No model, base_url, or provider is assumed when the user hasn't
configured one. Previously the defaults dict in cli.py, AIAgent
constructor args, and several fallback paths all hardcoded
anthropic/claude-opus-4.6 + openrouter.ai/api/v1 — silently routing
unconfigured users to OpenRouter, which 404s for anyone using a
different provider.
Now empty defaults force the setup wizard to run, and existing users
who already completed setup are unaffected (their config.yaml has
the model they chose).
Files changed:
- cli.py: defaults dict, _DEFAULT_CONFIG_MODEL
- run_agent.py: AIAgent.__init__ defaults, main() defaults
- hermes_cli/config.py: DEFAULT_CONFIG
- hermes_cli/runtime_provider.py: is_fallback sentinel
- acp_adapter/session.py: default_model
- tests: updated to reflect empty defaults
OpenAI's newer models (GPT-5, Codex) give stronger instruction-following
weight to the 'developer' role vs 'system'. Swap the role at the API
boundary in _build_api_kwargs() for the chat_completions path so internal
message representation stays consistent ('system' everywhere).
Applies regardless of provider — OpenRouter, Nous portal, direct, etc.
The codex_responses path (direct OpenAI) uses 'instructions' instead of
message roles, so it's unaffected.
DEVELOPER_ROLE_MODELS constant in prompt_builder.py defines the matching
model name substrings: ('gpt-5', 'codex').
* fix: force-close TCP sockets on client cleanup, detect and recover dead connections
When a provider drops connections mid-stream (e.g. OpenRouter outage),
httpx's graceful close leaves sockets in CLOSE-WAIT indefinitely. These
zombie connections accumulate and can prevent recovery without restarting.
Changes:
- _force_close_tcp_sockets: walks the httpx connection pool and issues
socket.shutdown(SHUT_RDWR) + close() to force TCP RST on every socket
when a client is closed, preventing CLOSE-WAIT accumulation
- _cleanup_dead_connections: probes the primary client's pool for dead
sockets (recv MSG_PEEK), rebuilds the client if any are found
- Pre-turn health check at the start of each run_conversation call that
auto-recovers with a user-facing status message
- Primary client rebuild after stale stream detection to purge pool
- User-facing messages on streaming connection failures:
"Connection to provider dropped — Reconnecting (attempt 2/3)"
"Connection failed after 3 attempts — try again in a moment"
Made-with: Cursor
* fix: pool entry missing base_url for openrouter, clean error messages
- _resolve_runtime_from_pool_entry: add OPENROUTER_BASE_URL fallback
when pool entry has no runtime_base_url (pool entries from auth.json
credential_pool often omit base_url)
- Replace Rich console.print for auth errors with plain print() to
prevent ANSI escape code mangling through prompt_toolkit's stdout patch
- Force-close TCP sockets on client cleanup to prevent CLOSE-WAIT
accumulation after provider outages
- Pre-turn dead connection detection with auto-recovery and user message
- Primary client rebuild after stale stream detection
- User-facing status messages on streaming connection failures/retries
Made-with: Cursor
* fix(gateway): persist memory flush state to prevent redundant re-flushes on restart
The _session_expiry_watcher tracked flushed sessions in an in-memory set
(_pre_flushed_sessions) that was lost on gateway restart. Expired sessions
remained in sessions.json and were re-discovered every restart, causing
redundant AIAgent runs that burned API credits and blocked the event loop.
Fix: Add a memory_flushed boolean field to SessionEntry, persisted in
sessions.json. The watcher sets it after a successful flush. On restart,
the flag survives and the watcher skips already-flushed sessions.
- Add memory_flushed field to SessionEntry with to_dict/from_dict support
- Old sessions.json entries without the field default to False (backward compat)
- Remove the ephemeral _pre_flushed_sessions set from SessionStore
- Update tests: save/load roundtrip, legacy entry compat, auto-reset behavior
Show inline diffs in the CLI transcript when write_file, patch, or
skill_manage modifies files. Captures a filesystem snapshot before the
tool runs, computes a unified diff after, and renders it with ANSI
coloring in the activity feed.
Adds tool_start_callback and tool_complete_callback hooks to AIAgent
for pre/post tool execution notifications.
Also fixes _extract_parallel_scope_path to normalize relative paths
to absolute, preventing the parallel overlap detection from missing
conflicts when the same file is referenced with different path styles.
Gated by display.inline_diffs config option (default: true).
Based on PR #3774 by @kshitijk4poor.
The openai SDK's SyncAPIClient.is_closed is a method, not a property.
getattr(client, 'is_closed', False) returned the bound method object,
which is always truthy — causing _is_openai_client_closed() to report
all clients as closed and triggering unnecessary client recreation
(~100-200ms TCP+TLS overhead per API call).
Fix: check if is_closed is callable and call it, otherwise treat as bool.
Fixes#4377
Co-authored-by: Bartok9 <Bartok9@users.noreply.github.com>
Three bugs prevented credential pool rotation from working when multiple
Codex OAuth tokens were configured:
1. credential_pool was dropped during smart model turn routing.
resolve_turn_route() constructed runtime dicts without it, so the
AIAgent was created without pool access. Fixed in smart_model_routing.py
(no-route and fallback paths), cli.py, and gateway/run.py.
2. Eager fallback fired before pool rotation on 429. The rate-limit
handler at line ~7180 switched to a fallback provider immediately,
before _recover_with_credential_pool got a chance to rotate to the
next credential. Now deferred when the pool still has credentials.
3. (Non-issue) Retry budget was reported as too small, but successful
pool rotations already skip retry_count increment — no change needed.
