forked from molecule-ai/molecule-core
3d817a42b7
Hermes 4 is a hybrid-reasoning model trained on <think> tags; without asking
for thinking we pay flagship $/tok but get non-reasoning quality. This adds a
dedicated HermesA2AExecutor that dispatches to any OpenAI-compat endpoint
(OpenRouter, Nous Portal) and enables native reasoning for Hermes 4 models.
Key decisions:
- ProviderConfig + _reasoning_supported() detect Hermes 4 by model slug
substring ("hermes-4", "hermes4") — case-insensitive, no config needed
- extra_body={"reasoning": {"enabled": True}} sent only to Hermes 4 entries;
Hermes 3 path unchanged (no extra_body, no regressions)
- choices[0].message.reasoning + reasoning_details extracted and written to
an OTEL span (hermes.reasoning) — deliberately NOT echoed in the A2A reply
so the reasoning trace never contaminates the agent's next-turn context
- API key / base URL default to OPENAI_API_KEY / OPENAI_BASE_URL env vars
with openrouter.ai/api/v1 as the fallback endpoint
- _client injection parameter for unit tests (no live API calls needed)
- Error sanitization: only exception class name surfaces to user (mirrors
sanitize_agent_error() convention from cli_executor.py)
Test coverage: 35 tests, 100% coverage on all new code paths including:
- _reasoning_supported() — Hermes 4/3/unknown/empty/uppercase
- ProviderConfig — field assignment and capability flags
- extra_body presence for Hermes 4, absence for Hermes 3
- reasoning not in A2A reply; _log_reasoning called when trace present
- reasoning_details forwarded; span attributes set correctly
- Telemetry failure swallowed (never blocks response)
- API error → sanitized class-name-only reply
- cancel() → TaskStatusUpdateEvent(state=canceled)
Full suite: 990 passed, 0 failed (no regressions).
Resolves #496
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
328 lines
13 KiB
Python
328 lines
13 KiB
Python
"""OpenAI-compat A2A executor for Hermes models with native reasoning support.
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Dispatches to OpenRouter / Nous Portal (or any OpenAI-compatible endpoint)
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and enables Hermes 4 native reasoning when the model supports it.
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Reasoning (Hermes 4 only)
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--------------------------
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Hermes 4 is a hybrid-reasoning model trained on ``<think>`` tags. When
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``reasoning_supported`` is True for the active model, this executor appends:
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extra_body={"reasoning": {"enabled": True}}
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to the ``chat.completions.create()`` call. The ``openai`` SDK forwards
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``extra_body`` verbatim to the upstream provider, so both OpenRouter and
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Nous Portal receive it without needing provider-specific code paths.
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On response, ``choices[0].message.reasoning`` and
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``choices[0].message.reasoning_details`` are extracted and written to an
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OTEL activity span so operators can inspect the thinking trace in Langfuse
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/ Jaeger. The reasoning content is deliberately **not** included in the
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A2A reply — doing so would contaminate the agent's next-turn context with
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the model's internal scratchpad.
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Hermes 3 / unknown models
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--------------------------
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No ``extra_body`` is sent. The response is processed identically to any
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other OpenAI-compat model call. The Hermes 3 path is exercised by the
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existing adapter test suite and must remain unchanged.
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"""
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from __future__ import annotations
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import logging
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import os
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from typing import TYPE_CHECKING, Any
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from a2a.server.agent_execution import AgentExecutor, RequestContext
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from a2a.server.events import EventQueue
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from a2a.utils import new_agent_text_message
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if TYPE_CHECKING:
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from heartbeat import HeartbeatLoop
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logger = logging.getLogger(__name__)
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# ---------------------------------------------------------------------------
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# Per-model reasoning capability detection
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# ---------------------------------------------------------------------------
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# Substrings that identify a Hermes 4 model slug from either provider:
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# OpenRouter: "nousresearch/hermes-4-*", "nousresearch/nous-hermes-4-*"
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# Nous Portal: "hermes-4", "nous-hermes-4"
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#
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# Hermes 3 slugs ("hermes-3-llama-3.1-70b", etc.) do NOT contain any of
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# these patterns, so they correctly resolve to reasoning_supported=False.
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_HERMES4_PATTERNS: tuple[str, ...] = (
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"hermes-4",
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"hermes4",
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)
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def _reasoning_supported(model: str) -> bool:
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"""Return True if *model* identifies a Hermes 4 variant.
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Case-insensitive substring match against ``_HERMES4_PATTERNS``.
