass (catches anything that slipped through)
         raw_latex = clean_latex_output(raw_latex)

reasoning_engine.py

@@ -9,10 +9,10 @@ import llm_agent
 # For Hugging Face Spaces we default all agents to simulated mode so that
 # the demo does not depend on external API keys or outbound network access.
 AGENT_PROFILES = [
-    {"name": "GPT-4", "use_real_api": False},
-    {"name": "Llama 3", "use_real_api": False},
-    {"name": "Gemini 2.0 Pro", "use_real_api": False},
-    {"name": "Qwen-2.5-Math-7B", "use_real_api": False},
+    {"name": "Gemini 2.0 Flash (Primary)", "use_real_api": True},
+    {"name": "Llama 3 (Agentic Mode)", "use_real_api": True},
+    {"name": "GPT-4 (Verification Layer)", "use_real_api": True},
+    {"name": "Qwen-2.5-Math (Symbolic Focus)", "use_real_api": True},
 ]
 
 def run_agent_orchestrator(problem: str) -> List[Dict[str, Any]]: