main
20 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
emozilla
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0365f6202c |
feat: show model pricing for OpenRouter and Nous Portal providers
Display live per-million-token pricing from /v1/models when listing models for OpenRouter or Nous Portal. Prices are shown in a column-aligned table with decimal points vertically aligned for easy comparison. Pricing appears in three places: - /provider slash command (table with In/Out headers) - hermes model picker (aligned columns in both TerminalMenu and numbered fallback) Implementation: - Add fetch_models_with_pricing() in models.py with per-base_url module-level cache (one network call per endpoint per session) - Add _format_price_per_mtok() with fixed 2-decimal formatting - Add format_model_pricing_table() for terminal table display - Add get_pricing_for_provider() convenience wrapper - Update _prompt_model_selection() to accept optional pricing dict - Wire pricing through _model_flow_openrouter/nous in main.py - Update test mocks for new pricing parameter |
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Teknium
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924bc67eee |
feat(memory): pluggable memory provider interface with profile isolation, review fixes, and honcho CLI restoration (#4623)
* feat(memory): add pluggable memory provider interface with profile isolation Introduces a pluggable MemoryProvider ABC so external memory backends can integrate with Hermes without modifying core files. Each backend becomes a plugin implementing a standard interface, orchestrated by MemoryManager. Key architecture: - agent/memory_provider.py — ABC with core + optional lifecycle hooks - agent/memory_manager.py — single integration point in the agent loop - agent/builtin_memory_provider.py — wraps existing MEMORY.md/USER.md Profile isolation fixes applied to all 6 shipped plugins: - Cognitive Memory: use get_hermes_home() instead of raw env var - Hindsight Memory: check $HERMES_HOME/hindsight/config.json first, fall back to legacy ~/.hindsight/ for backward compat - Hermes Memory Store: replace hardcoded ~/.hermes paths with get_hermes_home() for config loading and DB path defaults - Mem0 Memory: use get_hermes_home() instead of raw env var - RetainDB Memory: auto-derive profile-scoped project name from hermes_home path (hermes-<profile>), explicit env var overrides - OpenViking Memory: read-only, no local state, isolation via .env MemoryManager.initialize_all() now injects hermes_home into kwargs so every provider can resolve profile-scoped storage without importing get_hermes_home() themselves. Plugin system: adds register_memory_provider() to PluginContext and get_plugin_memory_providers() accessor. Based on PR #3825. 46 tests (37 unit + 5 E2E + 4 plugin registration). * refactor(memory): drop cognitive plugin, rewrite OpenViking as full provider Remove cognitive-memory plugin (#727) — core mechanics are broken: decay runs 24x too fast (hourly not daily), prefetch uses row ID as timestamp, search limited by importance not similarity. Rewrite openviking-memory plugin from a read-only search wrapper into a full bidirectional memory provider using the complete OpenViking session lifecycle API: - sync_turn: records user/assistant messages to OpenViking session (threaded, non-blocking) - on_session_end: commits session to trigger automatic memory extraction into 6 categories (profile, preferences, entities, events, cases, patterns) - prefetch: background semantic search via find() endpoint - on_memory_write: mirrors built-in memory writes to the session - is_available: checks env var only, no network calls (ABC compliance) Tools expanded from 3 to 5: - viking_search: semantic search with mode/scope/limit - viking_read: tiered content (abstract ~100tok / overview ~2k / full) - viking_browse: filesystem-style navigation (list/tree/stat) - viking_remember: explicit memory storage via session - viking_add_resource: ingest URLs/docs into knowledge base Uses direct HTTP via httpx (no openviking SDK dependency needed). Response truncation on viking_read to prevent context flooding. * fix(memory): harden Mem0 plugin — thread safety, non-blocking sync, circuit breaker - Remove redundant mem0_context tool (identical to mem0_search with rerank=true, top_k=5 — wastes a tool slot and confuses the model) - Thread sync_turn so it's non-blocking — Mem0's server-side LLM extraction can take 5-10s, was stalling the agent after every turn - Add threading.Lock around _get_client() for thread-safe lazy init (prefetch and sync threads could race on first client