643b3f450d
check_vision_requirements (and five siblings: browser_vision, image/video generation, x_search, browser_vault) wrapped their whole probe in `except Exception: return False`. The registry then logged "returned False", indistinguishable from an unconfigured backend, and the only diagnostic for a crashed resolver was gone (#87950: named custom provider lookup failing in a long-lived multi-profile process, reported as vision tools silently vanishing). The registry owns the verdict: _run_check_fn_uncached and _check_fn_cached both catch, log with traceback, and return False. Let the exception reach them. Behaviour for the model is unchanged (tool hidden either way); agent.log now says why.
344 lines
15 KiB
Python
344 lines
15 KiB
Python
#!/usr/bin/env python3
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"""X Search tool backed by xAI's built-in ``x_search`` Responses API tool.
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Registers when either xAI credential path is available (``XAI_API_KEY`` or ``hermes auth add
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xai-oauth``). At call time an explicit ``XAI_API_KEY`` wins (``prefer_api_key=True``): x_search
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is API-metered and the subscription OAuth bearer answers ``/v1/responses`` without citations.
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Date filters are validated client-side so malformed windows fail fast instead of burning a
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billable call. Results carry ``degraded``: True when a narrowing filter was active AND xAI
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returned no citations in either channel (answer came from model knowledge, not the X index).
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"""
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from __future__ import annotations
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import json
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import logging
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import time
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from datetime import date, datetime, timezone
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from typing import Any, Dict, List, Optional, Tuple
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import requests
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from tools.registry import registry, tool_error
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from tools.xai_http import DEFAULT_XAI_BASE_URL, hermes_xai_user_agent, resolve_xai_http_credentials
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logger = logging.getLogger(__name__)
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DEFAULT_X_SEARCH_MODEL = "grok-4.5"
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DEFAULT_X_SEARCH_TIMEOUT_SECONDS = 180
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DEFAULT_X_SEARCH_RETRIES = 2
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X_SEARCH_REASONING_EFFORTS = ("low", "medium", "high", "xhigh")
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MAX_HANDLES = 10
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def _load_x_search_config() -> Dict[str, Any]:
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try:
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from hermes_cli.config import load_config
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return load_config().get("x_search", {}) or {}
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except Exception:
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return {}
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def _get_x_search_reasoning_effort() -> Optional[str]:
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raw_value = _load_x_search_config().get("reasoning_effort")
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effort = str(raw_value).strip().lower() if raw_value is not None else ""
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if effort and effort not in X_SEARCH_REASONING_EFFORTS:
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allowed = ", ".join(X_SEARCH_REASONING_EFFORTS)
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raise ValueError(f"x_search.reasoning_effort must be one of: {allowed} (got {raw_value!r})")
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return effort or None
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def _get_x_search_int(key: str, default: int, floor: int) -> int:
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try:
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return max(floor, int(_load_x_search_config().get(key, default)))
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except Exception:
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return default
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def _resolve_xai_bearer() -> Tuple[str, str, str]:
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"""Return ``(api_key, base_url, source)``; ``source`` is ``"xai-oauth"`` or ``"xai"``. Raises RuntimeError
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when no credential is usable (expiry between registration and call -> clean tool error, not a 401).
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x_search is API-index access: when a subscription OAuth credential is configured alongside a paid
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``XAI_API_KEY``, the OAuth path authorizes but answers ``/v1/responses`` in a degraded Grok explanatory
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mode with no citations, while the API key returns real posts (#88040). Pass ``prefer_api_key=True`` so
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the shared resolver checks the explicit API key first — same root cause as the TTS fix for #87045
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(#87081) — keeping OAuth as the fallback when no API key is configured.
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"""
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creds = resolve_xai_http_credentials(prefer_api_key=True)
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api_key = str(creds.get("api_key") or "").strip()
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if not api_key:
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raise RuntimeError(
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"No xAI credentials available. Run `hermes auth add xai-oauth` "
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"to sign in with your SuperGrok subscription, or set XAI_API_KEY."
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)
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base_url = str(creds.get("base_url") or DEFAULT_XAI_BASE_URL).strip().rstrip("/")
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return api_key, base_url, str(creds.get("provider") or "xai")
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def check_x_search_requirements() -> bool:
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"""True when xAI credentials resolve to a non-empty bearer (OAuth auto-refreshed)."""
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return bool(str(resolve_xai_http_credentials().get("api_key") or "").strip())
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def _normalize_handles(handles: Optional[List[str]], field_name: str) -> List[str]:
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cleaned = [h for h in (str(handle or "").strip().lstrip("@") for handle in handles or []) if h]
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if len(cleaned) > MAX_HANDLES:
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raise ValueError(f"{field_name} supports at most {MAX_HANDLES} handles")
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return cleaned
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def _parse_iso_date(value: str, field_name: str) -> Optional[date]:
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"""Strict YYYY-MM-DD or None for blank (xAI silently accepts malformed dates and returns no citations)."""
