Jun 30 - Fix Admin can't edit user profile

config.py

@@ -409,6 +409,24 @@ def initialize_database():
             conn.commit()
             logger.info("Migration: added idx_activity_log_time index to activity_log.")
 
+        # ── ai_analysis_log: add document_text column if missing ──────────────
+        cursor.execute(
+            """
+            SELECT COUNT(*) FROM information_schema.COLUMNS
+            WHERE TABLE_SCHEMA = DATABASE()
+              AND TABLE_NAME   = 'ai_analysis_log'
+              AND COLUMN_NAME  = 'document_text'
+            """
+        )
+        (has_doc_text,) = cursor.fetchone()
+        if not has_doc_text:
+            cursor.execute(
+                "ALTER TABLE ai_analysis_log "
+                "ADD COLUMN document_text MEDIUMTEXT NULL AFTER criteria_snapshot"
+            )
+            conn.commit()
+            logger.info("Migration: added document_text column to ai_analysis_log.")
+
         # ── Seed app_settings from environment variables (first-run bootstrap) ─
         # Uses INSERT IGNORE so values already saved via the Admin UI are never
         # overwritten — .env only fills in keys that are completely absent.

models.py

@@ -1367,15 +1367,17 @@ def delete_criterion(admin_id: int, criterion_id: int):
 
 
 def save_ai_analysis(user_id: int, file_names: str, model: str,
-                     verdict, criteria_snapshot, summary_text: str) -> int:
+                     verdict, criteria_snapshot, summary_text: str,
+                     document_text: str = None) -> int:
     conn = None
     try:
         conn = get_connection()
         cur = conn.cursor()
         cur.execute(
-            "INSERT INTO ai_analysis_log (user_id, file_names, model, verdict, criteria_snapshot, summary_text) "
-            "VALUES (%s,%s,%s,%s,%s,%s)",
-            (user_id, file_names, model, verdict, criteria_snapshot, summary_text),
+            "INSERT INTO ai_analysis_log "
+            "(user_id, file_names, model, verdict, criteria_snapshot, document_text, summary_text) "
+            "VALUES (%s,%s,%s,%s,%s,%s,%s)",
+            (user_id, file_names, model, verdict, criteria_snapshot, document_text, summary_text),
         )
         conn.commit()
         new_id = cur.lastrowid

routes/ai_summary.py

@@ -100,7 +100,8 @@ def analyze():
     ])
     analysis_id = save_ai_analysis(
         user["id"], ", ".join(file_names), model,
-        result.get("verdict"), criteria_snap, result.get("summary", "")
+        result.get("verdict"), criteria_snap, result.get("summary", ""),
+        document_text=combined,
     )
     log_action(user["id"], "AI_ANALYSIS", "ai_analysis_log", analysis_id,
                f"AI analysis on {len(file_names)} file(s). Verdict: {result.get('verdict')}.")
@@ -182,48 +183,113 @@ def _extract_text(file_obj, ext: str) -> str:
 # Office address used as origin for distance/travel-time estimates.
 _OFFICE_ADDRESS = "2815 Hartland Road, Falls Church, VA 22043, USA"
 
-# Stage 1 — extraction prompt (always sent)
-_EXTRACTION_PROMPT = """You are an expert government procurement analyst.
-The user has provided {n} document(s). Treat all provided content as a single combined source — do not analyze each file individually. Extract the following information once, consolidating details from all documents.
+# Document text limit per API call.
+# Stage 1 prompt template is ~1.8 KB overhead; 14 KB of doc text keeps the total
+# JSON payload well under Groq's request size limit on all plan tiers.
+_TEXT_LIMIT = 14_000
 
-IMPORTANT — Our office is located at:
-  {office}
-Use this as the ORIGIN address for all driving distance and travel time calculations in field #9 below.
+# Analyst persona — injected as the system message in every API call.
+_SYSTEM_PROMPT = (
+    "You are a senior government procurement analyst supporting a small business BD team. "
+    "Extract and organize solicitation information with precision. "
+    "Format all output in clean Markdown with tables and section headers. "
+    "Write \"Not specified\" for any field not found in the documents — never guess."
+)
 
-Extract and clearly label the following fields (write "N/A" if not found):
+# Stage 1 — extraction prompt (always sent).
+_EXTRACTION_PROMPT = """\
+Analyze the {n} document(s) below as one combined source. Do not analyze files individually.
+Write "Not specified in the document." for any field not found — never guess.
+Our office address (use as origin for all travel estimates): {office}
 
