Merge remote-tracking branch 'origin/main' into hermes/hermes-6b48295e

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Teknium 2026-06-11 07:38:25 -07:00
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239 changed files with 18356 additions and 2494 deletions

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@ -679,15 +679,28 @@ def recover_with_credential_pool(
# long-running TUI sessions stuck on stale tokens until the user
# exited and reopened.
is_entitlement = agent._is_entitlement_failure(error_context, status_code)
_auth_haystack = " ".join(
str(error_context.get(k) or "").lower()
for k in ("message", "reason", "code", "error")
if isinstance(error_context, dict)
)
if (
not is_entitlement
and status_code == 403
and "oauth authentication is currently not allowed for this organization" in _auth_haystack
):
is_entitlement = True
if (
not is_entitlement
and status_code == 403
and (agent.provider or "") == "anthropic"
and getattr(agent, "api_mode", "") == "anthropic_messages"
):
is_entitlement = True
if not is_entitlement and status_code == 403 and (agent.provider or "") == "xai-oauth":
_disambiguator_haystack = " ".join(
str(error_context.get(k) or "").lower()
for k in ("message", "reason", "code", "error")
if isinstance(error_context, dict)
)
_is_xai_auth_failure = (
"[wke=unauthenticated:" in _disambiguator_haystack
or "oauth2 access token could not be validated" in _disambiguator_haystack
"[wke=unauthenticated:" in _auth_haystack
or "oauth2 access token could not be validated" in _auth_haystack
)
if not _is_xai_auth_failure:
is_entitlement = True

View file

@ -1571,6 +1571,15 @@ def _convert_content_part_to_anthropic(part: Any) -> Optional[Dict[str, Any]]:
if ptype == "input_text":
block: Dict[str, Any] = {"type": "text", "text": part.get("text", "")}
elif ptype == "text":
# A stored Anthropic text block. Rebuild from whitelisted fields only —
# SDK response text blocks carry output-only siblings (parsed_output,
# citations=None) that the Messages INPUT schema rejects with HTTP 400
# "Extra inputs are not permitted". Do NOT dict(part) it verbatim.
block = {"type": "text", "text": part.get("text", "")}
cits = part.get("citations")
if isinstance(cits, list) and cits:
block["citations"] = cits
elif ptype in {"image_url", "input_image"}:
image_value = part.get("image_url", {})
url = image_value.get("url", "") if isinstance(image_value, dict) else str(image_value or "")
@ -1685,6 +1694,58 @@ def _content_parts_to_anthropic_blocks(parts: Any) -> List[Dict[str, Any]]:
return out
def _sanitize_replay_block(b: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""Strip output-only fields from a stored Anthropic content block so it is
valid as REQUEST input on replay.
The SDK response objects carry output-only attributes that the Messages
*input* schema forbids ("Extra inputs are not permitted"): text blocks get
``parsed_output``/``citations`` (when null), tool_use blocks get ``caller``,
etc. ``normalize_response`` captured blocks verbatim via ``_to_plain_data``,
so these leak back as input on the next turn HTTP 400.
Whitelist per type (NOT a blacklist) so future SDK output-only fields can't
reintroduce the bug. Returns a clean block, or None to drop it.
"""
if not isinstance(b, dict):
return None
btype = b.get("type")
if btype == "text":
out: Dict[str, Any] = {"type": "text", "text": b.get("text", "")}
# citations is input-valid ONLY when it's a non-empty list; the SDK
# emits citations=None on responses, which the input schema rejects.
cits = b.get("citations")
if isinstance(cits, list) and cits:
out["citations"] = cits
if isinstance(b.get("cache_control"), dict):
out["cache_control"] = b["cache_control"]
return out
if btype == "thinking":
out = {"type": "thinking", "thinking": b.get("thinking", "")}
if b.get("signature"):
out["signature"] = b["signature"]
return out
if btype == "redacted_thinking":
# Only valid with its data payload; drop if missing.
return {"type": "redacted_thinking", "data": b["data"]} if b.get("data") else None
if btype == "tool_use":
out = {
"type": "tool_use",
"id": _sanitize_tool_id(b.get("id", "")),
"name": b.get("name", ""),
"input": b.get("input", {}),
}
if isinstance(b.get("cache_control"), dict):
out["cache_control"] = b["cache_control"]
return out
if btype == "image":
src = b.get("source")
return {"type": "image", "source": src} if isinstance(src, dict) else None
# Unknown/unsupported block type on the input path — drop rather than risk
# another "Extra inputs are not permitted".
return None
def _convert_assistant_message(m: Dict[str, Any]) -> Dict[str, Any]:
"""Convert an assistant message to Anthropic content blocks.
@ -1692,6 +1753,55 @@ def _convert_assistant_message(m: Dict[str, Any]) -> Dict[str, Any]:
reasoning_content injection for Kimi/DeepSeek endpoints.
"""
content = m.get("content", "")
# Anthropic interleaved-thinking fast path: when this turn carries a
# verbatim, order-preserving block list (set by normalize_response only
# for turns that interleave SIGNED thinking with tool_use), replay it.
# Each block is run through _sanitize_replay_block to strip output-only
# SDK fields (parsed_output, caller, citations=None, …) that the Messages
# INPUT schema forbids — replaying them verbatim caused HTTP 400 "Extra
# inputs are not permitted" (text.parsed_output). Block ORDER is preserved
# (the reason this channel exists); only forbidden sibling fields are
# dropped, leaving thinking signatures and tool_use id/name/input intact.
ordered_blocks = m.get("anthropic_content_blocks")
if isinstance(ordered_blocks, list) and ordered_blocks:
# Re-source each tool_use input from the stored tool_calls map rather
# than the captured block. The ordered-blocks list captures tool_use
# input from the RAW API response (normalize_response), which is NOT
# credential-redacted; tool_calls[].function.arguments IS redacted at
# storage time (build_assistant_message, #19798). Replaying the raw
# block input would resurrect a secret the model inlined into a tool
# call (e.g. terminal(command="curl -H 'Authorization: Bearer sk-...'")
# onto the wire, even though the same value is redacted everywhere else
# in history. Keying by sanitized tool id preserves interleave order
# (the reason this channel exists) while swapping in the redacted
# input. Adapted from #36071 (replay-time tool-input re-sourcing).
redacted_input_by_id: Dict[str, Any] = {}
for tc in m.get("tool_calls", []) or []:
if not isinstance(tc, dict):
continue
fn = tc.get("function", {}) or {}
raw_args = fn.get("arguments", "{}")
try:
parsed_args = json.loads(raw_args) if isinstance(raw_args, str) else raw_args
except (json.JSONDecodeError, ValueError):
parsed_args = {}
redacted_input_by_id[_sanitize_tool_id(tc.get("id", ""))] = parsed_args
replayed: List[Dict[str, Any]] = []
for b in ordered_blocks:
clean = _sanitize_replay_block(b)
if clean is None:
continue
if clean.get("type") == "tool_use":
# Override raw (un-redacted) input with the redacted copy when
# we have one for this id; fall back to the sanitized block
# input only if the tool_call is missing (shape mismatch).
redacted = redacted_input_by_id.get(clean.get("id", ""))
if redacted is not None:
clean["input"] = redacted
replayed.append(clean)
if replayed:
return {"role": "assistant", "content": replayed}
blocks = _extract_preserved_thinking_blocks(m)
if content:
if isinstance(content, list):

