refactor: extract autocomplete service and fix tooltip screen-edge positioning

surfsense_backend/app/routes/autocomplete_routes.py

@@ -1,118 +1,14 @@
-import logging
-from typing import AsyncGenerator
-
 from fastapi import APIRouter, Depends, Query
 from fastapi.responses import StreamingResponse
-from langchain_core.messages import HumanMessage, SystemMessage
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.db import User, get_async_session
-from app.retriever.chunks_hybrid_search import ChucksHybridSearchRetriever
-from app.services.llm_service import get_agent_llm
+from app.services.autocomplete_service import stream_autocomplete
 from app.services.new_streaming_service import VercelStreamingService
 from app.users import current_active_user
 
-logger = logging.getLogger(__name__)
-
 router = APIRouter(prefix="/autocomplete", tags=["autocomplete"])
 
-AUTOCOMPLETE_SYSTEM_PROMPT = """You are an inline text autocomplete engine. Your job is to complete the user's text naturally.
-
-Rules:
-- Output ONLY the continuation text. Do NOT repeat what the user already typed.
-- Keep completions concise: 1-3 sentences maximum.
-- Match the user's tone, style, and language.
-- If knowledge base context is provided, use it to make the completion factually accurate and personalized.
-- Do NOT add quotes, explanations, or meta-commentary.
-- Do NOT start with a space unless grammatically required.
-- If you cannot produce a useful completion, output nothing."""
-
-KB_CONTEXT_TEMPLATE = """
-Relevant knowledge base context (use this to personalize the completion):
----
-{kb_context}
----
-"""
-
-
-async def _stream_autocomplete(
-    text: str,
-    cursor_position: int,
-    search_space_id: int,
-    session: AsyncSession,
-) -> AsyncGenerator[str, None]:
-    """Stream an autocomplete response with KB context."""
-    streaming_service = VercelStreamingService()
-
-    try:
-        # Text before cursor is what we're completing
-        text_before_cursor = text[:cursor_position] if cursor_position >= 0 else text
-
-        if not text_before_cursor.strip():
-            yield streaming_service.format_message_start()
-            yield streaming_service.format_finish()
-            yield streaming_service.format_done()
-            return
-
-        # Fast KB lookup: vector-only search, top 3 chunks, no planner LLM
-        kb_context = ""
-        try:
-            retriever = ChucksHybridSearchRetriever(session)
-            chunks = await retriever.vector_search(
-                query_text=text_before_cursor[-200:],  # last 200 chars for relevance
-                top_k=3,
-                search_space_id=search_space_id,
-            )
-            if chunks:
-                kb_snippets = []
-                for chunk in chunks:
-                    content = getattr(chunk, "content", None) or getattr(chunk, "chunk_text", "")
-                    if content:
-                        kb_snippets.append(content[:300])
-                if kb_snippets:
-                    kb_context = KB_CONTEXT_TEMPLATE.format(
-                        kb_context="\n\n".join(kb_snippets)
-                    )
-        except Exception as e:
-            logger.warning(f"KB search failed for autocomplete, proceeding without context: {e}")
-
-        # Get the search space's configured LLM
-        llm = await get_agent_llm(session, search_space_id)
-        if not llm:
-            yield streaming_service.format_message_start()
-            error_msg = "No LLM configured for this search space"
-            yield streaming_service.format_error(error_msg)
-            yield streaming_service.format_done()
-            return
-
-        system_prompt = AUTOCOMPLETE_SYSTEM_PROMPT
-        if kb_context:
-            system_prompt += kb_context
-
-        messages = [
-            SystemMessage(content=system_prompt),
-            HumanMessage(content=f"Complete this text:\n{text_before_cursor}"),
-        ]
-
-        # Stream the response
-        yield streaming_service.format_message_start()
-        text_id = streaming_service.generate_text_id()
-        yield streaming_service.format_text_start(text_id)
-
-        async for chunk in llm.astream(messages):
-            token = chunk.content if hasattr(chunk, "content") else str(chunk)
-            if token:
-                yield streaming_service.format_text_delta(text_id, token)
-
-        yield streaming_service.format_text_end(text_id)
-        yield streaming_service.format_finish()
-        yield streaming_service.format_done()
-
-    except Exception as e:
-        logger.error(f"Autocomplete streaming error: {e}")
-        yield streaming_service.format_error(str(e))
-        yield streaming_service.format_done()
-
 
 @router.post("/stream")
 async def autocomplete_stream(
@@ -122,12 +18,11 @@ async def autocomplete_stream(
     user: User = Depends(current_active_user),
     session: AsyncSession = Depends(get_async_session),
 ):
-    """Stream an autocomplete suggestion based on the current text and KB context."""
     if cursor_position < 0:
         cursor_position = len(text)
 
     return StreamingResponse(
-        _stream_autocomplete(text, cursor_position, search_space_id, session),
+        stream_autocomplete(text, cursor_position, search_space_id, session),
         media_type="text/event-stream",
         headers={
             **VercelStreamingService.get_response_headers(),