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fix(email): route summaries through shared LLM adapter (#5841)
* fix(email): route summaries through shared llm adapter * chore(ci): refresh PR checks * fix(email): preserve scheduled summary safeguards --------- Co-authored-by: Matyas Fenyves <16389204+uhhgoat@users.noreply.github.com>
This commit is contained in:
parent
e4fa4ae5dd
commit
42da399b4d
7 changed files with 670 additions and 60 deletions
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@ -247,6 +247,7 @@ import re as _re_reply
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_REPLY_OPEN_RE = _re_reply.compile(r"<<<\s*(?:REPLY|SUMMARY|OUTPUT)\s*>>+", _re_reply.I)
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_REPLY_CLOSE_RE = _re_reply.compile(r"<<<\s*END\s*>>+", _re_reply.I)
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_REPLY_ROLE_MARKER_RE = _re_reply.compile(r"</?\|(?:assistant|assistan|user|system|tool)\|>?|</\|end\|>?", _re_reply.I)
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_SUMMARY_BULLET_RE = _re_reply.compile(r"^(?:[-*\u2022]\s+|\d+[.)]\s+)")
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def _extract_reply(text: str) -> str:
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@ -277,6 +278,125 @@ def _extract_reply(text: str) -> str:
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return _strip_think(t).strip()
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def _build_email_summary_messages(sender: str, subject: str, body_for_llm: str) -> list[dict[str, str]]:
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return [
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{
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"role": "system",
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"content": (
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"You are an email summarizer. Format: 1-3 short bullet points "
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"(use '- '). Cover: main point, action items, deadlines. If the "
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"email has attachments (marked '--- ATTACHMENTS ---'), USE THEIR "
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"CONTENTS - pull invoice totals, deadlines, key clauses, concrete "
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"numbers/dates from PDFs/docs into the bullets. Be terse.\n\n"
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"OUTPUT FORMAT: Put ONLY the bullet points between these exact "
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"markers, each on its own line:\n"
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"<<<SUMMARY>>>\n"
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"- ...\n"
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"<<<END>>>\n"
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"Any reasoning must come BEFORE <<<SUMMARY>>> (ideally inside "
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"<think>...</think>). Only the text between the markers is kept."
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),
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},
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{
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"role": "user",
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"content": (
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f"From: {sender}\nSubject: {subject}\n\n{body_for_llm[:12000]}"
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"\n\n---\n\nSummarize the email. Output the bullets between "
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"<<<SUMMARY>>> and <<<END>>>."
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),
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},
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]
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async def _generate_email_summary(
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url: str,
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model: str,
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sender: str,
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subject: str,
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body_for_llm: str,
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*,
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headers: dict | None = None,
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max_tokens: int = 8192,
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timeout: int = 180,
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) -> str:
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"""Generate an interactive email summary through the shared LLM adapter."""
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from src.llm_core import llm_call_async
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raw = await llm_call_async(
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url=url,
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model=model,
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messages=_build_email_summary_messages(sender, subject, body_for_llm),
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temperature=0.3,
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max_tokens=max_tokens,
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headers=headers,
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timeout=timeout,
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workload="foreground",
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)
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return _normalize_email_summary(raw)
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async def _generate_scheduled_email_summary(
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url: str,
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model: str,
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sender: str,
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subject: str,
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body_for_llm: str,
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*,
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headers: dict | None = None,
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owner: str | None = None,
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max_tokens: int = 8192,
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timeout: int = 180,
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) -> str:
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"""Generate a scheduled summary through the background task candidate chain."""
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from src.task_endpoint import task_llm_call_async
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raw = await task_llm_call_async(
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messages=_build_email_summary_messages(sender, subject, body_for_llm),
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fallback_url=url,
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fallback_model=model,
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fallback_headers=headers,
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owner=owner,
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temperature=0.3,
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max_tokens=max_tokens,
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timeout=timeout,
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)
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return _normalize_email_summary(raw)
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def _normalize_email_summary(raw) -> str:
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"""Extract a stable cache/UI summary from provider output."""
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raw_text = raw or ""
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if _REPLY_OPEN_RE.search(raw_text):
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summary = _extract_reply(raw_text)
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if summary:
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return summary
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cleaned = _strip_think(raw_text).strip()
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bullets = [
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line.strip()
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for line in cleaned.splitlines()
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if _SUMMARY_BULLET_RE.match(line.strip())
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]
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if bullets:
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return "\n".join(bullets)
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return cleaned.strip()
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EMAIL_SUMMARY_ERROR_CODE = "email_summary_unavailable"
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EMAIL_SUMMARY_ERROR_MESSAGE = "Failed to summarize"
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def _email_summary_failure_log_detail(exc: BaseException) -> str:
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"""Return useful provider-failure metadata without echoing exception text."""