View file

@ -208,6 +208,41 @@ def is_stale_connection_error(exc: BaseException) -> bool:
return False
def is_streaming_access_denied_error(exc: BaseException) -> bool:
"""Return True when AWS denied the ``bedrock:InvokeModelWithResponseStream`` action.
IAM policies scoped to ``bedrock:InvokeModel`` only (a common least-privilege
setup) reject ``converse_stream()`` with an ``AccessDeniedException`` whose
message names the streaming action, e.g.::
User: arn:aws:iam::123456789012:user/x is not authorized to perform:
bedrock:InvokeModelWithResponseStream on resource: ...
This is permanent for the session retrying the stream can never succeed
so callers should flip to the non-streaming ``converse()`` path (which maps
to ``bedrock:InvokeModel``) instead of burning retries.
Detection is deliberately message-based: boto3 surfaces this as a
``ClientError`` with ``Error.Code == "AccessDeniedException"``, and the
AnthropicBedrock SDK wraps the same AWS response in its own exception
types, but both preserve the action name in the message.
"""
msg = str(exc).lower()
if "invokemodelwithresponsestream" not in msg:
return False
# ClientError with an explicit access-denied code is the canonical form.
try:
from botocore.exceptions import ClientError
except ImportError: # pragma: no cover — botocore always present with boto3
ClientError = None # type: ignore[assignment]
if ClientError is not None and isinstance(exc, ClientError):
code = (getattr(exc, "response", None) or {}).get("Error", {}).get("Code", "")
return code in ("AccessDeniedException", "UnauthorizedException")
# Wrapped forms (e.g. AnthropicBedrock SDK PermissionDeniedError) — match
# on the authorization-failure phrasing AWS uses.
return "not authorized" in msg or "accessdenied" in msg
# ---------------------------------------------------------------------------
# AWS credential detection
# ---------------------------------------------------------------------------
@ -1003,6 +1038,16 @@ def call_converse_stream(
try:
response = client.converse_stream(**kwargs)
except Exception as exc:
if is_streaming_access_denied_error(exc):
# IAM allows bedrock:InvokeModel but not
# InvokeModelWithResponseStream — permanent for this session.
# Fall back to the non-streaming converse() path.
logger.info(
"bedrock: converse_stream denied by IAM on (region=%s, model=%s) — "
"falling back to non-streaming converse().",
region, model,
)
return normalize_converse_response(client.converse(**kwargs))
if is_stale_connection_error(exc):
logger.warning(
"bedrock: stale-connection error on converse_stream(region=%s, "

View file

@ -952,6 +952,18 @@ def build_assistant_message(agent, assistant_message, finish_reason: str) -> dic
if preserved:
msg["reasoning_details"] = preserved
# Anthropic interleaved-thinking replay: when a turn interleaves signed
# thinking blocks with tool_use, the parallel reasoning_details +
# tool_calls fields lose the cross-type ordering, and reconstruction
# front-loads thinking — reordering signed blocks and triggering HTTP 400
# ("thinking ... blocks in the latest assistant message cannot be
# modified"). Carry the verbatim ordered block list so the adapter can
# replay the latest assistant message unchanged. See
# agent/transports/anthropic.py and agent/anthropic_adapter.py.
ordered_blocks = getattr(assistant_message, "anthropic_content_blocks", None)
if ordered_blocks:
msg["anthropic_content_blocks"] = ordered_blocks
# Codex Responses API: preserve encrypted reasoning items for
# multi-turn continuity. These get replayed as input on the next turn.
codex_items = getattr(assistant_message, "codex_reasoning_items", None)
@ -1603,6 +1615,8 @@ def interruptible_streaming_api_call(agent, api_kwargs: dict, *, on_first_delta=
_get_bedrock_runtime_client,
invalidate_runtime_client,
is_stale_connection_error,
is_streaming_access_denied_error,
normalize_converse_response,
stream_converse_with_callbacks,
)
region = api_kwargs.pop("__bedrock_region__", "us-east-1")
@ -1611,6 +1625,29 @@ def interruptible_streaming_api_call(agent, api_kwargs: dict, *, on_first_delta=
try:
raw_response = client.converse_stream(**api_kwargs)
except Exception as _bedrock_exc:
# IAM policies scoped to bedrock:InvokeModel only (no
# InvokeModelWithResponseStream) reject converse_stream()
# with AccessDeniedException. That denial is permanent for
# the session — fall back to the non-streaming converse()
# inline (it maps to bedrock:InvokeModel) and disable
# streaming for subsequent calls so we don't re-fail every
# turn.
if is_streaming_access_denied_error(_bedrock_exc):
agent._disable_streaming = True
agent._safe_print(
"\n⚠ AWS IAM denied bedrock:InvokeModelWithResponseStream — "
"falling back to non-streaming InvokeModel.\n"
" Grant that action to restore streaming output.\n"
)
logger.info(
"bedrock: converse_stream denied by IAM (%s) — "
"using non-streaming converse() for this session.",
type(_bedrock_exc).__name__,
)
result["response"] = normalize_converse_response(
client.converse(**api_kwargs)
)
return
# Evict the cached client on stale-connection failures
# so the outer retry loop builds a fresh client/pool.
if is_stale_connection_error(_bedrock_exc):
@ -1698,6 +1735,14 @@ def interruptible_streaming_api_call(agent, api_kwargs: dict, *, on_first_delta=
# poll loop uses this to detect stale connections that keep receiving
# SSE keep-alive pings but no actual data.
last_chunk_time = {"t": time.time()}
# Stale-stream patience, shared between the httpx socket read timeout
# (built in ``_call_chat_completions`` below) and the stale-stream detector
# (computed further down, before the worker thread starts). Initialized
# here so the read-timeout builder can floor itself at the stale value and
# never fire before the detector. ``None`` until the detector value is
# resolved, so the builder degrades to its plain default if it ever runs
# first.
_stream_stale_timeout = None
def _fire_first_delta():
if not first_delta_fired["done"] and on_first_delta:
@ -1734,6 +1779,26 @@ def interruptible_streaming_api_call(agent, api_kwargs: dict, *, on_first_delta=
"Local provider detected (%s) — stream read timeout raised to %.0fs",
agent.base_url, _stream_read_timeout,
)
elif (
_stream_read_timeout == 120.0
and _stream_stale_timeout is not None
and _stream_stale_timeout != float("inf")
and _stream_stale_timeout > _stream_read_timeout
):
# Cloud reasoning models (e.g. Opus) routinely pause mid-stream
# for minutes during extended thinking. The stale-stream
# detector is deliberately scaled up to tolerate this (180300s,
# see the stale-timeout block below), but the raw httpx socket
# read timeout defaulted to a flat 120s and fired *first* —
# tearing down a healthy reasoning stream before the stale
# detector (which owns retry + diagnostics) could act. Keep the
# socket read timeout in step with the detector so it no longer
# preempts it.
_stream_read_timeout = _stream_stale_timeout
logger.debug(
"Cloud reasoning stream — read timeout raised to %.0fs to "
"match stale-stream detector", _stream_read_timeout,
)
# Cap connect/pool at 60s even when provider timeout is higher.
# connect/pool cover TCP handshake, not model inference.
_conn_cap = min(_base_timeout, 60.0) if _provider_timeout_cfg is not None else 30.0
@ -2384,9 +2449,34 @@ def interruptible_streaming_api_call(agent, api_kwargs: dict, *, on_first_delta=
"stream" in _err_lower
and "not supported" in _err_lower
)
if _is_stream_unsupported:
# AWS Bedrock (AnthropicBedrock SDK path): IAM policies
# with bedrock:InvokeModel but not
# InvokeModelWithResponseStream reject messages.stream()
# with a permission error naming the streaming action.
# Permanent for the session — flip to non-streaming
# (messages.create() maps to bedrock:InvokeModel).
_is_bedrock_stream_denied = False
if (
not _is_stream_unsupported
and "invokemodelwithresponsestream" in _err_lower
):
# Cheap message pre-check before importing the
# adapter — bedrock_adapter triggers a lazy boto3
# install at import time, which must not run for
# unrelated providers' stream errors.
from agent.bedrock_adapter import (
is_streaming_access_denied_error,
)
_is_bedrock_stream_denied = (
is_streaming_access_denied_error(e)
)
if _is_stream_unsupported or _is_bedrock_stream_denied:
agent._disable_streaming = True
agent._safe_print(
"\n⚠ AWS IAM denied bedrock:InvokeModelWithResponseStream. "
"Switching to non-streaming.\n"
" Grant that action to restore streaming output.\n"
if _is_bedrock_stream_denied else
"\n⚠ Streaming is not supported for this "
"model/provider. Switching to non-streaming.\n"
" To avoid this delay, set display.streaming: false "

