Support Signal 'Note to Self' messages in single-number setups where
signal-cli is linked as a secondary device on the user's own account.
syncMessage.sentMessage envelopes addressed to the bot's own account
are now promoted to dataMessage for normal processing, while other
sync events (read receipts, typing, etc.) are still filtered.
Echo-back prevention mirrors the WhatsApp bridge pattern:
- Track timestamps of recently sent messages (bounded set of 50)
- When a Note to Self sync arrives, check if its timestamp matches
a recent outbound — skip if so (agent echo-back)
- Only process sync messages that are genuinely user-initiated
Based on PR #2115 by @Stonelinks with added echo-back protection.
* fix: preserve Ollama model:tag colons in context length detection
The colon-split logic in get_model_context_length() and
_query_local_context_length() assumed any colon meant provider:model
format (e.g. "local:my-model"). But Ollama uses model:tag format
(e.g. "qwen3.5:27b"), so the split turned "qwen3.5:27b" into just
"27b" — which matches nothing, causing a fallback to the 2M token
probe tier.
Now only recognised provider prefixes (local, openrouter, anthropic,
etc.) are stripped. Ollama model:tag names pass through intact.
* fix: update claude-opus-4-6 and claude-sonnet-4-6 context length from 200K to 1M
Both models support 1,000,000 token context windows. The hardcoded defaults
were set before Anthropic expanded the context for the 4.6 generation.
Verified via models.dev and OpenRouter API data.
---------
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
Co-authored-by: Test <test@test.com>
The colon-split logic in get_model_context_length() and
_query_local_context_length() assumed any colon meant provider:model
format (e.g. "local:my-model"). But Ollama uses model:tag format
(e.g. "qwen3.5:27b"), so the split turned "qwen3.5:27b" into just
"27b" — which matches nothing, causing a fallback to the 2M token
probe tier.
Now only recognised provider prefixes (local, openrouter, anthropic,
etc.) are stripped. Ollama model:tag names pass through intact.
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
- Add <thinking> tag to streaming filter's tag list
- When show_reasoning is on, route XML reasoning content to the
reasoning display box instead of silently discarding it
- Expand _strip_think_blocks to handle all tag variants:
<think>, <thinking>, <THINKING>, <reasoning>, <REASONING_SCRATCHPAD>
Place a sentinel in _running_agents immediately after the "already
running" guard check passes — before any await. Without this, the
numerous await points between the guard (line 1324) and agent
registration (track_agent at line 4790) create a window where a
second message for the same session can bypass the guard and start
a duplicate agent, corrupting the transcript.
The await gap includes: hook emissions, vision enrichment (external
API call), audio transcription (external API call), session hygiene
compression, and the run_in_executor call itself. For messages with
media attachments the window can be several seconds wide.
The sentinel is wrapped in try/finally so it is always cleaned up —
even if the handler raises or takes an early-return path. When the
real AIAgent is created, track_agent() overwrites the sentinel with
the actual instance (preserving interrupt support).
Also handles the edge case where a message arrives while the sentinel
is set but no real agent exists yet: the message is queued via the
adapter's pending-message mechanism instead of attempting to call
interrupt() on the sentinel object.
Add FastMCP skill to optional-skills/mcp/fastmcp/ with:
- SKILL.md with workflow, design patterns, quality checklist
- Templates: API wrapper, database server, file processor
- Scaffold CLI script for template instantiation
- FastMCP CLI reference documentation
Moved to optional-skills (requires pip install fastmcp).
Based on work by kshitijk4poor in PR #2096.
Closes#343
Show complete session IDs in 'hermes sessions list' instead of
truncating to 20 characters. Widens title column from 20→30 chars
and adjusts header widths accordingly.
Fixes#2068. Based on PR #2085 by @Nebula037 with a correction
to preserve the no-titles layout (the original PR accidentally
replaced the Preview/Src header with a duplicate Title/Preview header).
The install script creates venv/ but several docs referenced .venv/,
causing agents to fail with 'No such file or directory' when following
AGENTS.md instructions.
