Files
openswarm/backend/apps/agents/browser/browser_fast_path.py
T

254 lines
11 KiB
Python

"""
Browser fast path: skip the orchestrator for plainly browser-only requests.
The orchestrator LLM is ~2/3 of the token bill on a single-browser task and
adds two model turns of latency, all to decide "delegate this to a browser
agent" and then restate the agent's own outcome. When the request is clearly
just browsing, dispatch the browser sub-agent directly and let its Done
message (a clean human reply already) be the reply.
Three gates, all conservative; any miss falls through to the orchestrator:
1. eligibility: first message of an agent session on a dashboard, no
attachments/images/skills/forced tools (those need the orchestrator).
2. a zero-cost wordlist prefilter, so non-browsy chats never pay the
classifier's latency.
3. a cheap-tier aux YES/NO classifier (provider-agnostic, timeboxed); only
an unambiguous YES takes the fast path.
"""
import asyncio
import logging
import re
import time
logger = logging.getLogger(__name__)
# Zero-cost smell test: only prompts that mention the web at all are worth a classifier call. False negatives just take the normal path.
P_BROWSY_RE = re.compile(
r"https?://|www\.|\b[a-z0-9-]+\.(com|org|net|io|co|ai|dev|app)\b"
r"|\b(browse|browser|website|web ?page|webpage|site|url|tab)\b"
r"|\b(go to|open|visit|navigate|log ?in|sign ?in|search on|look up on|check on)\b"
r"|\b(linkedin|twitter|x\.com|facebook|instagram|reddit|youtube|amazon|gmail|github"
r"|google|wikipedia|hacker ?news|tiktok|tinder|slack|notion|ebay|etsy|zillow|airbnb)\b",
re.I,
)
P_CLASSIFIER_SYSTEM = (
"You route requests to a web-browsing agent. It drives a real signed-in browser: "
"navigating sites, reading or extracting or counting what is on pages, clicking, "
"typing, and acting inside web apps (sending messages on LinkedIn or any site, "
"posting, ordering, booking, filling forms).\n"
"When a website or web app is the context, 'text/message/DM someone' means "
"sending the message inside that site, which is browsing. Treat 'text' as SMS "
"only when a phone number is given or no site is involved.\n"
"Line 1 of your reply is exactly one word: READ, ACT, or NO.\n"
"READ: the request only needs information from a PUBLIC page, no sign-in, no "
"account-specific data ('my' anything), and nothing on the page changes.\n"
"ACT: browsing completes it but it involves signing in, account data, "
"changing state (sending, posting, filling, booking, buying, opening the "
"user's own messages/feed), or the user wants a page left open on their "
"screen as the goal ('open X', 'pull up X', 'show me X'). When torn "
"between READ and ACT, say ACT.\n"
"NO: any part clearly needs something a browser cannot do: local files or "
"folders, writing or running code, a terminal, creating documents or "
"spreadsheets, SMS to a phone number, or other desktop apps. Also NO for "
"plain conversation or questions answerable without visiting any site.\n"
"Examples:\n"
"'go to maya's linkedin and text her thanks' -> ACT\n"
"'open hacker news and tell me the top story' -> READ (the answer is the "
"goal, not the open page)\n"
"'search wikipedia for tardigrades and open the article' -> ACT\n"
"'count the messages in my linkedin thread with bob' -> ACT\n"
"'find the report on stripe.com and save it to my desktop' -> NO\n"
"'text 555-0102 that I'm late' -> NO\n"
"If line 1 is NO, reply with exactly the word NO and nothing else.\n"
"If line 1 is READ or ACT, follow it with a short browsing brief:\n"
"ENTRY: the best starting URL; use a direct deep/search URL when the site's "
"pattern is well known (LinkedIn people search is "
"https://www.linkedin.com/search/results/people/?keywords=NAME).\n"
"Then 3-6 numbered steps, one short action each.\n"
"Copy any text the user wants typed, sent, or posted EXACTLY, character for "
"character. Never invent names, values, or wording the user did not give."
)
def fast_path_eligible(
prompt: str,
mode: str,
dashboard_id: str | None,
is_first_message: bool,
has_attachments: bool,
) -> bool:
"""Pure gate: cheap, no I/O. Follow-ups are excluded because the sub-agent
only receives the prompt text; the orchestrator carries the history a
follow-up usually leans on."""
if mode != "agent" or not dashboard_id or not is_first_message or has_attachments:
return False
if not prompt or not prompt.strip():
return False
return bool(P_BROWSY_RE.search(prompt))
def parse_verdict_and_brief(text: str) -> tuple[str, str]:
"""Line 1 carries READ/ACT/NO; the rest is the routing brief. Anything
unparseable is 'no' (normal path)."""
lines = (text or "").strip().splitlines()
head = lines[0].strip().upper() if lines else ""
if head.startswith("READ"):
verdict = "read"
elif head.startswith("ACT") or head.startswith("YES"):
verdict = "act"
else:
return "no", ""
brief = "\n".join(line for line in lines[1:] if line.strip()).strip()
return verdict, brief[:700]
P_ENTRY_RE = re.compile(r"^\s*ENTRY:\s*(https?://\S+)", re.I | re.M)
def entry_url_from_brief(brief: str) -> str:
"""The brief's ENTRY deep URL, or ''. Powers dispatch pre-navigation: a NEW
card opens directly on it instead of google, killing the orient+navigate
turns; a REUSED card is never moved (its deeper live state wins)."""
m = P_ENTRY_RE.search(brief or "")
return m.group(1).rstrip(".,;)") if m else ""
def compose_task(prompt: str, brief: str) -> str:
"""User's words first and authoritative; the brief is advisory routing.