700
agent/coding_context.py Normal file
View file

@ -0,0 +1,700 @@
"""Coding-context awareness — base Hermes, every interactive surface.
When the user runs Hermes inside a code workspace (CLI, TUI, desktop app, or an
editor over ACP), Hermes shifts into a **coding posture**. This module is the
single place that decides whether we're in that posture and what it implies,
so the rest of the codebase never re-derives "are we coding?" on its own.
Architecture one seam, many consumers
----------------------------------------
The posture is modelled as a frozen :class:`RuntimeMode` selected from a small
:class:`ContextProfile` registry (today: ``coding`` and ``general``). A profile
is *data* it declares the toolset to collapse to, the operating brief to
inject, and hints for other domains (model routing, memory, subagents). Every
domain reads the same resolved object instead of probing git/config itself:
* **System prompt** ``RuntimeMode.system_blocks()`` the operating brief +
a live git/workspace snapshot (``agent/system_prompt.py``).
* **Toolset** ``RuntimeMode.toolset_selection()`` the ``coding`` toolset
plus the user's enabled MCP servers (``cli.py`` / ``tui_gateway``). Only
under the opt-in ``focus`` mode: the default posture is prompt-only and
never touches the user's configured toolsets (toolsets like messaging /
smart-home / music are off-by-default anyway, and someone who explicitly
enabled image-gen or Spotify shouldn't lose it for being in a git repo).
* **Delegation** subagents inherit the parent's toolset and run through the
same prompt builder, so the coding posture propagates to children for free.
* **Model / memory / compression** declared on the profile
(``model_hint``, ``memory_policy``) as the extension seam; consumers read
``mode.profile`` rather than re-deciding.
Cache safety
------------
The mode is resolved **once** and is immutable. The workspace snapshot is built
once at prompt-build time and baked into the *stable* system-prompt tier never
re-probed per turn (that would shatter the prompt cache). Branch and dirty state
drift mid-session, so the brief tells the model to re-check with ``git`` before
acting on the snapshot. A ``/coding`` flip therefore only takes effect next
session (deferred), the same contract as ``/skills install`` vs ``--now``.
Activation (config ``agent.coding_context``):
* ``auto`` (default) posture (brief + snapshot) on an interactive coding
surface sitting in a code workspace (git repo or recognised project root).
Prompt-only; toolsets untouched.
* ``focus`` like ``auto``, but additionally collapses the toolset to the
``coding`` set + enabled MCP servers. Explicit opt-in for a lean schema.
* ``on`` force the posture anywhere (incl. non-workspaces). Prompt-only.
* ``off`` disable entirely.
"""
from __future__ import annotations
import json
import logging
import os
import re
import subprocess
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Optional
logger = logging.getLogger("hermes.coding_context")
CODING_TOOLSET = "coding"
# Surfaces where a coding posture makes sense under ``auto``. Messaging
# platforms (telegram, discord, slack, …) are intentionally absent — a chat bot
# in a group is not pair-programming.
INTERACTIVE_CODING_PLATFORMS = {"cli", "tui", "acp", "desktop", ""}
# Project-root signals that mark a directory as a code workspace even when it
# isn't (yet) a git repo. Cheap filename checks — no parsing.
_PROJECT_MARKERS = (
"pyproject.toml", "setup.py", "setup.cfg", "requirements.txt",
"package.json", "tsconfig.json", "deno.json",
"Cargo.toml", "go.mod", "pom.xml", "build.gradle", "build.gradle.kts",
"Gemfile", "composer.json", "mix.exs", "pubspec.yaml",
"CMakeLists.txt", "Makefile", "Dockerfile",
"AGENTS.md", "CLAUDE.md", ".cursorrules",
)
# Agent-instruction files surfaced separately from manifests in the snapshot.
_CONTEXT_FILES = ("AGENTS.md", "CLAUDE.md", ".cursorrules")
# Lockfile → package manager, checked in priority order.
_PY_LOCKFILES = (("uv.lock", "uv"), ("poetry.lock", "poetry"), ("Pipfile.lock", "pipenv"))
_JS_LOCKFILES = (
("pnpm-lock.yaml", "pnpm"), ("bun.lockb", "bun"), ("bun.lock", "bun"),
("yarn.lock", "yarn"), ("package-lock.json", "npm"),
)
# package.json scripts / Makefile targets worth surfacing as verify commands.
_VERIFY_TARGETS = ("test", "tests", "lint", "typecheck", "check", "build", "fmt", "format")
_MAX_VERIFY_COMMANDS = 8
_MAX_FACT_FILE_BYTES = 256 * 1024
_GIT_TIMEOUT = 2.5
# Per-model edit-format steering. Matching the edit tool format to how a model
# was trained reduces mistakes and wasted reasoning (OpenAI/Codex handle
# patch-style diffs best; Anthropic models — and most open-weight coding
# models, whose RL scaffolds use str_replace-style editors — do best with
# string-replacement). Our `patch` tool exposes both: mode="patch" (V4A
# multi-file) and mode="replace" (find-and-swap). We nudge each family toward
# its native format. Unknown families get nothing (the brief's neutral wording
# stands). Substrings match the model id; aligned with TOOL_USE_ENFORCEMENT_MODELS.
_EDIT_FORMAT_GUIDANCE: dict[str, tuple[tuple[str, ...], str]] = {
"patch": (
("gpt", "codex"),
"- Edit format: author new files with `write_file`; for edits to "
"existing code prefer `patch` with `mode='patch'` (V4A multi-file diff) "
"for structured or multi-file changes — it's the diff format you handle "
"most reliably. Use `mode='replace'` for a single small swap.",
),
"replace": (
("claude", "sonnet", "opus", "haiku",
"gemini", "gemma", "deepseek", "qwen", "kimi", "glm", "grok",
"hermes", "llama", "mistral", "devstral", "minimax"),
"- Edit format: author new files with `write_file`; for edits to "
"existing code prefer `patch` in `mode='replace'` — match a unique "
"snippet and swap it. Reach for `mode='patch'` (V4A) only when an edit "
"genuinely spans several files at once.",
),
}
def _model_family(model: Optional[str]) -> Optional[str]:
"""Classify a model id into an edit-format family key, or ``None``.
Used to steer the coding posture toward the edit tool format a model was
trained on. Family-agnostic by design: an unrecognised model gets ``None``
and the operating brief's neutral edit wording applies.
"""
if not model:
return None
lowered = model.lower()
for family, (needles, _line) in _EDIT_FORMAT_GUIDANCE.items():
if any(n in lowered for n in needles):
return family
return None
def _edit_format_line(model: Optional[str]) -> str:
"""The edit-format guidance line for this model's family (``""`` if none)."""
family = _model_family(model)
if family is None:
return ""
return _EDIT_FORMAT_GUIDANCE[family][1]
# Operating brief for the coding posture. Tool names referenced here (read_file,
# search_files, patch, write_file, terminal, todo) are in the coding toolset and
# in _HERMES_CORE_TOOLS, so they're present on every surface this fires on.
CODING_AGENT_GUIDANCE = (
"You are a coding agent pairing with the user inside their codebase. "
"Operate like a careful senior engineer.\n"
"\n"
"Gather context first:\n"
"- Read the relevant files with `read_file` and locate code with "
"`search_files` before changing anything. Trace a symbol to its definition "
"and usages rather than guessing its shape.\n"
"- Batch independent lookups: when several reads/searches don't depend on "
"each other, issue them together in one turn instead of one at a time.\n"
"- Never invent files, symbols, APIs, or imports. If you haven't seen it in "
"the repo, go look. Don't assume a library is available — check the project "
"manifest (pyproject.toml / package.json / Cargo.toml / go.mod) and how "
"neighbouring files import it.\n"
"\n"
"Make changes through the tools, not the chat:\n"
"- Edit with `patch`/`write_file`. Do NOT print code blocks to the user as "
"a substitute for editing — apply the change, then summarise it. Only show "
"code when the user explicitly asks to see it.\n"
"- Match the project's existing style and conventions; AGENTS.md / "
"CLAUDE.md / .cursorrules already in context win over your defaults. Touch "
"only what the task needs — no drive-by refactors, renames, or reformatting "
"— and add any imports/dependencies your code requires.\n"
"- If an edit fails to apply, re-read the file to get the current exact "
"contents before retrying — don't repeat a stale patch. If the same region "
"fails twice, rewrite the enclosing function or file with `write_file` "
"instead of attempting a third patch.\n"
"\n"
"Verify, and know when to stop:\n"
"- Use `terminal` for git, builds, tests, and inspection. Run the relevant "