-  1. Solicitation Number
-  2. Solicitation Type  (e.g. RFP, RFQ, IFB, etc.)
-  3. Set-Aside          (e.g. Small Business, 8(a), N/A)
-  4. Description / Scope of Work
-  5. Work Site / Location(s)
-  6. Pre-Proposal Conference / Site-Visit  (date, time, full address)
-  7. Point of Contact (POC)  (name, phone, email)
-  8. Total Square Footage    (if applicable)
-  9. Driving Distance & Travel Time
-     - Origin: {office}
-     - Destination: Pre-Proposal Conference or primary Work Site address
-     - Provide your best estimate of driving distance (miles) and typical driving time using major highways
-     - Note that these are AI estimates; actual times may vary with traffic
- 10. Last Day to Submit Questions
- 11. Due Date & Time
- 12. Any other notable requirements or deadlines
+---
 
-Then provide a detailed OVERALL SUMMARY covering:
+## Solicitation Details
 
-  A. Scope of Work
-  B. Contract Period
-  C. Proposal Submission Requirements
-  D. Key Deadlines & Action Items
+| Field | Value |
+|---|---|
+| Solicitation Number | |
+| Solicitation Type | (RFP / RFQ / IFB / IDIQ / BPA / etc.) |
+| Set-Aside | (Small Business / 8(a) / SDVOSB / HUBZone / WOSB / Unrestricted / etc.) |
+| Issuing Agency / Office | |
+| Contract Type | (FFP / T&M / Cost-Plus / IDIQ / etc.) |
+| Contract Period | |
+| NAICS Code | |
+| Estimated Value | |
+| Work Site / Location(s) | |
+| Total Square Footage | |
+| Last Day to Submit Questions | |
+| **Proposal Due Date & Time** | |
+| Award / Period of Performance Start | |
 
-Be precise, detailed, and use bullet points throughout.
-If information is not explicitly stated in the documents, note it as "Not specified in the document."
+---
+
+## Pre-Proposal Conference / Site Visit
+
+| Field | Value |
+|---|---|
+| Date & Time | |
+| Full Address | |
+| Attendance | (Mandatory / Optional / N/A) |
+| RSVP Required | |
+
+---
+
+## Point of Contact
+
+| Field | Value |
+|---|---|
+| Name & Title | |
+| Phone | |
+| Email | |
+| Questions Submission Method | |
+
+---
+
+## Travel Estimate
+
+| Field | Value |
+|---|---|
+| Origin | {office} |
+| Destination | (Pre-Proposal Conference address or primary work site) |
+| Estimated Driving Distance | |
+| Estimated Drive Time | |
+
+*(AI estimates — verify with a mapping service before scheduling.)*
+
+---
+
+## Scope of Work
+
+*(Detail the required services, deliverables, and performance standards. Use bullet points.)*
+
+---
+
+## Notable Requirements
+
+*(Security clearances, bonding, certifications, teaming restrictions, tight timelines, incumbent indicators, or other bid/no-bid risk factors. Use bullet points.)*
+
+---
+
+## Overall Summary
+
+**A. Scope of Work:**
+
+**B. Contract Period & Value:**
+
+**C. Proposal Submission Requirements:**
+
+**D. Key Deadlines & Action Items:**
+
+---
 
 DOCUMENTS:
 {documents}"""
 
-# Stage 2 — criteria evaluation suffix (appended only when active criteria exist)
-_CRITERIA_PROMPT_SUFFIX = """
+# Criteria evaluation — appended to the extraction prompt in the same API call.
+# A single call avoids the rate-limit (429) that two back-to-back calls trigger
+# on Groq's free tier.
+_CRITERIA_SUFFIX = """
 
 ================================================================================
 OPPORTUNITY ALIGNMENT EVALUATION
@@ -255,23 +321,21 @@ in plain business language."""
 
 
 def _call_groq(api_key: str, model: str, text: str, criteria: list) -> dict:
-    """Call the Groq chat completions REST API directly (no SDK required)."""
-    import re
+    """Single Groq API call: extraction + optional criteria evaluation in one request."""
+    truncated = len(text) > _TEXT_LIMIT
+    doc_text  = text[:_TEXT_LIMIT]
+    n         = doc_text.count("=== ") or 1
 
