Hermes-agent
This commit is contained in:
Zakaria
@@ -0,0 +1,608 @@
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"""Background memory/skill review — fork the agent to evaluate the turn.
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After every turn, ``AIAgent.run_conversation`` may call
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:func:`spawn_background_review` to fire off a daemon thread that replays
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the conversation snapshot in a forked :class:`AIAgent` and asks itself
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"should any skill/memory be saved or updated?". Writes go straight to
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the memory + skill stores. Main conversation and prompt cache are never
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touched.
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The fork inherits the parent's live runtime (provider, model, base_url,
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credentials, cached system prompt) so it hits the same prefix cache and
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uses the same auth. It runs with a tool whitelist limited to memory and
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skill management tools; everything else is denied at runtime.
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See the ``hermes-agent-dev`` skill (``references/self-improvement-loop.md``)
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for invariants and PR review criteria.
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"""
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from __future__ import annotations
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import contextlib
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import json
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import logging
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import os
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from typing import Any, Dict, List, Optional
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logger = logging.getLogger(__name__)
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# Review-prompt strings — used by ``spawn_background_review_thread`` to build
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# the user-message that the forked review agent receives. AIAgent exposes
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# them as class attributes (``_MEMORY_REVIEW_PROMPT`` etc.) for back-compat;
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# the actual text lives here so future edits are one-place.
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_MEMORY_REVIEW_PROMPT = (
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"Review the conversation above and consider saving to memory if appropriate.\n\n"
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"Focus on:\n"
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"1. Has the user revealed things about themselves — their persona, desires, "
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"preferences, or personal details worth remembering?\n"
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"2. Has the user expressed expectations about how you should behave, their work "
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"style, or ways they want you to operate?\n\n"
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"If something stands out, save it using the memory tool. "
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"If nothing is worth saving, just say 'Nothing to save.' and stop."
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)
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_SKILL_REVIEW_PROMPT = (
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"Review the conversation above and update the skill library. Be "
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"ACTIVE — most sessions produce at least one skill update, even if "
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"small. A pass that does nothing is a missed learning opportunity, "
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"not a neutral outcome.\n\n"
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"Target shape of the library: CLASS-LEVEL skills, each with a rich "
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"SKILL.md and a `references/` directory for session-specific detail. "
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"Not a long flat list of narrow one-session-one-skill entries. This "
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"shapes HOW you update, not WHETHER you update.\n\n"
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"Signals to look for (any one of these warrants action):\n"
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" • User corrected your style, tone, format, legibility, or "
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"verbosity. Frustration signals like 'stop doing X', 'this is too "
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"verbose', 'don't format like this', 'why are you explaining', "
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"'just give me the answer', 'you always do Y and I hate it', or an "
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"explicit 'remember this' are FIRST-CLASS skill signals, not just "
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"memory signals. Update the relevant skill(s) to embed the "
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"preference so the next session starts already knowing.\n"
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" • User corrected your workflow, approach, or sequence of steps. "
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"Encode the correction as a pitfall or explicit step in the skill "
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"that governs that class of task.\n"
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" • Non-trivial technique, fix, workaround, debugging path, or "
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"tool-usage pattern emerged that a future session would benefit "
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"from. Capture it.\n"
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" • A skill that got loaded or consulted this session turned out "
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"to be wrong, missing a step, or outdated. Patch it NOW.\n\n"
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"Preference order — prefer the earliest action that fits, but do "
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"pick one when a signal above fired:\n"
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" 1. UPDATE A CURRENTLY-LOADED SKILL. Look back through the "
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"conversation for skills the user loaded via /skill-name or you "
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"read via skill_view. If any of them covers the territory of the "
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"new learning, PATCH that one first. It is the skill that was in "
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"play, so it's the right one to extend.\n"
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" 2. UPDATE AN EXISTING UMBRELLA (via skills_list + skill_view). "
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"If no loaded skill fits but an existing class-level skill does, "
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"patch it. Add a subsection, a pitfall, or broaden a trigger.\n"