"tests/linter/build and confirm they pass before claiming the work is done.\n"
"- Fix root causes, not symptoms: when you find a bug, check sibling call "
"paths for the same flaw and fix the class, not just the reported site.\n"
"- When fixing linter/type errors on a file, stop after about three "
"attempts on the same file and ask the user rather than looping.\n"
"- Track multi-step work with `todo`. Reference code as `path:line` instead "
"of pasting whole files.\n"
"\n"
"Respect the user's repo: don't commit, push, or rewrite history unless "
"asked, and never read, print, or commit secrets — leave `.env` and "
"credential files alone unless the user explicitly asks. The Workspace "
"block below is a snapshot from session start — re-run `git status`/"
"`git branch` before relying on it. Be concise: lead with the change or "
"answer, not a preamble."
)
# ── Context profiles (declarative posture definitions) ──────────────────────
@dataclass(frozen=True)
class ContextProfile:
"""A named operating posture. Pure data — consumers read these fields.
``toolset`` collapse to this toolset (+ enabled MCP) when no explicit
selection is pinned; ``None`` keeps the platform default.
``guidance`` operating brief injected into the stable system prompt;
``""`` injects nothing.
``model_hint`` routing preference key for smart model routing
(extension seam; not yet consumed by the router).
``memory_policy`` memory namespace/weighting hint (extension seam).
``hidden_skill_categories`` skill categories pruned from the system-prompt
skill index while this posture is active. Discovery-only:
nothing is disabled ``skills_list`` still returns the
full catalog and ``skill_view`` loads anything. Deny-list
semantics so unknown/custom categories stay visible.
"""
name: str
toolset: Optional[str] = None
guidance: str = ""
model_hint: Optional[str] = None
memory_policy: str = "default"
hidden_skill_categories: tuple[str, ...] = ()
# Skill categories that are clearly not part of a coding workflow. Hidden from
# the prompt's skill index in the coding posture (deny-list — anything not
# listed here, incl. custom user categories, stays visible). Coding-adjacent
# categories (devops, github, mcp, data-science, diagramming, research,
# security, …) are intentionally absent.
_NON_CODING_SKILL_CATEGORIES = (
"apple", "communication", "cooking", "creative", "email", "finance",
"gaming", "gifs", "health", "media", "music", "note-taking",
"productivity", "shopping", "smart-home", "social-media", "travel",
"yuanbao",
)
GENERAL_PROFILE = ContextProfile(name="general")
CODING_PROFILE = ContextProfile(
name="coding",
toolset=CODING_TOOLSET,
guidance=CODING_AGENT_GUIDANCE,
model_hint="coding",
memory_policy="project",
hidden_skill_categories=_NON_CODING_SKILL_CATEGORIES,
)
_PROFILES: dict[str, ContextProfile] = {
GENERAL_PROFILE.name: GENERAL_PROFILE,
CODING_PROFILE.name: CODING_PROFILE,
}
def get_profile(name: str) -> ContextProfile:
"""Return a registered profile, falling back to ``general``."""
return _PROFILES.get(name, GENERAL_PROFILE)
# ── Helpers ─────────────────────────────────────────────────────────────────
def _coding_mode(config: Optional[dict[str, Any]]) -> str:
"""Return the normalized ``agent.coding_context`` mode (auto/focus/on/off)."""
if config is None:
try:
from hermes_cli.config import load_config
config = load_config()
except Exception:
config = {}
raw = ((config or {}).get("agent", {}) or {}).get("coding_context", "auto")
mode = str(raw).strip().lower()
if mode in {"focus", "strict", "lean"}:
return "focus"
if mode in {"on", "true", "yes", "1", "always"}:
return "on"
if mode in {"off", "false", "no", "0", "never"}:
return "off"
return "auto"
def _resolve_cwd(cwd: Optional[str | Path]) -> Path:
if cwd:
return Path(cwd).expanduser()
try:
from agent.runtime_cwd import resolve_agent_cwd
return resolve_agent_cwd()
except Exception:
return Path(os.getcwd())
def _git_root(cwd: Path) -> Optional[Path]:
current = cwd.resolve()
for parent in [current, *current.parents]:
if (parent / ".git").exists():
return parent
return None
def _home() -> Optional[Path]:
try:
return Path.home().resolve()
except (OSError, RuntimeError):
return None
def _marker_root(cwd: Path) -> Optional[Path]:
"""Nearest ancestor that looks like a project root, or ``None``.
Walks up at most a few levels so a manifest in the workspace root counts
even when the user is in a subdirectory. ``$HOME`` itself is skipped a
Makefile or AGENTS.md sitting in the home directory is global user config,
not a project-root signal.
"""
current = cwd.resolve()
home = _home()
for depth, parent in enumerate([current, *current.parents]):
if depth > 6:
break
if parent == home:
continue
for marker in _PROJECT_MARKERS:
if (parent / marker).exists():
return parent
return None
def _detect_profile_name(mode: str, platform: str, cwd_str: str) -> str:
"""Resolve which profile applies.
``auto``/``focus``: coding when the surface is interactive AND the cwd is a
code workspace (a git repo or a recognised project root). ``on``: always
coding. ``off``: always general.
A git repo rooted at ``$HOME`` (the dotfiles pattern) is NOT a workspace
signal without the guard, every session anywhere under a dotfiles-managed
home directory would silently flip to the coding posture.
Detection is intentionally not memoized: it's a handful of ``stat`` calls,
and callers resolve the mode once per session anyway. Caching here would
risk a stale posture if a long-lived process (gateway/TUI) serves sessions
from different working directories.
"""
if mode == "off":
return GENERAL_PROFILE.name
if mode == "on":
return CODING_PROFILE.name
if platform and platform.strip().lower() not in INTERACTIVE_CODING_PLATFORMS:
return GENERAL_PROFILE.name
cwd = Path(cwd_str)
git_root = _git_root(cwd)
if git_root is not None and git_root == _home():
git_root = None # dotfiles repo at $HOME — not a code workspace
if git_root is not None or _marker_root(cwd) is not None:
return CODING_PROFILE.name
return GENERAL_PROFILE.name
# ── RuntimeMode (the seam) ──────────────────────────────────────────────────
@dataclass(frozen=True)
class RuntimeMode:
"""The resolved operating posture for a session. Immutable by construction.
Built once via :func:`resolve_runtime_mode` and consumed by every domain
that cares about the coding/general distinction. Never mutate or re-resolve
mid-session that would break the prompt cache.
"""
profile: ContextProfile
surface: str
cwd: Path
# The normalized ``agent.coding_context`` mode this posture was resolved
# under (auto/focus/on/off). Toolset collapse is gated on ``focus``.
config_mode: str = "auto"
# The model id this session runs (e.g. "anthropic/claude-opus-4.8"). Used
# only to steer edit-format guidance toward the model's family — see
# ``_edit_format_line``. Fixed for the session, so cache-safe.
model: Optional[str] = None
@property
def kind(self) -> str:
return self.profile.name
@property
def is_coding(self) -> bool:
return self.profile.name == CODING_PROFILE.name
def toolset_selection(self, config: Optional[dict[str, Any]] = None) -> Optional[list[str]]:
"""Toolset list for this posture, or ``None`` to keep the platform default.
Non-``None`` only under the opt-in ``focus`` mode. The default posture
is prompt-only: most strippable toolsets are off-by-default anyway, and
a user who explicitly enabled one (image-gen for frontend/game assets,
messaging for build notifications, ) keeps it while coding.
Callers apply this only when the user hasn't pinned an explicit
selection (``--toolsets``, ``HERMES_TUI_TOOLSETS``, ); they never
override a pin. Returns the profile's toolset plus enabled MCP servers.
"""
if self.config_mode != "focus":
return None
if self.profile.toolset is None:
return None
return [self.profile.toolset, *_enabled_mcp_servers(config)]
def system_blocks(self) -> list[str]:
"""Stable system-prompt blocks for this posture (brief + workspace).
The operating brief carries a model-family edit-format nudge appended
to it (one cached string, not a separate block) so the model is steered
toward the `patch` mode it handles best see ``_edit_format_line``.
"""
if not self.is_coding:
return []
blocks: list[str] = []
if self.profile.guidance:
brief = self.profile.guidance
edit_line = _edit_format_line(self.model)
if edit_line:
brief = f"{brief}\n{edit_line}"
blocks.append(brief)
workspace = build_coding_workspace_block(self.cwd)
if workspace:
blocks.append(workspace)
return blocks
def hidden_skill_categories(self) -> frozenset[str]:
"""Skill categories to prune from the prompt's skill index (may be empty)."""