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detail = f"type={type(exc).__name__}"
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status = getattr(exc, "status_code", None)
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if status is None:
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status = getattr(getattr(exc, "response", None), "status_code", None)
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if isinstance(status, int):
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detail += f" status={status}"
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return detail
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def _apply_email_style_mechanics(text: str) -> str:
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"""Enforce deterministic writing-style mechanics that models often miss."""
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if not text:
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@ -40,6 +40,7 @@ from routes.email_helpers import (
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_pre_retrieve_context,
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_attach_compose_uploads, _cleanup_compose_uploads, _q,
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SCHEDULED_DB, _EMAIL_REPLY_SYS_PROMPT_BASE, _email_cache_owner_clause,
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_generate_scheduled_email_summary, _email_summary_failure_log_detail,
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)
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logger = logging.getLogger(__name__)
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@ -653,6 +654,7 @@ async def _auto_summarize_pass_single(days_back: int = 1, account_id: str | None
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no_msgid = 0
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examined = 0
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_summaries_created = 0
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_summary_failed = 0
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_events_created = 0
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_replies_drafted = 0
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_reply_failed = 0
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@ -785,16 +787,17 @@ async def _auto_summarize_pass_single(days_back: int = 1, account_id: str | None
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if need_sum:
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try:
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summary = await task_llm_call_async(
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messages=[
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{"role": "system", "content": "You are an email summarizer. Format: 1-3 short bullet points (use '- '). Cover: main point, action items, deadlines. If the email has attachments (marked '--- ATTACHMENTS ---'), USE THEIR CONTENTS — pull out invoice totals, deadlines, key clauses, any concrete numbers/dates in PDFs/docs, and reflect them in the bullets. Be terse.\n\nOUTPUT FORMAT: Put ONLY the bullet points between these exact markers, each on its own line:\n<<<SUMMARY>>>\n- ...\n<<<END>>>\nAny reasoning or planning must come BEFORE <<<SUMMARY>>> (ideally inside <think>...</think>). Only the text between the markers is kept."},
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{"role": "user", "content": f"From: {sender}\nSubject: {subject}\n\n{body_for_llm[:12000]}\n\n---\n\nSummarize the email. Output the bullets between <<<SUMMARY>>> and <<<END>>>."},
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],
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fallback_url=url, fallback_model=model, fallback_headers=headers,
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summary = await _generate_scheduled_email_summary(
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url=url,
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model=model,
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sender=sender,
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subject=subject,
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body_for_llm=body_for_llm,
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headers=req_headers,
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owner=account_owner or None,
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temperature=0.3, max_tokens=16384, timeout=240,
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max_tokens=16384,
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timeout=240,
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)
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summary = _extract_reply((summary or "").strip())
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if summary:
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_c = _sql3.connect(SCHEDULED_DB)
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_c.execute("""
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@ -808,10 +811,19 @@ async def _auto_summarize_pass_single(days_back: int = 1, account_id: str | None
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_summaries_created += 1
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_uid_text = uid.decode() if isinstance(uid, bytes) else str(uid)
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_detail_lines.append(f"summary · {_folder}#{_uid_text} · {subject or '(no subject)'} — {sender or '(unknown sender)'}")
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else:
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_summary_failed += 1
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_uid_text = uid.decode() if isinstance(uid, bytes) else str(uid)
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_detail_lines.append(f"summary empty · {_folder}#{_uid_text} · {subject or '(no subject)'} — {sender or '(unknown sender)'}")
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except Exception as e:
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_summary_failed += 1
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_uid_text = uid.decode() if isinstance(uid, bytes) else str(uid)
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_detail_lines.append(f"summary failed · {_folder}#{_uid_text} · {subject or '(no subject)'} — {sender or '(unknown sender)'}")
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logger.warning(f"Auto-summary {uid} failed: {e}")
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logger.warning(
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"Auto-summary uid=%s failed %s",
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_uid_text,
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_email_summary_failure_log_detail(e),
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)
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if need_reply:
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await _emit_progress(progress_cb, f"Drafting reply {processed + 1}/{_max_process} · checked {examined}/{len(uid_list)}")
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@ -1320,6 +1332,8 @@ async def _auto_summarize_pass_single(days_back: int = 1, account_id: str | None
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parts.append(f"processed {processed} new")
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if auto_sum:
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parts.append(f"summarized {_summaries_created}")
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if _summary_failed:
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parts.append(f"{_summary_failed} summary failed")
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if auto_reply_draft:
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parts.append(f"drafted {_replies_drafted} repl" + ("y" if _replies_drafted == 1 else "ies"))
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if _reply_failed:
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@ -57,7 +57,8 @@ from routes.email_helpers import (
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_extract_attachment_to_disk, _extract_html, _extract_text,
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_fetch_sender_thread_context, _pre_retrieve_context,
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_EMAIL_REPLY_SYS_PROMPT_BASE, _POOL_HOOKS,
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_friendly_email_auth_error,
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_friendly_email_auth_error, _email_summary_failure_log_detail,
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_generate_email_summary, EMAIL_SUMMARY_ERROR_CODE, EMAIL_SUMMARY_ERROR_MESSAGE,
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SendEmailRequest, ExtractStyleRequest,
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ATTACHMENTS_DIR, COMPOSE_UPLOADS_DIR, SCHEDULED_DB,
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attachment_extract_dir, _email_cache_owner_clause, email_translation_body_hash,
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@ -4766,8 +4767,6 @@ def setup_email_routes():
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"""Generate a quick AI summary of an email body."""