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" 3. ADD A SUPPORT FILE under an existing umbrella. Skills can be "
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"packaged with three kinds of support files — use the right "
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"directory per kind:\n"
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" • `references/<topic>.md` — session-specific detail (error "
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"transcripts, reproduction recipes, provider quirks) AND "
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"condensed knowledge banks: quoted research, API docs, external "
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"authoritative excerpts, or domain notes you found while working "
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"on the problem. Write it concise and for the value of the task, "
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"not as a full mirror of upstream docs.\n"
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" • `templates/<name>.<ext>` — starter files meant to be "
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"copied and modified (boilerplate configs, scaffolding, a "
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"known-good example the agent can `reproduce with modifications`).\n"
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" • `scripts/<name>.<ext>` — statically re-runnable actions "
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"the skill can invoke directly (verification scripts, fixture "
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"generators, deterministic probes, anything the agent should run "
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"rather than hand-type each time).\n"
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" Add support files via skill_manage action=write_file with "
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"file_path starting 'references/', 'templates/', or 'scripts/'. "
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"The umbrella's SKILL.md should gain a one-line pointer to any "
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"new support file so future agents know it exists.\n"
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" 4. CREATE A NEW CLASS-LEVEL UMBRELLA SKILL when no existing "
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"skill covers the class. The name MUST be at the class level. "
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"The name MUST NOT be a specific PR number, error string, feature "
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"codename, library-alone name, or 'fix-X / debug-Y / audit-Z-today' "
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"session artifact. If the proposed name only makes sense for "
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"today's task, it's wrong — fall back to (1), (2), or (3).\n\n"
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"User-preference embedding (important): when the user expressed a "
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"style/format/workflow preference, the update belongs in the "
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"SKILL.md body, not just in memory. Memory captures 'who the user "
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"is and what the current situation and state of your operations "
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"are'; skills capture 'how to do this class of task for this "
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"user'. When they complain about how you handled a task, the "
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"skill that governs that task needs to carry the lesson.\n\n"
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"If you notice two existing skills that overlap, note it in your "
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"reply — the background curator handles consolidation at scale.\n\n"
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"Protected skills (DO NOT edit these):\n"
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" • Bundled skills (shipped with Hermes, e.g. 'hermes-agent').\n"
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" • Hub-installed skills (installed via 'hermes skills install').\n"
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"Pinned skills (marked via 'hermes curator pin') CAN be improved — "
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"pin only blocks deletion/archive/consolidation by the curator, not "
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"content updates. Patch them when a pitfall or missing step turns up, "
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"same as any other agent-created skill.\n"
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"If the only skills that need updating are protected, say\n"
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"'Nothing to save.' and stop.\n\n"
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"Do NOT capture (these become persistent self-imposed constraints "
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"that bite you later when the environment changes):\n"
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" • Environment-dependent failures: missing binaries, fresh-install "
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"errors, post-migration path mismatches, 'command not found', "
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"unconfigured credentials, uninstalled packages. The user can fix "
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"these — they are not durable rules.\n"
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" • Negative claims about tools or features ('browser tools do not "
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"work', 'X tool is broken', 'cannot use Y from execute_code'). These "
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"harden into refusals the agent cites against itself for months "
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"after the actual problem was fixed.\n"
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" • Session-specific transient errors that resolved before the "
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"conversation ended. If retrying worked, the lesson is the retry "
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"pattern, not the original failure.\n"
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" • One-off task narratives. A user asking 'summarize today's "
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"market' or 'analyze this PR' is not a class of work that warrants "
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"a skill.\n\n"
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"If a tool failed because of setup state, capture the FIX (install "
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"command, config step, env var to set) under an existing setup or "
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"troubleshooting skill — never 'this tool does not work' as a "
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"standalone constraint.\n\n"
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"'Nothing to save.' is a real option but should NOT be the "
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"default. If the session ran smoothly with no corrections and "
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"produced no new technique, just say 'Nothing to save.' and stop. "
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"Otherwise, act."