Reported by community member Schinsly who identified all three root
causes and verified the fix locally with multiple Codex accounts.
* feat(file_tools): harden read_file with size guard, dedup, and device blocking
Three improvements to read_file_tool to reduce wasted context tokens and
prevent process hangs:
1. Character-count guard: reads that produce more than 100K characters
(≈25-35K tokens across tokenisers) are rejected with an error that
tells the model to use offset+limit for a smaller range. The
effective cap is min(file_size, 100K) so small files that happen to
have long lines aren't over-penalised. Large truncated files also
get a hint nudging toward targeted reads.
2. File-read deduplication: when the same (path, offset, limit) is read
a second time and the file hasn't been modified (mtime unchanged),
return a lightweight stub instead of re-sending the full content.
Writes and patches naturally change mtime, so post-edit reads always
return fresh content. The dedup cache is cleared on context
compression — after compression the original read content is
summarised away, so the model needs the full content again.
3. Device path blocking: paths like /dev/zero, /dev/random, /dev/stdin
etc. are rejected before any I/O to prevent process hangs from
infinite-output or blocking-input devices.
Tests: 17 new tests covering all three features plus the dedup-reset-
on-compression integration. All 52 file-read tests pass (35 existing +
17 new). Full tool suite (2124 tests) passes with 0 failures.
* feat: make file_read_max_chars configurable, add docs
Add file_read_max_chars to DEFAULT_CONFIG (default 100K). read_file_tool
reads this on first call and caches for the process lifetime. Users on
large-context models can raise it; users on small local models can lower it.
Also adds a 'File Read Safety' section to the configuration docs
explaining the char limit, dedup behavior, and example values.
When an OAuth token refresh fails on a 401 error, the pool recovery
would return 'not recovered' without trying the next credential in the
pool. This meant users who added a second valid credential via
'hermes auth add' would never see it used when the primary credential
was dead.
Now: try refresh first (handles expired tokens quickly), and if that
fails, rotate to the next available credential — same as 429/402
already did.
Adds three tests covering 401 refresh success, refresh-fail-then-rotate,
and refresh-fail-with-no-remaining-credentials.
Some models (e.g. Kimi K2.5 on Alibaba OpenAI-compatible endpoint)
emit reasoning text followed by a closing </think> without a matching
opening <think> tag. The existing paired-tag regexes in
_strip_think_blocks() cannot match these orphaned tags, so </think>
leaks into user-facing responses on all platforms.
Add a catch-all regex that strips any remaining opening or closing
think/thinking/reasoning/REASONING_SCRATCHPAD tags after the existing
paired-block removal pass.
Closes#4285
* feat(auth): add same-provider credential pools and rotation UX
Add same-provider credential pooling so Hermes can rotate across
multiple credentials for a single provider, recover from exhausted
credentials without jumping providers immediately, and configure
that behavior directly in hermes setup.
- agent/credential_pool.py: persisted per-provider credential pools
- hermes auth add/list/remove/reset CLI commands
- 429/402/401 recovery with pool rotation in run_agent.py
- Setup wizard integration for pool strategy configuration
- Auto-seeding from env vars and existing OAuth state
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
Salvaged from PR #2647
* fix(tests): prevent pool auto-seeding from host env in credential pool tests
Tests for non-pool Anthropic paths and auth remove were failing when
host env vars (ANTHROPIC_API_KEY) or file-backed OAuth credentials
were present. The pool auto-seeding picked these up, causing unexpected
pool entries in tests.
- Mock _select_pool_entry in auxiliary_client OAuth flag tests
- Clear Anthropic env vars and mock _seed_from_singletons in auth remove test
* feat(auth): add thread safety, least_used strategy, and request counting
- Add threading.Lock to CredentialPool for gateway thread safety
(concurrent requests from multiple gateway sessions could race on
pool state mutations without this)
- Add 'least_used' rotation strategy that selects the credential
with the lowest request_count, distributing load more evenly
- Add request_count field to PooledCredential for usage tracking
- Add mark_used() method to increment per-credential request counts
- Wrap select(), mark_exhausted_and_rotate(), and try_refresh_current()
with lock acquisition
- Add tests: least_used selection, mark_used counting, concurrent
thread safety (4 threads × 20 selects with no corruption)
* feat(auth): add interactive mode for bare 'hermes auth' command
When 'hermes auth' is called without a subcommand, it now launches an
interactive wizard that:
1. Shows full credential pool status across all providers
2. Offers a menu: add, remove, reset cooldowns, set strategy
3. For OAuth-capable providers (anthropic, nous, openai-codex), the
add flow explicitly asks 'API key or OAuth login?' — making it
clear that both auth types are supported for the same provider
4. Strategy picker shows all 4 options (fill_first, round_robin,
least_used, random) with the current selection marked
5. Remove flow shows entries with indices for easy selection
The subcommand paths (hermes auth add/list/remove/reset) still work
exactly as before for scripted/non-interactive use.
* fix(tests): update runtime_provider tests for config.yaml source of truth (#4165)
Tests were using OPENAI_BASE_URL env var which is no longer consulted
after #4165. Updated to use model config (provider, base_url, api_key)
which is the new single source of truth for custom endpoint URLs.
* feat(auth): support custom endpoint credential pools keyed by provider name
Custom OpenAI-compatible endpoints all share provider='custom', making
the provider-keyed pool useless. Now pools for custom endpoints are
keyed by 'custom:<normalized_name>' where the name comes from the
custom_providers config list (auto-generated from URL hostname).