-    n = text.count("=== ") or 1  # count file separators for the prompt header
-    truncated = len(text) > 14000
-
-    # Build the two-stage prompt matching the desktop app exactly
     prompt = _EXTRACTION_PROMPT.format(
-        n=n, office=_OFFICE_ADDRESS, documents=text[:14000]
+        n=n, office=_OFFICE_ADDRESS, documents=doc_text
     )
 
     if criteria:
         criteria_list = "\n".join(
-            f"  {i+1}. {c['title']}: {c['description']}"
+            f"{i+1}. **{c['title']}**: {c['description']}"
             for i, c in enumerate(criteria)
         )
-        prompt += _CRITERIA_PROMPT_SUFFIX.format(criteria_list=criteria_list)
+        prompt += _CRITERIA_SUFFIX.format(criteria_list=criteria_list)
 
     response = http_requests.post(
         "https://api.groq.com/openai/v1/chat/completions",
@@ -281,11 +345,14 @@ def _call_groq(api_key: str, model: str, text: str, criteria: list) -> dict:
         },
         json={
             "model":       model,
-            "messages":    [{"role": "user", "content": prompt}],
+            "messages":    [
+                {"role": "system", "content": _SYSTEM_PROMPT},
+                {"role": "user",   "content": prompt},
+            ],
             "max_tokens":  4096,
-            "temperature": 0.2,
+            "temperature": 0.1,
         },
-        timeout=90,
+        timeout=120,
     )
     if not response.ok:
         logger.error(f"Groq API {response.status_code}: {response.text[:300]}")
@@ -293,7 +360,6 @@ def _call_groq(api_key: str, model: str, text: str, criteria: list) -> dict:
 
     content = response.json()["choices"][0]["message"]["content"] or ""
 
-    # Parse the machine-readable RECOMMENDATION label (only present when criteria used)
     verdict = None
     if criteria:
         match = re.search(
@@ -358,6 +424,81 @@ def delete_criterion_view(criterion_id):
     return redirect(url_for("ai_summary.ai_summary"))
 
 
+@ai_summary_bp.route("/chat", methods=["POST"])
+@login_required
+def chat():
+    """Follow-up Q&A about a previously analyzed document."""
+    user = session["user"]
+    data = request.get_json(silent=True) or {}
+    analysis_id = data.get("analysis_id")
+    messages    = data.get("messages") or []
+
+    if not analysis_id:
+        return jsonify({"error": "analysis_id is required."}), 400
+    if not messages or not isinstance(messages, list):
+        return jsonify({"error": "messages is required."}), 400
+
+    record = get_ai_analysis_detail(int(analysis_id))
+    if not record:
+        return jsonify({"error": "Analysis not found."}), 404
+
+    api_key = (os.environ.get("GROQ_API_KEY") or "").strip() or get_setting("groq.api_key", "").strip()
+    if not api_key:
+        return jsonify({"error": "Groq API key is not configured."}), 400
+
+    model = get_setting("groq.model", GROQ_MODELS[0])
+
+    # Prefer raw document text so the AI can answer questions from source material.
+    # Fall back to the stored summary for analyses run before this feature was added.
+    raw_text = (record.get("document_text") or "").strip()
+    if raw_text:
+        context_label = "ORIGINAL DOCUMENT CONTENT"
+        context_body  = raw_text[:12000]
+    else:
+        context_label = "ANALYZED DOCUMENT SUMMARY"
+        context_body  = (record.get("summary_text") or "")[:8000]
+
+    system_msg = (
+        "You are a government procurement analyst assistant. "
+        "The user has questions about a solicitation document. "
+        "Answer based solely on the document content provided below. "
+        "If the information is not present, say so clearly. Be concise and direct.\n\n"
+        f"## {context_label}\n\n" + context_body
+    )
+
+    # Sanitize and cap conversation history at 20 turns
+    api_messages = []
+    for m in messages[-20:]:
+        role    = m.get("role")    if isinstance(m, dict) else None
+        content = (m.get("content") or "").strip() if isinstance(m, dict) else ""
+        if role in ("user", "assistant") and content:
+            api_messages.append({"role": role, "content": content})
+
+    if not api_messages or api_messages[-1]["role"] != "user":
+        return jsonify({"error": "Last message must be from the user."}), 400
+
+    try:
+        response = http_requests.post(
+            "https://api.groq.com/openai/v1/chat/completions",
+            headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
+            json={
+                "model":       model,
+                "messages":    [{"role": "system", "content": system_msg}] + api_messages,
+                "max_tokens":  1024,
+                "temperature": 0.2,
+            },
+            timeout=60,
+        )
+        if not response.ok:
+            logger.error(f"Groq chat {response.status_code}: {response.text[:200]}")
+            response.raise_for_status()
+        reply = response.json()["choices"][0]["message"]["content"] or ""
+        return jsonify({"reply": reply})
+    except Exception as e:
+        logger.error(f"AI chat error: {e}")
+        return jsonify({"error": f"Chat failed: {e}"}), 500
+
+
 @ai_summary_bp.route("/history/<int:analysis_id>")
 @login_required
 def analysis_detail(analysis_id):