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)
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_COMBINED_REVIEW_PROMPT = (
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"Review the conversation above and update two things:\n\n"
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"**Memory**: who the user is. Did the user reveal persona, "
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"desires, preferences, personal details, or expectations about "
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"how you should behave? Save facts about the user and durable "
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"preferences with the memory tool.\n\n"
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"**Skills**: how to do this class of task. Be ACTIVE — most "
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"sessions produce at least one skill update. A pass that does "
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"nothing is a missed learning opportunity, not a neutral outcome.\n\n"
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"Target shape of the skill library: CLASS-LEVEL skills with a rich "
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"SKILL.md and a `references/` directory for session-specific detail. "
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"Not a long flat list of narrow one-session-one-skill entries.\n\n"
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"Signals that warrant a skill update (any one is enough):\n"
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" • User corrected your style, tone, format, legibility, "
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"verbosity, or approach. Frustration is a FIRST-CLASS skill "
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"signal, not just a memory signal. 'stop doing X', 'don't format "
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"like this', 'I hate when you Y' — embed the lesson in the skill "
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"that governs that task so the next session starts fixed.\n"
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" • Non-trivial technique, fix, workaround, or debugging path "
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"emerged.\n"
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" • A skill that was loaded or consulted turned out wrong, "
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"missing, or outdated — patch it now.\n\n"
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"Preference order for skills — pick the earliest that fits:\n"
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" 1. UPDATE A CURRENTLY-LOADED SKILL. Check what skills were "
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"loaded via /skill-name or skill_view in the conversation. If one "
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"of them covers the learning, PATCH it first. It was in play; "
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"it's the right place.\n"
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" 2. UPDATE AN EXISTING UMBRELLA (skills_list + skill_view to "
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"find the right one). Patch it.\n"
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" 3. ADD A SUPPORT FILE under an existing umbrella via "
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"skill_manage action=write_file. Three kinds: "
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"`references/<topic>.md` for session-specific detail OR condensed "
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"knowledge banks (quoted research, API docs excerpts, domain "
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"notes) written concise and task-focused; `templates/<name>.<ext>` "
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"for starter files meant to be copied and modified; "
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"`scripts/<name>.<ext>` for statically re-runnable actions "
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"(verification, fixture generators, probes). Add a one-line "
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"pointer in SKILL.md so future agents find them.\n"
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" 4. CREATE A NEW CLASS-LEVEL UMBRELLA when nothing exists. "
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"Name at the class level — NOT a PR number, error string, "
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"codename, library-alone name, or 'fix-X / debug-Y' session "
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"artifact. If the name only fits today's task, fall back to (1), "
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"(2), or (3).\n\n"
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"User-preference embedding: when the user complains about how "
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"you handled a task, update the skill that governs that task — "
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"memory alone isn't enough. Memory says 'who the user is and "
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"what the current situation and state of your operations are'; "
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"skills say 'how to do this class of task for this user'. Both "
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"should carry user-preference lessons when relevant.\n\n"
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"If you notice overlapping existing skills, mention it — the "
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"background curator handles consolidation.\n\n"
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"Protected skills (DO NOT edit these):\n"
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" • Bundled skills (shipped with Hermes, e.g. 'hermes-agent').\n"
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" • Hub-installed skills (installed via 'hermes skills install').\n"
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||||
"Pinned skills (marked via 'hermes curator pin') CAN be improved — "
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"pin only blocks deletion/archive/consolidation by the curator, not "
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||||
"content updates. Patch them when a pitfall or missing step turns up, "
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"same as any other agent-created skill.\n"
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"If the only skills that need updating are protected, say\n"
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"'Nothing to save.' and stop.\n\n"
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"Do NOT capture as skills (these become persistent self-imposed "
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"constraints that bite you later when the environment changes):\n"
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" • Environment-dependent failures: missing binaries, fresh-install "
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"errors, post-migration path mismatches, 'command not found', "
|
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"unconfigured credentials, uninstalled packages. The user can fix "
|
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"these — they are not durable rules.\n"
|
||||
" • Negative claims about tools or features ('browser tools do not "
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"work', 'X tool is broken', 'cannot use Y from execute_code'). These "
|
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"harden into refusals the agent cites against itself for months "
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"after the actual problem was fixed.\n"
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" • Session-specific transient errors that resolved before the "
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"conversation ended. If retrying worked, the lesson is the retry "
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"pattern, not the original failure.\n"
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||||
" • One-off task narratives. A user asking 'summarize today's "
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"market' or 'analyze this PR' is not a class of work that warrants "
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"a skill.\n\n"
|
||||
"If a tool failed because of setup state, capture the FIX (install "
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"command, config step, env var to set) under an existing setup or "
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"troubleshooting skill — never 'this tool does not work' as a "
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"standalone constraint.\n\n"
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"Act on whichever of the two dimensions has real signal. If "
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"genuinely nothing stands out on either, say 'Nothing to save.' "
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"and stop — but don't reach for that conclusion as a default."
