mirror of
https://github.com/NousResearch/hermes-agent.git
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66827f8947
Remove unused imports (F401) and duplicate/shadowed import redefinitions (F811) across the codebase using ruff's safe autofixes. No behavioral changes -- imports only. - ~1400 safe autofixes applied across 644 files (net -1072 lines) - __init__.py re-exports preserved (excluded from F401 removal so public re-export surfaces stay intact) - Re-exports that are imported or monkeypatched by tests but look unused in their defining module are kept with explicit # noqa: F401 (gateway/run.py load_dotenv; run_agent re-exports from agent.message_sanitization, agent.context_compressor, agent.retry_utils, agent.prompt_builder, agent.process_bootstrap, agent.codex_responses_adapter) - Unsafe F841 (unused-variable) fixes deliberately skipped -- those can change behavior when the RHS has side effects - ruff lints remain disabled in pyproject.toml (only PLW1514 is selected); this is a one-time cleanup, not a config change Verification: - python -m compileall: clean - pytest --collect-only: all 27161 tests collect (zero import errors) - core entry points import clean (run_agent, model_tools, cli, toolsets, hermes_state, batch_runner, gateway) - static scan: every name any test imports directly from an edited module still resolves
525 lines
19 KiB
Python
525 lines
19 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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Authentication
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--------------
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The tool registers when **either** xAI credential path is available:
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* ``XAI_API_KEY`` is set in ``~/.hermes/.env`` or the process environment
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(paid xAI API key), OR
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* The user is signed in via xAI Grok OAuth — SuperGrok subscription —
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i.e. ``hermes auth add xai-oauth`` has been run and the stored refresh
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token still works.
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Credential preference at call time matches
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:func:`tools.xai_http.resolve_xai_http_credentials`: SuperGrok OAuth first,
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direct OAuth resolver second, ``XAI_API_KEY`` last. That helper also
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auto-refreshes the OAuth access token when it's within the refresh skew
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window, so a ``True`` from :func:`check_x_search_requirements` means the
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bearer is fetchable AND non-empty.
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Defensive output
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----------------
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The tool surfaces two additional signals beyond xAI's raw response so callers
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can tell a real citation-backed answer from an unsourced one:
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* ``from_date`` / ``to_date`` are validated client-side before the HTTP call.
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Malformed (non ``YYYY-MM-DD``), inverted (``from_date > to_date``), and
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pure-future ranges (``from_date`` later than today UTC) fail fast with a
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clear error instead of burning an API call. ``to_date`` in the future is
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still allowed so callers can legitimately request "from yesterday to
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tomorrow".
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* Successful responses carry ``degraded`` and ``degraded_reason`` fields.
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``degraded`` is ``True`` when any narrowing filter (handles or dates) was
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active AND xAI returned no citations in either the top-level ``citations``
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array or the inline ``url_citation`` annotations. In that case the
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``answer`` came from the model's own knowledge rather than the X index,
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and the caller should treat the result as unsourced.
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Salvaged from PR #10786 (originally by @Jaaneek); credential resolution
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reworked to honor both auth modes per Teknium's design.
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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 hermes_xai_user_agent, resolve_xai_http_credentials
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logger = logging.getLogger(__name__)
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DEFAULT_XAI_BASE_URL = "https://api.x.ai/v1"
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DEFAULT_X_SEARCH_MODEL = "grok-4.20-reasoning"
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DEFAULT_X_SEARCH_TIMEOUT_SECONDS = 180
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DEFAULT_X_SEARCH_RETRIES = 2
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MAX_HANDLES = 10
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# ---------------------------------------------------------------------------
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# Config
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# ---------------------------------------------------------------------------
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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_model() -> str:
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cfg = _load_x_search_config()
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return (str(cfg.get("model") or "").strip() or DEFAULT_X_SEARCH_MODEL)
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def _get_x_search_timeout_seconds() -> int:
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cfg = _load_x_search_config()
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raw_value = cfg.get("timeout_seconds", DEFAULT_X_SEARCH_TIMEOUT_SECONDS)
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try:
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return max(30, int(raw_value))
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except Exception:
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return DEFAULT_X_SEARCH_TIMEOUT_SECONDS
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def _get_x_search_retries() -> int:
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cfg = _load_x_search_config()
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raw_value = cfg.get("retries", DEFAULT_X_SEARCH_RETRIES)
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try:
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return max(0, int(raw_value))
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except Exception:
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return DEFAULT_X_SEARCH_RETRIES
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# ---------------------------------------------------------------------------
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# Credential resolution
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# ---------------------------------------------------------------------------
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def _resolve_xai_bearer() -> Tuple[str, str, str]:
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"""Return ``(api_key, base_url, source)``.