- Pool key format: 'custom:together.ai', 'custom:local-(localhost:8080)'
- load_pool('custom:name') seeds from custom_providers api_key AND
model.api_key when base_url matches
- hermes auth add/list now shows custom endpoints alongside registry
providers
- _resolve_openrouter_runtime and _resolve_named_custom_runtime check
pool before falling back to single config key
- 6 new tests covering custom pool keying, seeding, and listing
* docs: add Excalidraw diagram of full credential pool flow
Comprehensive architecture diagram showing:
- Credential sources (env vars, auth.json OAuth, config.yaml, CLI)
- Pool storage and auto-seeding
- Runtime resolution paths (registry, custom, OpenRouter)
- Error recovery (429 retry-then-rotate, 402 immediate, 401 refresh)
- CLI management commands and strategy configuration
Open at: https://excalidraw.com/#json=2Ycqhqpi6f12E_3ITyiwh,c7u9jSt5BwrmiVzHGbm87g
* fix(tests): update setup wizard pool tests for unified select_provider_and_model flow
The setup wizard now delegates to select_provider_and_model() instead
of using its own prompt_choice-based provider picker. Tests needed:
- Mock select_provider_and_model as no-op (provider pre-written to config)
- Call _stub_tts BEFORE custom prompt_choice mock (it overwrites it)
- Pre-write model.provider to config so the pool step is reached
* docs: add comprehensive credential pool documentation
- New page: website/docs/user-guide/features/credential-pools.md
Full guide covering quick start, CLI commands, rotation strategies,
error recovery, custom endpoint pools, auto-discovery, thread safety,
architecture, and storage format.
- Updated fallback-providers.md to reference credential pools as the
first layer of resilience (same-provider rotation before cross-provider)
- Added hermes auth to CLI commands reference with usage examples
- Added credential_pool_strategies to configuration guide
* chore: remove excalidraw diagram from repo (external link only)
* refactor: simplify credential pool code — extract helpers, collapse extras, dedup patterns
- _load_config_safe(): replace 4 identical try/except/import blocks
- _iter_custom_providers(): shared generator for custom provider iteration
- PooledCredential.extra dict: collapse 11 round-trip-only fields
(token_type, scope, client_id, portal_base_url, obtained_at,
expires_in, agent_key_id, agent_key_expires_in, agent_key_reused,
agent_key_obtained_at, tls) into a single extra dict with
__getattr__ for backward-compatible access
- _available_entries(): shared exhaustion-check between select and peek
- Dedup anthropic OAuth seeding (hermes_pkce + claude_code identical)
- SimpleNamespace replaces class _Args boilerplate in auth_commands
- _try_resolve_from_custom_pool(): shared pool-check in runtime_provider
Net -17 lines. All 383 targeted tests pass.
---------
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
Adds /btw <question> — ask a quick follow-up using the current
session context without interrupting the main conversation.
- Snapshots conversation history, answers with a no-tools agent
- Response is not persisted to session history or DB
- Runs in a background thread (CLI) / async task (gateway)
- Per-session guard prevents concurrent /btw in gateway
Implementation:
- model_tools.py: enabled_toolsets=[] now correctly means "no tools"
(was falsy, fell through to default "all tools")
- run_agent.py: persist_session=False gates _persist_session()
- cli.py: _handle_btw_command (background thread, Rich panel output)
- gateway/run.py: _handle_btw_command + _run_btw_task (async task)
- hermes_cli/commands.py: CommandDef for "btw"
Inspired by PR #3504 by areu01or00, reimplemented cleanly on current
main with the enabled_toolsets=[] fix and without the __btw_no_tools__
hack.
When context compression fails, users now see hints suggesting /new
or /compress instead of a dead-end error. Covers all 4 error paths:
payload-too-large, max compression attempts (2 paths), and context
length exceeded.
Closes#4061
Salvaged from PR #4076 by SHL0MS.
Co-authored-by: SHL0MS <SHL0MS@users.noreply.github.com>
When context compression fires during run_conversation() in the gateway,
the compressed messages were silently lost on the next turn. Two bugs:
1. Agent-side: _flush_messages_to_session_db() calculated
flush_from = max(len(conversation_history), _last_flushed_db_idx).
After compression, _last_flushed_db_idx was correctly reset to 0,
but conversation_history still had its original pre-compression
length (e.g. 200). Since compressed messages are shorter (~30),
messages[200:] was empty — nothing written to the new session's
SQLite.
Fix: Set conversation_history = None after each _compress_context()
call so start_idx = 0 and all compressed messages are flushed.
2. Gateway-side: history_offset was always len(agent_history) — the
original pre-compression length. After compression shortened the
message list, agent_messages[200:] was empty, causing the gateway
to fall back to writing only a user/assistant pair, losing the
compressed summary and tail context.
Fix: Detect session splits (agent.session_id != original) and set
history_offset = 0 so all compressed messages are written to JSONL.
* feat: add /yolo slash command to toggle dangerous command approvals
Adds a /yolo command that toggles HERMES_YOLO_MODE at runtime, skipping
all dangerous command approval prompts for the current session. Works in
both CLI and gateway (Telegram, Discord, etc.).
- /yolo -> ON: all commands auto-approved, no confirmation prompts
- /yolo -> OFF: normal approval flow restored
The --yolo CLI flag already existed for launch-time opt-in. This adds
the ability to toggle mid-session without restarting.
Session-scoped — resets when the process ends. Uses the existing
HERMES_YOLO_MODE env var that check_all_command_guards() already
respects.
* fix: prevent context pressure warning spam (agent loop + gateway rate-limit)
Two complementary fixes for repeated context pressure warnings spamming
gateway users (Telegram, Discord, etc.):
1. Agent-level loop fix (run_agent.py):
After compression, only reset _context_pressure_warned if the
post-compression estimate is actually below the 85% warning level.