creation) - Add circuit breaker: after 5 consecutive API failures, pause calls for 120s instead of hammering a down server every turn. Auto-resets after cooldown. Logs a warning when tripped. - Track success/failure in prefetch, sync_turn, and all tool calls - Wait for previous sync to finish before starting a new one (prevents unbounded thread accumulation on rapid turns) - Clean up shutdown to join both prefetch and sync threads * fix(memory): enforce single external memory provider limit MemoryManager now rejects a second non-builtin provider with a warning. Built-in memory (MEMORY.md/USER.md) is always accepted. Only ONE external plugin provider is allowed at a time. This prevents tool schema bloat (some providers add 3-5 tools each) and conflicting memory backends. The warning message directs users to configure memory.provider in config.yaml to select which provider to activate. Updated all 47 tests to use builtin + one external pattern instead of multiple externals. Added test_second_external_rejected to verify the enforcement. * feat(memory): add ByteRover memory provider plugin Implements the ByteRover integration (from PR #3499 by hieuntg81) as a MemoryProvider plugin instead of direct run_agent.py modifications. ByteRover provides persistent memory via the brv CLI — a hierarchical knowledge tree with tiered retrieval (fuzzy text then LLM-driven search). Local-first with optional cloud sync. Plugin capabilities: - prefetch: background brv query for relevant context - sync_turn: curate conversation turns (threaded, non-blocking) - on_memory_write: mirror built-in memory writes to brv - on_pre_compress: extract insights before context compression Tools (3): - brv_query: search the knowledge tree - brv_curate: store facts/decisions/patterns - brv_status: check CLI version and context tree state Profile isolation: working directory at $HERMES_HOME/byterover/ (scoped per profile). Binary resolution cached with thread-safe double-checked locking. All write operations threaded to avoid blocking the agent (curate can take 120s with LLM processing). * fix(memory): thread remaining sync_turns, fix holographic, add config key Plugin fixes: - Hindsight: thread sync_turn (was blocking up to 30s via _run_in_thread) - RetainDB: thread sync_turn (was blocking on HTTP POST) - Both: shutdown now joins sync threads alongside prefetch threads Holographic retrieval fixes: - reason(): removed dead intersection_key computation (bundled but never used in scoring). Now reuses pre-computed entity_residuals directly, moved role_content encoding outside the inner loop. - contradict(): added _MAX_CONTRADICT_FACTS=500 scaling guard. Above 500 facts, only checks the most recently updated ones to avoid O(n^2) explosion (~125K comparisons at 500 is acceptable). Config: - Added memory.provider key to DEFAULT_CONFIG ("" = builtin only). No version bump needed (deep_merge handles new keys automatically). * feat(memory): extract Honcho as a MemoryProvider plugin Creates plugins/honcho-memory/ as a thin adapter over the existing honcho_integration/ package. All 4 Honcho tools (profile, search, context, conclude) move from the normal tool registry to the MemoryProvider interface. The plugin delegates all work to HonchoSessionManager — no Honcho logic is reimplemented. It uses the existing config chain: $HERMES_HOME/honcho.json -> ~/.honcho/config.json -> env vars. Lifecycle hooks: - initialize: creates HonchoSessionManager via existing client factory - prefetch: background dialectic query - sync_turn: records messages + flushes to API (threaded) - on_memory_write: mirrors user profile writes as conclusions - on_session_end: flushes all pending messages This is a prerequisite for the MemoryManager wiring in run_agent.py. Once wired, Honcho goes through the same provider interface as all other memory plugins, and the scattered Honcho code in run_agent.py can be consolidated into the single MemoryManager integration point. * feat(memory): wire MemoryManager into run_agent.py Adds 8 integration points for the external memory provider plugin, all purely additive (zero existing code modified): 1. Init (~L1130): Create MemoryManager, find matching plugin provider from memory.provider config, initialize with session context 2. Tool injection (~L1160): Append provider tool schemas to self.tools and self.valid_tool_names after memory_manager init 3. System prompt (~L2705): Add external provider's system_prompt_block alongside existing MEMORY.md/USER.md blocks 4. Tool routing (~L5362): Route provider tool calls through memory_manager.handle_tool_call() before the catchall handler 5. Memory write