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try:
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from src.endpoint_resolver import resolve_endpoint
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from src.llm_core import _uses_max_completion_tokens, _restricts_temperature
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import requests as _req
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body = data.get("body", "")
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subject = data.get("subject", "")
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@ -4778,7 +4777,11 @@ def setup_email_routes():
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if account_id:
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_assert_owns_account(account_id, owner)
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if not body:
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return {"success": False, "error": "No body provided"}
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return {
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"success": False,
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"error": "No body provided",
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"error_code": "email_summary_missing_body",
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}
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# If we know which UID this is, fetch the raw message and pull
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# attachment text so the summary can reference invoice totals,
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@ -4807,53 +4810,43 @@ def setup_email_routes():
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if not url:
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url, model, headers = resolve_endpoint("default", owner=owner)
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if not url or not model:
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return {"success": False, "error": "No LLM endpoint configured"}
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return {
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"success": False,
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"error": "No model configured for email summaries",
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"error_code": "email_summary_not_configured",
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}
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req_headers = {"Content-Type": "application/json"}
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if headers:
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req_headers.update(headers)
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tok_key = "max_completion_tokens" if _uses_max_completion_tokens(model) else "max_tokens"
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payload = {
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"model": model,
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"messages": [
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{"role": "system", "content": "You are an email summarizer. Format: 1-3 short bullet points (use '- '). Cover: main point, action items, deadlines. If the email has attachments (marked '--- ATTACHMENTS ---'), USE THEIR CONTENTS — pull invoice totals, deadlines, key clauses, concrete numbers/dates from PDFs/docs into the bullets. Be terse.\n\nOUTPUT FORMAT: Put ONLY the bullet points between these exact markers, each on its own line:\n<<<SUMMARY>>>\n- ...\n<<<END>>>\nAny reasoning must come BEFORE <<<SUMMARY>>> (ideally inside <think>...</think>). Only the text between the markers is kept."},
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{"role": "user", "content": f"From: {sender}\nSubject: {subject}\n\n{body_for_llm[:12000]}\n\n---\n\nSummarize the email. Output the bullets between <<<SUMMARY>>> and <<<END>>>."},
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],
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tok_key: 8192,
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"temperature": 0.3,
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"stream": False,
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}
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# Reasoning models (o1/o3/o4/gpt-5) reject an explicit temperature.
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if _restricts_temperature(model):
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payload.pop("temperature", None)
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resp = await asyncio.to_thread(
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_req.post, url, json=payload, headers=req_headers, timeout=180
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)
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if not resp.ok:
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return {"success": False, "error": f"LLM HTTP {resp.status_code}"}
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rdata = resp.json()
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msg = (rdata.get("choices") or [{}])[0].get("message", {})
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content = (msg.get("content") or "").strip()
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content = _extract_reply(content)
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try:
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content = await _generate_email_summary(
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url=url,
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model=model,
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sender=sender,
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subject=subject,
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body_for_llm=body_for_llm,
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headers=req_headers,
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max_tokens=8192,
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timeout=180,
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)
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except Exception as e:
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logger.warning(
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"Email summary LLM call failed %s",
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_email_summary_failure_log_detail(e),
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)
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return {
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"success": False,
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"error": EMAIL_SUMMARY_ERROR_MESSAGE,
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"error_code": EMAIL_SUMMARY_ERROR_CODE,
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}
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if not content:
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# Model put everything in reasoning_content — extract bullet points
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rc = (msg.get("reasoning_content") or "").strip()
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# Find bullet-point style output (lines starting with -, •, *, or numbered)
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bullet_lines = []
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for line in rc.split("\n"):
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stripped = line.strip()
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if re.match(r"^[-•*]\s+|^\d+[.)]\s+", stripped):
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bullet_lines.append(stripped)
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if bullet_lines:
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content = "\n".join(bullet_lines)
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else:
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# Last resort: take the last paragraph
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paragraphs = [p.strip() for p in rc.split("\n\n") if p.strip()]
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content = paragraphs[-1] if paragraphs else rc[:500]
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if not content:
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return {"success": False, "error": "Empty response from model"}
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return {
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"success": False,
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"error": "The model returned an empty summary",
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"error_code": "email_summary_empty",
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}
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# Cache the summary if we have a message_id
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mid = data.get("message_id", "")
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@ -4876,8 +4869,15 @@ def setup_email_routes():
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return {"success": True, "summary": content, "model_used": model}
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except Exception as e:
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logger.error(f"Failed to summarize: {e}")
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return {"success": False, "error": "Mail operation failed"}
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logger.error(
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"Email summary route failed %s",
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_email_summary_failure_log_detail(e),
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)
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return {
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"success": False,
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"error": EMAIL_SUMMARY_ERROR_MESSAGE,
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"error_code": EMAIL_SUMMARY_ERROR_CODE,
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}
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@router.post("/translate")
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async def translate_email(data: dict, owner: str = Depends(require_owner)):
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@ -13,7 +13,7 @@ import { makeWindowDraggable } from './windowDrag.js';
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import {
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_esc, _escLinkify, _extractName, _parseTurnMeta,
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_formatBubbleDate, _formatRecipients, _senderColor, _initials,
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_sanitizeHtml,
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_sanitizeHtml, _renderEmailSummaryError,
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_TALON_WROTE, _TALON_FROM, _TALON_SENT, _TALON_SUBJ, _TALON_TO,
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_TALON_ORIG_RE, _SIG_BLOAT_MIN_CHARS,
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} from './emailLibrary/utils.js';
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@ -7259,12 +7259,11 @@ async function _generateSummary(reader, data, btn) {
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if (label) label.textContent = 'Summary';
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}
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} else {
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content.innerHTML = `<span style="color:var(--red)">${_esc(result.error || 'Failed to summarize')}</span>`;
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panel.remove();
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_renderEmailSummaryError(content, result);
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}
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} catch (e) {
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sp.destroy();
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panel.remove();
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_renderEmailSummaryError(content, null);
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if (uiModule) uiModule.showError?.('Failed to summarize');
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} finally {
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if (btn) btn.disabled = false;
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|
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@ -30,6 +30,25 @@ export function _esc(text) {
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return div.innerHTML;
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}
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const _EMAIL_SUMMARY_ERROR_MESSAGES = Object.freeze({
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email_summary_missing_body: 'No email body to summarize',
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email_summary_not_configured: 'No model configured for email summaries',
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email_summary_empty: 'The model returned an empty summary',
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email_summary_unavailable: 'Failed to summarize',
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});
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export function _emailSummaryErrorMessage(result) {
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const code = String(result?.error_code || '');
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return _EMAIL_SUMMARY_ERROR_MESSAGES[code] || 'Failed to summarize';
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}
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export function _renderEmailSummaryError(container, result) {