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)
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def summarize_background_review_actions(
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review_messages: List[Dict],
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prior_snapshot: List[Dict],
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) -> List[str]:
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"""Build the human-facing action summary for a background review pass.
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Walks the review agent's session messages and collects "successful tool
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action" descriptions to surface to the user (e.g. "Memory updated").
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Tool messages already present in ``prior_snapshot`` are skipped so we
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don't re-surface stale results from the prior conversation that the
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review agent inherited via ``conversation_history`` (issue #14944).
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Matching is by ``tool_call_id`` when available, with a content-equality
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fallback for tool messages that lack one.
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"""
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existing_tool_call_ids = set()
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existing_tool_contents = set()
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for prior in prior_snapshot or []:
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if not isinstance(prior, dict) or prior.get("role") != "tool":
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continue
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tcid = prior.get("tool_call_id")
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if tcid:
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existing_tool_call_ids.add(tcid)
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else:
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content = prior.get("content")
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if isinstance(content, str):
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existing_tool_contents.add(content)
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actions: List[str] = []
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for msg in review_messages or []:
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if not isinstance(msg, dict) or msg.get("role") != "tool":
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continue
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tcid = msg.get("tool_call_id")
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if tcid and tcid in existing_tool_call_ids:
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continue
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if not tcid:
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content_str = msg.get("content")
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if isinstance(content_str, str) and content_str in existing_tool_contents:
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continue
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try:
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data = json.loads(msg.get("content", "{}"))
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except (json.JSONDecodeError, TypeError):
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continue
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if not isinstance(data, dict) or not data.get("success"):
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continue
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message = data.get("message", "")
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target = data.get("target", "")
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if "created" in message.lower():
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actions.append(message)
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elif "updated" in message.lower():
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actions.append(message)
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elif "added" in message.lower() or (target and "add" in message.lower()):
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label = "Memory" if target == "memory" else "User profile" if target == "user" else target
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actions.append(f"{label} updated")
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elif "Entry added" in message:
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label = "Memory" if target == "memory" else "User profile" if target == "user" else target
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actions.append(f"{label} updated")
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elif "removed" in message.lower() or "replaced" in message.lower():
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label = "Memory" if target == "memory" else "User profile" if target == "user" else target
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actions.append(f"{label} updated")
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return actions
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def build_memory_write_metadata(
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agent: Any,
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*,
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write_origin: Optional[str] = None,
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execution_context: Optional[str] = None,
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task_id: Optional[str] = None,
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tool_call_id: Optional[str] = None,
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) -> Dict[str, Any]:
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"""Build provenance metadata for external memory-provider mirrors."""
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metadata: Dict[str, Any] = {
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"write_origin": write_origin or getattr(agent, "_memory_write_origin", "assistant_tool"),
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"execution_context": (
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execution_context
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or getattr(agent, "_memory_write_context", "foreground")
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),
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"session_id": agent.session_id or "",
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"parent_session_id": agent._parent_session_id or "",
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"platform": agent.platform or os.environ.get("HERMES_SESSION_SOURCE", "cli"),
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"tool_name": "memory",
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}
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if task_id:
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metadata["task_id"] = task_id
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if tool_call_id:
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metadata["tool_call_id"] = tool_call_id
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return {k: v for k, v in metadata.items() if v not in {None, ""}}
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||||
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def _run_review_in_thread(
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agent: Any,
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messages_snapshot: List[Dict],
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prompt: str,
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) -> None:
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"""Worker function executed in the background-review daemon thread.
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||||
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Spawns a forked ``AIAgent`` inheriting the parent's runtime, runs the
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review prompt, and surfaces a compact action summary back to the user
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||||
via ``agent._safe_print`` and ``agent.background_review_callback``.
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"""
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# Local import to avoid a hard circular dep at module load.
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from run_agent import AIAgent
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from tools.terminal_tool import set_approval_callback as _set_approval_callback
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# Install a non-interactive approval callback on this worker
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# thread so any dangerous-command guard the review agent trips
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||||
# resolves to "deny" instead of falling back to input() -- which
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# deadlocks against the parent's prompt_toolkit TUI (#15216).