return frozenset(self.profile.hidden_skill_categories)
def resolve_runtime_mode(
*,
platform: Optional[str] = None,
cwd: Optional[str | Path] = None,
config: Optional[dict[str, Any]] = None,
model: Optional[str] = None,
) -> RuntimeMode:
"""Resolve the operating posture once. Cheap — a handful of ``stat`` calls.
This is the single entry point every domain should call. The returned
object is immutable and safe to cache for the session. Detection itself is
intentionally *not* memoized (see ``_detect_profile_name``) so a long-lived
process can't pin a stale posture; callers resolve once per session and
hold the result. ``model`` is recorded only to steer edit-format guidance;
it never affects detection.
"""
resolved_cwd = _resolve_cwd(cwd)
mode = _coding_mode(config)
name = _detect_profile_name(
mode, (platform or "").strip().lower(), str(resolved_cwd)
)
return RuntimeMode(
profile=get_profile(name),
surface=platform or "",
cwd=resolved_cwd,
config_mode=mode,
model=model,
)
# ── Back-compat surface (thin wrappers over RuntimeMode) ────────────────────
def is_coding_context(
*,
platform: Optional[str] = None,
cwd: Optional[str | Path] = None,
config: Optional[dict[str, Any]] = None,
) -> bool:
"""Whether Hermes should operate in its coding posture right now."""
return resolve_runtime_mode(platform=platform, cwd=cwd, config=config).is_coding
def coding_selection(
*,
platform: Optional[str] = None,
cwd: Optional[str | Path] = None,
config: Optional[dict[str, Any]] = None,
) -> Optional[list[str]]:
"""Toolset selection for the coding posture.
``None`` unless the user opted into ``focus`` mode AND the posture is
active the default coding posture never overrides configured toolsets.
"""
return resolve_runtime_mode(
platform=platform, cwd=cwd, config=config
).toolset_selection(config)
def coding_system_blocks(
*,
platform: Optional[str] = None,
cwd: Optional[str | Path] = None,
config: Optional[dict[str, Any]] = None,
model: Optional[str] = None,
) -> list[str]:
"""Stable system-prompt blocks for the current posture (empty when general).
``model`` steers the brief's edit-format nudge toward the model's family.
"""
return resolve_runtime_mode(
platform=platform, cwd=cwd, config=config, model=model
).system_blocks()
def coding_hidden_skill_categories(
*,
platform: Optional[str] = None,
cwd: Optional[str | Path] = None,
config: Optional[dict[str, Any]] = None,
) -> frozenset[str]:
"""Skill categories the active posture prunes from the prompt's skill index.
Empty outside the coding posture. Discovery-only: hidden skills remain
loadable via ``skills_list`` / ``skill_view``.
"""
return resolve_runtime_mode(
platform=platform, cwd=cwd, config=config
).hidden_skill_categories()
def _enabled_mcp_servers(config: Optional[dict[str, Any]]) -> list[str]:
"""Names of MCP servers the user has enabled — kept in the coding posture.
MCP servers (figma, browser, tophat, ) are explicitly configured and part
of the coding workflow, not noise to strip.
"""
try:
from hermes_cli.config import read_raw_config
from hermes_cli.tools_config import _parse_enabled_flag
servers = read_raw_config().get("mcp_servers") or {}
return [
str(name)
for name, cfg in servers.items()
if isinstance(cfg, dict)
and _parse_enabled_flag(cfg.get("enabled", True), default=True)
]
except Exception:
return []
# ── git/workspace probe ─────────────────────────────────────────────────────
def _git(cwd: Path, *args: str) -> str:
try:
out = subprocess.run(
["git", "-C", str(cwd), *args],
capture_output=True,
text=True,
timeout=_GIT_TIMEOUT,
)
except (OSError, subprocess.SubprocessError):
return ""
return out.stdout.strip() if out.returncode == 0 else ""
def _parse_status(porcelain: str) -> tuple[dict[str, str], dict[str, int]]:
"""Parse ``git status --porcelain=2 --branch`` into branch + counts."""
branch: dict[str, str] = {}
counts = {"staged": 0, "modified": 0, "untracked": 0, "conflicts": 0}
for line in porcelain.splitlines():
if line.startswith("# branch.head"):
branch["head"] = line.split(maxsplit=2)[-1]
elif line.startswith("# branch.upstream"):
branch["upstream"] = line.split(maxsplit=2)[-1]
elif line.startswith("# branch.ab"):
parts = line.split()
branch["ahead"], branch["behind"] = parts[2].lstrip("+"), parts[3].lstrip("-")
elif line.startswith(("1 ", "2 ")):
xy = line.split(maxsplit=2)[1]
if xy[0] != ".":
counts["staged"] += 1
if xy[1] != ".":
counts["modified"] += 1
elif line.startswith("u "):
counts["conflicts"] += 1
elif line.startswith("? "):
counts["untracked"] += 1
return branch, counts
def _read_small(path: Path) -> str:
"""Read a small text file, or ``""`` — never raises, never reads huge files."""
try:
if not path.is_file() or path.stat().st_size > _MAX_FACT_FILE_BYTES:
return ""
return path.read_text(encoding="utf-8", errors="replace")
except OSError:
return ""
def _project_facts(root: Path) -> list[str]:
"""Detected project facts for the workspace snapshot.
The point is to hand the model its *verify loop* up front which manifest,
which package manager, and the exact test/lint/build commands instead of
making it rediscover them every session. Cheap: stat calls plus reads of a
couple of small files; built once at prompt-build time (cache-safe).
"""
facts: list[str] = []
manifests = [m for m in _PROJECT_MARKERS if m not in _CONTEXT_FILES and (root / m).is_file()]
package_managers = [
pm for lock, pm in (*_PY_LOCKFILES, *_JS_LOCKFILES) if (root / lock).is_file()
]
if manifests:
line = f"- Project: {', '.join(manifests[:6])}"
if package_managers:
line += f" ({'/'.join(dict.fromkeys(package_managers))})"
facts.append(line)
verify: list[str] = []
if (root / "scripts" / "run_tests.sh").is_file():
verify.append("scripts/run_tests.sh")
if (root / "package.json").is_file():
try:
scripts = json.loads(_read_small(root / "package.json") or "{}").get("scripts") or {}
except (json.JSONDecodeError, AttributeError):
scripts = {}
js_pm = next((pm for lock, pm in _JS_LOCKFILES if (root / lock).is_file()), "npm")
verify.extend(f"{js_pm} run {name}" for name in _VERIFY_TARGETS if name in scripts)
if (root / "pytest.ini").is_file() or "[tool.pytest" in _read_small(root / "pyproject.toml"):
verify.append("pytest")
makefile = _read_small(root / "Makefile")
if makefile:
verify.extend(
f"make {name}" for name in _VERIFY_TARGETS
if re.search(rf"^{re.escape(name)}\s*:", makefile, re.MULTILINE)
)
if verify:
deduped = list(dict.fromkeys(verify))[:_MAX_VERIFY_COMMANDS]
facts.append(f"- Verify: {'; '.join(deduped)}")
context_files = [c for c in _CONTEXT_FILES if (root / c).is_file()]
if context_files:
facts.append(f"- Context files: {', '.join(context_files)}")
return facts
def build_coding_workspace_block(cwd: Optional[str | Path] = None) -> str:
"""Workspace snapshot for the system prompt (empty outside a workspace).
Git state (branch/status/commits) when the cwd is in a repo, plus detected
project facts (manifest, package manager, verify commands, context files)
so marker-only (non-git) projects still get a snapshot.
"""
resolved = _resolve_cwd(cwd)
git_root = _git_root(resolved)
root = git_root or _marker_root(resolved)
if root is None:
return ""
lines = ["Workspace (snapshot at session start — re-check with `git` before acting on it):"]
lines.append(f"- Root: {root}")
if git_root is not None:
branch, counts = _parse_status(_git(root, "status", "--porcelain=2", "--branch"))
head = branch.get("head", "")
if head and head != "(detached)":
line = f"- Branch: {head}"
if branch.get("upstream"):
line += f" \u2192 {branch['upstream']}"
ahead, behind = branch.get("ahead", "0"), branch.get("behind", "0")
if ahead != "0" or behind != "0":
line += f" (ahead {ahead}, behind {behind})"
lines.append(line)
elif head == "(detached)":
lines.append("- Branch: (detached HEAD)")
# Linked worktree: the per-worktree git dir differs from the shared common dir.
git_dir, common_dir = _git(root, "rev-parse", "--git-dir"), _git(root, "rev-parse", "--git-common-dir")
if git_dir and common_dir and Path(git_dir).resolve() != Path(common_dir).resolve():
main_tree = Path(common_dir).resolve().parent
lines.append(f"- Worktree: linked (primary tree at {main_tree})")
dirty = [f"{n} {label}" for label, n in (
("staged", counts["staged"]), ("modified", counts["modified"]),
("untracked", counts["untracked"]), ("conflicts", counts["conflicts"]),
) if n]
lines.append(f"- Status: {', '.join(dirty) if dirty else 'clean'}")
recent = _git(root, "log", "-3", "--pretty=%h %s")
if recent:
lines.append("- Recent commits:")
lines.extend(f" {c}" for c in recent.splitlines())
lines.extend(_project_facts(root))
return "\n".join(lines)

