mirror of
https://github.com/MODSetter/SurfSense.git
synced 2026-04-25 16:56:22 +02:00
664c43ca13
- Introduced RequestPerfMiddleware to log request performance metrics, including slow request thresholds. - Updated various services and retrievers to utilize the new performance logging utility for better tracking of execution times. - Enhanced existing methods with detailed performance logs for operations such as embedding, searching, and indexing. - Removed deprecated logging setup in stream_new_chat and replaced it with the new performance logger.
350 lines
14 KiB
Python
350 lines
14 KiB
Python
"""
|
|
SurfSense deep agent implementation.
|
|
|
|
This module provides the factory function for creating SurfSense deep agents
|
|
with configurable tools via the tools registry and configurable prompts
|
|
via NewLLMConfig.
|
|
"""
|
|
|
|
import asyncio
|
|
import logging
|
|
import time
|
|
from collections.abc import Sequence
|
|
from typing import Any
|
|
|
|
from deepagents import create_deep_agent
|
|
from deepagents.backends.protocol import SandboxBackendProtocol
|
|
from langchain_core.language_models import BaseChatModel
|
|
from langchain_core.tools import BaseTool
|
|
from langgraph.types import Checkpointer
|
|
from sqlalchemy.ext.asyncio import AsyncSession
|
|
|
|
from app.agents.new_chat.context import SurfSenseContextSchema
|
|
from app.agents.new_chat.llm_config import AgentConfig
|
|
from app.agents.new_chat.system_prompt import (
|
|
build_configurable_system_prompt,
|
|
build_surfsense_system_prompt,
|
|
)
|
|
from app.agents.new_chat.tools.registry import build_tools_async
|
|
from app.db import ChatVisibility
|
|
from app.services.connector_service import ConnectorService
|
|
from app.utils.perf import get_perf_logger
|
|
|
|
_perf_log = get_perf_logger()
|
|
|
|
# =============================================================================
|
|
# Connector Type Mapping
|
|
# =============================================================================
|
|
|
|
# Maps SearchSourceConnectorType enum values to the searchable document/connector types
|
|
# used by the knowledge_base tool. Some connectors map to different document types.
|
|
_CONNECTOR_TYPE_TO_SEARCHABLE: dict[str, str] = {
|
|
# Direct mappings (connector type == searchable type)
|
|
"TAVILY_API": "TAVILY_API",
|
|
"SEARXNG_API": "SEARXNG_API",
|
|
"LINKUP_API": "LINKUP_API",
|
|
"BAIDU_SEARCH_API": "BAIDU_SEARCH_API",
|
|
"SLACK_CONNECTOR": "SLACK_CONNECTOR",
|
|
"TEAMS_CONNECTOR": "TEAMS_CONNECTOR",
|
|
"NOTION_CONNECTOR": "NOTION_CONNECTOR",
|
|
"GITHUB_CONNECTOR": "GITHUB_CONNECTOR",
|
|
"LINEAR_CONNECTOR": "LINEAR_CONNECTOR",
|
|
"DISCORD_CONNECTOR": "DISCORD_CONNECTOR",
|
|
"JIRA_CONNECTOR": "JIRA_CONNECTOR",
|
|
"CONFLUENCE_CONNECTOR": "CONFLUENCE_CONNECTOR",
|
|
"CLICKUP_CONNECTOR": "CLICKUP_CONNECTOR",
|
|
"GOOGLE_CALENDAR_CONNECTOR": "GOOGLE_CALENDAR_CONNECTOR",
|
|
"GOOGLE_GMAIL_CONNECTOR": "GOOGLE_GMAIL_CONNECTOR",
|
|
"GOOGLE_DRIVE_CONNECTOR": "GOOGLE_DRIVE_FILE", # Connector type differs from document type
|
|