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const message = container.ownerDocument.createElement('span');
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message.style.color = 'var(--red)';
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message.textContent = _emailSummaryErrorMessage(result);
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container.replaceChildren(message);
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}
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function _attrEsc(text) {
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return String(text ?? '')
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.replace(/"/g, '"')
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52
tests/test_email_summary_error_ui_js.py
Normal file
52
tests/test_email_summary_error_ui_js.py
Normal file
|
|
@ -0,0 +1,52 @@
|
|||
import json
|
||||
import shutil
|
||||
import subprocess
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
_REPO = Path(__file__).resolve().parent.parent
|
||||
_UTILS = (_REPO / "static" / "js" / "emailLibrary" / "utils.js").as_posix()
|
||||
_HAS_NODE = shutil.which("node") is not None
|
||||
|
||||
pytestmark = pytest.mark.skipif(not _HAS_NODE, reason="node binary not on PATH")
|
||||
|
||||
|
||||
def test_email_summary_renderer_ignores_untrusted_provider_error_text():
|
||||
secret = (
|
||||
"endpoint=https://private.example.internal/v1 provider=ollama "
|
||||
"model=private-model response_body=private-response "
|
||||
"Authorization: Bearer token-secret-value"
|
||||
)
|
||||
script = f"""
|
||||
import {{ _renderEmailSummaryError }} from '{_UTILS}';
|
||||
const host = {{
|
||||
ownerDocument: {{
|
||||
createElement() {{ return {{ style: {{}}, textContent: '' }}; }},
|
||||
}},
|
||||
replaceChildren(node) {{ this.child = node; }},
|
||||
}};
|
||||
_renderEmailSummaryError(host, {{
|
||||
error_code: 'email_summary_unavailable',
|
||||
error: {json.dumps(secret)},
|
||||
}});
|
||||
console.log(JSON.stringify({{
|
||||
text: host.child.textContent,
|
||||
color: host.child.style.color,
|
||||
}}));
|
||||
"""
|
||||
|
||||
proc = subprocess.run(
|
||||
["node", "--input-type=module"],
|
||||
input=script,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
cwd=str(_REPO),
|
||||
timeout=30,
|
||||
)
|
||||
|
||||
assert proc.returncode == 0, proc.stderr
|
||||
rendered = json.loads(proc.stdout)
|
||||
assert rendered == {"text": "Failed to summarize", "color": "var(--red)"}
|
||||
assert secret not in proc.stdout
|
||||
406
tests/test_email_summary_llm.py
Normal file
406
tests/test_email_summary_llm.py
Normal file
|
|
@ -0,0 +1,406 @@
|
|||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sqlite3
|
||||
import sys
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
_TMP_DATA = Path(tempfile.mkdtemp(prefix="odysseus-email-summary-"))
|
||||
os.environ.setdefault("DATA_DIR", str(_TMP_DATA))
|
||||
os.environ.setdefault("DATABASE_URL", f"sqlite:///{_TMP_DATA / 'app.db'}")
|
||||
|
||||
PROJECT_ROOT = Path(__file__).resolve().parent.parent
|
||||
if str(PROJECT_ROOT) not in sys.path:
|
||||
sys.path.insert(0, str(PROJECT_ROOT))
|
||||
|
||||
|
||||
def _route_endpoint(router, path: str, method: str):
|
||||
method = method.upper()
|
||||
for route in router.routes:
|
||||
if route.path == path and method in getattr(route, "methods", set()):
|
||||
return route.endpoint
|
||||
raise AssertionError(f"route not found: {method} {path}")
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_generate_email_summary_uses_shared_llm_adapter(monkeypatch):
|
||||
import routes.email_helpers as email_helpers
|
||||
import src.llm_core as llm_core
|
||||
|
||||
calls = {}
|
||||
|
||||
async def fake_llm_call_async(url, model, messages, **kwargs):
|
||||
calls["url"] = url
|
||||
calls["model"] = model
|
||||
calls["messages"] = messages
|
||||
calls["kwargs"] = kwargs
|
||||
return "thinking before marker\n<<<SUMMARY>>>\n- Pay the invoice by Friday.\n<<<END>>>"
|
||||
|
||||
monkeypatch.setattr(llm_core, "llm_call_async", fake_llm_call_async)
|
||||
|
||||
summary = await email_helpers._generate_email_summary(
|
||||
url="https://chatgpt.com/backend-api/codex/responses",
|
||||
model="gpt-5.5",
|
||||
sender="Billing <billing@example.com>",
|
||||
subject="Invoice due",
|
||||
body_for_llm="Please pay invoice 123 by Friday.",
|
||||
headers={"Authorization": "Bearer test"},
|
||||
max_tokens=1234,
|
||||
timeout=45,
|
||||
)
|
||||
|
||||
assert summary == "- Pay the invoice by Friday."
|
||||
assert calls["url"] == "https://chatgpt.com/backend-api/codex/responses"
|
||||
assert calls["model"] == "gpt-5.5"
|
||||
assert calls["kwargs"]["headers"] == {"Authorization": "Bearer test"}
|
||||
assert calls["kwargs"]["temperature"] == 0.3
|
||||
assert calls["kwargs"]["max_tokens"] == 1234
|
||||
assert calls["kwargs"]["timeout"] == 45
|
||||
assert calls["kwargs"]["workload"] == "foreground"
|
||||
assert calls["messages"][0]["role"] == "system"
|
||||
assert calls["messages"][1]["role"] == "user"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_scheduled_email_summary_uses_background_fallback_chain(monkeypatch):
|
||||
import routes.email_helpers as email_helpers
|
||||
import src.llm_core as llm_core
|
||||
import src.task_endpoint as task_endpoint
|
||||
|
||||
candidates = [
|
||||
("http://primary.invalid/v1", "primary-model", {"X-Candidate": "primary"}),
|
||||
("http://fallback.invalid/v1", "fallback-model", {"X-Candidate": "fallback"}),
|
||||
]
|
||||
resolve_calls = []
|
||||
wait_calls = []
|
||||
llm_calls = []
|
||||
|
||||
def fake_resolve_task_candidates(**kwargs):
|
||||
resolve_calls.append(kwargs)
|
||||
return candidates
|
||||
|
||||
async def fake_wait_for_interactive_quiet(label):
|
||||
wait_calls.append(label)
|
||||
return False
|
||||
|
||||
async def fake_llm_call_async(url, model, messages, **kwargs):
|
||||
llm_calls.append((url, model, messages, kwargs))
|
||||
if model == "primary-model":
|
||||
raise RuntimeError("primary unavailable")
|
||||
return "<<<SUMMARY>>>\n- Used the fallback model.\n<<<END>>>"
|
||||
|
||||
monkeypatch.setattr(task_endpoint, "resolve_task_candidates", fake_resolve_task_candidates)
|
||||
monkeypatch.setattr(task_endpoint, "wait_for_interactive_quiet", fake_wait_for_interactive_quiet)
|
||||
monkeypatch.setattr(llm_core, "llm_call_async", fake_llm_call_async)
|
||||
|
||||
summary = await email_helpers._generate_scheduled_email_summary(
|
||||
url="http://caller-fallback.invalid/v1",
|
||||
model="caller-fallback-model",
|
||||
sender="Sender <sender@example.com>",
|
||||
subject="Scheduled subject",
|
||||
body_for_llm="Please summarize this scheduled email.",
|
||||
headers={"Authorization": "Bearer test"},
|
||||
owner="alice",
|
||||
max_tokens=321,
|
||||
timeout=54,
|
||||
)
|
||||
|
||||
assert summary == "- Used the fallback model."