Previously the flag was unconditionally reset, causing the warning
to re-fire every loop iteration when compression couldn't reduce
below 85% of the threshold (e.g. very low threshold like 15%,
or system prompt alone exceeds the warning level).
2. Gateway-level rate-limit (gateway/run.py, salvaged from PR #3786):
Per-chat_id cooldown of 1 hour on compression warning messages.
Both warning paths ('still large after compression' and 'compression
failed') are gated. Defense-in-depth — even if the agent-level fix
has edge cases, users won't see more than one warning per hour.
Co-authored-by: dlkakbs <dlkakbs@users.noreply.github.com>
---------
Co-authored-by: dlkakbs <dlkakbs@users.noreply.github.com>
When the API doesn't provide a call_id for tool calls, the fallback
generated a random uuid4 hex. This made every API call's input unique
when replayed, preventing OpenAI's prompt cache from matching the
prefix across turns.
Replaced all four uuid4 fallback sites with a deterministic hash of
(function_name, arguments, position_index). The same tool call now
always produces the same fallback call_id, preserving cache-friendly
input stability.
Affected code paths:
- _chat_messages_to_responses_input() — Codex input reconstruction
- _normalize_codex_response() — function_call and custom_tool_call
- _build_assistant_message() — assistant message construction
When stdout is closed (piped to a dead process, broken terminal),
Python raises ValueError('I/O operation on closed file'), not OSError.
_safe_print and the API error printer only caught OSError, letting the
ValueError propagate and crash the agent.
Salvaged from PR #3760 by @apexscaleai. Fixes#3534.
Co-authored-by: apexscaleai <apexscaleai@users.noreply.github.com>
Tool call previews (paths, commands, queries) were hardcoded to truncate
at 35-40 chars across CLI spinners, completion lines, and gateway progress
messages. Users could not see full file paths in tool output.
New config option: display.tool_preview_length (default 0 = no limit).
Set a positive number to truncate at that length.
Changes:
- display.py: module-level _tool_preview_max_len with getter/setter;
build_tool_preview() and get_cute_tool_message() _trunc/_path respect it
- cli.py: reads config at startup, spinner widget respects config
- gateway/run.py: reads config per-message, progress callback respects config
- run_agent.py: removed redundant 30-char quiet-mode spinner truncation
- config.py: added display.tool_preview_length to DEFAULT_CONFIG
Reported by kriskaminski
When compression creates a child session with a new session_id,
session_log_file was still pointing to the old session's JSON file.
This caused _save_session_log() to write new data to the wrong file.
Closes#3731.
Co-authored-by: kelsia14 <kelsia14@users.noreply.github.com>
Some providers (Fireworks AI) reject tools=null, and others (Anthropic)
reject tools=[]. The safest approach is to not include the key at all
when there are no tools — the OpenAI SDK treats a missing parameter as
NOT_GIVEN and omits it from the request entirely.
Inspired by PR #3736 (@kelsia14).
Extends the single fallback_model mechanism into an ordered chain.
When the primary model fails, Hermes tries each fallback provider in
sequence until one succeeds or the chain is exhausted.
Config format (new):
fallback_providers:
- provider: openrouter
model: anthropic/claude-sonnet-4
- provider: openai
model: gpt-4o
Legacy single-dict fallback_model format still works unchanged.
Key fix vs original PR: the call sites in the retry loop now use
_fallback_index < len(_fallback_chain) instead of the old one-shot
_fallback_activated guard, so the chain actually advances through
all configured providers.
Changes:
- run_agent.py: _fallback_chain list + _fallback_index replaces
one-shot _fallback_model; _try_activate_fallback() advances
through chain; failed provider resolution skips to next entry;
call sites updated to allow chain advancement
- cli.py: reads fallback_providers with legacy fallback_model compat
- gateway/run.py: same
- hermes_cli/config.py: fallback_providers: [] in DEFAULT_CONFIG
- tests: 12 new chain tests + 6 existing test fixtures updated
Co-authored-by: uzaylisak <uzaylisak@users.noreply.github.com>
When hitting rate limits (429), the agent now:
- Extracts the Retry-After header from the provider response and uses it
as the wait time instead of blind exponential backoff (capped at 120s)
- Shows rate-limit-specific messaging: 'Rate limit reached. Waiting Xs
before retry (attempt N/M)...'
- Shows a distinct exhaustion message: 'Rate limit persisted after N
retries. Please try again later.'
Non-429 errors keep the existing exponential backoff and generic messaging.
Co-authored-by: ygd58 <ygd58@users.noreply.github.com>
When a user runs 'hermes update', the Python process caches old modules
in sys.modules. After git pull updates files on disk, lazy imports of
newly-updated modules fail because they try to import display_hermes_home
from the cached (old) hermes_constants which doesn't have the function.
This specifically broke the gateway auto-restart in cmd_update — importing
hermes_cli/gateway.py triggered the top-level 'from hermes_constants
import display_hermes_home' against the cached old module. The ImportError
was silently caught, so the gateway was never restarted after update.
Users with a running gateway then hit the ImportError on their next
Telegram/Discord message when the stale gateway process lazily loaded
run_agent.py (new version) which also had the top-level import.
Fixes:
- hermes_cli/gateway.py: lazy import at call site (line 940)
- run_agent.py: lazy import at call site (line 6927)
- tools/terminal_tool.py: lazy imports at 3 call sites
- tools/tts_tool.py: static schema string (no module-level call)
- hermes_cli/auth.py: lazy import at call site (line 2024)
- hermes_cli/main.py: reload hermes_constants after git pull in cmd_update
Also fixes 4 pre-existing test failures in test_parse_env_var caused by
NameError on display_hermes_home in terminal_tool.py.