View file

@ -2221,30 +2221,54 @@ def run_conversation(
print(f"{agent.log_prefix} • Legacy cleanup: hermes config set ANTHROPIC_TOKEN \"\"")
print(f"{agent.log_prefix} • Clear stale keys: hermes config set ANTHROPIC_API_KEY \"\"")
# ── Thinking block signature recovery ─────────────────
# Thinking block signature recovery.
#
# Anthropic signs thinking blocks against the full turn
# content. Any upstream mutation (context compression,
# content. Any upstream mutation (context compression,
# session truncation, message merging) invalidates the
# signature → HTTP 400. Recovery: strip reasoning_details
# from all messages so the next retry sends no thinking
# blocks at all. One-shot — don't retry infinitely.
# signature and the API replies HTTP 400 ("invalid
# signature" or "cannot be modified"). Recovery strips
# ``reasoning_details`` so the retry sends no thinking
# blocks at all. One-shot per outer loop.
#
# The strip targets ``api_messages``, which is the
# API-call-time list that ``_build_api_kwargs`` consumes
# on every retry. ``api_messages`` was populated once at
# the start of the turn from shallow copies of
# ``messages``, so mutating it does not touch the
# canonical store. The previous implementation popped
# ``reasoning_details`` from ``messages`` instead, which
# had two problems: ``api_messages`` carried its own
# reference to the field through the shallow copy, so the
# retry's wire payload still included thinking blocks and
# the recovery never reached the API; and the mutation
# persisted into ``state.db`` through any subsequent
# ``_persist_session`` call, permanently corrupting the
# conversation. Future turns would replay the stripped
# state, hit the same 400, and the agent would terminate
# with ``max_retries_exhausted``, often spawning
# cascading compaction-ended sessions chained off the
# corrupted parent.
if (
classified.reason == FailoverReason.thinking_signature
and not _retry.thinking_sig_retry_attempted
):
_retry.thinking_sig_retry_attempted = True
for _m in messages:
if isinstance(_m, dict):
_api_stripped = 0
for _m in api_messages:
if isinstance(_m, dict) and "reasoning_details" in _m:
_m.pop("reasoning_details", None)
_api_stripped += 1
agent._vprint(
f"{agent.log_prefix}⚠️ Thinking block signature invalid — "
f"stripped all thinking blocks, retrying...",
f"{agent.log_prefix}⚠️ Thinking block signature invalid, "
f"stripped reasoning_details from api_messages for retry...",
force=True,
)
logger.warning(
"%sThinking block signature recovery: stripped "
"reasoning_details from %d messages",
agent.log_prefix, len(messages),
"reasoning_details from %d api_messages "
"(canonical messages unchanged)",
agent.log_prefix, _api_stripped,
)
continue