Fixes#2066
MiniMax's default base URL was /v1 which caused runtime_provider to
default to chat_completions mode (OpenAI-style Authorization: Bearer
header). MiniMax rejects this with a 401 because they require the
Anthropic-style x-api-key header.
Changes:
- auth.py: Change default inference_base_url for minimax and minimax-cn
from /v1 to /anthropic
- runtime_provider.py: Auto-correct stale /v1 URLs from existing .env
files to /anthropic, and always default minimax/minimax-cn providers
to anthropic_messages mode
- Update tests to reflect new defaults, add tests for stale URL
auto-correction and explicit api_mode override
Based on PR #2100 by @devorun. Fixes#2094.
Co-authored-by: Test <test@test.com>
Local models (especially Qwen 3.5) sometimes wrap their entire response
inside <think> tags, leaving actual content empty. Previously this caused
3 retries and then an error, wasting tokens and failing the request.
Now when retries are exhausted and reasoning_text contains the response,
it is used as final_response instead of returning an error. The user
sees the actual answer instead of "Model generated only think blocks."
Custom endpoints (LM Studio, Ollama, vLLM, llama.cpp) silently fall
back to 2M tokens when /v1/models doesn't include context_length.
Adds _query_local_context_length() which queries server-specific APIs:
- LM Studio: /api/v1/models (max_context_length + loaded instances)
- Ollama: /api/show (model_info + num_ctx parameters)
- llama.cpp: /props (n_ctx from default_generation_settings)
- vLLM: /v1/models/{model} (max_model_len)
Prefers loaded instance context over max (e.g., 122K loaded vs 1M max).
Results are cached via save_context_length() to avoid repeated queries.
Also fixes detect_local_server_type() misidentifying LM Studio as
Ollama (LM Studio returns 200 for /api/tags with an error body).
When LM Studio has a model loaded with a custom context size (e.g.,
122K), prefer that over the model's max_context_length (e.g., 1M).
This makes the TUI status bar show the actual runtime context window.
Instead of defaulting to 2M for unknown local models, query the server
API for the real context length. Supports Ollama (/api/show), vLLM
(max_model_len), and LM Studio (/v1/models). Results are cached to
avoid repeated queries.
Two issues with /model preventing proper provider switching:
1. Bare provider names not detected: typing '/model nous' treated 'nous'
as a model name instead of triggering a provider switch. Fixed by adding
step 0 in detect_provider_for_model() that checks if the input matches
a known provider name/alias (excluding 'custom'/'openrouter' which need
explicit model names) and returns that provider's default model.
2. Custom endpoint details hidden: /model (no args) showed '[custom]' with
just a usage hint but no endpoint URL or model name. Now displays the
configured base_url for custom providers in both CLI and gateway.
Note: config base_url and OPENAI_BASE_URL are intentionally NOT cleared on
provider switch — dedicated provider paths (nous, anthropic, codex) have
their own credential resolution that ignores these, and clearing them would
destroy the user's custom endpoint config, preventing switching back.
Co-authored-by: Test <test@test.com>
Previously, Tab only handled dropdown completions. Users seeing gray
ghost text from history-based suggestions had no way to accept them
with Tab - they had to use Right arrow or Ctrl+E.
Now Tab follows priority:
1. Completion menu open → accept selected completion
2. Ghost text suggestion available → accept auto-suggestion
3. Otherwise → start completion menu
This matches user intuition that Tab should 'complete what I see.'
* fix(codex): treat reasoning-only responses as incomplete, not stop
When a Codex Responses API response contains only reasoning items
(encrypted thinking state) with no message text or tool calls, the
_normalize_codex_response method was setting finish_reason='stop'.
This sent the response into the empty-content retry loop, which
burned 3 retries and then failed — exactly the pattern Nester
reported in Discord.
Two fixes:
1. _normalize_codex_response: reasoning-only responses (reasoning_items_raw
non-empty but no final_text) now get finish_reason='incomplete', routing
them to the Codex continuation path instead of the retry loop.
2. Incomplete handling: also checks for codex_reasoning_items when deciding
whether to preserve an interim message, so encrypted reasoning state is
not silently dropped when there is no visible reasoning text.