templates/admin/users.html

@@ -32,7 +32,7 @@
         <td class="text-muted">{{ u.created_at.strftime('%Y-%m-%d') if u.created_at else '—' }}</td>
         <td class="actions">
           <button class="btn btn-ghost btn-sm js-edit-user"
-            data-user="{{ u|tojson|e }}">✎ Edit</button>
+            data-user='{{ u|tojson }}'>✎ Edit</button>
           {% if u.email %}
           <button class="btn btn-ghost btn-sm js-send-reset"
                   data-id="{{ u.id }}" data-username="{{ u.username }}" data-email="{{ u.email }}"

templates/ai_summary.html

@@ -96,6 +96,7 @@
           <button class="btn btn-secondary btn-sm" id="btn-copy" onclick="copyOutput()" style="display:none">📋 Copy</button>
           <button class="btn btn-secondary btn-sm" id="btn-save" onclick="saveOutput()" style="display:none">💾 Save as TXT</button>
           <button class="btn btn-secondary btn-sm" id="btn-clear" onclick="clearOutput()" style="display:none">🗑 Clear</button>
+          <button class="btn btn-primary btn-sm" id="btn-chat-live" onclick="openChat(_liveAnalysisId)" style="display:none">💬 Chat</button>
         </div>
       </div>
 
@@ -269,16 +270,33 @@
     </div>
     <div class="modal-footer">
       <button class="btn btn-danger btn-sm" id="btn-delete-analysis" style="margin-right:auto;display:none" onclick="deleteAnalysis()">🗑 Delete</button>
+      <button class="btn btn-secondary btn-sm" onclick="openChat(_currentAnalysisId)">💬 Chat</button>
       <button class="btn btn-secondary" onclick="closeModal('modal-history')">Close</button>
     </div>
   </div>
 </div>
 
+<!-- ── Chat Modal ────────────────────────────────────────────── -->
+<div class="modal-overlay" id="modal-chat">
+  <div class="modal chat-modal">
+    <div class="modal-header">
+      <span class="modal-title">💬 Ask AI about this document</span>
+      <button class="modal-close" onclick="closeModal('modal-chat')">✕</button>
+    </div>
+    <div id="chat-messages" class="chat-messages"></div>
+    <div class="chat-input-row">
+      <input type="text" id="chat-input" class="chat-input" placeholder="Ask a question about this document…" autocomplete="off">
+      <button class="btn btn-primary" id="btn-chat-send" onclick="sendChatMessage()">Send</button>
+    </div>
+  </div>
+</div>
+
 <!-- marked.js for markdown rendering -->
 <script src="https://cdnjs.cloudflare.com/ajax/libs/marked/9.1.6/marked.min.js"></script>
 
 <script>
 var IS_ADMIN = {{ 'true' if is_admin else 'false' }};
+var _liveAnalysisId = null;   // set after a live analysis completes
 
 /* ─── Markdown renderer config ──────────────────────────────── */
 marked.setOptions({ breaks: true, gfm: true });
@@ -310,16 +328,6 @@ var _rawText = '';   // kept for copy/save
 
 function showResult(data) {
   _rawText = data.summary || '';
-  var fileList = (data.file_names || '').split(', ').map(function(f) {
-    return '  - ' + f;
-  }).join('\n');
-  var criteriaNote = data.criteria_count > 0
-    ? 'Criteria evaluated: ' + data.criteria_count
-    : 'No evaluation criteria configured.';
-  var header = 'AI Extraction  |  Model: ' + (data.model || '')
-    + '\nFiles analyzed (' + (data.file_count || 1) + '):\n' + fileList
-    + '\n' + criteriaNote
-    + '\n' + '='.repeat(60);
 
