Phase 21: Intent-first pipeline, visible ack, KV-stable system prompt

Pipeline changes (generation_task.py, intent.py):
- Remove optimistic streaming queue/race (_drain_queue deleted)
- Remove _generate_acknowledgment — ack now embedded in intent JSON
- Round 0: await intent (~400ms), stream ack immediately as TTFT,
  then execute tool sequentially; chat-only streams directly
- IntentResult.ack: one-sentence acknowledgment, intent max_tokens 200→350
- _parse_intent extracts and trims ack field

KV cache stability (llm.py, generation_buffer.py, generation_task.py):
- build_context: replace cached_note_ids with include_note_ids
- Auto-found notes populate context_meta["auto_notes"] for sidebar but
  are NOT injected into system prompt (--- Related Notes --- removed)
- Explicitly included notes injected as --- Included Notes ---
- _conv_note_cache dict + get/set/clear functions removed from generation_buffer.py
- All clear_conv_note_cache() calls removed

Cold model retry (llm.py):
- generate_completion (used by classify_intent) retries on HTTP 500:
  3 attempts with 3s/6s delays — prevents intent failure during cold load

API + frontend (routes/chat.py, stores/chat.ts, views/ChatView.vue, components/ChatPanel.vue):
- exclude_note_ids → include_note_ids throughout
- ChatView sidebar: Suggested (auto-found, + to include) + In Context (× to remove)
- ChatPanel: remove exclude button from context pills; no IDs passed to sendMessage

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

src/fabledassistant/services/llm.py

@@ -1,3 +1,4 @@
+import asyncio
 import json
 import logging
 import re
@@ -178,21 +179,41 @@ async def stream_chat_with_tools(
 
 
 async def generate_completion(messages: list[dict], model: str, max_tokens: int = 4096) -> str:
-    """Non-streaming chat completion, returns full response text."""
-    async with httpx.AsyncClient(timeout=httpx.Timeout(1800.0, connect=30.0, read=300.0)) as client:
-        resp = await client.post(
-            f"{Config.OLLAMA_URL}/api/chat",
-            json={
-                "model": model,
-                "messages": messages,
-                "stream": False,
-                "think": False,
-                "options": {"num_predict": max_tokens},
-            },
-        )
-        resp.raise_for_status()
-        data = resp.json()
-        return data.get("message", {}).get("content", "")
+    """Non-streaming chat completion, returns full response text.
+
+    Retries up to 2 times on Ollama 500 errors (cold model loading race).
+    """
+    last_exc: Exception | None = None
+    for attempt in range(3):
+        if attempt > 0:
+            delay = 3.0 * attempt
+            logger.warning(
+                "generate_completion 500 (attempt %d/3), retrying in %.0fs", attempt, delay
+            )
+            await asyncio.sleep(delay)
+        try:
+            async with httpx.AsyncClient(timeout=httpx.Timeout(1800.0, connect=30.0, read=300.0)) as client:
+                resp = await client.post(
+                    f"{Config.OLLAMA_URL}/api/chat",
+                    json={
+                        "model": model,
+                        "messages": messages,
+                        "stream": False,
+                        "think": False,
+                        "options": {"num_predict": max_tokens},
+                    },
+                )
+                resp.raise_for_status()
+                data = resp.json()
+                return data.get("message", {}).get("content", "")
+        except httpx.HTTPStatusError as exc:
+            last_exc = exc
+            if exc.response.status_code != 500:
+                break
+        except Exception as exc:
+            last_exc = exc
+            break
+    raise last_exc
 
 
 async def fetch_url_content(url: str) -> str:
@@ -307,7 +328,7 @@ async def build_context(
     user_message: str,
     exclude_note_ids: list[int] | None = None,
     history_summary: str | None = None,
-    cached_note_ids: list[int] | None = None,
+    include_note_ids: list[int] | None = None,
 ) -> tuple[list[dict], dict]:
     """Build messages array for Ollama with system prompt and context.
 
