From e0ddd65f1d5cb2ad4becc6112b30243785e6275f Mon Sep 17 00:00:00 2001
From: Ionel Andrei Cataon <ionelandreicataon@proton.com>
Date: Wed, 18 Feb 2026 17:48:47 +0200
Subject: [PATCH] s

---
 .../src/main/webapp/index.html                | 37 +++++++++++--------
 1 file changed, 22 insertions(+), 15 deletions(-)

diff --git a/proiect-nutritie-java/src/main/webapp/index.html b/proiect-nutritie-java/src/main/webapp/index.html
index b1f4c81..b0b4de6 100644
--- a/proiect-nutritie-java/src/main/webapp/index.html
+++ b/proiect-nutritie-java/src/main/webapp/index.html
@@ -102,7 +102,7 @@
         <div id="chat" class="chat-container">
             <div class="msg ai shadow">
                 <h5 class="fw-bold text-primary">System Online.</h5>
-                Mathematical verification is now active. All meal plans are audited for calorie accuracy.
+                Staple-scaling protocol active. All meal plans are calculated for exact mathematical compliance.
             </div>
         </div>
         <div class="input-area">
@@ -168,31 +168,38 @@
 
     async function talk(custom) {
         const box = document.getElementById('chat'), input = document.getElementById('uIn');
-        const text = custom === 'GENERATE_SHOPPING_LIST' ? "GENERATE_SHOPPING_LIST: Provide a shopping list based on the active meal plan." : (custom || input.value);
+        const targetKcal = document.getElementById('kcal').innerText;
+        const text = custom === 'GENERATE_SHOPPING_LIST' ? "GENERATE_SHOPPING_LIST" : (custom || input.value);
         if(!text) return;
         if(!custom) { box.innerHTML += `<div class="msg user shadow-sm">${text}</div>`; input.value=""; }
-        const id = 'ai-'+Date.now(); box.innerHTML += `<div id="${id}" class="msg ai shadow">Auditing calories...</div>`;
+        const id = 'ai-'+Date.now(); box.innerHTML += `<div id="${id}" class="msg ai shadow">Calculating exact portions...</div>`;
         box.scrollTop = box.scrollHeight;
 
-        const sysPrompt = {role:"system", content: `Expert Dietitian. TARGET: ${document.getElementById('kcal').innerText} kcal. SYSTEM: ${isMetric ? 'METRIC' : 'IMPERIAL'}.
+        const sysPrompt = {role:"system", content: `Expert Dietitian. TARGET: ${targetKcal} kcal. 
 
-        MATH VERIFICATION RULE:
-        1. You are forbidden from hallucinating totals.
-        2. Before writing the 'Daily Total', you MUST manually sum the calories of every ingredient you listed.
-        3. If the sum is less than ${document.getElementById('kcal').innerText}, you MUST increase the Weight (RAW) of starch/protein sources (e.g., 100g -> 250g) until the math is perfect.
-        4. Meal Total MUST = Sum of ingredient calories.
-        5. Daily Total MUST = Sum of all Meal Totals.
+        STRICT CALORIE ARCHITECTURE:
+        1. NO RECOMMENDATIONS AT THE END. You must NEVER finish with "to meet your goal, add X." All calories must be ALREADY in the table.
+        2. MANDATORY STAPLE SCALING: If the sum is below ${targetKcal}, increase the RAW weight of Rice, Oats, Bread, or Meat (e.g., 100g -> 350g) within the tables until the total is EXACT.
+        3. MATHEMATICAL LOCK: Ingredient calories must sum to 'Meal Total', and all 'Meal Totals' must sum to EXACTLY ${targetKcal}. No exceptions.
+        4. No hallucinations. I am checking the math for every row.
 
-        OUTPUT FORMAT:
-        - Table: | Ingredient | Weight (RAW) | Calories | P(g) | C(g) | F(g) |
-        - After each table: "Meal Total: [Kcal] | [P] | [C] | [F]"
-        - Final line: **Daily Total: [Sum] kcal**.`};
+        FORMAT:
+        ### [Day]
+        #### [Meal Name]
+        | Ingredient | Weight (RAW) | Calories | P(g) | C(g) | F(g) |
+        Meal Total: [Kcal] | [P] | [C] | [F]
+        
+        **Daily Total: [Sum] kcal** (Must be ${targetKcal})`};
         
         conversationHistory.push({role: "user", content: text});
         try {
             const res = await fetch("https://api.groq.com/openai/v1/chat/completions", {
                 method: "POST", headers: {"Content-Type":"application/json", "Authorization":`Bearer ${API}`},
-                body: JSON.stringify({ model:"llama-3.3-70b-versatile", messages:[sysPrompt, ...conversationHistory], temperature: 0.1})
+                body: JSON.stringify({ 
+                    model:"llama-3.3-70b-versatile", 
+                    messages:[sysPrompt, ...conversationHistory],
+                    temperature: 0.0 // Forced precision
+                })
             });
             const d = await res.json();
             const aiMsg = d.choices[0].message.content;