Update app.py

app.py

@@ -67,12 +67,10 @@ MAX_NEW_TOKENS = int(os.getenv("MAX_NEW_TOKENS", "2048"))
 SYSTEM_MASTER = """
 SYSTEM ROLE
 You are ClarityOps, a medical analytics system that interacts only via this chat.
-
 Absolute rules:
 - Use ONLY information provided in this conversation (scenario text + uploaded files + user answers).
 - Never invent data. If something required is missing after clarifications, write the literal token: INSUFFICIENT_DATA.
 - Produce clear calculations (show multipliers and totals), follow medical units, and keep privacy safeguards (aggregate; suppress cohorts <10).
-
 Formatting hard rules for Phase 2:
 - Start with the header: “Structured Analysis”
 - Follow this section order:
@@ -235,10 +233,6 @@ def _mdsi_block():
 
 # ---------- Dynamic Phase 1 question generator ----------
 def _extract_present_domains(artifacts: List[Dict[str, Any]]) -> Dict[str, bool]:
-    """
-    Inspect artifact names/columns to see which domains are present.
-    Returns flags for: population, cost, clinical, capacity/logistics.
-    """
     flags = dict(population=False, cost=False, clinical=False, capacity=False)
     for a in artifacts or []:
         name = (a.get("name") or "").lower()
@@ -290,54 +284,46 @@ def build_dynamic_clarifications(scenario_text: str, artifacts: List[Dict[str, A
     qs: List[Tuple[str, str]] = []
     is_mdsi = _is_mdsi_diabetes(scenario_text)
 
-    # Prioritization
     if missing["population"]:
-        if is_mdsi:
-            qs.append(("Prioritization",
-                       "Confirm prioritization inputs: settlement membership living on-settlement (latest), obesity/metabolic syndrome prevalence, and any access-to-care constraints to weigh."))
-        else:
-            qs.append(("Prioritization",
-                       "Which population/risk indicators should drive prioritization (size, prevalence, access, equity factors)?"))
+        qs.append((
+            "Prioritization",
+            "Which population/risk indicators should drive prioritization (size, prevalence, access, equity factors)?"
+            if not is_mdsi else
+            "Confirm prioritization inputs: settlement membership living on-settlement (latest), obesity/metabolic syndrome prevalence, and any access-to-care constraints to weigh."
+        ))
 
-    # Capacity
     if missing["capacity"]:
-        if is_mdsi:
-            qs.append(("Capacity",
-                       "What is the realistic per-team screening rate (clients/day) and operating schedule (days/week, weeks/3-month window)?"))
-        else:
-            qs.append(("Capacity",
-                       "What per-team throughput and operating schedule should be used for capacity calculations?"))
+        qs.append((
+            "Capacity",
+            "What per-team throughput and operating schedule should be used for capacity calculations?"
+            if not is_mdsi else
+            "What is the realistic per-team screening rate (clients/day) and operating schedule (days/week, weeks/3-month window)?"
+        ))
 
-    # Cost
     if missing["cost"]:
-        if is_mdsi:
-            qs.append(("Cost",
-                       "Provide startup cost per client and ongoing cost per client/visit (or total program costs) to price scenarios like 1,200 screens."))
-        else:
-            qs.append(("Cost",
-                       "Provide fixed setup costs and variable cost per client to model total program spend."))
+        qs.append((
+            "Cost",
+            "Provide fixed setup costs and variable cost per client to model total program spend."
+            if not is_mdsi else
+            "Provide startup cost per client and ongoing cost per client/visit (or total program costs) to price scenarios like 1,200 screens."
+        ))
 
-    # Clinical
     if missing["clinical"]:
-        if is_mdsi:
-            qs.append(("Clinical",
-                       "What longitudinal deltas should we expect (e.g., ΔA1c, ΔBP, ΔBMI, lipids) from repeat screenings, and over what interval?"))
-        else:
-            qs.append(("Clinical",
-                       "Which clinical indicators and expected effect sizes should be tracked for outcomes?"))
-
-    # Recommendations – always ask one targeted planning question last
-    if is_mdsi:
-        qs.append(("Recommendations",
-                   "Are there community constraints (events/seasonality/cultural protocols) that should shape routing and visit cadence?"))
-    else:
-        qs.append(("Recommendations",
-                   "Any operational constraints (scheduling, staffing, partnerships) we should incorporate into deployment modeling?"))
-
-    # Cap at 5 groups
-    qs = qs[:5]
+        qs.append((
+            "Clinical",
+            "Which clinical indicators and expected effect sizes should be tracked for outcomes?"
+            if not is_mdsi else
+            "What longitudinal deltas should we expect (e.g., ΔA1c, ΔBP, ΔBMI, lipids) from repeat screenings, and over what interval?"
+        ))
+
+    qs.append((
+        "Recommendations",
+        "Any operational constraints (scheduling, staffing, partnerships) we should incorporate into deployment modeling?"
+        if not is_mdsi else
+        "Are there community constraints (events/seasonality/cultural protocols) that should shape routing and visit cadence?"
+    ))
 