|
||||
assert resolve_calls == [{
|
||||
"fallback_url": "http://caller-fallback.invalid/v1",
|
||||
"fallback_model": "caller-fallback-model",
|
||||
"fallback_headers": {"Authorization": "Bearer test"},
|
||||
"owner": "alice",
|
||||
}]
|
||||
assert wait_calls == ["background task LLM"]
|
||||
assert [call[1] for call in llm_calls] == ["primary-model", "fallback-model"]
|
||||
assert all(call[3]["workload"] == "background" for call in llm_calls)
|
||||
assert all(call[3]["max_tokens"] == 321 for call in llm_calls)
|
||||
assert all(call[3]["timeout"] == 54 for call in llm_calls)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_scheduled_local_summary_is_preempted_by_foreground_call(monkeypatch):
|
||||
import routes.email_helpers as email_helpers
|
||||
import src.llm_core as llm_core
|
||||
import src.task_endpoint as task_endpoint
|
||||
|
||||
local_url = "http://127.0.0.1:11434/v1/chat/completions"
|
||||
background_started = asyncio.Event()
|
||||
never_release = asyncio.Event()
|
||||
observed_workloads = []
|
||||
|
||||
monkeypatch.setenv("ODYSSEUS_LOCAL_MODEL_GATE", "true")
|
||||
monkeypatch.setenv("BACKGROUND_TASK_FOREGROUND_GATE", "false")
|
||||
monkeypatch.setattr(llm_core, "_LOCAL_MODEL_LOCK", asyncio.Lock())
|
||||
monkeypatch.setattr(llm_core, "_LOCAL_MODEL_CURRENT", {})
|
||||
monkeypatch.setattr(llm_core, "_LOCAL_MODEL_WAITING_FOREGROUND", 0)
|
||||
monkeypatch.setattr(
|
||||
task_endpoint,
|
||||
"resolve_task_candidates",
|
||||
lambda **_kwargs: [(local_url, "scheduled-model", {})],
|
||||
)
|
||||
|
||||
async def fake_wait_for_interactive_quiet(_label):
|
||||
return False
|
||||
|
||||
async def gated_llm_call(url, model, messages, **kwargs):
|
||||
assert messages
|
||||
workload = kwargs.get("workload")
|
||||
observed_workloads.append(workload)
|
||||
async with llm_core._local_model_slot(url, model, workload=workload):
|
||||
background_started.set()
|
||||
await never_release.wait()
|
||||
return "unreachable"
|
||||
|
||||
monkeypatch.setattr(task_endpoint, "wait_for_interactive_quiet", fake_wait_for_interactive_quiet)
|
||||
monkeypatch.setattr(llm_core, "llm_call_async", gated_llm_call)
|
||||
|
||||
background_task = asyncio.create_task(email_helpers._generate_scheduled_email_summary(
|
||||
url=local_url,
|
||||
model="scheduled-model",
|
||||
sender="Sender",
|
||||
subject="Scheduled",
|
||||
body_for_llm="Scheduled body",
|
||||
owner="alice",
|
||||
))
|
||||
foreground_task = None
|
||||
try:
|
||||
await asyncio.wait_for(background_started.wait(), timeout=1)
|
||||
|
||||
async def run_foreground():
|
||||
async with llm_core._local_model_slot(
|
||||
local_url,
|
||||
"interactive-model",
|
||||
workload="foreground",
|
||||
):
|
||||
return True
|
||||
|
||||
foreground_task = asyncio.create_task(run_foreground())
|
||||
with pytest.raises(asyncio.CancelledError):
|
||||
await asyncio.wait_for(background_task, timeout=1)
|
||||
assert await asyncio.wait_for(foreground_task, timeout=1) is True
|
||||
assert observed_workloads == ["background"]
|
||||
finally:
|
||||
for task in (background_task, foreground_task):
|
||||
if task is not None and not task.done():
|
||||
task.cancel()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_manual_email_summary_uses_shared_helper_and_caches(tmp_path, monkeypatch):
|
||||
import routes.email_helpers as email_helpers
|
||||
import routes.email_routes as email_routes
|
||||
import src.endpoint_resolver as endpoint_resolver
|
||||
|
||||
db_path = tmp_path / "scheduled_emails.db"
|
||||
monkeypatch.setattr(email_helpers, "SCHEDULED_DB", db_path)
|
||||
monkeypatch.setattr(email_routes, "SCHEDULED_DB", db_path)
|
||||
email_helpers._init_scheduled_db()
|
||||
|
||||
resolve_calls = []
|
||||
|