View file

@ -858,6 +858,20 @@ def _detect_tool_failure(tool_name: str, result: str | None) -> tuple[bool, str]
return False, ""
def _used_free_parallel(result: str | None) -> bool:
"""True when a web result came from Parallel's free Search MCP.
Only the keyless Parallel path tags its result with ``provider="parallel"``;
the paid REST path and every other provider omit it. Used to label the tool
line "Parallel search" / "Parallel fetch" exactly when the free MCP served
the call.
"""
if not isinstance(result, str) or '"provider"' not in result:
return False
data = safe_json_loads(result)
return isinstance(data, dict) and str(data.get("provider", "")).lower() == "parallel"
def get_cute_tool_message(
tool_name: str, args: dict, duration: float, result: str | None = None,
) -> str:
@ -895,15 +909,17 @@ def get_cute_tool_message(
return f"{line}{failure_suffix}"
if tool_name == "web_search":
return _wrap(f"┊ 🔍 search {_trunc(args.get('query', ''), 42)} {dur}")
verb = "Parallel search" if _used_free_parallel(result) else "search"
return _wrap(f"┊ 🔍 {verb:<9} {_trunc(args.get('query', ''), 42)} {dur}")
if tool_name == "web_extract":
verb = "Parallel fetch" if _used_free_parallel(result) else "fetch"
urls = args.get("urls", [])
if urls:
url = urls[0] if isinstance(urls, list) else str(urls)
domain = url.replace("https://", "").replace("http://", "").split("/")[0]
extra = f" +{len(urls)-1}" if len(urls) > 1 else ""
return _wrap(f"┊ 📄 fetch {_trunc(domain, 35)}{extra} {dur}")
return _wrap(f"┊ 📄 fetch pages {dur}")
return _wrap(f"┊ 📄 {verb:<9} {_trunc(domain, 35)}{extra} {dur}")
return _wrap(f"┊ 📄 {verb:<9} pages {dur}")
if tool_name == "terminal":
return _wrap(f"┊ 💻 $ {_trunc(args.get('command', ''), 42)} {dur}")
if tool_name == "process":

View file

@ -549,14 +549,32 @@ def classify_api_error(
should_fallback=True,
)
# Anthropic thinking block signature invalid (400).
# Anthropic thinking block recovery (400). Two distinct failure modes,
# same recovery (strip all reasoning_details and retry without thinking
# blocks — see the thinking_signature handler in conversation_loop.py):
# 1. Signature mismatch: a thinking block is signed against the full
# turn content; any upstream mutation (context compression, session
# truncation, message merging) invalidates the signature.
# Pattern: "signature" + "thinking".
# 2. Frozen-block mutation: Anthropic rejects any change to the
# thinking/redacted_thinking blocks in the *latest* assistant
# message — "`thinking` or `redacted_thinking` blocks in the latest
# assistant message cannot be modified. These blocks must remain as
# they were in the original response." This carries no "signature"
# token, so the original pattern missed it and the turn hard-aborted
# as a non-retryable client error instead of self-healing.
# Pattern: "thinking" + ("cannot be modified" | "must remain as they were").
# Don't gate on provider — OpenRouter proxies Anthropic errors, so the
# provider may be "openrouter" even though the error is Anthropic-specific.
# The message pattern ("signature" + "thinking") is unique enough.
# The combined patterns are unique enough.
if (
status_code == 400
and "signature" in error_msg
and "thinking" in error_msg
and (
"signature" in error_msg
or "cannot be modified" in error_msg
or "must remain as they were" in error_msg
)
):
return _result(
FailoverReason.thinking_signature,

View file

@ -1118,11 +1118,12 @@ def _skill_should_show(
def build_skills_system_prompt(
available_tools: "set[str] | None" = None,
available_toolsets: "set[str] | None" = None,
hidden_categories: "frozenset[str] | None" = None,
) -> str:
"""Build a compact skill index for the system prompt.
Two-layer cache:
1. In-process LRU dict keyed by (skills_dir, tools, toolsets)
1. In-process LRU dict keyed by (skills_dir, tools, toolsets, hidden)
2. Disk snapshot (``.skills_prompt_snapshot.json``) validated by
mtime/size manifest survives process restarts
@ -1132,6 +1133,12 @@ def build_skills_system_prompt(
scanned alongside the local ``~/.hermes/skills/`` directory. External dirs
are read-only they appear in the index but new skills are always created
in the local dir. Local skills take precedence when names collide.
``hidden_categories`` (e.g. from the coding posture see
agent/coding_context.py) prunes whole categories from the rendered index.
Discovery-only: the snapshot stores everything, ``skills_list`` /
``skill_view`` still reach every skill, and a footer note tells the model
the full catalog exists.
"""
skills_dir = get_skills_dir()
external_dirs = get_all_skills_dirs()[1:] # skip local (index 0)
@ -1156,6 +1163,7 @@ def build_skills_system_prompt(
tuple(sorted(str(ts) for ts in (available_toolsets or set()))),
_platform_hint,
tuple(sorted(disabled)),
tuple(sorted(hidden_categories or ())),
)
with _SKILLS_PROMPT_CACHE_LOCK:
cached = _SKILLS_PROMPT_CACHE.get(cache_key)
@ -1289,6 +1297,26 @@ def build_skills_system_prompt(
except Exception as e:
logger.debug("Could not read external skill description %s: %s", desc_file, e)
# Posture-driven category pruning (e.g. non-coding skills while pairing on
# code). Match on the top-level category segment so nested categories
# ("social-media/twitter") are pruned with their parent.
hidden_note = ""
if hidden_categories:
before = sum(len(v) for v in skills_by_category.values())
skills_by_category = {
cat: entries
for cat, entries in skills_by_category.items()
if cat.split("/", 1)[0] not in hidden_categories
}
pruned = before - sum(len(v) for v in skills_by_category.values())
if pruned:
hidden_note = (
f"\n(Note: {pruned} skill(s) in categories unrelated to the "
"current coding context are not listed here. The full catalog "
"is available via skills_list if the user asks for something "
"outside this list.)"
)
if not skills_by_category:
result = ""
else:
@ -1337,6 +1365,7 @@ def build_skills_system_prompt(
"</available_skills>\n"
"\n"
"Only proceed without loading a skill if genuinely none are relevant to the task."
+ hidden_note
)
# ── Store in LRU cache ────────────────────────────────────────────