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# Same pattern as _subagent_auto_deny in tools/delegate_tool.py.
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def _bg_review_auto_deny(command, description, **kwargs):
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logger.warning(
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||||
"Background review auto-denied dangerous command: %s (%s)",
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||||
command, description,
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||||
)
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||||
return "deny"
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||||
try:
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||||
_set_approval_callback(_bg_review_auto_deny)
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||||
except Exception:
|
||||
pass
|
||||
|
||||
review_agent = None
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||||
review_messages: List[Dict] = []
|
||||
try:
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with open(os.devnull, "w", encoding="utf-8") as _devnull, \
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contextlib.redirect_stdout(_devnull), \
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||||
contextlib.redirect_stderr(_devnull):
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# Inherit the parent agent's live runtime (provider, model,
|
||||
# base_url, api_key, api_mode) so the fork uses the exact
|
||||
# same credentials the main turn is using. Without this,
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||||
# AIAgent.__init__ re-runs auto-resolution from env vars,
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||||
# which fails for OAuth-only providers, session-scoped
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||||
# creds, or credential-pool setups where the resolver can't
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||||
# reconstruct auth from scratch -- producing the spurious
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||||
# "No LLM provider configured" warning at end of turn.
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||||
_parent_runtime = agent._current_main_runtime()
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||||
_parent_api_mode = _parent_runtime.get("api_mode") or None
|
||||
# The review fork needs to call agent-loop tools (memory,
|
||||
# skill_manage). Those tools require Hermes' own dispatch,
|
||||
# which the codex_app_server runtime bypasses entirely
|
||||
# (it runs the turn inside codex's subprocess). So when
|
||||
# the parent is on codex_app_server, downgrade the review
|
||||
# fork to codex_responses — same auth/credentials, but
|
||||
# talks to the OpenAI Responses API directly so Hermes
|
||||
# owns the loop and the agent-loop tools dispatch.
|
||||
if _parent_api_mode == "codex_app_server":
|
||||
_parent_api_mode = "codex_responses"
|
||||
# skip_memory=True keeps the review fork from
|
||||
# touching external memory plugins (honcho, mem0,
|
||||
# supermemory, etc.). Without it, the fork's
|
||||
# __init__ rebuilds its own _memory_manager from
|
||||
# config, scoped to the parent's session_id, and
|
||||
# run_conversation() then leaks the harness prompt
|
||||
# into the user's real memory namespace via three
|
||||
# ingestion sites: on_turn_start (cadence + turn
|
||||
# message), prefetch_all (recall query), and
|
||||
# sync_all (harness prompt + review output recorded
|
||||
# as a (user, assistant) turn pair). Built-in
|
||||
# MEMORY.md / USER.md state is re-bound from the
|
||||
# parent below so memory(action="add") writes from
|
||||
# the review still land on disk; the review just
|
||||
# has zero side effects on external providers.
|
||||
# Match parent's toolset config so ``tools[]`` is byte-identical
|
||||
# in the request body — Anthropic's cache key includes it.
|
||||
# (The runtime whitelist below still restricts dispatch.)
|
||||
review_agent = AIAgent(
|
||||
model=agent.model,
|
||||
max_iterations=16,
|
||||
quiet_mode=True,
|
||||
platform=agent.platform,
|
||||
provider=agent.provider,
|
||||
api_mode=_parent_api_mode,
|
||||
base_url=_parent_runtime.get("base_url") or None,
|
||||
api_key=_parent_runtime.get("api_key") or None,
|
||||
credential_pool=getattr(agent, "_credential_pool", None),
|
||||
parent_session_id=agent.session_id,
|
||||
enabled_toolsets=getattr(agent, "enabled_toolsets", None),
|
||||
disabled_toolsets=getattr(agent, "disabled_toolsets", None),
|
||||
skip_memory=True,
|
||||
)
|
||||
review_agent._memory_write_origin = "background_review"
|
||||
review_agent._memory_write_context = "background_review"