||||
def fake_resolve_endpoint(kind, owner=None):
|
||||
resolve_calls.append((kind, owner))
|
||||
assert kind == "utility"
|
||||
assert owner == "alice"
|
||||
return (
|
||||
"https://chatgpt.com/backend-api/codex/responses",
|
||||
"gpt-5.5",
|
||||
{"Authorization": "Bearer test"},
|
||||
)
|
||||
|
||||
helper_calls = {}
|
||||
|
||||
async def fake_generate_email_summary(**kwargs):
|
||||
helper_calls.update(kwargs)
|
||||
return "- Manual summary"
|
||||
|
||||
monkeypatch.setattr(endpoint_resolver, "resolve_endpoint", fake_resolve_endpoint)
|
||||
monkeypatch.setattr(email_routes, "_generate_email_summary", fake_generate_email_summary)
|
||||
|
||||
router = email_routes.setup_email_routes()
|
||||
summarize = _route_endpoint(router, "/api/email/summarize", "POST")
|
||||
|
||||
result = await summarize(
|
||||
{
|
||||
"body": "This is a long enough email body for manual summary.",
|
||||
"subject": "Manual subject",
|
||||
"from": "Sender <sender@example.com>",
|
||||
"message_id": "<manual@example.com>",
|
||||
"folder": "INBOX",
|
||||
},
|
||||
owner="alice",
|
||||
)
|
||||
|
||||
assert result == {
|
||||
"success": True,
|
||||
"summary": "- Manual summary",
|
||||
"model_used": "gpt-5.5",
|
||||
}
|
||||
assert resolve_calls == [("utility", "alice")]
|
||||
assert helper_calls["url"] == "https://chatgpt.com/backend-api/codex/responses"
|
||||
assert helper_calls["model"] == "gpt-5.5"
|
||||
assert helper_calls["headers"]["Authorization"] == "Bearer test"
|
||||
assert helper_calls["headers"]["Content-Type"] == "application/json"
|
||||
|
||||
conn = sqlite3.connect(db_path)
|
||||
try:
|
||||
row = conn.execute(
|
||||
"SELECT owner, summary, model_used FROM email_summaries WHERE message_id=?",
|
||||
("<manual@example.com>",),
|
||||
).fetchone()
|
||||
finally:
|
||||
conn.close()
|
||||
assert row == ("alice", "- Manual summary", "gpt-5.5")
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize("exception_kind", ["http", "runtime"])
|
||||
async def test_manual_email_summary_never_exposes_provider_exception(
|
||||
monkeypatch,
|
||||
caplog,
|
||||
exception_kind,
|
||||
):
|
||||
from fastapi import HTTPException
|
||||
import routes.email_routes as email_routes
|
||||
import src.endpoint_resolver as endpoint_resolver
|
||||
|
||||
secret_detail = (
|
||||
"endpoint=https://private.example.internal/v1 provider=ollama "
|
||||
"model=private-model response_body=private-response "
|
||||
"Authorization: Bearer token-secret-value"
|
||||
)
|
||||
|
||||
def fake_resolve_endpoint(kind, owner=None):
|
||||
assert kind == "utility"
|
||||
assert owner == "alice"
|
||||
return (
|
||||
"https://private.example.internal/v1",
|
||||
"private-model",
|
||||
{"Authorization": "Bearer token-secret-value"},
|
||||
)
|
||||
|
||||
async def fail_summary(**_kwargs):
|
||||
if exception_kind == "http":
|
||||
raise HTTPException(status_code=502, detail=secret_detail)
|
||||
raise RuntimeError(secret_detail)
|
||||
|
||||
monkeypatch.setattr(endpoint_resolver, "resolve_endpoint", fake_resolve_endpoint)
|
||||
monkeypatch.setattr(email_routes, "_generate_email_summary", fail_summary)
|
||||
caplog.set_level(logging.WARNING, logger=email_routes.__name__)
|
||||
|
||||
router = email_routes.setup_email_routes()
|
||||
summarize = _route_endpoint(router, "/api/email/summarize", "POST")
|
||||
result = await summarize(
|
||||
{
|
||||
"body": "This email body is long enough to summarize.",
|
||||
"subject": "Sensitive provider failure",
|
||||
"from": "Sender <sender@example.com>",
|
||||
},
|
||||
owner="alice",
|
||||
)
|
||||
|
||||
assert result == {
|
||||
"success": False,
|
||||
"error": "Failed to summarize",
|
||||
"error_code": "email_summary_unavailable",
|
||||
}
|
