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chore: linting

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DESKTOP-RTLN3BA\$punk 2026-04-07 03:10:06 -07:00
parent 82b5c7f19e
commit 91ea293fa2
14 changed files with 285 additions and 264 deletions
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27
surfsense_backend/app/agents/autocomplete/autocomplete_agent.py
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@ -16,7 +16,8 @@ from __future__ import annotations
import asyncio
import logging
import uuid
from typing import Any, AsyncGenerator
from collections.abc import AsyncGenerator
from typing import Any
from deepagents.graph import BASE_AGENT_PROMPT
from deepagents.middleware.patch_tool_calls import PatchToolCallsMiddleware
@ -122,6 +123,7 @@ def _build_autocomplete_system_prompt(app_name: str, window_title: str) -> str:
class _KBResult:
"""Container for pre-computed KB filesystem results."""
__slots__ = ("files", "ls_ai_msg", "ls_tool_msg")
def __init__(
@ -171,13 +173,16 @@ async def precompute_kb_filesystem(
return _KBResult()
doc_paths = [
p for p, v in new_files.items()
p
for p, v in new_files.items()
if p.startswith("/documents/") and v is not None
]
tool_call_id = f"auto_ls_{uuid.uuid4().hex[:12]}"
ai_msg = AIMessage(
content="",
tool_calls=[{"name": "ls", "args": {"path": "/documents"}, "id": tool_call_id}],
tool_calls=[
{"name": "ls", "args": {"path": "/documents"}, "id": tool_call_id}
],
)
tool_msg = ToolMessage(
content=str(doc_paths) if doc_paths else "No documents found.",
@ -186,7 +191,9 @@ async def precompute_kb_filesystem(
return _KBResult(files=new_files, ls_ai_msg=ai_msg, ls_tool_msg=tool_msg)
except Exception:
logger.warning("KB pre-computation failed, proceeding without KB", exc_info=True)
logger.warning(
"KB pre-computation failed, proceeding without KB", exc_info=True
)
return _KBResult()
@ -320,7 +327,9 @@ async def stream_autocomplete_agent(
)
try:
async for event in agent.astream_events(input_data, config=config, version="v2"):
async for event in agent.astream_events(
input_data, config=config, version="v2"
):
event_type = event.get("event", "")
if event_type == "on_chat_model_stream":
@ -338,7 +347,9 @@ async def stream_autocomplete_agent(
yield step_event
current_text_id = streaming_service.generate_text_id()
yield streaming_service.format_text_start(current_text_id)
yield streaming_service.format_text_delta(current_text_id, content)
yield streaming_service.format_text_delta(
current_text_id, content
)
elif event_type == "on_tool_start":
active_tool_depth += 1
@ -425,5 +436,7 @@ def _describe_tool_call(tool_name: str, tool_input: Any) -> tuple[str, list[str]
pat = inp.get("pattern", "")
path = inp.get("path", "")
display_pat = pat[:60] + ("…" if len(pat) > 60 else "")
return "Searching content", [f'"{display_pat}"' + (f" in {path}" if path else "")]
return "Searching content", [
f'"{display_pat}"' + (f" in {path}" if path else "")
]
return f"Using {tool_name}", []