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``source`` is one of ``"xai-oauth"`` or ``"xai"`` so callers (and tests)
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can tell which credential path won. Raises ``RuntimeError`` if no usable
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credential is available — the registered :func:`check_x_search_requirements`
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gate makes that case unreachable in normal operation, but the runtime
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check exists so a credential that expires between registration and
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invocation produces a clean tool error instead of a 401.
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"""
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creds = resolve_xai_http_credentials()
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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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source = str(creds.get("provider") or "xai")
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return api_key, base_url, source
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def check_x_search_requirements() -> bool:
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"""Return True when xAI credentials are available AND valid.
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``resolve_xai_http_credentials`` calls
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:func:`hermes_cli.auth.resolve_xai_oauth_runtime_credentials` which
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auto-refreshes the OAuth access token if it's expiring; a successful
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return therefore implies a usable bearer.
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"""
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try:
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creds = resolve_xai_http_credentials()
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return bool(str(creds.get("api_key") or "").strip())
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except Exception:
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return False
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _normalize_handles(handles: Optional[List[str]], field_name: str) -> List[str]:
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cleaned: List[str] = []
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for handle in handles or []:
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normalized = str(handle or "").strip().lstrip("@")
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if normalized:
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cleaned.append(normalized)
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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) -> date:
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"""Parse a strict YYYY-MM-DD string into a ``date``.
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xAI accepts any string in the ``from_date``/``to_date`` slots and silently
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returns an answer with no citations when the value is malformed or refers
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to a window where no posts can exist. That behavior burns a billable API
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call and produces a confident-sounding fluff answer that's hard for callers
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to distinguish from a real result. Validating client-side fails fast and
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gives the agent a clear error to act on.
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"""
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raw = value.strip()
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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(
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f"{field_name} must be YYYY-MM-DD (got {raw!r})"
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) from exc
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def _validate_date_range(from_date: str, to_date: str) -> None:
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"""Validate ``from_date`` / ``to_date`` before they reach xAI.
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Rules:
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* Either field, if non-empty, must parse as ``YYYY-MM-DD``.
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* When both are set, ``from_date <= to_date``.
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* ``from_date`` must not be later than today UTC — no posts can exist
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in a window that hasn't started yet, so the call would be guaranteed
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to return zero citations. ``to_date`` in the future is allowed
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(callers may legitimately set "from yesterday to tomorrow").
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"""
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parsed_from: Optional[date] = None
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parsed_to: Optional[date] = None
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if from_date.strip():
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parsed_from = _parse_iso_date(from_date, "from_date")
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if to_date.strip():
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parsed_to = _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 "
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f"to_date ({parsed_to.isoformat()})"
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)
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if parsed_from is not None:
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today_utc = datetime.now(timezone.utc).date()
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if 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 "
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f"{today_utc.isoformat()})"
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)
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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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parts: List[str] = []
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for item in payload.get("output", []) or []:
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if item.get("type") != "message":
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continue
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for content in item.get("content", []) or []:
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ctype = content.get("type")
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if ctype in {"output_text", "text"}:
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text = str(content.get("text") or "").strip()
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if text:
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parts.append(text)
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return "\n\n".join(parts).strip()
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def _extract_inline_citations(payload: Dict[str, Any]) -> List[Dict[str, Any]]:
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citations: List[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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continue
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for content in item.get("content", []) or []:
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for annotation in content.get("annotations", []) or []:
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if annotation.get("type") != "url_citation":
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continue
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citations.append(
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{
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"url": annotation.get("url", ""),
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"title": annotation.get("title", ""),
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"start_index": annotation.get("start_index"),
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"end_index": annotation.get("end_index"),
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}
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)
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return citations
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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 isinstance(payload, dict):
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code = str(payload.get("code") or "").strip()
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error = str(payload.get("error") or "").strip()
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message = error or str(payload)
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if code and code not in message:
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message = f"{code}: {message}"
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return message or str(exc)
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text = str(getattr(response, "text", "") or "").strip()
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if text:
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return text[:500]
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return str(exc)
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# ---------------------------------------------------------------------------
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# Tool implementation
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# ---------------------------------------------------------------------------
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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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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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return tool_error("allowed_x_handles and excluded_x_handles cannot be used together")
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try:
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_validate_date_range(from_date, to_date)
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except ValueError as exc:
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return tool_error(str(exc))
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tool_def: Dict[str, Any] = {"type": "x_search"}
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if allowed:
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tool_def["allowed_x_handles"] = allowed
