* Fix#3409: Add fallback to session_search to prevent false negatives on summarization failure
Fixes#3409. When the auxiliary summarizer fails or returns None, the tool now returns a raw fallback preview of the matched session instead of silently dropping it and returning an empty list
* fix: clean up fallback logic — separate exception handling from preview
Restructure the loop: handle exceptions first (log + nullify), build
entry dict once, then branch on result truthiness. Removes duplicated
field assignments and makes the control flow linear.
---------
Co-authored-by: devorun <130918800+devorun@users.noreply.github.com>
Salvage of #3389 by @binhnt92 with reasoning fallback and retry logic added on top.
All 7 auxiliary LLM call sites now use extract_content_or_reasoning() which mirrors the main agent loop's behavior: extract content, strip think blocks, fall back to structured reasoning fields, retry on empty.
Closes#3389.
When third-party tools (Paperclip orchestrator, etc.) spawn hermes chat
as a subprocess, their sessions pollute user session history and search.
- hermes chat --source <tag> (also HERMES_SESSION_SOURCE env var)
- exclude_sources parameter on list_sessions_rich() and search_messages()
- Sessions with source=tool hidden from sessions list/browse/search
- Third-party adapters pass --source tool to isolate agent sessions
Cherry-picked from PR #3208 by HenkDz.
Co-authored-by: Henkey <noonou7@gmail.com>
In gateway mode, async tools (vision_analyze, web_extract, session_search)
deadlock because _run_async() spawns a thread with asyncio.run(), creating
a new event loop, but _get_cached_client() returns an AsyncOpenAI client
bound to a different loop. httpx.AsyncClient cannot work across event loop
boundaries, causing await client.chat.completions.create() to hang forever.
Fix: include the event loop identity in the async client cache key so each
loop gets its own AsyncOpenAI instance. Also fix session_search_tool.py
which had its own broken asyncio.run()-in-thread pattern — now uses the
centralized _run_async() bridge.
When session_search is called without a query (or with an empty query),
it now returns metadata for the most recent sessions instead of erroring.
This lets the agent quickly see what was worked on recently without
needing specific keywords.
Returns for each session: session_id, title, source, started_at,
last_active, message_count, preview (first user message).
Zero LLM cost — pure DB query. Current session lineage and child
delegation sessions are excluded.
The agent can then keyword-search specific sessions if it needs
deeper context from any of them.
Cherry-picked from PR #2201 by @Gutslabs.
session_search resolved hits to parent/root sessions but only excluded
the exact current_session_id. If the active session was a child
continuation (compression/delegation), its parent could still appear
as a 'past' conversation result.
Fix: resolve current_session_id to its lineage root before filtering,
so the entire active lineage (parent and children) is excluded.
- Add 'emoji' field to ToolEntry and 'get_emoji()' to ToolRegistry
- Add emoji= to all 50+ registry.register() calls across tool files
- Add get_tool_emoji() helper in agent/display.py with 3-tier resolution:
skin override → registry default → hardcoded fallback
- Replace hardcoded emoji maps in run_agent.py, delegate_tool.py, and
gateway/run.py with centralized get_tool_emoji() calls
- Add 'tool_emojis' field to SkinConfig so skins can override per-tool
emojis (e.g. ares skin could use swords instead of wrenches)
- Add 11 tests (5 registry emoji, 6 display/skin integration)
- Update AGENTS.md skin docs table
Based on the approach from PR #1061 by ForgingAlex (emoji centralization
in registry). This salvage fixes several issues from the original:
- Does NOT split the cronjob tool (which would crash on missing schemas)
- Does NOT change image_generate toolset/requires_env/is_async
- Does NOT delete existing tests
- Completes the centralization (gateway/run.py was missed)
- Hooks into the skin system for full customizability
Remove diary-style memory framing from the system prompt and memory tool
schema, explicitly steer task/session logs to session_search, and clarify
that session_search is for cross-session recall after checking the current
conversation first. Add regression tests for the updated guidance text.
Add centralized call_llm() and async_call_llm() functions that own the
full LLM request lifecycle:
1. Resolve provider + model from task config or explicit args
2. Get or create a cached client for that provider
3. Format request args (max_tokens handling, provider extra_body)
4. Make the API call with max_tokens/max_completion_tokens retry
5. Return the response
Config: expanded auxiliary section with provider:model slots for all
tasks (compression, vision, web_extract, session_search, skills_hub,
mcp, flush_memories). Config version bumped to 7.