   // Verdict banner
   var banner = document.getElementById('verdict-banner');
@@ -331,15 +339,36 @@ function showResult(data) {
     banner.innerHTML = '';
   }
 
-  // Render output: header as plain preformatted, then markdown body
-  document.getElementById('ai-output').innerHTML =
-    '<pre class="ai-header-block">' + escHtml(header) + '</pre>'
-    + '<div class="ai-rendered-output">' + renderAI(_rawText) + '</div>';
+  // Meta pill bar (replaces old <pre> header block)
+  var files = (data.file_names || '').split(', ').filter(Boolean);
+  var metaHtml = '<div class="ai-meta-bar">'
+    + '<span class="ai-meta-pill">' + escHtml(data.model || 'AI') + '</span>'
+    + '<span class="ai-meta-pill">📄 ' + files.length + ' file' + (files.length !== 1 ? 's' : '')
+    + (files.length <= 3 ? ': ' + files.map(escHtml).join(', ') : '') + '</span>'
+    + (data.criteria_count > 0 ? '<span class="ai-meta-pill ai-meta-pill-green">✓ ' + data.criteria_count + ' criteria evaluated</span>' : '')
+    + (data.truncated ? '<span class="ai-meta-pill ai-meta-pill-warn">⚠ Document truncated to first ~14 000 chars</span>' : '')
+    + '</div>';
+
+  // Render markdown, then colorize evaluation keywords
+  var rendered = document.createElement('div');
+  rendered.className = 'ai-rendered-output';
+  rendered.innerHTML = renderAI(_rawText);
+  colorizeEval(rendered);
+
+  var outputEl = document.getElementById('ai-output');
+  outputEl.innerHTML = metaHtml;
+  outputEl.appendChild(rendered);
 
   // Show action buttons
   document.getElementById('btn-copy').style.display  = '';
   document.getElementById('btn-save').style.display  = '';
   document.getElementById('btn-clear').style.display = '';
+
+  // Show chat button and remember which analysis is loaded
+  if (data.analysis_id) {
+    _liveAnalysisId = data.analysis_id;
+    document.getElementById('btn-chat-live').style.display = '';
+  }
 }
 
 function clearOutput() {
@@ -351,6 +380,8 @@ function clearOutput() {
   document.getElementById('btn-copy').style.display      = 'none';
   document.getElementById('btn-save').style.display      = 'none';
   document.getElementById('btn-clear').style.display     = 'none';
+  document.getElementById('btn-chat-live').style.display = 'none';
+  _liveAnalysisId = null;
 }
 
 function copyOutput() {
@@ -586,8 +617,9 @@ document.querySelectorAll('.history-row').forEach(function(row) {
           } catch(e) { /* ignore malformed snapshot */ }
         }
 
