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

surfsense_backend/app/services/autocomplete_service.py

@@ -0,0 +1,110 @@
+import logging
+from typing import AsyncGenerator
+
+from langchain_core.messages import HumanMessage, SystemMessage
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.retriever.chunks_hybrid_search import ChucksHybridSearchRetriever
+from app.services.llm_service import get_agent_llm
+from app.services.new_streaming_service import VercelStreamingService
+
+logger = logging.getLogger(__name__)
+
+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 _retrieve_kb_context(
+    session: AsyncSession,
+    text: str,
+    search_space_id: int,
+) -> str:
+    try:
+        retriever = ChucksHybridSearchRetriever(session)
+        chunks = await retriever.vector_search(
+            query_text=text[-200:],
+            top_k=3,
+            search_space_id=search_space_id,
+        )
+        if not chunks:
+            return ""
+        snippets = []
+        for chunk in chunks:
+            content = getattr(chunk, "content", None) or getattr(chunk, "chunk_text", "")
+            if content:
+                snippets.append(content[:300])
+        if not snippets:
+            return ""
+        return KB_CONTEXT_TEMPLATE.format(kb_context="\n\n".join(snippets))
+    except Exception as e:
+        logger.warning(f"KB search failed for autocomplete, proceeding without context: {e}")
+        return ""
+
+
+async def stream_autocomplete(
+    text: str,
+    cursor_position: int,
+    search_space_id: int,
+    session: AsyncSession,
+) -> AsyncGenerator[str, None]:
+    """Build context, call the LLM, and yield SSE-formatted tokens."""
+    streaming = VercelStreamingService()
+    text_before_cursor = text[:cursor_position] if cursor_position >= 0 else text
+
+    if not text_before_cursor.strip():
+        yield streaming.format_message_start()
+        yield streaming.format_finish()
+        yield streaming.format_done()
+        return
+
+    kb_context = await _retrieve_kb_context(session, text_before_cursor, search_space_id)
+
+    llm = await get_agent_llm(session, search_space_id)
+    if not llm:
+        yield streaming.format_message_start()
+        yield streaming.format_error("No LLM configured for this search space")
+        yield streaming.format_done()
+        return
+
+    system_prompt = SYSTEM_PROMPT
+    if kb_context:
+        system_prompt += kb_context
+
+    messages = [
+        SystemMessage(content=system_prompt),
+        HumanMessage(content=f"Complete this text:\n{text_before_cursor}"),
+    ]
+
+    try:
+        yield streaming.format_message_start()
+        text_id = streaming.generate_text_id()
+        yield streaming.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.format_text_delta(text_id, token)
+
+        yield streaming.format_text_end(text_id)
+        yield streaming.format_finish()
+        yield streaming.format_done()
+
+    except Exception as e:
+        logger.error(f"Autocomplete streaming error: {e}")
+        yield streaming.format_error(str(e))
+        yield streaming.format_done()