SurfSense/surfsense_backend/app/agents/chat/anonymous_chat/agent.py
DESKTOP-RTLN3BA\$punk 1fd58752a3 feat: update environment variables and enhance scraping capabilities
- Adjusted Google Maps and YouTube micro pricing in the .env.example file for better cost management.
- Introduced new environment variables for captcha solving and stealth browser hardening to improve scraping resilience.
- Removed outdated smoke test for scraper API endpoints to streamline testing.
- Enhanced anonymous chat agent's system prompt to clarify capabilities and suggest account creation for advanced features.
- Updated Reddit fetch logic to prioritize new session handling and improve resilience against IP-related issues.
- Added compacting functionality for scraper results to optimize data handling and presentation.
- Improved workspace and document management tools with clearer descriptions and enhanced functionality.
- Introduced new UI components for agent setup guidance in the web application.
2026-07-06 20:27:36 -07:00

181 lines
8.4 KiB
Python

"""Minimal anonymous / free-chat agent.
The no-login chat experience must stay dead simple: the user asks a question
and the model answers over an optionally uploaded **read-only** document. We
deliberately bypass the full SurfSense deep agent stack (filesystem,
file-intent, knowledge-base persistence, subagents, skills, memory) because
those middlewares stage or persist "documents" that an anonymous session can
never see again -- which produced phantom "I saved it to a file" answers for
free users.
For any other SurfSense capability (including web search) the model is
instructed (via the system prompt built here) to tell the user to create a
free account instead of pretending to perform the action.
"""
from __future__ import annotations
from datetime import UTC, datetime
from typing import Any
from deepagents.backends import StateBackend
from langchain.agents import create_agent
from langchain.agents.middleware import (
ModelCallLimitMiddleware,
)
from langchain_core.language_models import BaseChatModel
from langgraph.types import Checkpointer
from app.agents.chat.shared.context import SurfSenseContextSchema
from app.agents.chat.shared.middleware import (
RetryAfterMiddleware,
create_surfsense_compaction_middleware,
)
# Cap how much of an uploaded document we inline into the system prompt. The
# upload endpoint allows files up to several MB, but the doc is re-sent on
# every turn and counts against the anonymous token quota, so we bound it.
_MAX_DOC_CHARS = 50_000
def build_anonymous_system_prompt(anon_doc: dict[str, Any] | None = None) -> str:
"""Build the system prompt for the minimal anonymous chat agent.
The prompt keeps the assistant focused on plain Q/A from model knowledge,
inlines any uploaded document as read-only context, and treats the chat as
a registration funnel: every other SurfSense capability (scraping, live
data, deliverables, knowledge base, automations) redirects to sign-up, and
the assistant softly suggests an account when the conversation reveals a
competitive-intelligence need the platform serves.
"""
today = datetime.now(UTC).strftime("%A, %B %d, %Y")
doc_section = ""
if anon_doc:
title = str(anon_doc.get("title") or "uploaded_document")
content = str(anon_doc.get("content") or "")
truncated = content[:_MAX_DOC_CHARS]
truncation_note = ""
if len(content) > _MAX_DOC_CHARS:
truncation_note = (
"\n\n[Note: the document was truncated because it is large; "
"only the beginning is shown.]"
)
doc_section = (
"\n\n## Uploaded document (read-only)\n"
f'The user uploaded a document named "{title}". Its contents are '
"provided below for reference only. You may read it and answer "
"questions about it, but you cannot modify, save, or store it.\n\n"
f'<uploaded_document title="{title}">\n'
f"{truncated}{truncation_note}\n"
"</uploaded_document>"
)
return (
"You are SurfSense's free AI assistant, available to everyone without "
"login. SurfSense is the open-source competitive intelligence platform: "
"registered users get specialist agents that pull live market data from "
"Reddit, YouTube, Google Maps, Google Search, and the open web, turn it "
"into cited briefs, reports, podcasts, and presentations, keep findings "
"in a searchable knowledge base, and run scheduled monitoring "
"automations — plus a REST scraping API and MCP server for their own "
"agents.\n\n"
f"Today's date is {today}.\n\n"
"## How to help\n"
"- Answer the user's questions directly and conversationally. You are "
"a straightforward question-and-answer assistant.\n"
"- Answer from your own knowledge. You do NOT have web access here, so "
"for current, real-time, or fast-changing facts (news, prices, "
"weather, recent events, live data) say you can't look them up in the "
"free experience and may be out of date.\n"
"- Be concise, accurate, and helpful. Use Markdown formatting when it "
"improves readability."