Prep for profiles: user-facing messages now use display_hermes_home() so
diagnostic output shows the correct path for each profile.
New helper: display_hermes_home() in hermes_constants.py
12 files swept, ~30 user-facing string replacements.
Includes dynamic TTS schema description.
Self-hosted Honcho on localhost doesn't require authentication, but
both the activation gates and the SDK client required an API key.
Combined fix from three contributor PRs:
- Relax all 8 activation gates to accept (api_key OR base_url) as
valid credentials (#3482 by @cameronbergh)
- Use 'local' placeholder for the SDK client when base_url points to
localhost/127.0.0.1/::1 (#3570 by @ygd58)
Files changed: run_agent.py (2 gates), cli.py (1 gate),
gateway/run.py (1 gate), honcho_integration/cli.py (2 gates),
hermes_cli/doctor.py (2 gates), honcho_integration/client.py (SDK).
Co-authored-by: cameronbergh <cameronbergh@users.noreply.github.com>
Co-authored-by: ygd58 <ygd58@users.noreply.github.com>
Co-authored-by: devorun <devorun@users.noreply.github.com>
Pasting text from rich-text editors (Google Docs, Word, etc.) can inject
lone surrogate characters (U+D800..U+DFFF) that are invalid UTF-8.
The OpenAI SDK serializes messages with ensure_ascii=False, then encodes
to UTF-8 for the HTTP body — surrogates crash this with:
UnicodeEncodeError: 'utf-8' codec can't encode character '\udce2'
Three-layer fix:
1. Primary: sanitize user_message at the top of run_conversation()
2. CLI: sanitize in chat() before appending to conversation_history
3. Safety net: catch UnicodeEncodeError in the API error handler,
sanitize the entire messages list in-place, and retry once.
Also exclude UnicodeEncodeError from is_local_validation_error
so it doesn't get classified as non-retryable.
Includes 14 new tests covering the sanitization helpers and the
integration with run_conversation().
Ollama reuses index 0 for every tool call in a parallel batch,
distinguishing them only by id. The streaming accumulator now
detects a new non-empty id at an already-active index and redirects
it to a fresh slot, preventing names and arguments from being
concatenated into a single tool call.
No-op for normal providers that use incrementing indices.
Co-authored-by: dmater01 <dmater01@users.noreply.github.com>
* fix(provider): remove MiniMax /v1→/anthropic auto-correction to allow user override
The minimax-specific auto-correction in runtime_provider.py was
preventing users from overriding to the OpenAI-compatible endpoint
via MINIMAX_BASE_URL. Users in certain regions get nginx 404 on
api.minimax.io/anthropic and need to switch to api.minimax.chat/v1.
The generic URL-suffix detection already handles /anthropic →
anthropic_messages, so the minimax-specific code was redundant for
the default path and harmful for the override path.
Now: default /anthropic URL works via generic detection, user
override to /v1 gets chat_completions mode naturally.
Closes#3546 (different approach — respects user overrides instead
of changing the default endpoint).
* fix(display): show reasoning during streaming even when tool calls suppress content
When a model generates content (containing <REASONING_SCRATCHPAD> tags)
alongside tool calls in the same API response, content deltas were
suppressed from streaming once any tool call chunk arrived. This
prevented the CLI's tag extraction from running, so reasoning was
never shown during streaming. The post-response fallback then
displayed reasoning AFTER the already-visible streamed response,
creating a confusing reversed order.
Fix: route suppressed content to stream_delta_callback even when tool
calls are present. The CLI's _stream_delta handles tag extraction —
reasoning tags are routed to the reasoning display box, while
non-reasoning text is handled by the existing stream display logic.
This ensures reasoning appears before tool execution and the final
response, matching the expected visual order.
The TOOL_USE_ENFORCEMENT_GUIDANCE injection (added in #3528) was
hardcoded to only match gpt/codex model names. This makes it a
config option so users can turn it on for any model family.
New config key: agent.tool_use_enforcement
- "auto" (default): matches gpt/codex (existing behavior)
- true: inject for all models
- false: never inject
- list of strings: custom model-name substrings to match
e.g. ["gpt", "codex", "deepseek", "qwen"]
No version bump needed — deep merge provides the default
automatically for existing installs.
12 new tests covering all config modes.
The plugin system defined six lifecycle hooks but only pre_tool_call and
post_tool_call were invoked. This activates the remaining four so that
external plugins (e.g. memory systems) can hook into the conversation
loop without touching core code.
Hook semantics:
- on_session_start: fires once when a new session is created
- pre_llm_call: fires once per turn before the tool-calling loop;
plugins can return {"context": "..."} to inject into the ephemeral
system prompt (not cached, not persisted)
- post_llm_call: fires once per turn after the loop completes, with
user_message and assistant_response for sync/storage
- on_session_end: fires at the end of every run_conversation call
invoke_hook() now returns a list of non-None callback return values,
enabling pre_llm_call context injection while remaining backward
compatible (existing hooks that return None are unaffected).
Salvaged from PR #2823.
Co-authored-by: Nicolò Boschi <boschi1997@gmail.com>
Root cause: Anthropic buffers entire tool call arguments and goes silent
for minutes while thinking (verified: 167s gap with zero SSE events on
direct API). OpenRouter's upstream proxy times out after ~125s of
inactivity and drops the connection with 'Network connection lost'.