|
||||
review_agent._memory_store = agent._memory_store
|
||||
review_agent._memory_enabled = agent._memory_enabled
|
||||
review_agent._user_profile_enabled = agent._user_profile_enabled
|
||||
review_agent._memory_nudge_interval = 0
|
||||
review_agent._skill_nudge_interval = 0
|
||||
# Suppress all status/warning emits from the fork so the
|
||||
# user only sees the final successful-action summary.
|
||||
# Without this, mid-review "Iteration budget exhausted",
|
||||
# rate-limit retries, compression warnings, and other
|
||||
# lifecycle messages bubble up through _emit_status ->
|
||||
# _vprint and leak past the stdout redirect (they go via
|
||||
# _print_fn/status_callback, which bypass sys.stdout).
|
||||
review_agent.suppress_status_output = True
|
||||
# Inherit the parent's cached system prompt verbatim so
|
||||
# the review fork's outbound HTTP request hits the same
|
||||
# Anthropic/OpenRouter prefix cache the parent warmed.
|
||||
# Without this, the fork rebuilds the system prompt from
|
||||
# scratch (fresh _hermes_now() timestamp, fresh
|
||||
# session_id, narrower toolset → different skills_prompt)
|
||||
# and the byte-exact prefix-cache key misses. See
|
||||
# issue #25322 and PR #17276 for the full analysis +
|
||||
# measured impact (~26% end-to-end cost reduction on
|
||||
# Sonnet 4.5).
|
||||
review_agent._cached_system_prompt = agent._cached_system_prompt
|
||||
# Defensive: pin session_start + session_id to the
|
||||
# parent's so any code path that re-renders parts of
|
||||
# the system prompt (compression, plugin hooks) still
|
||||
# produces byte-identical output. The cached-prompt
|
||||
# assignment above already short-circuits the normal
|
||||
# rebuild path, but these pins guarantee parity even
|
||||
# if a future code path bypasses the cache.
|
||||
review_agent.session_start = agent.session_start
|
||||
review_agent.session_id = agent.session_id
|
||||
# Never let the review fork compress. It shares the parent's
|
||||
# session_id, so if it won a compression race it would rotate the
|
||||
# parent into a NEW child that the gateway never adopts (the fork
|
||||
# is single-lifecycle and dies right after this run_conversation).
|
||||
# The foreground turn would then start from the stale parent and
|
||||
# compress it again, leaving the same parent with two sibling
|
||||
# children (issue #38727). Review also needs full context to
|
||||
# produce a good memory/skill summary — compressing would strip
|
||||
# detail. Both compression triggers in conversation_loop.py gate on
|
||||
# agent.compression_enabled, so this short-circuits both paths.
|
||||
review_agent.compression_enabled = False
|
||||
|
||||
from model_tools import get_tool_definitions
|
||||
from hermes_cli.plugins import (
|
||||
set_thread_tool_whitelist,
|
||||
clear_thread_tool_whitelist,
|
||||
)
|
||||
|
||||
review_whitelist = {
|
||||
t["function"]["name"]
|
||||
for t in get_tool_definitions(
|
||||
enabled_toolsets=["memory", "skills"],
|
||||
quiet_mode=True,
|
||||
)
|
||||
}
|
||||
set_thread_tool_whitelist(
|
||||
review_whitelist,
|
||||
deny_msg_fmt=(
|
||||
"Background review denied non-whitelisted tool: "
|
||||
"{tool_name}. Only memory/skill tools are allowed."
|
||||
),
|
||||
)
|
||||
try:
|
||||
review_agent.run_conversation(
|
||||
user_message=(
|
||||
prompt
|
||||
+ "\n\nYou can only call memory and skill "
|
||||
"management tools. Other tools will be denied "
|
||||
"at runtime — do not attempt them."
|
||||
),
|
||||
conversation_history=messages_snapshot,
|
||||
)
|
||||
finally:
|
||||
clear_thread_tool_whitelist()
|
||||
|
||||
# Snapshot review actions before teardown. close() is allowed to
|
||||
# clean per-session state, but the user-visible self-improvement
|
||||
# summary still needs the completed review agent's tool results.
|
||||
review_messages = list(getattr(review_agent, "_session_messages", []))
