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