||||
exposed = json.dumps(result) + caplog.text
|
||||
for marker in (
|
||||
"private.example.internal",
|
||||
"ollama",
|
||||
"private-model",
|
||||
"private-response",
|
||||
"token-secret-value",
|
||||
):
|
||||
assert marker not in exposed
|
||||
assert f"type={'HTTPException' if exception_kind == 'http' else 'RuntimeError'}" in caplog.text
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_scheduled_email_summary_uses_shared_helper_and_caches(tmp_path, monkeypatch):
|
||||
import routes.email_helpers as email_helpers
|
||||
import routes.email_pollers as email_pollers
|
||||
|
||||
db_path = tmp_path / "scheduled_emails.db"
|
||||
monkeypatch.setattr(email_helpers, "SCHEDULED_DB", db_path)
|
||||
monkeypatch.setattr(email_pollers, "SCHEDULED_DB", db_path)
|
||||
email_helpers._init_scheduled_db()
|
||||
|
||||
raw_email = (
|
||||
b"From: Sender <sender@example.com>\r\n"
|
||||
b"To: Alice <alice@example.com>\r\n"
|
||||
b"Subject: Scheduled subject\r\n"
|
||||
b"Message-ID: <scheduled@example.com>\r\n"
|
||||
b"Date: Tue, 01 Jan 2026 12:00:00 +0000\r\n"
|
||||
b"Content-Type: text/plain; charset=utf-8\r\n"
|
||||
b"\r\n"
|
||||
+ (b"Please review this scheduled summary email. " * 8)
|
||||
)
|
||||
|
||||
class FakeImap:
|
||||
def __init__(self):
|
||||
self.logout_calls = 0
|
||||
|
||||
def select(self, _folder, readonly=True):
|
||||
return "OK", []
|
||||
|
||||
def uid(self, command, *args):
|
||||
if command == "SEARCH":
|
||||
return "OK", [b"1"]
|
||||
if command == "FETCH":
|
||||
return "OK", [(b"1 (RFC822)", raw_email)]
|
||||
raise AssertionError(f"unexpected uid command: {command!r} {args!r}")
|
||||
|
||||
def logout(self):
|
||||
self.logout_calls += 1
|
||||
|
||||
fake_conn = FakeImap()
|
||||
|
||||
def fake_resolve_task_candidates(owner=None):
|
||||
assert owner == "alice"
|
||||
return [(
|
||||
"https://chatgpt.com/backend-api/codex/responses",
|
||||
"gpt-5.5",
|
||||
{"Authorization": "Bearer test"},
|
||||
)]
|
||||
|
||||
helper_calls = {}
|
||||
|
||||
async def fake_generate_email_summary(**kwargs):
|
||||
helper_calls.update(kwargs)
|
||||
return "- Scheduled summary"
|
||||
|
||||
monkeypatch.setattr(email_pollers, "_load_settings", lambda: {"email_auto_summarize": True})
|
||||
monkeypatch.setattr(email_pollers, "_owner_for_email_account", lambda _account_id: "alice")
|
||||
monkeypatch.setattr(email_pollers, "_imap_connect", lambda account_id=None, owner="": fake_conn)
|
||||
monkeypatch.setattr(email_pollers, "_get_email_config", lambda account_id=None, owner="": {"from_address": "alice@example.com"})
|
||||
monkeypatch.setattr(email_pollers, "resolve_task_candidates", fake_resolve_task_candidates)
|
||||
monkeypatch.setattr(email_pollers, "_generate_scheduled_email_summary", fake_generate_email_summary)
|
||||
|
||||
result = await email_pollers._auto_summarize_pass_single(account_id="acct-alice")
|
||||
|
||||
assert "summarized 1" in result
|
||||
assert "summary failed" not in result
|
||||
assert helper_calls["url"] == "https://chatgpt.com/backend-api/codex/responses"
|
||||
assert helper_calls["model"] == "gpt-5.5"
|
||||
assert helper_calls["headers"]["Authorization"] == "Bearer test"
|
||||
assert helper_calls["headers"]["Content-Type"] == "application/json"
|
||||
assert helper_calls["owner"] == "alice"
|
||||
assert fake_conn.logout_calls == 1
|
||||
|
||||
conn = sqlite3.connect(db_path)
|
||||
try:
|
||||
row = conn.execute(
|
||||
"SELECT owner, summary, model_used FROM email_summaries WHERE message_id=?",
|
||||
("<scheduled@example.com>",),
|
||||
).fetchone()
|
||||
finally:
|
||||
conn.close()
|
||||
assert row == ("alice", "- Scheduled summary", "gpt-5.5")
|
||||
Loading…
Add table
Add a link
Reference in a new issue