bridge (~L5353): Notify external provider via on_memory_write() when the built-in memory tool writes 6. Pre-compress (~L5233): Call on_pre_compress() before context compression discards messages 7. Prefetch (~L6421): Inject provider prefetch results into the current-turn user message (same pattern as Honcho turn context) 8. Turn sync + session end (~L8161, ~L8172): sync_all() after each completed turn, queue_prefetch_all() for next turn, on_session_end() + shutdown_all() at conversation end All hooks are wrapped in try/except — a failing provider never breaks the agent. The existing memory system, Honcho integration, and all other code paths are completely untouched. Full suite: 7222 passed, 4 pre-existing failures. * refactor(memory): remove legacy Honcho integration from core Extracts all Honcho-specific code from run_agent.py, model_tools.py, toolsets.py, and gateway/run.py. Honcho is now exclusively available as a memory provider plugin (plugins/honcho-memory/). Removed from run_agent.py (-457 lines): - Honcho init block (session manager creation, activation, config) - 8 Honcho methods: _honcho_should_activate, _strip_honcho_tools, _activate_honcho, _register_honcho_exit_hook, _queue_honcho_prefetch, _honcho_prefetch, _honcho_save_user_observation, _honcho_sync - _inject_honcho_turn_context module-level function - Honcho system prompt block (tool descriptions, CLI commands) - Honcho context injection in api_messages building - Honcho params from __init__ (honcho_session_key, honcho_manager, honcho_config) - HONCHO_TOOL_NAMES constant - All honcho-specific tool dispatch forwarding Removed from other files: - model_tools.py: honcho_tools import, honcho params from handle_function_call - toolsets.py: honcho toolset definition, honcho tools from core tools list - gateway/run.py: honcho params from AIAgent constructor calls Removed tests (-339 lines): - 9 Honcho-specific test methods from test_run_agent.py - TestHonchoAtexitFlush class from test_exit_cleanup_interrupt.py Restored two regex constants (_SURROGATE_RE, _BUDGET_WARNING_RE) that were accidentally removed during the honcho function extraction. The honcho_integration/ package is kept intact — the plugin delegates to it. tools/honcho_tools.py registry entries are now dead code (import commented out in model_tools.py) but the file is preserved for reference. Full suite: 7207 passed, 4 pre-existing failures. Zero regressions. * refactor(memory): restructure plugins, add CLI, clean gateway, migration notice Plugin restructure: - Move all memory plugins from plugins/<name>-memory/ to plugins/memory/<name>/ (byterover, hindsight, holographic, honcho, mem0, openviking, retaindb) - New plugins/memory/__init__.py discovery module that scans the directory directly, loading providers by name without the general plugin system - run_agent.py uses load_memory_provider() instead of get_plugin_memory_providers() CLI wiring: - hermes memory setup — interactive curses picker + config wizard - hermes memory status — show active provider, config, availability - hermes memory off — disable external provider (built-in only) - hermes honcho — now shows migration notice pointing to hermes memory setup Gateway cleanup: - Remove _get_or_create_gateway_honcho (already removed in prev commit) - Remove _shutdown_gateway_honcho and _shutdown_all_gateway_honcho methods - Remove all calls to shutdown methods (4 call sites) - Remove _honcho_managers/_honcho_configs dict references Dead code removal: - Delete tools/honcho_tools.py (279 lines, import was already commented out) - Delete tests/gateway/test_honcho_lifecycle.py (131 lines, tested removed methods) - Remove if False placeholder from run_agent.py Migration: - Honcho migration notice on startup: detects existing honcho.json or ~/.honcho/config.json, prints guidance to run hermes memory setup. Only fires when memory.provider is not set and not in quiet mode. Full suite: 7203 passed, 4 pre-existing failures. Zero regressions. * feat(memory): standardize plugin config + add per-plugin documentation Config architecture: - Add save_config(values, hermes_home) to MemoryProvider ABC - Honcho: writes to $HERMES_HOME/honcho.json (SDK native) - Mem0: writes to $HERMES_HOME/mem0.json - Hindsight: writes to $HERMES_HOME/hindsight/config.json - Holographic: writes to config.yaml under plugins.hermes-memory-store - OpenViking/RetainDB/ByteRover: env-var only (default no-op) Setup wizard (hermes memory setup): - Now calls provider.save_config() for non-secret config - Secrets still go to .env via env vars - Only memory.provider activation key goes to config.yaml Documentation: - README.md for each of the 7 providers in plugins/memory/<name>/ - Requirements, setup (wizard + manual), config reference, tools table - Consistent format across all providers The contract for new memory plugins: - get_config_schema() declares all fields (REQUIRED) - save_config() writes native config (REQUIRED if not env-var-only) - Secrets use env_var field in schema, written to .env by wizard - README.md in the plugin directory * docs: add memory providers user guide + developer guide New pages: - user-guide/features/memory-providers.md — comprehensive guide covering all 7 shipped providers (Honcho, OpenViking, Mem0, Hindsight, Holographic, RetainDB, ByteRover). Each with setup, config, tools, cost, and unique features. Includes comparison table and profile isolation notes. - developer-guide/memory-provider-plugin.md — how to build a new memory provider plugin. Covers ABC, required methods, config schema, save_config, threading contract, profile isolation, testing. Updated pages: - user-guide/features/memory.md — replaced Honcho section with link to new Memory Providers page - user-guide/features/honcho.md — replaced with migration redirect to the new Memory Providers page - sidebars.ts — added both new pages to navigation * fix(memory): auto-migrate Honcho users to memory provider plugin When honcho.json or ~/.honcho/config.json exists but memory.provider is not set, automatically set memory.provider: honcho in config.yaml and activate the plugin. The plugin reads the same config files, so all data and credentials are preserved. Zero user action needed. Persists the migration to config.yaml so it only fires once. Prints a one-line confirmation in non-quiet mode. * fix(memory): only auto-migrate Honcho when enabled + credentialed Check HonchoClientConfig.enabled AND (api_key OR base_url) before auto-migrating — not just file existence. Prevents false activation for users who disabled Honcho, stopped using it (config lingers), or have ~/.honcho/ from a different tool. * feat(memory): auto-install pip dependencies during hermes memory setup Reads pip_dependencies from plugin.yaml, checks which are missing, installs them via pip before config walkthrough. Also shows install guidance for external_dependencies (e.g. brv CLI for ByteRover). Updated all 7 plugin.yaml files with pip_dependencies: - honcho: honcho-ai - mem0: mem0ai - openviking: httpx - hindsight: hindsight-client - holographic: (none) - retaindb: requests - byterover: (external_dependencies for brv CLI) * fix: remove remaining Honcho crash risks from cli.py and gateway cli.py: removed Honcho session re-mapping block (would crash importing deleted tools/honcho_tools.py), Honcho flush on compress, Honcho session display on startup, Honcho shutdown on exit, honcho_session_key AIAgent param. gateway/run.py: removed honcho_session_key params from helper methods, sync_honcho param, _honcho.shutdown() block. tests: fixed test_cron_session_with_honcho_key_skipped (was passing removed honcho_key param to _flush_memories_for_session). * fix: include plugins/ in pyproject.toml package list Without this, plugins/memory/ wouldn't be included in non-editable installs. Hermes always runs from the repo checkout so this is belt- and-suspenders, but prevents breakage if the install method changes. * fix(memory): correct pip-to-import name mapping for dep checks The heuristic dep.replace('-', '_') fails for packages where the pip name differs from the import name: honcho-ai→honcho, mem0ai→mem0, hindsight-client→hindsight_client. Added explicit mapping table so hermes memory setup doesn't try to reinstall already-installed packages. * chore: remove dead code from old plugin memory registration path - hermes_cli/plugins.py: removed register_memory_provider(), _memory_providers list, get_plugin_memory_providers() — memory providers now use plugins/memory/ discovery, not the general plugin system - hermes_cli/main.py: stripped 74 lines of dead honcho argparse subparsers (setup, status, sessions, map, peer, mode, tokens, identity, migrate) — kept only the migration redirect - agent/memory_provider.py: updated docstring to reflect new registration path - tests: replaced TestPluginMemoryProviderRegistration with TestPluginMemoryDiscovery that tests the actual plugins/memory/ discovery system. Added 3 new tests (discover, load, nonexistent). * chore: delete dead honcho_integration/cli.py and its tests cli.py (794 lines) was the old 'hermes honcho' command handler — nobody calls it since cmd_honcho was replaced with a migration redirect. Deleted tests that imported from removed code: - tests/honcho_integration/test_cli.py (tested _resolve_api_key) - tests/honcho_integration/test_config_isolation.py (tested CLI config paths) - tests/tools/test_honcho_tools.py (tested the deleted tools/honcho_tools.py) Remaining honcho_integration/ files (actively used by the plugin): - client.py (445 lines) — config loading, SDK client creation - session.py (991 lines) — session management, queries, flush * refactor: move honcho_integration/ into the honcho plugin Moves client.py (445 lines) and session.py (991 lines) from the top-level honcho_integration/ package into plugins/memory/honcho/. No Honcho code remains in the main codebase. - plugins/memory/honcho/client.py — config loading, SDK client creation - plugins/memory/honcho/session.py — session management, queries, flush - Updated all imports: run_agent.py (auto-migration), hermes_cli/doctor.py, plugin __init__.py, session.py cross-import, all tests - Removed honcho_integration/ package and pyproject.toml entry - Renamed tests/honcho_integration/ → tests/honcho_plugin/ * docs: update architecture + gateway-internals for memory provider system - architecture.md: replaced honcho_integration/ with plugins/memory/ - gateway-internals.md: replaced Honcho-specific session routing and flush lifecycle docs with generic memory provider interface docs * fix: update stale mock path for resolve_active_host after honcho plugin migration * fix(memory): address review feedback — P0 lifecycle, ABC contract, honcho CLI restore Review feedback from Honcho devs (erosika): P0 — Provider lifecycle: - Remove on_session_end() + shutdown_all() from run_conversation() tail (was killing providers after every turn in multi-turn sessions) - Add shutdown_memory_provider() method on AIAgent for callers - Wire shutdown into CLI atexit, reset_conversation, gateway stop/expiry Bug fixes: - Remove sync_honcho=False kwarg from /btw callsites (TypeError crash) - Fix doctor.py references to dead 'hermes honcho setup' command - Cache prefetch_all() before tool loop (was re-calling every iteration) ABC contract hardening (all backwards-compatible): - Add session_id kwarg to prefetch/sync_turn/queue_prefetch - Make on_pre_compress() return str (provider insights in compression) - Add **kwargs to on_turn_start() for runtime context - Add on_delegation() hook for parent-side subagent observation - Document agent_context/agent_identity/agent_workspace kwargs on initialize() (prevents cron corruption, enables profile scoping) - Fix docstring: single external provider, not multiple Honcho CLI restoration: - Add plugins/memory/honcho/cli.py (from main's honcho_integration/cli.py with imports adapted to plugin path) - Restore full hermes honcho command with all subcommands (status, peer, mode, tokens, identity, enable/disable, sync, peers, --target-profile) - Restore auto-clone on profile creation + sync on hermes update - hermes honcho setup now redirects to hermes memory setup * fix(memory): wire on_delegation, skip_memory for cron/flush, fix ByteRover return type - Wire on_delegation() in delegate_tool.py — parent's memory provider is notified with task+result after each subagent completes - Add skip_memory=True to cron scheduler (prevents cron system prompts from corrupting user representations — closes #4052) - Add skip_memory=True to gateway flush agent (throwaway agent shouldn't activate memory provider) - Fix ByteRover on_pre_compress() return type: None -> str * fix(honcho): port profile isolation fixes from PR #4632 Ports 5 bug fixes found during profile testing (erosika's PR #4632): 1. 3-tier config resolution — resolve_config_path() now checks $HERMES_HOME/honcho.json → ~/.hermes/honcho.json → ~/.honcho/config.json (non-default profiles couldn't find shared host blocks) 2. Thread host=_host_key() through from_global_config() in cmd_setup, cmd_status, cmd_identity (--target-profile was being ignored) 3. Use bare profile name as aiPeer (not host key with dots) — Honcho's peer ID pattern is ^[a-zA-Z0-9_-]+$, dots are invalid 4. Wrap add_peers() in try/except — was fatal on new AI peers, killed all message uploads for the session 5. Gate Honcho clone behind --clone/--clone-all on profile create (bare create should be blank-slate) Also: sanitize assistant_peer_id via _sanitize_id() * fix(tests): add module cleanup fixture to test_cli_provider_resolution test_cli_provider_resolution._import_cli() wipes tools.*, cli, and run_agent from sys.modules to force fresh imports, but had no cleanup. This poisoned all subsequent tests on the same xdist worker — mocks targeting tools.file_tools, tools.send_message_tool, etc. patched the NEW module object while already-imported functions still referenced the OLD one. Caused ~25 cascade failures: send_message KeyError, process_registry FileNotFoundError, file_read_guards timeouts, read_loop_detection file-not-found, mcp_oauth None port, and provider_parity/codex_execution stale tool lists. Fix: autouse fixture saves all affected modules before each test and restores them after, matching the pattern in test_managed_browserbase_and_modal.py. |