Fix: Send the x-anthropic-beta: fine-grained-tool-streaming-2025-05-14
header for Claude models on OpenRouter. This makes Anthropic stream
tool call arguments token-by-token instead of buffering them, keeping
the connection alive through OpenRouter's proxy.
Live-tested: the exact prompt that consistently failed at ~128s now
completes successfully — 2,972 lines written, 49K tokens, 8 minutes.
Additional improvements:
1. Send explicit max_tokens for Claude through OpenRouter. Without it,
OpenRouter defaults to 65,536 (confirmed via echo_upstream_body) —
only half of Opus 4.6's 128K limit.
2. Classify SSE 'Network connection lost' as retryable in the streaming
inner retry loop. The OpenAI SDK raises APIError from SSE error
events, which was bypassing our transient error retry logic.
3. Actionable diagnostic guidance when stream-drop retries exhaust.
Cherry-pick of feat/gpt-tool-steering with modifications:
1. Tool-use enforcement prompt (refactored from GPT-specific):
- Renamed GPT_TOOL_USE_GUIDANCE -> TOOL_USE_ENFORCEMENT_GUIDANCE
- Added TOOL_USE_ENFORCEMENT_MODELS tuple: ('gpt', 'codex')
- Injection logic now checks against the tuple instead of hardcoding
'gpt' — adding new model families is a one-line change
- Addresses models describing actions instead of making tool calls
2. Budget warning history stripping:
- _strip_budget_warnings_from_history() strips _budget_warning JSON
keys and [BUDGET WARNING: ...] text from tool results at the start
of run_conversation()
- Prevents old budget warnings from poisoning subsequent turns
Based on PR #3479 by teknium1.
* fix: cap context pressure percentage at 100% in display
The forward-looking token estimate can overshoot the compaction threshold
(e.g. a large tool result pushes it from 70% to 109% in one step). The
progress bar was already capped via min(), but pct_int was not — causing
the user to see '109% to compaction' which is confusing.
Cap pct_int at 100 in both CLI and gateway display functions.
Reported by @JoshExile82.
* refactor: use real API token counts for compression decisions
Replace the rough chars/3 estimation with actual prompt_tokens +
completion_tokens from the API response. The estimation was needed to
predict whether tool results would push context past the threshold, but
the default 50% threshold leaves ample headroom — if tool results push
past it, the next API call reports real usage and triggers compression
then.
This removes all estimation from the compression and context pressure
paths, making both 100% data-driven from provider-reported token counts.
Also removes the dead _msg_count_before_tools variable.
When finish_reason='length' and the response contains only reasoning
(think blocks or empty content), the model exhausted its output token
budget on thinking with nothing left for the actual response.
Previously, this fell into either:
- chat_completions: 3 useless continuation retries (model hits same limit)
- anthropic/codex: generic 'Response truncated' error with rollback
Now: detect the think-only + length condition early and return immediately
with a targeted error message: 'Model used all output tokens on reasoning
with none left for the response. Try lowering reasoning effort or
increasing max_tokens.'
This saves 2 wasted API calls on the chat_completions path and gives
users actionable guidance instead of a cryptic error.
The existing think-only retry logic (finish_reason='stop') is unchanged —
that's a genuine model glitch where retrying can help.
The Anthropic adapter defaulted to max_tokens=16384 when no explicit value
was configured. This severely limits thinking-enabled models where thinking
tokens count toward max_tokens:
- Claude Opus 4.6 supports 128K output but was capped at 16K
- Claude Sonnet 4.6 supports 64K output but was capped at 16K
With extended thinking (adaptive or budget-based), the model could exhaust
the entire 16K on reasoning, leaving zero tokens for the actual response.
This caused two user-visible errors:
- 'Response truncated (finish_reason=length)' — thinking consumed most tokens
- 'Response only contains think block with no content' — thinking consumed all
Fix: add _ANTHROPIC_OUTPUT_LIMITS lookup table (sourced from Anthropic docs
and Cline's model catalog) and use the model's actual output limit as the
default. Unknown future models default to 128K (the current maximum).
Also adds context_length clamping: if the user configured a smaller context
window (e.g. custom endpoint), max_tokens is clamped to context_length - 1
to avoid exceeding the window.
Closes#2706
Models like GLM-5/5.1 can think for 15+ minutes. The previous 900s
(15 min) default for HERMES_API_TIMEOUT killed legitimate requests.
Raised to 1800s (30 min) in both places that read the env var:
- _build_api_kwargs() timeout (non-streaming total timeout)
- _call_chat_completions() write timeout (streaming connection)
The streaming per-chunk read timeout (60s) and stale stream detector
(180-300s) are unchanged — those are appropriate for inter-chunk timing.
Two independent bugs caused the reasoning box to appear three times when
the model produced reasoning + tool_calls:
Bug A: _build_assistant_message() re-fired reasoning_callback with the full
reasoning text even when streaming had already displayed it. The original
guard only checked structured reasoning_content deltas, but reasoning also
arrives via content tag extraction (<REASONING_SCRATCHPAD>/<think> tags
in delta.content), which went through _fire_stream_delta not
_fire_reasoning_delta. Fix: skip the callback entirely when streaming is
active — both paths display reasoning during the stream. Any reasoning not
shown during streaming is caught by the CLI post-response fallback.
Bug B: The post-response reasoning display checked _reasoning_stream_started,
but that flag was reset by _reset_stream_state() during intermediate turn
boundaries (when stream_delta_callback(None) fires between tool calls).
Introduced _reasoning_shown_this_turn flag that persists across the tool
loop and is only reset at the start of each user turn.
Live-tested in PTY: reasoning now shows exactly once per API call, no
duplicates across tool-calling loops.