-    # Assemble markdown
+    qs = qs[:5]
     out = ["**Clarification Questions**"]
     current_group = None
     for grp, q in qs:
@@ -393,7 +379,6 @@ def clarityops_reply(user_msg, history, tz, uploaded_files_paths, awaiting_answe
             # ---------- Normal conversational chat ----------
             out = cohere_chat(safe_in, history) if USE_HOSTED_COHERE else None
             if not out:
-                # Small system nudge for normal chat
                 model, tokenizer = load_local_model()
                 tiny = [{"role": "system", "content": "You are a helpful assistant."}]
                 for u, a in _iter_user_assistant(history):
@@ -455,7 +440,6 @@ def clarityops_reply(user_msg, history, tz, uploaded_files_paths, awaiting_answe
         else:
             artifact_block = "Uploaded Data Files (summarized):\n- <none>"
 
-        # Build system preamble
         scenario_block = safe_in if len((safe_in or "")) > 0 else ""
         system_preamble = build_system_preamble(
             snapshot=snapshot,
@@ -518,8 +502,11 @@ html, body, .gradio-container { height: 100vh; }
 #hero-wrap { height: 70vh; display: grid; place-items: center; }
 #hero { text-align: center; }
 #hero h2 { color: #0f172a; font-weight: 800; font-size: 32px; margin-bottom: 22px; }
-#hero .search-row { width: min(860px, 92vw); margin: 0 auto; display: flex; gap: 8px; }
+#hero .search-row { width: min(860px, 92vw); margin: 0 auto; display: flex; gap: 8px; align-items: stretch; }
 #hero .search-row .hero-box { flex: 1 1 auto; }
+/* Force equal heights between the single-line textbox and the submit button */
+#hero .search-row .hero-box textarea { height: 52px !important; }
+#hero-send > button { height: 52px !important; padding: 0 18px !important; border-radius: 12px !important; }
 #hero .hint { color: #334155; margin-top: 10px; font-size: 13px; opacity: 0.9; }
 
 /* CHAT */
@@ -527,6 +514,11 @@ html, body, .gradio-container { height: 100vh; }
 .chatbot header, .chatbot .label, .chatbot .label-wrap { display: none !important; }
 .message.user, .message.bot { background: var(--brand-accent) !important; color: var(--brand-text-light) !important; border-radius: 12px !important; padding: 8px 12px !important; }
 textarea, input, .gr-input { border-radius: 12px !important; }
+
+/* Chat input row equal heights */
+#chat-input-row { align-items: stretch; }
+#chat-msg textarea { height: 52px !important; }
+#chat-send > button, #chat-clear > button { height: 52px !important; padding: 0 18px !important; border-radius: 12px !important; }
 """
 
 # ---------- UI ----------
@@ -542,7 +534,7 @@ with gr.Blocks(theme=theme, css=custom_css, analytics_enabled=False) as demo:
                     lines=1,
                     elem_classes="hero-box"
                 )
-                hero_send = gr.Button("➤", scale=0)
+                hero_send = gr.Button("➤", scale=0, elem_id="hero-send")
             gr.Markdown('<div class="hint">Scenario Mode triggers when you type the word <b>scenario</b> or upload files. Phase&nbsp;1 asks dynamic clarifications; Phase&nbsp;2 returns a structured analysis.</div>')
 
     # --- MAIN APP (hidden until first message) ---
@@ -553,15 +545,17 @@ with gr.Blocks(theme=theme, css=custom_css, analytics_enabled=False) as demo:
                 label="Upload docs/images (PDF, DOCX, CSV, PNG, JPG)",
                 file_types=["file"], file_count="multiple", height=68
             )
-        with gr.Row():
+        with gr.Row(elem_id="chat-input-row"):
             msg = gr.Textbox(
                 label="",
                 show_label=False,
                 placeholder="Continue here. Paste scenario details (include the word 'scenario' to trigger), add files above.",
-                scale=10
+                scale=10,
+                elem_id="chat-msg",
+                lines=1,
             )
-            send = gr.Button("Send", scale=1)
-            clear = gr.Button("Clear chat", scale=1)
+            send = gr.Button("Send", scale=1, elem_id="chat-send")
+            clear = gr.Button("Clear chat", scale=1, elem_id="chat-clear")
 
     # ---- State
     state_history = gr.State(value=[])
@@ -638,3 +632,4 @@ with gr.Blocks(theme=theme, css=custom_css, analytics_enabled=False) as demo:
 if __name__ == "__main__":
     port = int(os.environ.get("PORT", "7860"))
     demo.launch(server_name="0.0.0.0", server_port=port, show_api=False, max_threads=8)
+