|
||||
|
||||
# Tear down memory providers while stdout is still
|
||||
# redirected so background thread teardown (Honcho flush,
|
||||
# Hindsight sync, etc.) stays silent. The finally block
|
||||
# below is a safety net for the exception path.
|
||||
try:
|
||||
review_agent.shutdown_memory_provider()
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
review_agent.close()
|
||||
except Exception:
|
||||
pass
|
||||
review_agent = None
|
||||
|
||||
# Scan the review agent's messages for successful tool actions
|
||||
# and surface a compact summary to the user. Tool messages
|
||||
# already present in messages_snapshot must be skipped, since
|
||||
# the review agent inherits that history and would otherwise
|
||||
# re-surface stale "created"/"updated" messages from the prior
|
||||
# conversation as if they just happened (issue #14944).
|
||||
actions = summarize_background_review_actions(
|
||||
review_messages,
|
||||
messages_snapshot,
|
||||
)
|
||||
|
||||
if actions:
|
||||
summary = " · ".join(dict.fromkeys(actions))
|
||||
agent._safe_print(
|
||||
f" 💾 Self-improvement review: {summary}"
|
||||
)
|
||||
_bg_cb = agent.background_review_callback
|
||||
if _bg_cb:
|
||||
try:
|
||||
_bg_cb(
|
||||
f"💾 Self-improvement review: {summary}"
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
except Exception as e:
|
||||
logger.warning("Background memory/skill review failed: %s", e)
|
||||
agent._emit_auxiliary_failure("background review", e)
|
||||
finally:
|
||||
# Safety-net cleanup for the exception path. Normal
|
||||
# completion already shut down inside redirect_stdout above.
|
||||
# Re-open devnull here so any teardown output (Honcho flush,
|
||||
# Hindsight sync, background thread joins) stays silent even
|
||||
# on the exception path where redirect_stdout already exited.
|
||||
if review_agent is not None:
|
||||
try:
|
||||
with open(os.devnull, "w", encoding="utf-8") as _fn, \
|
||||
contextlib.redirect_stdout(_fn), \
|
||||
contextlib.redirect_stderr(_fn):
|
||||
try:
|
||||
review_agent.shutdown_memory_provider()
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
review_agent.close()
|
||||
except Exception:
|
||||
pass
|
||||
except Exception:
|
||||
pass
|
||||
# Clear the approval callback on this bg-review thread so a
|
||||
# recycled thread-id doesn't inherit a stale reference.
|
||||
try:
|
||||
_set_approval_callback(None)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def spawn_background_review_thread(
|
||||
agent: Any,
|
||||
messages_snapshot: List[Dict],
|
||||
review_memory: bool = False,
|
||||
review_skills: bool = False,
|
||||
):
|
||||
"""Build the review thread target and prompt for a background review.
|
||||
|
||||
Returns a ``(target, prompt)`` tuple. The caller (``AIAgent._spawn_background_review``)
|
||||
owns the actual ``threading.Thread`` construction so test-level patches
|
||||
of ``run_agent.threading.Thread`` keep working.
|
||||
"""
|
||||
# Pick the right prompt based on which triggers fired. Allow per-agent
|
||||
# override (the prompts moved to module-level constants but old code paths
|
||||
# that set agent._MEMORY_REVIEW_PROMPT etc. directly keep working).
|
||||
if review_memory and review_skills:
|
||||
prompt = getattr(agent, "_COMBINED_REVIEW_PROMPT", _COMBINED_REVIEW_PROMPT)
|
||||
elif review_memory:
|
||||
prompt = getattr(agent, "_MEMORY_REVIEW_PROMPT", _MEMORY_REVIEW_PROMPT)
|
||||
else:
|
||||
prompt = getattr(agent, "_SKILL_REVIEW_PROMPT", _SKILL_REVIEW_PROMPT)
|
||||
|
||||
def _target() -> None:
|
||||
_run_review_in_thread(agent, messages_snapshot, prompt)
|
||||
|
||||
return _target, prompt
|
||||
|
||||
|
||||
__all__ = [
|
||||
"_MEMORY_REVIEW_PROMPT",
|
||||
"_SKILL_REVIEW_PROMPT",
|
||||
"_COMBINED_REVIEW_PROMPT",
|
||||
"spawn_background_review_thread",
|
||||
"summarize_background_review_actions",
|
||||
"build_memory_write_metadata",
|
||||
]
|
||||
Reference in New Issue
Block a user