Import AITURK IDE 1.0.0-beta.1 from Hermes 63279301; preserve MIT license

agent/thinking_timeout_guidance.py

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+"""Thinking-timeout detection and user-facing guidance for reasoning models.
+
+When a known reasoning model (NVIDIA Nemotron 3 Ultra, OpenAI o1/o3,
+Anthropic Opus 4.x thinking, DeepSeek R1, Qwen QwQ, xAI Grok reasoning)
+hits a transport-layer error before the first content token arrives, the
+upstream proxy has almost certainly idle-killed a long thinking stream —
+not a true context overflow or a configuration error.  The user needs
+distinct guidance for this case:
+
+    "The model's thinking phase exceeded the upstream proxy's idle
+     timeout before the first content token arrived.  This is a known
+     issue with reasoning models behind cloud gateways (NVIDIA NIM,
+     OpenAI, Anthropic, DeepSeek).  Workarounds in priority order:
+     1. Set `providers.<provider>.models.<model>.stale_timeout_seconds: 900`
+        in `~/.hermes/config.yaml` to extend the per-call timeout...
+     2. Lower `reasoning_budget` or set `reasoning_effort: medium`...
+     3. Use a smaller / faster reasoning model..."
+
+The existing `_is_stream_drop` guidance at
+``agent/conversation_loop.py:3464-3486`` fires for large-file-write
+stream drops ("try execute_code with Python's open() for large files")
+which is the WRONG advice for the thinking-timeout case.  This module
+provides the detection and the message as standalone helpers so the
+detection logic is unit-testable without driving the full retry loop,
+and the message text can be regression-tested for spelling and accuracy.
+
+Part 2 of Fixes #52310.
+"""
+
+from __future__ import annotations
+
+from typing import Optional
+
+
+# Substring set that identifies a transport-layer failure on the
+# response stream.  Same shape as the existing
+# ``_SERVER_DISCONNECT_PATTERNS`` in ``agent/error_classifier.py:394``
+# but extended to also catch the OSS-level error signature
+# (``broken pipe`` / ``errno 32``) that the upstream kill surfaces
+# to the OpenAI SDK wrapper.
+_THINKING_TIMEOUT_SUBSTRINGS: tuple[str, ...] = (
+    "broken pipe",
+    "errno 32",
+    "remote protocol",
+    "connection reset",
+    "connection lost",
+    "peer closed",
+    "server disconnected",
+)
+
+
+def is_thinking_timeout(classified: object, model: str, error_msg: str) -> bool:
+    """Return True when a reasoning model's thinking phase hit a transport kill.
+
+    Args:
+        classified: a :class:`agent.error_classifier.ClassifiedError` instance
+            (duck-typed here to avoid an import cycle in unit tests).
+        model: the model slug at failure time (e.g.
+            ``"nvidia/nemotron-3-ultra-550b-a55b"``).
+        error_msg: lowercased string representation of the underlying
+            exception (typically ``str(api_error).lower()``).
+
+    Returns True when ALL conditions hold:
+        1. ``classified.reason == FailoverReason.timeout`` (the classifier
+           override at ``agent/error_classifier.py:720-738`` ensures this
+           is the case for reasoning models even on large sessions).
+        2. ``api_error`` has no ``.status_code`` attribute set (transport
+           disconnect, not an HTTP error).
+        3. ``model`` is in the reasoning-model allowlist (reuses
+           ``agent.reasoning_timeouts.get_reasoning_stale_timeout_floor``).
+        4. ``error_msg`` contains one of the transport-kill substrings.
+
+    Non-reasoning models always return False.  Non-transport errors
+    (billing / rate_limit / auth / context_overflow / format_error)
+    always return False.  HTTP-status errors always return False.
+    """
+    # Import here (not at module top) to keep this helper cheap to
+    # import even from callers that don't need it.  ``agent.reasoning_timeouts``
+    # is small and dependency-free.
+    from agent.reasoning_timeouts import get_reasoning_stale_timeout_floor
+
+    # Condition 1: classifier says timeout.  Use a string/value check
+    # rather than importing FailoverReason so this module has zero
+    # import cycles from the error_classifier package.
+    reason = getattr(classified, "reason", None)
+    reason_value = getattr(reason, "value", None)
+    if reason_value != "timeout":
+        return False
+
+    # Condition 2: no HTTP status code (transport, not API error).
+    # Caller is expected to gate on ``getattr(api_error, "status_code", None) is None``
+    # before calling this helper; the surface here is just the post-gate
+    # boolean so the caller can pass an already-prepped error_msg.
+
+    # Condition 3: reasoning model allowlist.
+    if get_reasoning_stale_timeout_floor(model) is None:
+        return False
+
+    # Condition 4: transport-kill substring in the error message.
+    error_msg_lower = (error_msg or "").lower()
+    return any(p in error_msg_lower for p in _THINKING_TIMEOUT_SUBSTRINGS)
+
+
+def build_thinking_timeout_guidance(
+    provider: str, model: str, model_label: Optional[str] = None,
+) -> str:
+    """Return the user-facing guidance string appended to ``_final_response``.
+
+    Args:
+        provider: provider slug (e.g. ``"nvidia"``, ``"openai"``).
+        model: bare model slug the user would put in their config
+            (e.g. ``"nemotron-3-ultra-550b-a55b"`` if the user uses
+            NVIDIA direct, or the full ``"nvidia/nemotron-3-ultra-550b-a55b"``
+            if they go through an aggregator).  Used verbatim in the
+            config snippet so the user can copy-paste.
+        model_label: optional short label for the model name in the
+            prose (e.g. ``"Nemotron 3 Ultra"``).  Falls back to the
+            slug if not provided.
+    """
+    label = model_label or model
+    return (
+        "\n\nThe model's thinking phase exceeded the upstream proxy's "
+        "idle timeout before the first content token arrived. This is a "
+        f"known issue with reasoning models (like {label}) behind cloud "
+        "gateways (NVIDIA NIM, OpenAI, Anthropic, DeepSeek). Workarounds "
+        "in priority order:\n"
+        f"1. Set `providers.{provider}.models.{model}.stale_timeout_seconds: 900` "
+        "in `~/.hermes/config.yaml` to extend the per-call timeout. "
+        "(Hermes's built-in floor is 600s for known reasoning models — "
+        "if you still see this after raising, the upstream cap is even "
+        "shorter.)\n"
+        "2. Lower `reasoning_budget` or set `reasoning_effort: medium` on this "
+        "model if the provider supports it.\n"
+        "3. Use a smaller / faster reasoning model if the task doesn't "
+        "require deep thinking."
+    )