feat: AI chat session conclusion + survey completion & management

AI Assistant - Conclude Session:
- 3-step modal: select outcome (resolved/escalated/paused), add notes, AI-generated summary
- AI generates structured ticket notes from conversation transcript (PSA-ready format)
- Copy to clipboard for pasting into ticketing systems
- "Resume in New Chat" for paused sessions (pre-loads context into new chat)
- Backend: POST /chats/{id}/conclude endpoint, conclusion_summary/outcome/concluded_at fields
- Migration 048: add conclusion fields to assistant_chats

Survey Completion Flow:
- Email-to-self option after submission (branded HTML email with formatted responses)
- Finish button navigates to /survey/thank-you page
- Thank you page with close-window message and feedback email callout
- Already-submitted state updated with same messaging
- Backend: POST /survey/email-copy public endpoint

Survey Admin Management:
- Read/unread indicators (cyan dot, bold name, auto-mark on expand)
- Unread count stat card
- Per-row context menu: mark read/unread, archive/unarchive, delete
- Bulk actions bar: select all, mark read/unread, archive, delete
- Show Archived toggle to filter archived responses
- Backend: 7 new admin endpoints (read, unread, archive, unarchive, delete, bulk)
- Migration 049: add is_read, archived_at to survey_responses

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/services/assistant_chat_service.py

@@ -228,6 +228,117 @@ def _auto_title(message: str) -> str:
     return title
 
 
+CONCLUSION_SYSTEM_PROMPT = """\
+You are a ticket documentation specialist for MSP (Managed Service Provider) teams. \
+Your job is to transform an AI troubleshooting conversation into clean, professional \
+ticket notes that can be pasted directly into a PSA/ticketing system (ConnectWise, \
+Autotask, HaloPSA, etc.).
+
+## Output Format
+
+Generate a structured summary using this exact format:
+
+**Subject:** [One-line summary of the issue]
+
+**Outcome:** {outcome_label}
+
+**Problem Description:**
+[2-3 sentence summary of the original problem]
+
+**Steps Taken:**
+1. [Step] — [Result/finding]
+2. [Step] — [Result/finding]
+(list all troubleshooting steps from the conversation)
+
+**Current Status:**
+[Where things stand now — what was resolved, what remains]
+
+{notes_section}
+
+**Key Findings:**
+- [Important discovery or configuration detail]
+- [Any relevant error codes, settings, or values identified]
+
+{resume_section}
+
+## Rules
+- Be concise but thorough — these notes will be read by another engineer
+- Include specific technical details (commands run, error messages, config values)
+- Use plain text formatting (no HTML) — bold with ** is fine
+- Do NOT include conversational filler, greetings, or meta-commentary
+- Extract ALL actionable steps from the conversation, in chronological order
+- If the conversation identified root cause, state it clearly
+"""
+
+
+async def generate_conclusion_summary(
+    chat: "AssistantChat",
+    outcome: str,
+    notes: str | None = None,
+) -> str:
+    """Generate a ticket-ready summary from a concluded chat conversation."""
+    outcome_labels = {
+        "resolved": "Resolved",
+        "escalated": "Escalated",
+        "paused": "Paused — To Be Continued",
+    }
+    outcome_label = outcome_labels.get(outcome, outcome)
+
+    notes_section = ""
+    if notes:
+        notes_section = f"\n**Engineer Notes:**\n{notes}\n"
+
+    resume_section = ""
+    if outcome == "paused":
+        resume_section = (
+            "\n**Next Steps (for resumption):**\n"
+            "- [What needs to happen next]\n"
+            "- [Any pending actions or follow-ups]\n"
+        )
+    elif outcome == "escalated":
+        resume_section = (
+            "\n**Escalation Details:**\n"
+            "- [Reason for escalation]\n"
+            "- [Recommended next steps for receiving team/tier]\n"
+        )
+
+    # Build the conversation transcript for the AI
+    transcript_lines = []
+    for msg in chat.messages:
+        role_label = "ENGINEER" if msg["role"] == "user" else "AI ASSISTANT"
+        transcript_lines.append(f"[{role_label}]: {msg['content']}")
+
+    transcript = "\n\n".join(transcript_lines)
+
+    prompt = (
+        f"Outcome: {outcome_label}\n\n"
+        f"{'Engineer Notes: ' + notes if notes else '(No additional notes)'}\n\n"
+        f"--- CONVERSATION TRANSCRIPT ---\n\n{transcript}\n\n"
+        f"--- END TRANSCRIPT ---\n\n"
+        f"Generate the ticket notes now. Replace all placeholder brackets with actual content from the conversation. "
+        f"The notes_section placeholder should be: {notes_section or '(omit this section)'}\n"
+        f"The resume_section placeholder should be filled based on the conversation context."
+    )
+
+    system_with_vars = CONCLUSION_SYSTEM_PROMPT.replace(
+        "{outcome_label}", outcome_label
+    ).replace(
+        "{notes_section}", notes_section or ""
+    ).replace(
+        "{resume_section}", resume_section
+    )
+
+    content, _, _ = await _call_ai(
+        system_base=system_with_vars,
+        rag_context="",
+        history=[],
+        new_message=prompt,
+        max_tokens=2048,
+    )
+
+    return content
+
+
 async def create_chat(
     user_id: UUID,
     account_id: UUID,