Adds 4 regression tests covering:
- Unit: reasoning-only → incomplete, reasoning+content → stop
- E2E: reasoning-only → continuation → final answer succeeds
- E2E: encrypted reasoning items preserved in interim messages
* fix(codex): ensure reasoning items have required following item in API input
Follow-up to the reasoning-only response fix. Three additional issues
found by tracing the full replay path:
1. _chat_messages_to_responses_input: when a reasoning-only interim
message was converted to Responses API input, the reasoning items
were emitted as the last items with no following item. The Responses
API requires a following item after each reasoning item (otherwise:
'missing_following_item' error, as seen in OpenHands #11406). Now
emits an empty assistant message as the required following item when
content is empty but reasoning items were added.
2. Duplicate detection: two consecutive reasoning-only incomplete
messages with identical empty content/reasoning but different
encrypted codex_reasoning_items were incorrectly treated as
duplicates, silently dropping the second response's reasoning state.
Now includes codex_reasoning_items in the duplicate comparison.
3. Added tests for both the API input conversion path and the duplicate
detection edge case.
Research context: verified against OpenCode (uses Vercel AI SDK, no
retry loop so avoids the issue), Clawdbot (drops orphaned reasoning
blocks entirely), and OpenHands (hit the missing_following_item error).
Our approach preserves reasoning continuity while satisfying the API
constraint.
---------
Co-authored-by: Test <test@test.com>
* fix: persist ACP sessions to disk so they survive process restarts
The ACP adapter stored sessions entirely in-memory. When the editor
restarted the ACP subprocess (idle timeout, crash, system sleep/wake,
editor restart), all sessions were lost. The editor's load_session /
resume_session calls would fail to find the session, forcing a new
empty session and losing all conversation history.
Changes:
- SessionManager now persists each session as a JSON file under
~/.hermes/acp_sessions/<session_id>.json
- get_session() transparently restores from disk when not in memory
- update_cwd(), fork_session(), list_sessions() all check disk
- server.py calls save_session() after prompt completion, /reset,
/compact, and model switches
- cleanup() and remove_session() delete disk files too
- Sessions have a 7-day TTL; expired sessions are pruned on startup
- Atomic writes via tempfile + os.replace to prevent corruption
- 11 new tests covering persistence, disk restoration, and TTL expiry
* refactor: use SessionDB instead of JSON files for ACP session persistence
Replace the standalone JSON file persistence layer with SessionDB
(~/.hermes/state.db) integration. ACP sessions now:
- Share the same DB as CLI and gateway sessions
- Are searchable via session_search (FTS5)
- Get token tracking, cost tracking, and session titles for free
- Follow existing session pruning policies
Key changes:
- _get_db() lazily creates a SessionDB, resolving HERMES_HOME
dynamically (not at import time) for test compatibility
- _persist() creates session record + replaces messages in DB
- _restore() loads from DB with source='acp' filter
- cwd stored in model_config JSON field (no schema migration)
- Model values coerced to str to handle mock agents in tests
- Removed: json files, sessions_dir, ttl_days, _expire logic
- Tests updated: DB-backed persistence, FTS search, tool_call
round-tripping, source filtering
---------
Co-authored-by: Test <test@test.com>
* fix: prevent unavailable tool names from leaking into model schemas
When web_search/web_extract fail check_fn (no API key configured), their
names were still leaking into tool descriptions via two paths:
1. execute_code schema: sandbox_enabled was computed from tools_to_include
(pre-filter) instead of the actual available tools (post-filter), so
the execute_code description listed web_search/web_extract as available
sandbox imports even when they weren't.
2. browser_navigate schema: hardcoded description said 'prefer web_search
or web_extract' regardless of whether those tools existed.
The model saw these references, assumed the tools existed, and tried
calling them directly — triggering 'Unknown tool' errors.
Fix: compute available_tool_names from the filtered result set and use
that for both execute_code sandbox listing and browser_navigate description
patching.
* docs: add pitfall about cross-tool references in schema descriptions
---------
Co-authored-by: Test <test@test.com>
Authored by Hanai. Allows overriding the OpenAI TTS endpoint via
tts.openai.base_url in config.yaml for self-hosted or OpenAI-compatible
TTS services. Falls back to api.openai.com when not set.