"AIRTABLE_CONNECTOR": "AIRTABLE_CONNECTOR",
|
|
"LUMA_CONNECTOR": "LUMA_CONNECTOR",
|
|
"ELASTICSEARCH_CONNECTOR": "ELASTICSEARCH_CONNECTOR",
|
|
"WEBCRAWLER_CONNECTOR": "CRAWLED_URL", # Maps to document type
|
|
"BOOKSTACK_CONNECTOR": "BOOKSTACK_CONNECTOR",
|
|
"CIRCLEBACK_CONNECTOR": "CIRCLEBACK", # Connector type differs from document type
|
|
"OBSIDIAN_CONNECTOR": "OBSIDIAN_CONNECTOR",
|
|
# Composio connectors
|
|
"COMPOSIO_GOOGLE_DRIVE_CONNECTOR": "COMPOSIO_GOOGLE_DRIVE_CONNECTOR",
|
|
"COMPOSIO_GMAIL_CONNECTOR": "COMPOSIO_GMAIL_CONNECTOR",
|
|
"COMPOSIO_GOOGLE_CALENDAR_CONNECTOR": "COMPOSIO_GOOGLE_CALENDAR_CONNECTOR",
|
|
}
|
|
|
|
# Document types that don't come from SearchSourceConnector but should always be searchable
|
|
_ALWAYS_AVAILABLE_DOC_TYPES: list[str] = [
|
|
"EXTENSION", # Browser extension data
|
|
"FILE", # Uploaded files
|
|
"NOTE", # User notes
|
|
"YOUTUBE_VIDEO", # YouTube videos
|
|
]
|
|
|
|
|
|
def _map_connectors_to_searchable_types(
|
|
connector_types: list[Any],
|
|
) -> list[str]:
|
|
"""
|
|
Map SearchSourceConnectorType enums to searchable document/connector types.
|
|
|
|
This function:
|
|
1. Converts connector type enums to their searchable counterparts
|
|
2. Includes always-available document types (EXTENSION, FILE, NOTE, YOUTUBE_VIDEO)
|
|
3. Deduplicates while preserving order
|
|
|
|
Args:
|
|
connector_types: List of SearchSourceConnectorType enum values
|
|
|
|
Returns:
|
|
List of searchable connector/document type strings
|
|
"""
|
|
result_set: set[str] = set()
|
|
result_list: list[str] = []
|
|
|
|
# Add always-available document types first
|
|
for doc_type in _ALWAYS_AVAILABLE_DOC_TYPES:
|
|
if doc_type not in result_set:
|
|
result_set.add(doc_type)
|
|
result_list.append(doc_type)
|
|
|
|
# Map each connector type to its searchable equivalent
|
|
for ct in connector_types:
|
|
# Handle both enum and string types
|
|
ct_str = ct.value if hasattr(ct, "value") else str(ct)
|
|
searchable = _CONNECTOR_TYPE_TO_SEARCHABLE.get(ct_str)
|
|
if searchable and searchable not in result_set:
|
|
result_set.add(searchable)
|
|
result_list.append(searchable)
|
|
|
|
return result_list
|
|
|
|
|
|
# =============================================================================
|
|
# Deep Agent Factory
|
|
# =============================================================================
|
|
|
|
|
|
async def create_surfsense_deep_agent(
|
|
llm: BaseChatModel,
|
|
search_space_id: int,
|
|
db_session: AsyncSession,
|
|
connector_service: ConnectorService,
|
|
checkpointer: Checkpointer,
|
|
user_id: str | None = None,
|
|
thread_id: int | None = None,
|
|
agent_config: AgentConfig | None = None,
|
|
enabled_tools: list[str] | None = None,
|
|
disabled_tools: list[str] | None = None,
|
|
additional_tools: Sequence[BaseTool] | None = None,
|
|
firecrawl_api_key: str | None = None,
|
|
thread_visibility: ChatVisibility | None = None,
|
|
sandbox_backend: SandboxBackendProtocol | None = None,
|
|
):
|
|
"""
|
|
Create a SurfSense deep agent with configurable tools and prompts.
