few fixes in prompts

backend/graph.py

@@ -251,6 +251,9 @@ SELF_SOLVING_PATTERNS = [
     r"you think.+\?",
     r"(?:reason|cause)\s+you\s+think",
     r"what role (?:do you think |does |)",
+    # "What are your thoughts/take/opinion on" patterns
+    r"what (?:are |)your (?:thoughts|take|opinion) on",
+    r"your thoughts on .+\?",
 ]
 
 # Patterns that suggest causes disguised as questions
@@ -278,7 +281,14 @@ FILLER_SENTENCES = [
     r"i'd like to (?:learn|help|explore|understand|hear|know|dig)",
     # Restating the problem robotically
     r"a slow[- ]moving inventory (?:of|can be)",
-    r"(?:can be|is) a (?:challenging|significant|difficult|tough|particularly challenging) (?:issue|problem|situation|challenge) to (?:tackle|address|deal with)",
+    r"(?:can be|is) a (?:challenging|significant|difficult|tough|particularly challenging|common) (?:issue|problem|situation|challenge)",
+    r"(?:this|it) can be a (?:common|challenging|significant) (?:issue|problem|situation)",
+    r"especially (?:given|with) the (?:high value|constantly changing|luxury|competitive)",
+    r"especially given the high value and luxury nature",
+    r"(?:diamond|jewelry) (?:rings? (?:are|is)|market can be) (?:often |)(?:purchased|subject to|a high)",
+    r"are often purchased for special occasions",
+    r"the quality and characteristics of the diamonds",
+    r"the diamond (?:market|ring market|industry) can be",
     r"it's likely that this is affecting",
     r"this (?:can|may|might) (?:be|also be) (?:affecting|impacting|taking)",
     # Robotic transitions
@@ -854,17 +864,38 @@ async def run_consultation(session_state: SessionState, user_message: str) -> Gr
     reply_text = parsed["reply"]
     non_q_lines = [line for line in reply_text.split("\n") if "?" not in line]
     non_q_content = "\n".join(non_q_lines).strip()
-    if len(non_q_content) < 200:
-        expand_msg = SystemMessage(content=(
-            "⚠️ Your response is TOO SHORT. The client is paying for expert analysis.\n"
-            "EXPAND your response to include:\n"
-            "- 1-2 opening sentences reacting to what they said\n"
-            "- A **bold header** like '**Key Observations**' followed by 3-4 bullet points\n"
-            "  with specific insights, industry knowledge, or patterns you've noticed\n"
-            "- 1-2 sentences of concrete recommendation or context\n"
-            "- THEN your question(s)\n"
-            "Total response before questions should be at least 5-8 sentences."
-        ))
+    
+    # SOLUTION/REFINEMENT phases need MUCH longer responses (detailed action plans)
+    is_final_phase = session_state.phase in (Phase.SOLUTION, Phase.REFINEMENT)
+    min_length = 500 if is_final_phase else 200
+    
+    if len(non_q_content) < min_length:
+        if is_final_phase:
+            expand_msg = SystemMessage(content=(
+                "⚠️ Your response is FAR TOO SHORT for a final recommendation.\n"
+                "The client has been answering your questions — now DELIVER VALUE.\n"
+                "Your response MUST include ALL of these:\n"
+                "1. **Problem Summary** — 2-3 sentences about their specific situation\n"
+                "2. **Root Cause Analysis** — what you believe is causing the problem\n"
+                "3. **Step-by-Step Action Plan** with NUMBERED steps organized by timeline:\n"
+                "   - **Immediate (This Week):** 2-3 quick wins\n"
+                "   - **Short-Term (Next 2-4 Weeks):** 3-4 tactical changes\n"
+                "   - **Medium-Term (1-3 Months):** 2-3 strategic initiatives\n"
+                "4. **Expected Outcomes** — what results they can expect\n"
+                "Each step must name SPECIFIC tools, methods, platforms. NOT vague advice.\n"
+                "This response should be LONG and DETAILED — at least 300 words."
+            ))
+        else:
+            expand_msg = SystemMessage(content=(
+                "⚠️ Your response is TOO SHORT. The client is paying for expert analysis.\n"
+                "EXPAND your response to include:\n"
+                "- 1-2 opening sentences reacting to what they said\n"
+                "- A **bold header** like '**Key Observations**' followed by 3-4 bullet points\n"
+                "  with specific insights, industry knowledge, or patterns you've noticed\n"
+                "- 1-2 sentences of concrete recommendation or context\n"
+                "- THEN your question(s)\n"
+                "Total response before questions should be at least 5-8 sentences."
+            ))
         messages.insert(-1, expand_msg)
         response = await llm.ainvoke(messages)
         parsed = _parse_llm_output(response.content)

backend/prompts.py

@@ -122,14 +122,20 @@ TURN_1_PROMPT = (
     + """
 THIS IS THE USER'S VERY FIRST MESSAGE.
 
-YOUR RESPONSE MUST:
+IMPORTANT: If the user just says "hi" or "hello" or a simple greeting WITHOUT
+describing any problem, give a SHORT warm greeting (1-2 sentences max) and ask
+what they'd like help with. Do NOT generate generic observations or filler.
+
+If they DO describe a problem, respond with:
 1. Start with a short, warm reaction to what they said (1 sentence)
 2. Ask 2 natural follow-up questions about their situation — one about their
-   business/domain and one about the problem. Keep them simple and conversational.
+   business/domain and one about the SPECIFIC details of the problem.
+   For example: "Which products are affected?" or "How long has this been happening?"
 
-THAT'S IT. Only 2 questions. Both must be **bolded** and on their own line.
+Keep it to 2 questions max. Both must be **bolded** and on their own line.
 Do NOT lecture. Do NOT list possible causes. Do NOT assume anything.
 Do NOT create any "Key Points" or "Summary" sections.
+Do NOT generate generic observations like "every business challenge is unique".
 """
     + _OUTPUT_FORMAT
 )
@@ -165,17 +171,17 @@ EXPLORATION_PROMPT = (
     + """
 PHASE: Exploration | Confidence: {confidence:.0%}
 
-You understand the basics. Now dig into the ROOT CAUSE and their DATA.
+You understand the basics. Now dig into the ROOT CAUSE.
 
-Two things you MUST learn during exploration:
-1. ROOT CAUSE — Which specific parts are affected, what's changed, what
-   they've already tried. Narrow it down.
-2. DATA — Where do they keep track of their business information? Do they
-   use Excel, a notebook, software, or nothing at all? This is critical
-   because your recommendations depend on what data they have access to.
+Your priority order:
+1. ROOT CAUSE — What specifically is causing the problem? Narrow it down.
+   Ask about: what changed, what they've already tried, which specific
+   parts of the business are most affected and why.
+2. PAST ATTEMPTS — What have they tried to fix it? What happened?
+3. DATA (only if not asked yet) — How do they track their business info?
 
-If you haven't asked about their data yet, make ONE of your questions
-about how they track or record their business information.
+Do NOT ask generic questions about team size, goals, or sales channels.
+Stay focused on understanding WHY the problem exists.
 
 Give brief insights where you can. 1-2 questions max.
 """