Skill replay keys on the parent's user message, so brief variance is safe."""
if not brief:
return prompt
return (
f"{prompt}\n\n"
"[routing brief from a fast pre-pass; follow it unless the live page disagrees]\n"
f"{brief}"
)
def dispatch_failed(result: dict) -> bool:
"""Fail-closed: a real completion sets done=True (the sub-agent called Done
with success, and the honesty gate agreed). Anything else, a hung/errored
dispatch or the model reporting it couldn't, means recovery should run. The
recovery task's verify-first wording makes a rare redundant retry safe."""
return not (isinstance(result, dict) and result.get("done", False))
NO_DASHBOARD_REPLY = (
"I can't drive a browser right now because no OpenSwarm window is connected. "
"Open the app window and send this again."
)
def recovery_task(prompt: str, first_report: str, verified_undelivered: bool = False) -> str:
"""One informed retry, replacing the orchestrator's recovery role. With
verified_undelivered the send-probe already proved nothing landed, so the
retry gets clearance instead of hedging; otherwise verify-first wording
keeps a maybe-already-sent irreversible step from repeating."""
report = (first_report or "").strip()[:600] or "no report (the browser died)"
guard = (
"A read-only check JUST confirmed the message is NOT yet delivered, so "
"performing the send is safe. Do it exactly ONCE, solo, with `expect` proof."
) if verified_undelivered else (
"If that attempt may have already performed an irreversible step "
"(send/submit/post/pay), FIRST verify on the page whether it happened; "
"if it did, do NOT repeat it, report DONE with that proof."
)
return (
"A previous browser attempt at this task did not finish. It reported:\n"
f"{report}\n\n"
f"Finish the task: {prompt}\n\n{guard}"
)
def send_probe_task(prompt: str, payload: str) -> str:
"""Recovery pre-check for send-class failures: a read-only dispatch whose
verdict gates the retry in code (r44's retry skipped its promised verify
step, so prose alone is not a guard)."""
return (
"READ-ONLY verification, do NOT send, type, click any send/submit "
"control, or open a compose box. A previous attempt at the task below "
f"may or may not have already delivered its message:\n{prompt}\n\n"
"Check the relevant conversation/thread/history for this exact text:\n"
f'"{payload}"\n'
"Count near-variants too (extra whitespace, duplicated text). "
"End with exactly one line: 'OUTCOME: PAYLOAD-FOUND <where and timestamp>' "
"or 'OUTCOME: PAYLOAD-NOT-FOUND'."
)
def probe_verdict(summary: str) -> str:
"""'found' | 'not-found' | 'unknown'. NOT-FOUND is checked first because
the FOUND token is its substring."""
s = (summary or "").upper()
if "PAYLOAD-NOT-FOUND" in s:
return "not-found"
if "PAYLOAD-FOUND" in s:
return "found"
return "unknown"
def already_sent_reply(payload: str, probe_report: str) -> str:
"""First attempt delivered before dying; the fix is evidence, not a resend."""
proof = (probe_report or "").strip()[:400]
return (
"The first attempt actually delivered the message before it lost the "
f'browser: a read-only check found "{payload}" already in the '
f"conversation, so I did NOT send it again.\n\n{proof}"
)
def unverifiable_reply(payload: str, first_report: str) -> str:
"""Fail-closed: can't prove the send didn't land, so don't risk a double."""
report = (first_report or "").strip()[:400]
return (
"The browser attempt failed after it had already typed the message "
f'("{payload}"), and a read-only check could not confirm whether it was '
"sent. I'm not retrying an irreversible send blind; please glance at "
f"the thread and re-ask if it's missing.\n\nFirst attempt: {report}"
)
def normalize_for_classifier(prompt: str) -> str:
"""Haiku reads bare 'text him' as SMS even with a site as context. In the
browsy-prefiltered pool, text-with-no-phone-number is in-site messaging,
so spell it out for the small model. Only the classifier sees this."""
if re.search(r"\d{7,}", prompt):
return prompt
return re.sub(r"\btext(ing|ed|s)?\b", "message", prompt, flags=re.I)
async def classify_and_brief(prompt: str, settings, primary_api: str | None) -> tuple[str, str]:
"""One cheap aux call returns a READ/ACT/NO verdict plus a routing brief
(entry URL + step outline), timeboxed; any failure means NO (normal path)."""
t0 = time.monotonic()
try:
from backend.apps.settings.credentials import get_anthropic_client_for_model
from backend.apps.agents.providers.registry import resolve_aux_model
aux_model, _ = await resolve_aux_model(
settings, preferred_tier="haiku", primary_api=primary_api,
)
client = get_anthropic_client_for_model(settings, aux_model)
resp = await asyncio.wait_for(
client.messages.create(
model=aux_model,
max_tokens=250,
temperature=0,
system=P_CLASSIFIER_SYSTEM,
messages=[{"role": "user", "content": normalize_for_classifier(prompt[:2000])}],
),
timeout=8.0,
)
from backend.apps.agents.core.aux_llm import safe_resp_text
verdict, brief = parse_verdict_and_brief(safe_resp_text(resp))
logger.info(
f"[browser-fast-path] classifier: {verdict.upper()} brief={len(brief)}ch "
f"model={aux_model} in {int((time.monotonic() - t0) * 1000)}ms"
)
return verdict, brief
except Exception as e:
logger.warning(f"[browser-fast-path] classifier unavailable, normal path: {e}")
return "no", ""