|
|
|
|
The agent comes with built-in tools that can be configured:
|
|
- search_knowledge_base: Search the user's personal knowledge base
|
|
- generate_podcast: Generate audio podcasts from content
|
|
- generate_image: Generate images from text descriptions using AI models
|
|
- link_preview: Fetch rich previews for URLs
|
|
- display_image: Display images in chat
|
|
- scrape_webpage: Extract content from webpages
|
|
- save_memory: Store facts/preferences about the user
|
|
- recall_memory: Retrieve relevant user memories
|
|
|
|
The agent also includes TodoListMiddleware by default (via create_deep_agent) which provides:
|
|
- write_todos: Create and update planning/todo lists for complex tasks
|
|
|
|
The system prompt can be configured via agent_config:
|
|
- Custom system instructions (or use defaults)
|
|
- Citation toggle (enable/disable citation requirements)
|
|
|
|
Args:
|
|
llm: ChatLiteLLM instance for the agent's language model
|
|
search_space_id: The user's search space ID
|
|
db_session: Database session for tools that need DB access
|
|
connector_service: Initialized connector service for knowledge base search
|
|
checkpointer: LangGraph checkpointer for conversation state persistence.
|
|
Use AsyncPostgresSaver for production or MemorySaver for testing.
|
|
user_id: The current user's UUID string (required for memory tools)
|
|
agent_config: Optional AgentConfig from NewLLMConfig for prompt configuration.
|
|
If None, uses default system prompt with citations enabled.
|
|
enabled_tools: Explicit list of tool names to enable. If None, all default tools
|
|
are enabled. Use this to limit which tools are available.
|
|
disabled_tools: List of tool names to disable. Applied after enabled_tools.
|
|
Use this to exclude specific tools from the defaults.
|
|
additional_tools: Extra custom tools to add beyond the built-in ones.
|
|
These are always added regardless of enabled/disabled settings.
|
|
firecrawl_api_key: Optional Firecrawl API key for premium web scraping.
|
|
Falls back to Chromium/Trafilatura if not provided.
|
|
sandbox_backend: Optional sandbox backend (e.g. DaytonaSandbox) for
|
|
secure code execution. When provided, the agent gets an
|
|
isolated ``execute`` tool for running shell commands.
|
|
|
|
Returns:
|
|
CompiledStateGraph: The configured deep agent
|
|
|
|
Examples:
|
|
# Create agent with all default tools and default prompt
|
|
agent = create_surfsense_deep_agent(llm, search_space_id, db_session, ...)
|
|
|
|
# Create agent with custom prompt configuration
|
|
agent = create_surfsense_deep_agent(
|
|
llm, search_space_id, db_session, ...,
|
|
agent_config=AgentConfig(
|
|
provider="OPENAI",
|
|
model_name="gpt-4",
|
|
api_key="...",
|
|
system_instructions="Custom instructions...",
|
|
citations_enabled=False,
|
|
)
|
|
)
|
|
|
|
# Create agent with only specific tools
|
|
agent = create_surfsense_deep_agent(
|
|
llm, search_space_id, db_session, ...,
|
|
enabled_tools=["search_knowledge_base", "link_preview"]
|
|
)
|
|
|
|
# Create agent without podcast generation
|
|
agent = create_surfsense_deep_agent(
|
|
llm, search_space_id, db_session, ...,
|
|
disabled_tools=["generate_podcast"]
|
|
)
|
|
|
|
# Add custom tools
|
|
agent = create_surfsense_deep_agent(
|
|
llm, search_space_id, db_session, ...,
|
|
additional_tools=[my_custom_tool]
|
|
)
|
|
"""
|
|
_t_agent_total = time.perf_counter()
|
|
|
|
# Discover available connectors and document types for this search space
|
|
available_connectors: list[str] | None = None
|
|
available_document_types: list[str] | None = None
|
|
|
|
_t0 = time.perf_counter()
|
|
try:
|
|
connector_types = await connector_service.get_available_connectors(
|
|
search_space_id
|
|
)
|
|
if connector_types:
|
|
available_connectors = _map_connectors_to_searchable_types(connector_types)
|
|
|
|
available_document_types = await connector_service.get_available_document_types(
|
|
search_space_id
|
|
)
|
|
except Exception as e:
|
|
logging.warning(f"Failed to discover available connectors/document types: {e}")
|
|
_perf_log.info(
|
|
"[create_agent] Connector/doc-type discovery in %.3fs",
|
|
time.perf_counter() - _t0,
|
|
)