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raw = value.strip()
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if not raw:
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return None
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try:
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return datetime.strptime(raw, "%Y-%m-%d").date()
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except ValueError as exc:
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raise ValueError(f"{field_name} must be YYYY-MM-DD (got {raw!r})") from exc
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def _validate_date_range(from_date: str, to_date: str) -> None:
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"""Both parse as YYYY-MM-DD; from <= to; from not after today UTC (to may be in the future)."""
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parsed_from, parsed_to = _parse_iso_date(from_date, "from_date"), _parse_iso_date(to_date, "to_date")
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if parsed_from and parsed_to and parsed_from > parsed_to:
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raise ValueError(
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f"from_date ({parsed_from.isoformat()}) must be on or before to_date ({parsed_to.isoformat()})"
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)
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today_utc = datetime.now(timezone.utc).date()
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if parsed_from is not None and parsed_from > today_utc:
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raise ValueError(
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f"from_date ({parsed_from.isoformat()}) is in the future; "
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f"X Search only indexes past posts (today UTC is {today_utc.isoformat()})"
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)
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def _message_contents(payload: Dict[str, Any]):
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for item in payload.get("output", []) or []:
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if item.get("type") == "message":
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yield from item.get("content", []) or []
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def _extract_response_text(payload: Dict[str, Any]) -> str:
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output_text = str(payload.get("output_text") or "").strip()
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if output_text:
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return output_text
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contents = (c for c in _message_contents(payload) if c.get("type") in {"output_text", "text"})
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parts = (str(c.get("text") or "").strip() for c in contents)
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return "\n\n".join(p for p in parts if p).strip()
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def _extract_inline_citations(payload: Dict[str, Any]) -> List[Dict[str, Any]]:
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return [
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{
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"url": a.get("url", ""), "title": a.get("title", ""),
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"start_index": a.get("start_index"), "end_index": a.get("end_index"),
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}
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for content in _message_contents(payload)
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for a in content.get("annotations", []) or []
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if a.get("type") == "url_citation"
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]
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def _http_error_message(exc: requests.HTTPError) -> str:
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response = getattr(exc, "response", None)
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if response is None:
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return str(exc)
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try:
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payload = response.json()
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except Exception:
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payload = None
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if not isinstance(payload, dict):
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text = str(getattr(response, "text", "") or "").strip()
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return text[:500] if text else str(exc)
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code = str(payload.get("code") or "").strip()
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message = str(payload.get("error") or "").strip() or str(payload)
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return (f"{code}: {message}" if code and code not in message else message) or str(exc)
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def _error_json(error: str, exc: BaseException) -> str:
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body = {"success": False, "provider": "xai", "tool": "x_search", "error": error}
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return json.dumps({**body, "error_type": type(exc).__name__}, ensure_ascii=False)
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def _post_with_retries(url: str, headers: Dict[str, str], payload: Dict[str, Any]) -> requests.Response:
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"""POST with retries on 5xx / timeout / connection errors; re-raises the last failure."""
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timeout_seconds = _get_x_search_int("timeout_seconds", DEFAULT_X_SEARCH_TIMEOUT_SECONDS, 30)
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max_retries = _get_x_search_int("retries", DEFAULT_X_SEARCH_RETRIES, 0)
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for attempt in range(max_retries + 1):
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try:
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response = requests.post(url, headers=headers, json=payload, timeout=timeout_seconds)
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response.raise_for_status()
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return response
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except requests.HTTPError as e:
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status_code = getattr(getattr(e, "response", None), "status_code", None)
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if status_code is None or status_code < 500 or attempt >= max_retries:
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raise
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kind, detail = "upstream", _http_error_message(e)
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except (requests.ReadTimeout, requests.ConnectionError) as e:
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if attempt >= max_retries:
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raise
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kind, detail = "transient", e
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logger.warning("x_search %s failure on attempt %s/%s: %s", kind, attempt + 1, max_retries + 1, detail)
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time.sleep(min(5.0, 1.5 * (attempt + 1)))
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raise RuntimeError("x_search request did not return a response")
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def _build_x_search_tool_def(
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allowed_x_handles, excluded_x_handles, from_date: str, to_date: str,
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enable_image_understanding: bool, enable_video_understanding: bool,
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) -> Tuple[Dict[str, Any], List[str]]:
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"""Return ``(tool_def, active_filters)``; raises ValueError on invalid filters."""