The stale stream detector (90s timeout) was killing healthy connections
during the model's thinking phase, producing self-inflicted
RemoteProtocolError ("peer closed connection without sending complete
message body"). Three issues:
1. last_chunk_time was never reset between inner stream retries, so
subsequent attempts inherited the previous attempt's stale budget
2. The non-streaming fallback path didn't reset the timer either
3. 90s base timeout was too aggressive for large-context Opus sessions
where thinking time before first token routinely exceeds 90s
Fix: reset last_chunk_time at the start of each streaming attempt and
before the non-streaming fallback. Increase base timeout to 180s and
scale to 300s for >100K token contexts.
Made-with: Cursor
Three improvements salvaged from PR #3225 by Mibayy:
1. Add /resume slash command handler in CLI process_command(). The
command was registered in the commands registry but had no handler,
so typing /resume produced 'Unknown command'. The handler resolves
by title or session ID, ends the current session cleanly, loads
conversation history from SQLite, re-opens the target session, and
syncs the AIAgent instance. Follows the same pattern as new_session().
2. Add truncation guard in _save_session_log(). When resuming a session
whose messages weren't fully written to SQLite, the agent starts with
partial history and the first save would overwrite the full JSON log
on disk. The guard reads the existing file and skips the write if it
already has more messages than the current batch.
3. Add reopen_session() method to SessionDB. Proper API for clearing
ended_at/end_reason instead of reaching into _conn directly.
Note: Bug 1 from the original PR (INSERT OR IGNORE + _session_db = None)
is already fixed on main — skipped as redundant.
Closes#3123.
When _try_activate_fallback() switches to the fallback model, it
updates the agent's model/provider/client but never touches
self.context_compressor. The compressor keeps the primary model's
context_length and threshold_tokens, so compression decisions use
wrong limits — a 200K primary → 32K fallback still uses 200K-based
thresholds, causing oversized sessions to overflow the fallback.
Update the compressor's model, credentials, context_length, and
threshold_tokens after fallback activation using get_model_context_length()
for the new model.
Cherry-picked from PR #3202 by binhnt92.
Co-authored-by: binhnt92 <binhnt.ht.92@gmail.com>
* fix(gateway): silence flush agent terminal output
quiet_mode=True only suppresses AIAgent init messages.
Tool call output still leaks to the terminal through
_safe_print → _print_fn during session reset/expiry.
Since #2670 injected live memory state into the flush prompt,
the flush agent now reliably calls memory tools — making the
output leak noticeable for the first time.
Set _print_fn to a no-op so the background flush is fully silent.
* test(gateway): add test for flush agent terminal silence + fix dotenv mock
- Add TestFlushAgentSilenced: verifies _print_fn is set to a no-op on
the flush agent so tool output never leaks to the terminal
- Fix pre-existing test failures: replace patch('run_agent.AIAgent')
with sys.modules mock to avoid importing run_agent (requires openai)
- Add autouse _mock_dotenv fixture so all tests in this file run
without the dotenv package installed
* fix(display): route KawaiiSpinner output through print_fn to fully silence flush agent
The previous fix set tmp_agent._print_fn = no-op on the flush agent but
spinner output and quiet-mode cute messages bypassed _print_fn entirely:
- KawaiiSpinner captured sys.stdout at __init__ and wrote directly to it
- quiet-mode tool results used builtin print() instead of _safe_print()
Add optional print_fn parameter to KawaiiSpinner.__init__; _write routes
through it when set. Pass self._print_fn to all spinner construction sites
in run_agent.py and change the quiet-mode cute message print to _safe_print.
The existing gateway fix (tmp_agent._print_fn = lambda) now propagates
correctly through both paths.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(gateway): silence hygiene and compression background agents
Two more background AIAgent instances in the gateway were created with
quiet_mode=True but without _print_fn = no-op, causing tool output to
leak to the terminal:
- _hyg_agent (in-turn hygiene memory agent)
- tmp_agent (_compress_context path)
Apply the same _print_fn no-op pattern used for the flush agent.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* chore(display): remove unused _last_flush_time from KawaiiSpinner
Attribute was set but never read; upstream already removed it.
Leftover from conflict resolution during rebase onto upstream/main.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Dilee <uzmpsk.dilekakbas@gmail.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
The background memory/skill review (_spawn_background_review) runs
after the agent response when turn/iteration counters exceed their
thresholds. It saves memories and skills, then prints a summary like
'💾 Memory updated · User profile updated'. In CLI mode this goes to
the terminal via _safe_print. In gateway mode, _safe_print routes to
print() which goes to stdout — invisible to the user.
Add a background_review_callback attribute to AIAgent. When set, the
background review thread calls it with the summary string after saves
complete. The gateway wires this to adapter.send() via the same
run_coroutine_threadsafe bridge used by status_callback, delivering
the notification to the user's chat.
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>
except Exception does not catch KeyboardInterrupt (inherits from
BaseException). A second Ctrl+C during exit cleanup aborts pending
writes — Honcho observations dropped, SQLite sessions left unclosed,
cron job sessions never marked ended.
Changed to except (Exception, KeyboardInterrupt) at all five sites:
- cli.py: honcho.shutdown() and end_session() in finally exit block
- run_agent.py: _flush_honcho_on_exit atexit handler
- cron/scheduler.py: end_session() and close() in job finally block
Tests exercise the actual production code paths and confirm
KeyboardInterrupt propagates without the fix.
Co-authored-by: dieutx <dangtc94@gmail.com>
* fix(session-db): survive CLI/gateway concurrent write contention
Closes#3139
Three layered fixes for the scenario where CLI and gateway write to
state.db concurrently, causing create_session() to fail with
'database is locked' and permanently disabling session_search on the
gateway side.