@@ -376,64 +397,58 @@ async def build_context(
                 f"--- End Note ---"
             )
 
-    # Find related notes to inject into context.
-    # Priority: (1) use cached note IDs from a previous turn in this conversation
-    #           (2) try semantic search via nomic-embed-text
-    #           (3) fall back to keyword search
-    # The cache stabilises the system prompt prefix so Ollama's KV cache stays warm.
+    # Search for related notes to populate sidebar candidates.
+    # Results are NOT injected into the system prompt automatically — this keeps
+    # the system prompt prefix stable so Ollama's KV cache can reuse prefill state.
+    # Users can explicitly include notes via the sidebar (include_note_ids).
     search_exclude = set(exclude_set)
     if current_note_id:
         search_exclude.add(current_note_id)
 
     found_notes = []
-    if cached_note_ids:
-        # Load the same notes as last turn — keeps system prompt prefix identical.
-        try:
-            from fabledassistant.services.notes import get_note as _get_note
-            for nid in cached_note_ids:
-                if nid not in search_exclude:
-                    n = await _get_note(user_id, nid)
-                    if n:
-                        found_notes.append(n)
-        except Exception:
-            logger.warning("Failed to load cached notes for context", exc_info=True)
-            found_notes = []
+    # Try semantic search first; fall back to keyword search on failure / no results.
+    try:
+        from fabledassistant.services.embeddings import semantic_search_notes
+        found_notes = await semantic_search_notes(
+            user_id, user_message, exclude_ids=search_exclude or None, limit=3
+        )
+    except Exception:
+        logger.warning("Semantic note search failed, falling back to keyword search", exc_info=True)
 
     if not found_notes:
-        # Try semantic search first; fall back to keyword search on failure / no results.
-        try:
-            from fabledassistant.services.embeddings import semantic_search_notes
-            found_notes = await semantic_search_notes(
-                user_id, user_message, exclude_ids=search_exclude or None, limit=3
-            )
-        except Exception:
-            logger.warning("Semantic note search failed, falling back to keyword search", exc_info=True)
+        keywords = _extract_keywords(user_message)
+        if keywords:
+            try:
+                found_notes = await search_notes_for_context(
+                    user_id, keywords, exclude_ids=search_exclude or None, limit=3
+                )
+            except Exception:
+                logger.warning("Failed to search notes for context", exc_info=True)
 
-        if not found_notes:
-            keywords = _extract_keywords(user_message)
-            if keywords:
-                try:
-                    found_notes = await search_notes_for_context(
-                        user_id, keywords, exclude_ids=search_exclude or None, limit=3
-                    )
-                except Exception:
-                    logger.warning("Failed to search notes for context", exc_info=True)
-
-    if found_notes:
-        snippets: list[str] = []
-        for n in found_notes:
-            body_preview = n.body[:2000] if n.body else ""
-            snippets.append(f"- {n.title}: {body_preview}")
-            context_meta["auto_notes"].append({"id": n.id, "title": n.title})
-        system_parts.append(
-            "\n\n--- Related Notes ---\n"
-            + "\n".join(snippets)
-            + "\n--- End Related Notes ---"
-        )
-
-    # Expose note IDs so the caller can update the per-conversation cache.
+    # Populate sidebar candidates (never auto-injected).
+    for n in found_notes:
+        context_meta["auto_notes"].append({"id": n.id, "title": n.title})
     context_meta["auto_note_ids"] = [n.id for n in found_notes]
 
+    # Inject explicitly included notes (user opted in via sidebar click).
+    if include_note_ids:
+        from fabledassistant.services.notes import get_note as _get_note
+        included_snippets: list[str] = []
+        for nid in include_note_ids:
+            try:
+                n = await _get_note(user_id, nid)
+                if n:
+                    body_preview = n.body[:2000] if n.body else ""
+                    included_snippets.append(f"- {n.title}: {body_preview}")
+            except Exception:
+                logger.warning("Failed to load included note %d for context", nid, exc_info=True)
+        if included_snippets:
+            system_parts.append(
+                "\n\n--- Included Notes ---\n"
+                + "\n".join(included_snippets)
+                + "\n--- End Included Notes ---"
+            )
+
     # Fetch URL content from user message
     urls = _find_urls(user_message)
     for url in urls[:2]:  # Limit to 2 URLs