-        document.getElementById('hist-body').innerHTML =
-          renderAI(d.summary_text || '');
+        var histBody = document.getElementById('hist-body');
+        histBody.innerHTML = renderAI(d.summary_text || '');
+        colorizeEval(histBody);
         if (IS_ADMIN) {
           document.getElementById('btn-delete-analysis').style.display = '';
         }
@@ -638,6 +670,112 @@ function escHtml(str) {
     return {'&':'&amp;','<':'&lt;','>':'&gt;','"':'&quot;',"'":'&#39;'}[c];
   });
 }
+
+function colorizeEval(container) {
+  container.querySelectorAll('li, td, p').forEach(function(el) {
+    if (el.querySelector('ul,ol,table,div')) return;  // skip block containers
+    var h = el.innerHTML;
+    // Null-byte placeholders prevent cascading replacements
+    h = h.replace(/DOES NOT MEET/g,   '\x00NM\x00');
+    h = h.replace(/PARTIALLY MEETS/g, '\x00PM\x00');
+    h = h.replace(/\bMEETS\b/g,       '\x00M\x00');
+    h = h.replace(/CANNOT DETERMINE/g,'\x00CD\x00');
+    h = h.replace(/\x00NM\x00/g,  '<span class="eval-badge eval-not-meet">DOES NOT MEET</span>');
+    h = h.replace(/\x00PM\x00/g,  '<span class="eval-badge eval-partial">PARTIALLY MEETS</span>');
+    h = h.replace(/\x00M\x00/g,   '<span class="eval-badge eval-meets">MEETS</span>');
+    h = h.replace(/\x00CD\x00/g,  '<span class="eval-badge eval-unclear">CANNOT DETERMINE</span>');
+    h = h.replace(/Not specified in the document\./g,
+                  '<span class="eval-missing">Not specified in the document.</span>');
+    el.innerHTML = h;
+  });
+}
+
+/* ─── Chat ──────────────────────────────────────────────────── */
+var _chatAnalysisId = null;
+var _chatMessages   = [];
+
+function openChat(analysisId) {
+  if (!analysisId) { alert('No analysis loaded.'); return; }
+  _chatAnalysisId = analysisId;
+  _chatMessages   = [];
+  document.getElementById('chat-messages').innerHTML = '';
+  document.getElementById('chat-input').value = '';
+  // Close history modal if open, then open chat
+  closeModal('modal-history');
+  openModal('modal-chat');
+  _appendChatMsg('assistant',
+    'Hi! Ask me anything about this solicitation — dates, scope, contacts, requirements, and more.');
+  setTimeout(function() { document.getElementById('chat-input').focus(); }, 150);
+}
+
+function _appendChatMsg(role, content) {
+  var wrap = document.createElement('div');
+  wrap.className = 'chat-msg chat-msg-' + role;
+  var bubble = document.createElement('div');
+  bubble.className = 'chat-bubble';
+  bubble.innerHTML = renderAI(content);
+  wrap.appendChild(bubble);
+  var box = document.getElementById('chat-messages');
+  box.appendChild(wrap);
+  box.scrollTop = box.scrollHeight;
+}
+
+function _appendTyping() {
+  var wrap = document.createElement('div');
+  wrap.className = 'chat-msg chat-msg-assistant';
+  wrap.id = 'chat-typing';
+  wrap.innerHTML = '<div class="chat-bubble chat-typing"><span></span><span></span><span></span></div>';
+  var box = document.getElementById('chat-messages');
+  box.appendChild(wrap);
+  box.scrollTop = box.scrollHeight;
+}
+
+async function sendChatMessage() {
+  var input = document.getElementById('chat-input');
+  var text  = input.value.trim();
+  if (!text || !_chatAnalysisId) return;
+
+  var sendBtn = document.getElementById('btn-chat-send');
+  input.value    = '';
+  input.disabled = true;
+  sendBtn.disabled = true;
+
+  _chatMessages.push({ role: 'user', content: text });
+  _appendChatMsg('user', text);
+  _appendTyping();
+
+  try {
+    var resp = await fetch('/ai-summary/chat', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json', 'X-CSRFToken': getCsrfToken() },
+      body: JSON.stringify({ analysis_id: _chatAnalysisId, messages: _chatMessages }),
+    });
+    var data = await resp.json();
+    var typing = document.getElementById('chat-typing');
+    if (typing) typing.remove();
+
+    if (data.error) {
+      _chatMessages.pop();   // discard the failed user message
+      _appendChatMsg('assistant', '⚠ ' + escHtml(data.error));
+    } else {
+      _chatMessages.push({ role: 'assistant', content: data.reply });
+      _appendChatMsg('assistant', data.reply);
+    }
+  } catch(e) {
+    var typing = document.getElementById('chat-typing');
+    if (typing) typing.remove();
+    _chatMessages.pop();
+    _appendChatMsg('assistant', '⚠ Request failed. Please try again.');
+  } finally {
+    input.disabled   = false;
+    sendBtn.disabled = false;
+    input.focus();
+  }
+}
+
+document.getElementById('chat-input').addEventListener('keydown', function(e) {
+  if (e.key === 'Enter' && !e.shiftKey) { e.preventDefault(); sendChatMessage(); }
+});
 </script>
 
