Update llm_utils.py

llm_utils.py

@@ -6,14 +6,17 @@ def load_theorem_context(yaml_path="theorems.yaml"):
     with open(yaml_path, 'r') as f:
         data = yaml.safe_load(f)
 
+    if not isinstance(data, dict):
+        return "⚠️ Invalid theorems format in YAML."
+
     context_lines = []
     for idx, th in enumerate(data.get('theorems', []), 1):
         context_lines.append(
-            f"**Theorem {idx}: {th['name']}**\n"
-            f"- **Statement**: {th['statement']}\n"
-            f"- **Tags**: {', '.join(th['tags'])}\n"
-            f"- **When to Use**: {th['when_to_use']}\n"
-            f"- **Short Explanation**: {th['short_explanation']}\n"
+            f"**Theorem {idx}: {th.get('name', 'Unnamed')}**\n"
+            f"- **Statement**: {th.get('statement', 'N/A')}\n"
+            f"- **Tags**: {', '.join(th.get('tags', []))}\n"
+            f"- **When to Use**: {th.get('when_to_use', 'N/A')}\n"
+            f"- **Short Explanation**: {th.get('short_explanation', 'N/A')}\n"
         )
         context_lines.append('---')
 
@@ -26,18 +29,17 @@ def build_prompt(equation_type, solution_text, theorem_context):
         f"Each theorem includes:\n"
         f"- Name\n- Statement\n- Tags\n- When to use\n- Short Explanation\n\n"
         f"---\n\n"
-        f"### \U0001F4D8 Theorem Database:\n\n"
+        f"### 📘 Theorem Database:\n\n"
         f"{theorem_context}\n\n"
         f"---\n\n"
-        f"### \U0001F9EE Steps for solving a {equation_type} equation:\n\n"
+        f"### 🧮 User Steps for solving a {equation_type} equation:\n\n"
         f"{solution_text}\n\n"
         f"---\n\n"
-        f"### \U0001F3AF Task:\n"
-        f"Explain the solution step-by-step.\n"
+        f"### 🎯 Task:\n"
+        f"Explain each solution step clearly.\n"
         f"Use relevant theorems by number or name.\n"
-        f"Clarify why each step is mathematically valid.\n"
-        f"Make it understandable to a high school or early undergrad student.\n"
-        f"Don't repeat theorem texts — explain using them."
+        f"Make it understandable to a smart high school student.\n"
+        f"Focus on reasoning, not just restating the steps or theorems."
     )
 
 # === Request LLM explanation ===
@@ -56,26 +58,33 @@ def explain_with_llm(solution_text, equation_type, llm_url, yaml_path="theorems.
         )
 
         if response.status_code == 200:
-            res_json = response.json()
-            if isinstance(res_json, dict):
-                return res_json.get("explanation", "❌ No explanation returned.")
-            elif isinstance(res_json, list) and len(res_json) > 0:
-                return res_json[0]
+            result = response.json()
+
+            if isinstance(result, dict):
+                return result.get("explanation", "❌ No explanation returned.")
+            elif isinstance(result, list):
+                return result[0] if result else "❌ Empty response list."
             else:
-                return "❌ LLM response was empty or invalid."
-        else:
-            return f"❌ LLM request failed: {response.status_code}"
+                return f"❌ Unexpected LLM response format: {type(result)}"
+
+        return f"❌ LLM request failed: {response.status_code}"
 
     except Exception as e:
         return f"❌ LLM Error: {e}"
 
-# Optionally, this could be used for fallback cleaning too
+# === Request fallback if parsing failed ===
 def request_llm_fallback(bad_input, llm_url):
     try:
-        response = requests.post(f"{llm_url.strip()}/clean", json={"prompt": bad_input}, timeout=20)
-        if response.status_code == 200:
-            return response.json().get("cleaned_latex", bad_input)
+        response = requests.post(
+            f"{llm_url.strip()}/clean",
+            json={"prompt": bad_input},
+            timeout=20
+        )
+        result = response.json()
+        if isinstance(result, dict):
+            return result.get("cleaned_latex", bad_input)
         return bad_input
     except:
         return bad_input
 
+