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if excluded:
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tool_def["excluded_x_handles"] = excluded
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if from_date.strip():
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tool_def["from_date"] = from_date.strip()
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if to_date.strip():
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tool_def["to_date"] = to_date.strip()
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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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payload = {
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"model": _get_x_search_model(),
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"input": [
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{
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"role": "user",
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"content": query.strip(),
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}
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],
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"tools": [tool_def],
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"store": False,
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}
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timeout_seconds = _get_x_search_timeout_seconds()
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max_retries = _get_x_search_retries()
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response: Optional[requests.Response] = None
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for attempt in range(max_retries + 1):
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try:
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response = requests.post(
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f"{base_url}/responses",
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headers={
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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"User-Agent": hermes_xai_user_agent(),
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},
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json=payload,
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timeout=timeout_seconds,
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)
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response.raise_for_status()
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break
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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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logger.warning(
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"x_search upstream failure on attempt %s/%s: %s",
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attempt + 1,
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max_retries + 1,
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_http_error_message(e),
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)
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time.sleep(min(5.0, 1.5 * (attempt + 1)))
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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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logger.warning(
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"x_search transient failure on attempt %s/%s: %s",
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attempt + 1,
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max_retries + 1,
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e,
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)
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time.sleep(min(5.0, 1.5 * (attempt + 1)))
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if response is None:
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raise RuntimeError("x_search request did not return a response")
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data = response.json()
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answer = _extract_response_text(data)
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citations = list(data.get("citations") or [])
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inline_citations = _extract_inline_citations(data)
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# Degraded-result detection.
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#
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# xAI returns 200 OK with a synthesized answer even when its X index
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# has no posts matching the caller's narrowing filters. The answer
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# then comes from the model's training data, which is misleading
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# because it looks identical to a real, citation-backed result. When
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# any narrowing filter is active AND both citation channels came back
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# empty, mark the response as degraded so callers can decide to
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# broaden filters, retry, or fall back to a different source.
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active_filters: List[str] = []
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if allowed:
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active_filters.append("allowed_x_handles")
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if excluded:
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active_filters.append("excluded_x_handles")
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if from_date.strip():
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active_filters.append("from_date")
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if to_date.strip():
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active_filters.append("to_date")
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degraded = bool(active_filters) and not citations and not inline_citations
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degraded_reason = (
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f"no citations returned despite filters: {', '.join(active_filters)}"
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if degraded
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else None
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)
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return json.dumps(
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{
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"success": True,
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"provider": "xai",
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"credential_source": source,
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"tool": "x_search",
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"model": payload["model"],
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"query": query.strip(),
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"answer": answer,
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"citations": citations,
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"inline_citations": inline_citations,
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"degraded": degraded,
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"degraded_reason": degraded_reason,
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},
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ensure_ascii=False,
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)
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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 json.dumps(
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{
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"success": False,
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"provider": "xai",
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"tool": "x_search",
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"error": _http_error_message(e),
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"error_type": type(e).__name__,
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},
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ensure_ascii=False,
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)
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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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return json.dumps(
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{
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"success": False,
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"provider": "xai",
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"tool": "x_search",
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"error": f"xAI x_search timed out after {_get_x_search_timeout_seconds()} seconds",
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"error_type": type(e).__name__,
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},
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ensure_ascii=False,
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)
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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 json.dumps(
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{
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"success": False,
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"provider": "xai",
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"tool": "x_search",
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"error": str(e),
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"error_type": type(e).__name__,
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},
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ensure_ascii=False,
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)
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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. Use this for current discussion, reactions, or claims "
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"on X rather than general web pages. Available when xAI credentials "
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"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).",
|
|
},
|
|
"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(
|
|
query=args.get("query", ""),
|
|
allowed_x_handles=args.get("allowed_x_handles"),
|
|
excluded_x_handles=args.get("excluded_x_handles"),
|
|
from_date=args.get("from_date", ""),
|
|
to_date=args.get("to_date", ""),
|
|
enable_image_understanding=bool(args.get("enable_image_understanding", False)),
|
|
enable_video_understanding=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,
|
|
)
|