 <style>
@@ -663,45 +801,85 @@ function escHtml(str) {
 .ai-placeholder{
   padding:2rem 1.5rem;color:var(--text-muted);
 }
-.ai-header-block{
-  background:var(--bg-subtle);border-bottom:1px solid var(--border);
-  padding:.85rem 1.4rem;font-family:'DM Mono',monospace;font-size:.78rem;
-  color:var(--text-secondary);margin:0;white-space:pre-wrap;line-height:1.6;
-}
+
+/* ── Meta pill bar ─────────────────────────────────────────── */
 .ai-meta-bar{
-  padding:.6rem 1.5rem;font-size:.78rem;font-family:'DM Mono',monospace;
-  color:var(--text-muted);background:var(--bg-subtle);
+  display:flex;flex-wrap:wrap;gap:.4rem;align-items:center;
+  padding:.7rem 1.4rem;background:var(--bg-subtle);
   border-bottom:1px solid var(--border);
 }
+.ai-meta-pill{
+  display:inline-flex;align-items:center;
+  font-size:.72rem;font-family:'DM Mono',monospace;
+  background:var(--bg-card,#fff);color:var(--text-secondary);
+  border:1px solid var(--border);border-radius:999px;
+  padding:.18rem .65rem;white-space:nowrap;
+}
+.ai-meta-pill-green{border-color:#86efac;color:#15803d;background:#f0fdf4}
+.ai-meta-pill-warn{border-color:#fcd34d;color:#92400e;background:#fffbeb}
 
 /* ── Rendered markdown output ──────────────────────────────── */
 .ai-rendered-output{
-  padding:1.1rem 1.4rem 1.5rem;
-  font-size:.9rem;line-height:1.8;color:var(--text-secondary);
+  padding:1.4rem 1.75rem 2rem;
+  font-size:.9rem;line-height:1.85;color:var(--text);
 }
-.ai-rendered-output h1,.ai-rendered-output h2{
-  font-size:1rem;font-weight:700;color:var(--text);
-  margin:1.4rem 0 .5rem;padding-bottom:.3rem;
+.ai-rendered-output h1{
+  font-size:1.05rem;font-weight:800;color:var(--text);
+  margin:1.8rem 0 .6rem;padding-bottom:.4rem;
+  border-bottom:2px solid var(--accent);
+}
+.ai-rendered-output h2{
+  font-size:.97rem;font-weight:700;color:var(--text);
+  margin:1.5rem 0 .5rem;padding-bottom:.3rem;
   border-bottom:1px solid var(--border);
 }
-.ai-rendered-output h3,.ai-rendered-output h4{
-  font-size:.9rem;font-weight:700;color:var(--text);margin:1rem 0 .35rem;
+.ai-rendered-output h3{
+  font-size:.8rem;font-weight:700;letter-spacing:.06em;text-transform:uppercase;
+  color:var(--text-secondary);margin:1.25rem 0 .35rem;
 }
-.ai-rendered-output p{margin:.35rem 0}
+.ai-rendered-output h4{font-size:.9rem;font-weight:700;color:var(--text);margin:.9rem 0 .25rem}
+.ai-rendered-output p{margin:.4rem 0}
 .ai-rendered-output strong{color:var(--text);font-weight:700}
-.ai-rendered-output ul,.ai-rendered-output ol{
-  padding-left:1.4rem;margin:.35rem 0;
-}
-.ai-rendered-output li{margin:.2rem 0}
-.ai-rendered-output hr{
-  border:none;border-top:2px solid var(--border);margin:1.25rem 0;
-}
+.ai-rendered-output em{font-style:italic;color:var(--text-secondary)}
+.ai-rendered-output ul,.ai-rendered-output ol{padding-left:1.5rem;margin:.45rem 0 .65rem}
+.ai-rendered-output li{margin:.3rem 0;line-height:1.75}
+.ai-rendered-output hr{border:none;border-top:2px solid var(--border);margin:1.75rem 0}
 .ai-rendered-output pre,.ai-rendered-output code{
   font-family:'DM Mono',monospace;font-size:.82rem;
   background:var(--bg-subtle);border-radius:var(--r-sm);
 }
-.ai-rendered-output pre{padding:.75rem 1rem;overflow-x:auto}
-.ai-rendered-output code{padding:.1rem .3rem}
+.ai-rendered-output pre{padding:.75rem 1rem;overflow-x:auto;border:1px solid var(--border)}
+.ai-rendered-output code{padding:.15rem .35rem;border:1px solid var(--border)}
+
+/* Tables ── */
+.ai-rendered-output table{
+  width:100%;border-collapse:collapse;font-size:.845rem;
+  margin:.75rem 0 1.25rem;border:1px solid var(--border);
+  border-radius:var(--r-sm);overflow:hidden;display:table;
+}
+.ai-rendered-output th{
+  background:var(--bg-subtle);color:var(--text);font-weight:700;
+  padding:.5rem .9rem;border-bottom:2px solid var(--border);text-align:left;
+  font-size:.75rem;text-transform:uppercase;letter-spacing:.05em;white-space:nowrap;
+}
+.ai-rendered-output td{
+  padding:.45rem .9rem;border-bottom:1px solid var(--border);
+  vertical-align:top;color:var(--text-secondary);
+}
+.ai-rendered-output tr:last-child td{border-bottom:none}
+.ai-rendered-output tbody tr:hover td{background:var(--bg-subtle)}
+.ai-rendered-output td:first-child{font-weight:600;color:var(--text);width:38%;white-space:nowrap}
+
+/* Evaluation badges ── */
+.eval-badge{
+  display:inline-block;font-size:.72rem;font-weight:700;
+  padding:.1rem .5rem;border-radius:999px;border:1px solid;letter-spacing:.02em;
+}
+.eval-meets{background:#f0fdf4;color:#15803d;border-color:#86efac}
+.eval-not-meet{background:#fef2f2;color:#dc2626;border-color:#fca5a5}
+.eval-partial{background:#fffbeb;color:#92400e;border-color:#fcd34d}
+.eval-unclear{background:var(--bg-subtle);color:var(--text-secondary);border-color:var(--border)}
+.eval-missing{color:var(--text-muted);font-style:italic}
 