Migrated all auxiliary consumers:
- context_compressor.py: uses call_llm(task='compression')
- vision_tools.py: uses async_call_llm(task='vision')
- web_tools.py: uses async_call_llm(task='web_extract')
- session_search_tool.py: uses async_call_llm(task='session_search')
- browser_tool.py: uses call_llm(task='vision'/'web_extract')
- mcp_tool.py: uses call_llm(task='mcp')
- skills_guard.py: uses call_llm(provider='openrouter')
- run_agent.py flush_memories: uses call_llm(task='flush_memories')
Tests updated for context_compressor and MCP tool. Some test mocks
still need updating (15 remaining failures from mock pattern changes,
2 pre-existing).
Authored by aydnOktay. Adds TimeoutError handling for session summarization,
better exception specificity in _format_timestamp, defensive try/except in
_resolve_to_parent, and type hints.
session_search was returning the current session if it matched the
query, which is redundant — the agent already has the current
conversation context. This wasted an LLM summarization call and a
result slot.
Added current_session_id parameter to session_search(). The agent
passes self.session_id and the search filters out any results where
either the raw or parent-resolved session ID matches. Both the raw
match and the parent-resolved match are checked to handle child
sessions from delegation.
Two tests added verifying the exclusion works and that other
sessions are still returned.
- Enhanced Codex model discovery by fetching available models from the API, with fallback to local cache and defaults.
- Updated the context compressor's summary target tokens to 2500 for improved performance.
- Added external credential detection for Codex CLI to streamline authentication.
- Refactored various components to ensure consistent handling of authentication and model selection across the application.
- Added _max_tokens_param method in AIAgent to return appropriate max tokens parameter based on the provider (OpenAI vs. others).
- Updated API calls in AIAgent to utilize the new max tokens handling.
- Introduced auxiliary_max_tokens_param function in auxiliary_client for consistent max tokens management across auxiliary clients.
- Refactored multiple tools to use auxiliary_max_tokens_param for improved compatibility with different models and providers.
- Added functionality to include product attribution tags for Nous Portal in auxiliary API calls.
- Introduced a mechanism to determine if the auxiliary client is backed by Nous Portal, affecting the extra body of requests.
- Updated various tools to utilize the new extra body configuration for enhanced tracking in API calls.
- Added a new function to resolve child sessions to their parent, improving session grouping and deduplication.
- Refactored session summarization to run in parallel, enhancing performance and responsiveness.
- Updated search syntax documentation to clarify usage of keywords and phrases for better search results.
- Introduced a new `_format_timestamp` function to convert Unix timestamps and ISO strings into a human-readable date format.
- Updated the session metadata handling to use the new formatting function for improved clarity in session start dates.
- Adjusted the output structure to reflect the change from "Session started" to "Session date" for better user understanding.
- Introduced MEMORY_GUIDANCE and SESSION_SEARCH_GUIDANCE to improve agent's contextual awareness and proactive assistance.
- Updated AIAgent to conditionally include tool-aware guidance in prompts based on available tools.
- Enhanced descriptions in memory and session search schemas for clearer user instructions on when to utilize these features.
- Introduced a new DebugSession class in tools/debug_helpers.py to centralize debug logging functionality, replacing duplicated code across various tool modules.
- Updated image_generation_tool.py, mixture_of_agents_tool.py, vision_tools.py, web_tools.py, and others to utilize the new DebugSession for logging tool calls and saving debug logs.
- Enhanced maintainability and consistency in debug logging practices across the codebase.
Two-part implementation:
Part A - Curated Bounded Memory:
- New memory tool (tools/memory_tool.py) with MEMORY.md + USER.md stores
- Character-limited (2200/1375 chars), § delimited entries
- Frozen snapshot injected into system prompt at session start
- Model manages pruning via replace/remove with substring matching
- Usage indicator shown in system prompt header
Part B - SQLite Session Store:
- New hermes_state.py with SessionDB class, FTS5 full-text search
- Gateway session.py rewritten to dual-write SQLite + legacy JSONL
- Compression-triggered session splitting with parent_session_id chains
- New session_search tool with Gemini Flash summarization of matched sessions
- CLI session lifecycle (create on launch, close on exit)
Also:
- System prompt now cached per session, only rebuilt on compression
(fixes prefix cache invalidation from date/time changes every turn)
- Config version bumped to 3, hermes doctor checks for new artifacts
- Disabled in batch_runner and RL environments