1. Increase SQLite connection timeout: 10s -> 30s
hermes_state.py: longer window for the WAL writer to finish a batch
flush before the other process gives up entirely.
2. INSERT OR IGNORE in create_session
hermes_state.py: prevents IntegrityError on duplicate session IDs
(e.g. gateway restarts while CLI session is still alive).
3. Don't null out _session_db on create_session failure (main fix)
run_agent.py: a transient lock at agent startup must not permanently
disable session_search for the lifetime of that agent instance.
_session_db now stays alive so subsequent flushes and searches work
once the lock clears.
4. New ensure_session() helper + call it during flush
hermes_state.py: INSERT OR IGNORE for a minimal session row.
run_agent.py _flush_messages_to_session_db: calls ensure_session()
before appending messages, so the FK constraint is satisfied even
when create_session() failed at startup. No-op when the row exists.
* fix(state): release lock between context queries in search_messages
The context-window queries (one per FTS5 match) were running inside
the same lock acquisition as the primary FTS5 query, holding the lock
for O(N) sequential SQLite round-trips. Move per-match context fetches
outside the outer lock block so each acquires the lock independently,
keeping critical sections short and allowing other threads to interleave.
* fix(session): prefer longer source in load_transcript to prevent legacy truncation
When a long-lived session pre-dates SQLite storage (e.g. sessions
created before the DB layer was introduced, or after a clean
deployment that reset the DB), _flush_messages_to_session_db only
writes the *new* messages from the current turn to SQLite — it skips
messages already present in conversation_history, assuming they are
already persisted.
That assumption fails for legacy JSONL-only sessions:
Turn N (first after DB migration):
load_transcript(id) → SQLite: 0 → falls back to JSONL: 994 ✓
_flush_messages_to_session_db: skip first 994, write 2 new → SQLite: 2
Turn N+1:
load_transcript(id) → SQLite: 2 → returns immediately ✗
Agent sees 2 messages of history instead of 996
The same pattern causes the reported symptom: session JSON truncated
to 4 messages (_save_session_log writes agent.messages which only has
2 history + 2 new = 4).
Fix: always load both sources and return whichever is longer. For a
fully-migrated session SQLite will always be ≥ JSONL, so there is no
regression. For a legacy session that hasn't been bootstrapped yet,
JSONL wins and the full history is restored.
Closes#3212
* test: add load_transcript source preference tests for #3212
Covers: JSONL longer returns JSONL, SQLite longer returns SQLite,
SQLite empty falls back to JSONL, both empty returns empty, equal
length prefers SQLite (richer reasoning fields).
---------
Co-authored-by: Mibayy <mibayy@hermes.ai>
Co-authored-by: kewe63 <kewe.3217@gmail.com>
Co-authored-by: Mibayy <mibayy@users.noreply.github.com>
Two improvements salvaged from PR #2600 (paraddox):
1. Preflight compression now counts tool schema tokens alongside system
prompt and messages. With 50+ tools enabled, schemas can add 20-30K
tokens that were previously invisible to the estimator, delaying
compression until the API rejected the request.
2. Context probe persistence guard: when the agent steps down context
tiers after a context-length error, only provider-confirmed numeric
limits (parsed from the error message) are cached to disk. Guessed
fallback tiers from get_next_probe_tier() stay in-memory only,
preventing wrong values from polluting the persistent cache.
Co-authored-by: paraddox <paraddox@users.noreply.github.com>
_mute_post_response was set True whenever a turn had both content
and tool_calls, suppressing ALL subsequent _vprint output including
tool completion messages. This meant users only saw "preparing
search_files..." but never the result.
Now only mutes output when every tool in the batch is housekeeping
(memory, todo, skill_manage, session_search). Substantive tools
like search_files, read_file, write_file, terminal etc. keep their
completion messages visible.
Also fixes: run_conversation no longer raises on max retries
(returns graceful error dict instead), and cli.py wraps the agent
thread in try/except as a safety net.
Made-with: Cursor
The non-streaming API call path (_interruptible_api_call) had no
wall-clock timeout. When providers keep connections alive with SSE
keep-alive pings but never deliver a response, httpx's inactivity
timeout never fires and the call hangs indefinitely.
Subagents always used the non-streaming path because they have no
stream consumers (quiet_mode=True). This caused delegate_task to
hang for 40+ minutes in production.
The streaming path has two layers of protection:
- httpx read timeout (60s, HERMES_STREAM_READ_TIMEOUT)
- Stale stream detection (90s, HERMES_STREAM_STALE_TIMEOUT)
Both work because streaming sends chunks continuously — a 90-second
gap between chunks genuinely means the connection is broken, even for
reasoning models that take minutes to complete.
Now run_conversation() always prefers the streaming path. The streaming
method falls back to non-streaming automatically if the provider
doesn't support it. Stream delta callbacks are no-ops when no
consumers are registered, so there's no overhead for subagents.
Add _emit_status() helper that sends lifecycle notifications to both
CLI (via _vprint force=True) and gateway (via status_callback). No
retry, fallback, or compression path is silent anymore.
Pathways surfaced:
- General retry backoff: was logger-only, now shows countdown
- Provider fallback: changed raw print() to _emit_status for gateway
- Rate limit eager fallback: new notification before switching
- Empty/malformed response fallback: new notification
- Client error fallback: new notification with HTTP status
- Max retries fallback: new notification before attempting
- Max retries giving up: upgraded from _vprint to _emit_status
- Compression retry (413 + context overflow): upgraded to _emit_status
- Compression success + retry: upgraded to _emit_status (2 instances)