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>>> _reasoning_supported("nousresearch/hermes-4-0")
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True
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>>> _reasoning_supported("nousresearch/nous-hermes-4")
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True
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>>> _reasoning_supported("nousresearch/hermes-3-llama-3.1-70b")
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False
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>>> _reasoning_supported("gpt-4o")
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False
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"""
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model_lower = model.lower()
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return any(pat in model_lower for pat in _HERMES4_PATTERNS)
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# ---------------------------------------------------------------------------
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# ProviderConfig — per-provider / per-model capability flags
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# ---------------------------------------------------------------------------
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class ProviderConfig:
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"""Immutable capability record derived from a model identifier string.
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Attributes:
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model: Full model identifier (e.g. "nousresearch/hermes-4-0").
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reasoning_supported: True for Hermes 4 entries on OpenRouter / Nous
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Portal; False for Hermes 3 and all other models.
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Example::
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cfg = ProviderConfig("nousresearch/hermes-4-0")
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assert cfg.reasoning_supported is True
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cfg3 = ProviderConfig("nousresearch/hermes-3-llama-3.1-70b")
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assert cfg3.reasoning_supported is False
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"""
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__slots__ = ("model", "reasoning_supported")
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def __init__(self, model: str) -> None:
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self.model: str = model
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self.reasoning_supported: bool = _reasoning_supported(model)
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def __repr__(self) -> str: # pragma: no cover
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return (
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f"ProviderConfig(model={self.model!r}, "
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f"reasoning_supported={self.reasoning_supported})"
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)
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# ---------------------------------------------------------------------------
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# HermesA2AExecutor
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# ---------------------------------------------------------------------------
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class HermesA2AExecutor(AgentExecutor):
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"""A2A executor for Hermes models via OpenAI-compatible API.
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Compared to the LangGraph executor, this is intentionally thin:
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- Single API call per turn (no streaming or ReAct tool loop).
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- System prompt injected as the first ``messages[]`` entry.
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- Hermes 4 reasoning enabled via ``extra_body`` when supported.
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- Reasoning trace logged to OTEL span — never echoed in the reply.
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Parameters
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----------
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model:
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Full model identifier string (e.g. ``"nousresearch/hermes-4-0"``).
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Used to select the upstream model AND detect reasoning support.
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system_prompt:
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Optional system prompt prepended to every conversation.
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base_url:
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OpenAI-compat endpoint base URL. Defaults to
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``OPENAI_BASE_URL`` env var, then ``https://openrouter.ai/api/v1``.
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api_key:
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Provider API key. Defaults to ``OPENAI_API_KEY`` env var.
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heartbeat:
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Optional ``HeartbeatLoop`` instance used to surface the current
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task description in the platform UI.
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_client:
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Inject a pre-built ``AsyncOpenAI`` (or compatible mock) — for
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testing only. When provided, ``base_url`` and ``api_key`` are
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ignored.
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"""
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def __init__(
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self,
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model: str,
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system_prompt: str | None = None,
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base_url: str | None = None,
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api_key: str | None = None,
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heartbeat: "HeartbeatLoop | None" = None,
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_client: Any = None,
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) -> None:
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self.model = model
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self.system_prompt = system_prompt
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self._heartbeat = heartbeat
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self._provider = ProviderConfig(model)
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if _client is not None:
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# Test injection path — skip real AsyncOpenAI construction so
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# unit tests don't need a live OpenAI API key.
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self._client = _client
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else:
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# Lazy import keeps ``openai`` out of the global module-load path
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# so callers that never use HermesA2AExecutor don't pay the import
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# cost, and tests can stub ``sys.modules["openai"]`` before import.
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from openai import AsyncOpenAI
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self._client = AsyncOpenAI(
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base_url=(
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base_url
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or os.environ.get("OPENAI_BASE_URL", "https://openrouter.ai/api/v1")
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),
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api_key=(
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api_key
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or os.environ.get("OPENAI_API_KEY", "")
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),
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)
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# ------------------------------------------------------------------
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# Internal helpers
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# ------------------------------------------------------------------
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def _build_messages(self, user_input: str) -> list[dict]:
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"""Assemble the ``messages`` list: optional system prompt then user turn."""
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msgs: list[dict] = []
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if self.system_prompt:
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msgs.append({"role": "system", "content": self.system_prompt})
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msgs.append({"role": "user", "content": user_input})
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return msgs
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def _log_reasoning(
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self,
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context: RequestContext,
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reasoning: str | None,
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reasoning_details: object | None,
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) -> None:
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"""Write the Hermes 4 reasoning trace to an OTEL span.