|
|
|
|
# Build dependencies dict for the tools registry
|
|
visibility = thread_visibility or ChatVisibility.PRIVATE
|
|
|
|
# Extract the model's context window so tools can size their output.
|
|
_model_profile = getattr(llm, "profile", None)
|
|
_max_input_tokens: int | None = (
|
|
_model_profile.get("max_input_tokens")
|
|
if isinstance(_model_profile, dict)
|
|
else None
|
|
)
|
|
|
|
dependencies = {
|
|
"search_space_id": search_space_id,
|
|
"db_session": db_session,
|
|
"connector_service": connector_service,
|
|
"firecrawl_api_key": firecrawl_api_key,
|
|
"user_id": user_id,
|
|
"thread_id": thread_id,
|
|
"thread_visibility": visibility,
|
|
"available_connectors": available_connectors,
|
|
"available_document_types": available_document_types,
|
|
"max_input_tokens": _max_input_tokens,
|
|
}
|
|
|
|
# Disable Notion action tools if no Notion connector is configured
|
|
modified_disabled_tools = list(disabled_tools) if disabled_tools else []
|
|
has_notion_connector = (
|
|
available_connectors is not None and "NOTION_CONNECTOR" in available_connectors
|
|
)
|
|
if not has_notion_connector:
|
|
notion_tools = [
|
|
"create_notion_page",
|
|
"update_notion_page",
|
|
"delete_notion_page",
|
|
]
|
|
modified_disabled_tools.extend(notion_tools)
|
|
|
|
# Disable Linear action tools if no Linear connector is configured
|
|
has_linear_connector = (
|
|
available_connectors is not None and "LINEAR_CONNECTOR" in available_connectors
|
|
)
|
|
if not has_linear_connector:
|
|
linear_tools = [
|
|
"create_linear_issue",
|
|
"update_linear_issue",
|
|
"delete_linear_issue",
|
|
]
|
|
modified_disabled_tools.extend(linear_tools)
|
|
|
|
# Build tools using the async registry (includes MCP tools)
|
|
_t0 = time.perf_counter()
|
|
tools = await build_tools_async(
|
|
dependencies=dependencies,
|
|
enabled_tools=enabled_tools,
|
|
disabled_tools=modified_disabled_tools,
|
|
additional_tools=list(additional_tools) if additional_tools else None,
|
|
)
|
|
_perf_log.info(
|
|
"[create_agent] build_tools_async in %.3fs (%d tools)",
|
|
time.perf_counter() - _t0,
|
|
len(tools),
|
|
)
|
|
|
|
# Build system prompt based on agent_config
|
|
_t0 = time.perf_counter()
|
|
_sandbox_enabled = sandbox_backend is not None
|
|
if agent_config is not None:
|
|
system_prompt = build_configurable_system_prompt(
|
|
custom_system_instructions=agent_config.system_instructions,
|
|
use_default_system_instructions=agent_config.use_default_system_instructions,
|
|
citations_enabled=agent_config.citations_enabled,
|
|
thread_visibility=thread_visibility,
|
|
sandbox_enabled=_sandbox_enabled,
|
|
)
|
|
else:
|
|
system_prompt = build_surfsense_system_prompt(
|
|
thread_visibility=thread_visibility,
|
|
sandbox_enabled=_sandbox_enabled,
|
|
)
|
|
_perf_log.info(
|
|
"[create_agent] System prompt built in %.3fs", time.perf_counter() - _t0
|
|
)
|
|
|
|
# Build optional kwargs for the deep agent
|
|
deep_agent_kwargs: dict[str, Any] = {}
|
|
if sandbox_backend is not None:
|
|
deep_agent_kwargs["backend"] = sandbox_backend
|
|
|
|
_t0 = time.perf_counter()
|
|
agent = await asyncio.to_thread(
|
|
create_deep_agent,
|
|
model=llm,
|
|
tools=tools,
|
|
system_prompt=system_prompt,
|
|
context_schema=SurfSenseContextSchema,
|
|
checkpointer=checkpointer,
|
|
**deep_agent_kwargs,
|
|
)
|
|
_perf_log.info(
|
|
"[create_agent] Graph compiled (create_deep_agent) in %.3fs",
|
|
time.perf_counter() - _t0,
|
|
)
|
|
|
|
_perf_log.info(
|
|
"[create_agent] Total agent creation in %.3fs",
|
|
time.perf_counter() - _t_agent_total,
|
|
)
|
|
return agent
|