View file

@ -191,9 +191,21 @@ def build_system_prompt_parts(agent: Any, system_message: Optional[str] = None)
)
if toolset
}
# Coding posture prunes non-coding skill categories from the index
# (discovery-only — skills_list/skill_view still reach everything).
_hidden_cats = frozenset()
try:
from agent.coding_context import coding_hidden_skill_categories
_hidden_cats = coding_hidden_skill_categories(
platform=agent.platform, cwd=resolve_context_cwd()
)
except Exception:
_hidden_cats = frozenset()
skills_prompt = _r.build_skills_system_prompt(
available_tools=agent.valid_tool_names,
available_toolsets=avail_toolsets,
hidden_categories=_hidden_cats or None,
)
else:
skills_prompt = ""
@ -221,6 +233,26 @@ def build_system_prompt_parts(agent: Any, system_message: Optional[str] = None)
if _env_hints:
stable_parts.append(_env_hints)
# Coding posture (base Hermes, any interactive coding surface in a code
# workspace — see agent/coding_context.py). The operating brief + the live
# git/workspace snapshot are built once here and cached for the session;
# the snapshot is never re-probed per turn (that would break the prompt
# cache), so the brief tells the model to re-check git before relying on it.
if agent.valid_tool_names:
try:
from agent.coding_context import coding_system_blocks
stable_parts.extend(
coding_system_blocks(
platform=agent.platform,
cwd=resolve_context_cwd(),
model=agent.model,
)
)
except Exception:
# Coding-context probing must never block prompt build.
pass
# Local Python toolchain probe — names python/pip/uv/PEP-668 state when
# something is non-default so the model can pick the right install
# strategy without discovering by failure. Emits a single line; emits

View file

@ -417,7 +417,7 @@ def execute_tool_calls_concurrent(agent, assistant_message, messages: list, effe
# ── Logging / callbacks ──────────────────────────────────────────
tool_names_str = ", ".join(name for _, name, _, _, _, _ in parsed_calls)
if not agent.quiet_mode:
if not agent.quiet_mode and getattr(agent, "tool_progress_mode", "all") != "off":
print(f" ⚡ Concurrent: {num_tools} tool calls — {tool_names_str}")
for i, (tc, name, args, middleware_trace, block_result, blocked_by_guardrail) in enumerate(parsed_calls, 1):
args_str = json.dumps(args, ensure_ascii=False)
@ -702,7 +702,7 @@ def execute_tool_calls_concurrent(agent, assistant_message, messages: list, effe
if agent._should_emit_quiet_tool_messages():
cute_msg = _get_cute_tool_message_impl(name, args, tool_duration, result=function_result)
agent._safe_print(f" {cute_msg}")
elif getattr(agent, "tool_progress_mode", "all") != "off":
elif not agent.quiet_mode and getattr(agent, "tool_progress_mode", "all") != "off":
_preview_str = _multimodal_text_summary(function_result)
if agent.verbose_logging:
print(f" ✅ Tool {i+1} completed in {tool_duration:.2f}s")
@ -866,7 +866,7 @@ def execute_tool_calls_sequential(agent, assistant_message, messages: list, effe
elif function_name == "skill_manage":
agent._iters_since_skill = 0
if not agent.quiet_mode:
if not agent.quiet_mode and getattr(agent, "tool_progress_mode", "all") != "off":
args_str = json.dumps(function_args, ensure_ascii=False)
if agent.verbose_logging:
print(f" 📞 Tool {i}: {function_name}({list(function_args.keys())})")
@ -1384,7 +1384,7 @@ def execute_tool_calls_sequential(agent, assistant_message, messages: list, effe
# entire batch. The model sees it on the next API iteration.
agent._apply_pending_steer_to_tool_results(messages, 1)
if not agent.quiet_mode:
if not agent.quiet_mode and getattr(agent, "tool_progress_mode", "all") != "off":
if agent.verbose_logging:
print(f" ✅ Tool {i} completed in {tool_duration:.2f}s")
print(agent._wrap_verbose("Result: ", function_result))

View file

@ -84,7 +84,7 @@ class AnthropicTransport(ProviderTransport):
to OpenAI finish_reason, and collects reasoning_details in provider_data.
"""
import json
from agent.anthropic_adapter import _to_plain_data
from agent.anthropic_adapter import _to_plain_data, _sanitize_replay_block
from agent.transports.types import ToolCall
strip_tool_prefix = kwargs.get("strip_tool_prefix", False)
@ -94,14 +94,40 @@ class AnthropicTransport(ProviderTransport):
reasoning_parts = []
reasoning_details = []
tool_calls = []
# Verbatim, order-preserving copy of every content block in the turn.
# Anthropic signs each thinking block against the turn content that
# PRECEDES it at its position; when a turn interleaves thinking and
# tool_use (adaptive/interleaved thinking, Claude 4.6+), the parallel
# reasoning_details + tool_calls lists below lose that cross-type
# ordering. Replaying the latest assistant message in the wrong order
# invalidates the signatures -> HTTP 400 "thinking ... blocks in the
# latest assistant message cannot be modified". Preserve the exact
# block sequence here so the adapter can replay it unchanged. See
# tests/agent/test_anthropic_thinking_block_order.py.
ordered_blocks = []
for block in response.content:
block_dict = _to_plain_data(block)
clean_block = None
if isinstance(block_dict, dict):
# Sanitize at capture so output-only SDK fields (parsed_output,
# caller, citations=None, …) never persist to state.db and leak
# back as request input on replay → HTTP 400 "Extra inputs are
# not permitted". Defence-in-depth with the replay-side sanitize.
clean_block = _sanitize_replay_block(block_dict)
if clean_block is not None:
ordered_blocks.append(clean_block)
if block.type == "text":
text_parts.append(block.text)
elif block.type == "thinking":
reasoning_parts.append(block.thinking)
block_dict = _to_plain_data(block)
if isinstance(block_dict, dict):
elif block.type in ("thinking", "redacted_thinking"):
if block.type == "thinking":
reasoning_parts.append(block.thinking)
# Use the sanitized block (clean_block) for reasoning_details too,
# since _extract_preserved_thinking_blocks replays these on the
# non-ordered path. Falls back to raw only if sanitize dropped it.
if isinstance(clean_block, dict):
reasoning_details.append(clean_block)
elif isinstance(block_dict, dict):
reasoning_details.append(block_dict)
elif block.type == "tool_use":
name = block.name
@ -130,6 +156,23 @@ class AnthropicTransport(ProviderTransport):
provider_data = {}
if reasoning_details:
provider_data["reasoning_details"] = reasoning_details
# Only worth carrying the ordered-blocks channel when the turn
# actually interleaves signed thinking with tool_use — that's the
# only shape the parallel lists reconstruct incorrectly. A turn that
# is purely text, or thinking-then-tools with a single leading
# thinking block, replays correctly without it.
_has_signed_thinking = any(
isinstance(b, dict)
and b.get("type") in ("thinking", "redacted_thinking")
and (b.get("signature") or b.get("data"))
for b in ordered_blocks
)
_has_tool_use = any(
isinstance(b, dict) and b.get("type") == "tool_use"
for b in ordered_blocks
)
if _has_signed_thinking and _has_tool_use:
provider_data["anthropic_content_blocks"] = ordered_blocks
return NormalizedResponse(
content="\n".join(text_parts) if text_parts else None,

View file

@ -121,6 +121,18 @@ class NormalizedResponse:
pd = self.provider_data or {}
return pd.get("reasoning_details")
@property
def anthropic_content_blocks(self):
"""Verbatim, order-preserving Anthropic content blocks for a turn.
Present only when an Anthropic turn interleaves signed thinking with
tool_use the one shape the parallel reasoning_details + tool_calls
lists reconstruct in the wrong order, invalidating thinking-block
signatures on replay. See agent/transports/anthropic.py.
"""
pd = self.provider_data or {}
return pd.get("anthropic_content_blocks")
@property
def codex_reasoning_items(self):
pd = self.provider_data or {}