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allowed = _normalize_handles(allowed_x_handles, "allowed_x_handles")
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excluded = _normalize_handles(excluded_x_handles, "excluded_x_handles")
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if allowed and excluded:
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raise ValueError("allowed_x_handles and excluded_x_handles cannot be used together")
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_validate_date_range(from_date, to_date)
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tool_def: Dict[str, Any] = {"type": "x_search"}
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active_filters: List[str] = []
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filters = (("allowed_x_handles", allowed), ("excluded_x_handles", excluded),
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("from_date", from_date.strip()), ("to_date", to_date.strip()))
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for key, value in filters:
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if value:
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tool_def[key] = value
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active_filters.append(key)
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if enable_image_understanding:
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tool_def["enable_image_understanding"] = True
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if enable_video_understanding:
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tool_def["enable_video_understanding"] = True
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return tool_def, active_filters
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def x_search_tool(
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query: str,
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allowed_x_handles: Optional[List[str]] = None,
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excluded_x_handles: Optional[List[str]] = None,
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from_date: str = "",
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to_date: str = "",
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enable_image_understanding: bool = False,
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enable_video_understanding: bool = False,
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) -> str:
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if not query or not query.strip():
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return tool_error("query is required for x_search")
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try:
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api_key, base_url, source = _resolve_xai_bearer()
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except RuntimeError as exc:
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return tool_error(str(exc))
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try:
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tool_def, active_filters = _build_x_search_tool_def(
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allowed_x_handles, excluded_x_handles, from_date, to_date,
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enable_image_understanding, enable_video_understanding,
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)
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reasoning_effort = _get_x_search_reasoning_effort()
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except ValueError as exc:
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return tool_error(str(exc))
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try:
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payload = {
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"model": str(_load_x_search_config().get("model") or "").strip() or DEFAULT_X_SEARCH_MODEL,
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"input": [{"role": "user", "content": query.strip()}],
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"tools": [tool_def],
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"store": False,
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}
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if reasoning_effort:
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payload["reasoning"] = {"effort": reasoning_effort}
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headers = {
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"Authorization": f"Bearer {api_key}", "Content-Type": "application/json",
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"User-Agent": hermes_xai_user_agent(),
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}
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data = _post_with_retries(f"{base_url}/responses", headers, payload).json()
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citations = list(data.get("citations") or [])
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inline_citations = _extract_inline_citations(data)
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# xAI returns 200 with a synthesized answer even when no posts match the narrowing
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# filters; with both citation channels empty the answer came from training data.
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degraded = bool(active_filters) and not citations and not inline_citations
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result = {
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"success": True, "provider": "xai", "credential_source": source, "tool": "x_search",
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"model": payload["model"], "query": query.strip(), "answer": _extract_response_text(data),
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"citations": citations, "inline_citations": inline_citations, "degraded": degraded,
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"degraded_reason": (
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f"no citations returned despite filters: {', '.join(active_filters)}" if degraded else None
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),
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}
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return json.dumps(result, ensure_ascii=False)
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except requests.HTTPError as e:
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logger.error("x_search failed: %s", e, exc_info=True)
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return _error_json(_http_error_message(e), e)
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except requests.ReadTimeout as e:
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logger.error("x_search timed out: %s", e, exc_info=True)
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timeout = _get_x_search_int("timeout_seconds", DEFAULT_X_SEARCH_TIMEOUT_SECONDS, 30)
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return _error_json(f"xAI x_search timed out after {timeout} seconds", e)
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except Exception as e:
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logger.error("x_search failed: %s", e, exc_info=True)
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return _error_json(str(e), e)
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X_SEARCH_SCHEMA = {
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"name": "x_search",
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"description": (
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"Search X (Twitter) posts, profiles, and threads using xAI's built-in "
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"X Search tool. Read-only discovery only: use this for current "
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"discussion, reactions, or claims on public X rather than general web "
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"pages. Do not use it to post, reply, like, DM, upload media, delete, "
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"or inspect the user's authenticated X account — those require a "
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"separate authenticated X API surface outside this tool. Available "
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"when xAI credentials are configured (SuperGrok OAuth or XAI_API_KEY)."
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),
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"parameters": {
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"type": "object",
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"properties": {
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"query": {
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"type": "string",
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"description": "What to look up on X.",
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},
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"allowed_x_handles": {
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"type": "array",
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"items": {"type": "string"},
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"description": "Optional list of X handles to include exclusively (max 10).",
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},
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"excluded_x_handles": {
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"type": "array",
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"items": {"type": "string"},
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"description": "Optional list of X handles to exclude (max 10).",
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},
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"from_date": {
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"type": "string",
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"description": "Optional start date in YYYY-MM-DD format.",
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},
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"to_date": {
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"type": "string",
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"description": "Optional end date in YYYY-MM-DD format.",
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},
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"enable_image_understanding": {
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"type": "boolean",
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"description": "Whether xAI should analyze images attached to matching X posts.",
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"default": False,
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},
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"enable_video_understanding": {
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"type": "boolean",
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"description": "Whether xAI should analyze videos attached to matching X posts.",
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"default": False,
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},
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},
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"required": ["query"],
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},
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}
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def _handle_x_search(args, **kw):
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return x_search_tool(
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args.get("query", ""), args.get("allowed_x_handles"), args.get("excluded_x_handles"),
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args.get("from_date", ""), args.get("to_date", ""),
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bool(args.get("enable_image_understanding", False)),
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bool(args.get("enable_video_understanding", False)),
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)
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registry.register(
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name="x_search", toolset="x_search", schema=X_SEARCH_SCHEMA, handler=_handle_x_search,
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check_fn=check_x_search_requirements, requires_env=["XAI_API_KEY"], emoji="🐦",
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max_result_size_chars=100_000,
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)
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