Authored by Lovre Pešut (rovle). Migrates from deprecated find_one(labels=...)
to get(sandbox_name) with deterministic naming (hermes-{task_id}), plus legacy
fallback via list(labels=...) for pre-migration sandboxes.
When a cron job references a skill that is no longer installed,
_build_job_prompt() now logs a warning and injects a user-visible notice
into the prompt instead of raising RuntimeError. The job continues with
any remaining valid skills and the user prompt.
Adds 4 regression tests for missing skill handling.
find_one is being deprecated. Primary lookup now uses get() with a
deterministic sandbox name (hermes-{task_id}). A legacy fallback via
list(labels=...) ensures sandboxes created before this migration are
still resumable.
Authored by dusterbloom. Closes#1911.
Pre-computes SQL query strings at class definition time in insights.py,
adds identifier quoting for ALTER TABLE DDL in hermes_state.py, and adds
4 regression tests verifying query construction safety.
The merge at e7844e9c re-introduced a line in _build_child_agent() that
references _saved_tool_names — a variable only defined in _run_single_child().
This caused NameError on every delegate_task call, completely breaking
subagent delegation.
Moves the child._delegate_saved_tool_names assignment to _run_single_child()
where _saved_tool_names is actually defined, keeping the save/restore in the
same scope as the try/finally block.
Adds two regression tests from PR #2038 (YanSte).
Also fixes the same issue reported in PR #2048 (Gutslabs).
Co-authored-by: Yannick Stephan <yannick.stephan@gmail.com>
Co-authored-by: Guts <gutslabs@users.noreply.github.com>
Allow users to configure a custom base_url for the OpenAI TTS provider
in ~/.hermes/config.yaml under tts.openai.base_url. Defaults to the
official OpenAI endpoint. Enables use of self-hosted or OpenAI-compatible
TTS services (e.g. http://localhost:8000/v1).
Also adds a TTS configuration example block to cli-config.yaml.example.
Closes#1911
- insights.py: Pre-compute SELECT queries as class constants instead of
f-string interpolation at runtime. _SESSION_COLS is now evaluated once
at class definition time.
- hermes_state.py: Add identifier quoting and whitelist validation for
ALTER TABLE column names in schema migrations.
- Add 4 tests verifying no injection vectors in SQL query construction.
* fix: detect context length for custom model endpoints via fuzzy matching + config override
Custom model endpoints (non-OpenRouter, non-known-provider) were silently
falling back to 2M tokens when the model name didn't exactly match what the
endpoint's /v1/models reported. This happened because:
1. Endpoint metadata lookup used exact match only — model name mismatches
(e.g. 'qwen3.5:9b' vs 'Qwen3.5-9B-Q4_K_M.gguf') caused a miss
2. Single-model servers (common for local inference) required exact name
match even though only one model was loaded
3. No user escape hatch to manually set context length
Changes:
- Add fuzzy matching for endpoint model metadata: single-model servers
use the only available model regardless of name; multi-model servers
try substring matching in both directions
- Add model.context_length config override (highest priority) so users
can explicitly set their model's context length in config.yaml
- Log an informative message when falling back to 2M probe, telling
users about the config override option
- Thread config_context_length through ContextCompressor and AIAgent init
Tests: 6 new tests covering fuzzy match, single-model fallback, config
override (including zero/None edge cases).
* fix: auto-detect local model name and context length for local servers
Cherry-picked from PR #2043 by sudoingX.