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The trace is surfaced to Langfuse / Jaeger for operator inspection.
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It is intentionally **not** returned to the caller — including it in
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the A2A reply would contaminate the agent's next-turn context.
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Any exception is swallowed so a telemetry failure never blocks the
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response being returned.
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"""
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try:
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from builtin_tools.telemetry import (
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A2A_TASK_ID,
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WORKSPACE_ID_ATTR,
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get_tracer,
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)
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workspace_id = os.environ.get("WORKSPACE_ID", "unknown")
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tracer = get_tracer()
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with tracer.start_as_current_span("hermes.reasoning") as span:
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span.set_attribute(WORKSPACE_ID_ATTR, workspace_id)
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span.set_attribute(A2A_TASK_ID, context.context_id or "")
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span.set_attribute("hermes.model", self.model)
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span.set_attribute("hermes.reasoning_length", len(reasoning or ""))
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if reasoning:
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# Cap the preview attribute at 512 chars — full trace is
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# stored in the span exporter's data store.
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span.set_attribute("hermes.reasoning_preview", reasoning[:512])
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if reasoning_details is not None:
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span.set_attribute("hermes.has_reasoning_details", True)
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except Exception:
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logger.debug(
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"hermes_executor: reasoning OTEL log failed (non-fatal)", exc_info=True
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)
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# ------------------------------------------------------------------
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# AgentExecutor interface
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# ------------------------------------------------------------------
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async def execute(self, context: RequestContext, event_queue: EventQueue) -> None:
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"""Run a single Hermes turn and enqueue the reply as an A2A Message.
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Sequence:
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1. Extract user text from A2A message parts.
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2. Build ``messages[]`` (optional system + user).
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3. Call OpenAI-compat API; include ``extra_body`` for Hermes 4.
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4. Extract and log reasoning trace — does NOT appear in the reply.
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5. Enqueue a final ``Message`` with the content text.
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"""
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from shared_runtime import extract_message_text
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user_input = extract_message_text(context)
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if not user_input:
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parts = getattr(getattr(context, "message", None), "parts", None)
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logger.warning("HermesA2AExecutor: no text in message parts: %s", parts)
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await event_queue.enqueue_event(
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new_agent_text_message("Error: message contained no text content.")
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)
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return
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messages = self._build_messages(user_input)
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# Only Hermes 4 entries get extra_body — sending it to Hermes 3
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# or other models is a no-op at best; a 400 at worst.
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extra_body: dict | None = None
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if self._provider.reasoning_supported:
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extra_body = {"reasoning": {"enabled": True}}
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try:
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response = await self._client.chat.completions.create(
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model=self.model,
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messages=messages,
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extra_body=extra_body,
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)
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choice = response.choices[0]
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content: str = choice.message.content or ""
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# ``reasoning`` and ``reasoning_details`` are Hermes 4 / provider
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# extensions not defined in the openai SDK's ChatCompletionMessage
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# schema. They arrive as dynamic attributes when the upstream API
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# returns them; getattr guards against their absence.
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reasoning: str | None = getattr(choice.message, "reasoning", None)
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reasoning_details: object | None = getattr(
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choice.message, "reasoning_details", None
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)
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if reasoning or reasoning_details:
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logger.info(
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"hermes_executor: reasoning trace [model=%s len=%d]: %.200s...",
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self.model,
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len(reasoning or ""),
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reasoning or "",
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)
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# Log to OTEL — intentionally omitted from the A2A reply.
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self._log_reasoning(context, reasoning, reasoning_details)
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final_text = content.strip() or "(no response generated)"
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await event_queue.enqueue_event(new_agent_text_message(final_text))
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except Exception as exc:
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logger.error(
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"hermes_executor: API error [model=%s]: %s",
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self.model,
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type(exc).__name__,
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exc_info=True,
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)
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# Expose only the exception class name — not the message body,
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# which may contain API keys, rate-limit metadata, or provider
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# error details that shouldn't reach the end user.
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# Mirrors the sanitize_agent_error() convention in cli_executor.py.
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await event_queue.enqueue_event(
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new_agent_text_message(f"Agent error: {type(exc).__name__}")
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)
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async def cancel(self, context: RequestContext, event_queue: EventQueue) -> None:
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"""Cancel a running task — emits canceled state per A2A protocol."""
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from a2a.types import TaskState, TaskStatus, TaskStatusUpdateEvent
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await event_queue.enqueue_event(
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TaskStatusUpdateEvent(
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status=TaskStatus(state=TaskState.canceled),
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final=True,
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)
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)
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