f"{doc_section}\n\n"
"## What is not available here\n"
"This is the free, no-login experience. You CANNOT search the web or "
"scrape any platform (Reddit, YouTube, Google Maps, Google Search, "
"websites), save files or notes, upload additional files, generate "
"reports, podcasts, resumes, presentations, or images, search or build "
"a knowledge base, connect to apps (Gmail, Google Drive, Notion, "
"Slack, Calendar, Discord, and similar), set up automations or "
"monitoring, use the scraping API or MCP server, or remember anything "
"across sessions.\n\n"
"If the user asks for any of these, do NOT pretend to do them and "
"never claim you saved, created, scraped, or stored anything. Instead, "
"briefly say that this needs a free SurfSense account and invite them "
"to sign up at https://www.surfsense.com/register — name the specific "
"capability that would solve their request (e.g. 'a SurfSense account "
"can scrape those Reddit threads live and turn them into a cited "
"brief'). Then offer to help with what you can do here (answering from "
"your own knowledge and about any uploaded document).\n\n"
"## Suggesting SurfSense when it genuinely fits\n"
"You are also the front door to SurfSense. When the conversation "
"reveals a need the full platform serves — researching competitors, "
"tracking pricing or rankings, monitoring brand mentions or reviews, "
"gauging Reddit/YouTube sentiment, generating leads, needing current "
"web data, or wanting recurring reports — first answer as well as you "
"can from your own knowledge, then add ONE short sentence pointing out "
"that a free SurfSense account can do that with live data, linking "
"https://www.surfsense.com/register.\n"
"- Be helpful first, never salesy: the answer is the product; the "
"suggestion is a footnote.\n"
"- At most one suggestion per response, and stop suggesting entirely "
"if the user declines or ignores it.\n"
"- Do not suggest it for needs SurfSense does not serve (casual chat, "
"coding help, homework, creative writing)."
)
async def create_anonymous_chat_agent(
*,
llm: BaseChatModel,
checkpointer: Checkpointer,
anon_session_id: str | None = None,
anon_doc: dict[str, Any] | None = None,
):
"""Create a minimal Q/A agent for anonymous / free chat.
Unlike :func:`create_surfsense_deep_agent`, this agent has no filesystem,
file-intent, knowledge-base persistence, subagent, skills, or memory
middleware -- and no tools at all. It answers purely from the model's own
knowledge; any uploaded document is injected into the system prompt as
read-only context.
Args:
llm: The chat model to use (already built by the caller).
checkpointer: LangGraph checkpointer for the ephemeral anon thread.
anon_session_id: Anonymous session id (used only for telemetry/metadata).
anon_doc: Optional ``{"title", "content"}`` for an uploaded document.
"""
# Reliability-only middleware. Nothing here touches the database or
# filesystem: the call limit guards against loops, compaction summarises
# long histories into in-graph state, and retry handles provider rate
# limits.
middleware: list[Any] = [
ModelCallLimitMiddleware(thread_limit=120, run_limit=80, exit_behavior="end"),
create_surfsense_compaction_middleware(llm, StateBackend),
RetryAfterMiddleware(max_retries=3),
]
system_prompt = build_anonymous_system_prompt(anon_doc)
agent = create_agent(
llm,
system_prompt=system_prompt,
tools=[],
middleware=middleware,
context_schema=SurfSenseContextSchema,
checkpointer=checkpointer,
)
return agent.with_config(
{
"recursion_limit": 40,
"metadata": {
"ls_integration": "surfsense_anonymous_chat",
"anon_session_id": anon_session_id,
},
}
)
__all__ = ["build_anonymous_system_prompt", "create_anonymous_chat_agent"]