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MCP consolidation: - Route all MCP-capable connectors (Slack, Jira, Linear, ClickUp, Airtable, Notion, Confluence, interim Gmail/Calendar, custom MCP) through a single `mcp_discovery` subagent. Drive/OneDrive/Dropbox stay native to enrich the KB. - Deprecate Discord/Teams/Luma: no viable official MCP server. Google-only web search: - Remove the main-agent `web_search` tool and the SearXNG platform service; all public web search now flows through the `google_search` subagent via task(). - Deprecate the Tavily/SearXNG/Linkup/Baidu search connectors (HTTP 410 on create, "Deprecated" badge); guide heavy users to the custom MCP connector. - Remove web search from anonymous chat (pure Q&A). - Tear SearXNG out of docker compose + install scripts; drop tavily-python and linkup-sdk deps and their config/env vars. Fix: - metrics._package_version() now swallows any metadata lookup failure. A malformed editable-install distribution with no `Version` field raised KeyError deep in importlib.metadata, and since it runs on every record_subagent_invoke_duration call it was crashing every task() delegation. Verified end-to-end against live GPT-5.4. Co-authored-by: Cursor <cursoragent@cursor.com>
153 lines
6.4 KiB
Python
153 lines
6.4 KiB
Python
"""Minimal anonymous / free-chat agent.
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The no-login chat experience must stay dead simple: the user asks a question
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and the model answers over an optionally uploaded **read-only** document. We
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deliberately bypass the full SurfSense deep agent stack (filesystem,
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file-intent, knowledge-base persistence, subagents, skills, memory) because
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those middlewares stage or persist "documents" that an anonymous session can
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never see again -- which produced phantom "I saved it to a file" answers for
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free users.
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For any other SurfSense capability (including web search) the model is
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instructed (via the system prompt built here) to tell the user to create a
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free account instead of pretending to perform the action.
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"""
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from __future__ import annotations
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from datetime import UTC, datetime
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from typing import Any
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from deepagents.backends import StateBackend
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from langchain.agents import create_agent
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from langchain.agents.middleware import (
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ModelCallLimitMiddleware,
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)
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from langchain_core.language_models import BaseChatModel
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from langgraph.types import Checkpointer
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from app.agents.chat.shared.context import SurfSenseContextSchema
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from app.agents.chat.shared.middleware import (
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RetryAfterMiddleware,
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create_surfsense_compaction_middleware,
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)
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# Cap how much of an uploaded document we inline into the system prompt. The
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# upload endpoint allows files up to several MB, but the doc is re-sent on
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# every turn and counts against the anonymous token quota, so we bound it.
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_MAX_DOC_CHARS = 50_000
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def build_anonymous_system_prompt(anon_doc: dict[str, Any] | None = None) -> str:
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"""Build the system prompt for the minimal anonymous chat agent.
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The prompt keeps the assistant focused on plain Q/A + web search, inlines
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any uploaded document as read-only context, and redirects every other
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SurfSense feature to account registration.
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"""
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today = datetime.now(UTC).strftime("%A, %B %d, %Y")
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doc_section = ""
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if anon_doc:
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title = str(anon_doc.get("title") or "uploaded_document")
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content = str(anon_doc.get("content") or "")
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truncated = content[:_MAX_DOC_CHARS]
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truncation_note = ""
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if len(content) > _MAX_DOC_CHARS:
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truncation_note = (
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"\n\n[Note: the document was truncated because it is large; "
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"only the beginning is shown.]"
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)
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doc_section = (
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"\n\n## Uploaded document (read-only)\n"
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f'The user uploaded a document named "{title}". Its contents are '
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"provided below for reference only. You may read it and answer "
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"questions about it, but you cannot modify, save, or store it.\n\n"
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f'<uploaded_document title="{title}">\n'
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f"{truncated}{truncation_note}\n"
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"</uploaded_document>"
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)
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return (
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"You are SurfSense's free AI assistant, available to everyone without "
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"login.\n\n"
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f"Today's date is {today}.\n\n"
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"## How to help\n"
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"- Answer the user's questions directly and conversationally. You are "
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"a straightforward question-and-answer assistant.\n"
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"- Answer from your own knowledge. You do NOT have web access here, so "
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"for current, real-time, or fast-changing facts (news, prices, "
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"weather, recent events, live data) say you can't look them up in the "
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"free experience and may be out of date, and invite the user to create "
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"a free account for live web search.\n"
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"- Be concise, accurate, and helpful. Use Markdown formatting when it "
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"improves readability."
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f"{doc_section}\n\n"
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"## What is not available here\n"
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"This is the free, no-login experience. You CANNOT search the web, save "
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"files or notes, generate reports, podcasts, resumes, presentations, or "
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"images, search or build a knowledge base, connect to apps (Gmail, "
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"Google Drive, Notion, Slack, Calendar, Discord, and similar), set up "
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"automations, or remember anything across sessions.\n\n"
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"If the user asks for any of these, do NOT pretend to do them and "
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"never claim you saved, created, or stored anything. Instead, briefly "
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"let them know the feature requires a free SurfSense account and "
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"invite them to create one at https://www.surfsense.com. Then offer to "
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"help with what you can do here (answering questions from your own "
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"knowledge and about any uploaded document)."
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)
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async def create_anonymous_chat_agent(
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*,
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llm: BaseChatModel,
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checkpointer: Checkpointer,
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anon_session_id: str | None = None,
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anon_doc: dict[str, Any] | None = None,
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):
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"""Create a minimal Q/A agent for anonymous / free chat.
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Unlike :func:`create_surfsense_deep_agent`, this agent has no filesystem,
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file-intent, knowledge-base persistence, subagent, skills, or memory
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middleware -- and no tools at all. It answers purely from the model's own
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knowledge; any uploaded document is injected into the system prompt as
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read-only context.
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Args:
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llm: The chat model to use (already built by the caller).
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checkpointer: LangGraph checkpointer for the ephemeral anon thread.
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anon_session_id: Anonymous session id (used only for telemetry/metadata).
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anon_doc: Optional ``{"title", "content"}`` for an uploaded document.
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"""
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# Reliability-only middleware. Nothing here touches the database or
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# filesystem: the call limit guards against loops, compaction summarises
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# long histories into in-graph state, and retry handles provider rate
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# limits.
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middleware: list[Any] = [
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ModelCallLimitMiddleware(thread_limit=120, run_limit=80, exit_behavior="end"),
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create_surfsense_compaction_middleware(llm, StateBackend),
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RetryAfterMiddleware(max_retries=3),
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]
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system_prompt = build_anonymous_system_prompt(anon_doc)
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agent = create_agent(
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llm,
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system_prompt=system_prompt,
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tools=[],
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middleware=middleware,
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context_schema=SurfSenseContextSchema,
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checkpointer=checkpointer,
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)
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return agent.with_config(
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{
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"recursion_limit": 40,
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"metadata": {
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"ls_integration": "surfsense_anonymous_chat",
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"anon_session_id": anon_session_id,
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},
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}
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)
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__all__ = ["build_anonymous_system_prompt", "create_anonymous_chat_agent"]
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