- Auto-detect model name from local server's /v1/models when only one
model is loaded (no manual model name config needed)
- Add n_ctx_train and n_ctx to context length detection keys for llama.cpp
- Query llama.cpp /props endpoint for actual allocated context (not just
training context from GGUF metadata)
- Strip .gguf suffix from display in banner and status bar
- _auto_detect_local_model() in runtime_provider.py for CLI init
Co-authored-by: sudo <sudoingx@users.noreply.github.com>
* fix: revert accidental summary_target_tokens change + add docs for context_length config
- Revert summary_target_tokens from 2500 back to 500 (accidental change
during patching)
- Add 'Context Length Detection' section to Custom & Self-Hosted docs
explaining model.context_length config override
---------
Co-authored-by: Test <test@test.com>
Co-authored-by: sudo <sudoingx@users.noreply.github.com>
The gateway approval system previously intercepted bare 'yes'/'no' text
from the user's next message to approve/deny dangerous commands. This was
fragile and dangerous — if the agent asked a clarify question and the user
said 'yes' to answer it, the gateway would execute the pending dangerous
command instead. (Fixes#1888)
Changes:
- Remove bare text matching ('yes', 'y', 'approve', 'ok', etc.) from
_handle_message approval check
- Add /approve and /deny as gateway-only slash commands in the command
registry
- /approve supports scoping: /approve (one-time), /approve session,
/approve always (permanent)
- Add 5-minute timeout for stale approvals
- Gateway appends structured instructions to the agent response when a
dangerous command is pending, telling the user exactly how to respond
- 9 tests covering approve, deny, timeout, scoping, and verification
that bare 'yes' no longer triggers execution
Credit to @solo386 and @FlyByNight69420 for identifying and reporting
this security issue in PR #1971 and issue #1888.
Co-authored-by: Test <test@test.com>
After #1675 removed ANTHROPIC_BASE_URL env var support, the Anthropic
provider base URL was hardcoded to https://api.anthropic.com. Now reads
model.base_url from config.yaml as an override, falling back to the
default when not set. Also applies to the auxiliary client.
Cherry-picked from PR #1949 by @rivercrab26.
Co-authored-by: rivercrab26 <rivercrab26@users.noreply.github.com>
Three bugs prevented providers like MiniMax from using their
Anthropic-compatible endpoints (e.g. api.minimax.io/anthropic):
1. _VALID_API_MODES was missing 'anthropic_messages', so explicit
api_mode config was silently rejected and defaulted to
chat_completions.
2. API-key provider resolution hardcoded api_mode to 'chat_completions'
without checking model config or detecting Anthropic-compatible URLs.
3. run_agent.py auto-detection only recognized api.anthropic.com, not
third-party endpoints using the /anthropic URL convention.
Fixes:
- Add 'anthropic_messages' to _VALID_API_MODES
- API-key providers now check model config api_mode and auto-detect
URLs ending in /anthropic
- run_agent.py and fallback logic detect /anthropic URL convention
- 5 new tests covering all scenarios
Users can now either:
- Set MINIMAX_BASE_URL=https://api.minimax.io/anthropic (auto-detected)
- Set api_mode: anthropic_messages in model config (explicit)
- Use custom_providers with api_mode: anthropic_messages
Co-authored-by: Test <test@test.com>
When provider: custom is set in config.yaml with base_url and api_key,
those values are now used instead of falling back to OPENAI_BASE_URL and
OPENAI_API_KEY env vars. Also reads the 'api' field as an alternative to
'api_key' for config compatibility.
Cherry-picked from PR #1762 by crazywriter1.
Co-authored-by: crazywriter1 <53251494+crazywriter1@users.noreply.github.com>
_align_boundary_backward only checked messages[idx-1] to decide if
the compress-end boundary splits a tool_call/result group. When an
assistant issues 3+ parallel tool calls, their results span multiple
consecutive messages. If the boundary fell in the middle of that group,
the parent assistant was summarized away and orphaned tool results were
silently deleted by _sanitize_tool_pairs.
Now walks backward through all consecutive tool results to find the
parent assistant, then pulls the boundary before the entire group.
6 regression tests added in tests/test_compression_boundary.py.
Co-authored-by: Guts <Gutslabs@users.noreply.github.com>
Previously, if an error occurred during response processing in
_process_message_background (e.g. during extract_media, send, or
any uncaught exception from the handler), the error was only logged
to server console and the user was left with radio silence — typing
indicator stops but no message arrives.
Now the outer except block attempts to send the error type and detail
(truncated to 300 chars) to the user's chat, matching the format
already used by the inner handler in gateway/run.py.
Co-authored-by: Test <test@test.com>