 /* ── Criteria list ─────────────────────────────────────────── */
 .criteria-list{display:flex;flex-direction:column}
@@ -749,5 +927,64 @@ function escHtml(str) {
   .ai-layout{grid-template-columns:1fr}
   .ai-output-body{max-height:60vh}
 }
+
+/* ── Chat modal ────────────────────────────────────────────── */
+.chat-modal{
+  max-width:660px;width:100%;
+  display:flex;flex-direction:column;
+  height:75vh;max-height:600px;
+}
+.chat-messages{
+  flex:1;overflow-y:auto;
+  padding:.85rem 1.2rem;
+  display:flex;flex-direction:column;gap:.6rem;
+  background:var(--bg-subtle);
+}
+.chat-msg{display:flex}
+.chat-msg-user{justify-content:flex-end}
+.chat-msg-assistant{justify-content:flex-start}
+.chat-bubble{
+  max-width:82%;padding:.55rem .85rem;
+  border-radius:1rem;font-size:.865rem;line-height:1.6;
+}
+.chat-msg-user .chat-bubble{
+  background:var(--accent);color:#fff;
+  border-bottom-right-radius:.25rem;
+}
+.chat-msg-assistant .chat-bubble{
+  background:var(--bg-card,#fff);color:var(--text);
+  border:1px solid var(--border);
+  border-bottom-left-radius:.25rem;
+}
+.chat-bubble p{margin:.2rem 0}
+.chat-bubble p:first-child{margin-top:0}
+.chat-bubble p:last-child{margin-bottom:0}
+.chat-bubble ul,.chat-bubble ol{margin:.3rem 0;padding-left:1.2rem}
+.chat-bubble li{margin:.15rem 0}
+.chat-bubble strong{font-weight:700}
+.chat-bubble table{border-collapse:collapse;font-size:.82rem;width:100%}
+.chat-bubble th,.chat-bubble td{border:1px solid var(--border);padding:.2rem .5rem;text-align:left}
+.chat-msg-user .chat-bubble strong{color:#fff}
+/* Typing indicator */
+.chat-typing{display:flex;align-items:center;gap:4px;padding:.55rem .75rem}
+.chat-typing span{
+  display:inline-block;width:7px;height:7px;border-radius:50%;
+  background:var(--text-muted);animation:chatBounce 1.2s infinite;
+}
+.chat-typing span:nth-child(2){animation-delay:.2s}
+.chat-typing span:nth-child(3){animation-delay:.4s}
+@keyframes chatBounce{0%,80%,100%{transform:translateY(0)}40%{transform:translateY(-6px)}}
+/* Input row */
+.chat-input-row{
+  display:flex;gap:.5rem;padding:.75rem 1rem;
+  border-top:1px solid var(--border);background:var(--bg-card,#fff);
+  border-radius:0 0 var(--r) var(--r);
+}
+.chat-input{
+  flex:1;padding:.45rem .75rem;border:1px solid var(--border);
+  border-radius:var(--r-sm);font-family:inherit;font-size:.875rem;
+  background:var(--bg);color:var(--text);
+}
+.chat-input:focus{outline:none;border-color:var(--accent);box-shadow:0 0 0 3px var(--accent-light,rgba(59,130,246,.15))}
 </style>
 {% endblock %}