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Ben
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647f99d4dd |
fix: resolve post-merge issues in auxiliary_client and model flow
- Add missing `from agent.credential_pool import load_pool` import to auxiliary_client.py (introduced by the credential pool feature in main) - Thread `args` through `select_provider_and_model(args=None)` so TLS options from `cmd_model` reach `_model_flow_nous` - Mock `_require_tty` in test_cmd_model_forwards_nous_login_tls_options so it can run in non-interactive test environments Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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Ben Barclay
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a2e56d044b | Merge branch 'main' into rewbs/tool-use-charge-to-subscription | ||
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Teknium
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344239c2db |
feat: auto-detect models from server probe in custom endpoint setup (#4218)
Custom endpoint setup (_model_flow_custom) now probes the server first and presents detected models instead of asking users to type blind: - Single model: auto-confirms with Y/n prompt - Multiple models: numbered list picker, or type a name - No models / probe failed: falls back to manual input Context length prompt also moved after model selection so the user sees the verified endpoint before being asked for details. All recent fixes preserved: config dict sync (#4172), api_key persistence (#4182), no save_env_value for URLs (#4165). Inspired by PR #4194 by sudoingX — re-implemented against current main. Co-authored-by: Xpress AI (Dip KD) <200180104+sudoingX@users.noreply.github.com> |
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Teknium
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f890a94c12 |
refactor: make config.yaml the single source of truth for endpoint URLs (#4165)
OPENAI_BASE_URL was written to .env AND config.yaml, creating a dual-source
confusion. Users (especially Docker) would see the URL in .env and assume
that's where all config lives, then wonder why LLM_MODEL in .env didn't work.
Changes:
- Remove all 27 save_env_value("OPENAI_BASE_URL", ...) calls across main.py,
setup.py, and tools_config.py
- Remove OPENAI_BASE_URL env var reading from runtime_provider.py, cli.py,
models.py, and gateway/run.py
- Remove LLM_MODEL/HERMES_MODEL env var reading from gateway/run.py and
auxiliary_client.py — config.yaml model.default is authoritative
- Vision base URL now saved to config.yaml auxiliary.vision.base_url
(both setup wizard and tools_config paths)
- Tests updated to set config values instead of env vars
Convention enforced: .env is for SECRETS only (API keys). All other
configuration (model names, base URLs, provider selection) lives
exclusively in config.yaml.
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Teknium
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d30ea65c9b |
fix: URL-based auth for third-party Anthropic endpoints + CI test fixes (#4148)
* fix(tests): mock sys.stdin.isatty for cmd_model TTY guard * fix(tests): update camofox snapshot format + trajectory compressor mock path - test_browser_camofox: mock response now uses snapshot format (accessibility tree) - test_trajectory_compressor: mock _get_async_client instead of setting async_client directly * fix: URL-based auth detection for third-party Anthropic endpoints + test fixes Reverts the key-prefix approach from #4093 which broke JWT and managed key OAuth detection. Instead, detects third-party endpoints by URL: if base_url is set and isn't anthropic.com, it's a proxy (Azure AI Foundry, AWS Bedrock, etc.) that uses x-api-key regardless of key format. Auth decision chain is now: 1. _requires_bearer_auth(url) → MiniMax → Bearer 2. _is_third_party_anthropic_endpoint(url) → Azure/Bedrock → x-api-key 3. _is_oauth_token(key) → OAuth on direct Anthropic → Bearer 4. else → x-api-key Also includes test fixes from PR #4051 by @erosika: - Mock sys.stdin.isatty for cmd_model TTY guard - Update camofox snapshot format mock - Fix trajectory compressor async client mock path --------- Co-authored-by: Erosika <eri@plasticlabs.ai> |
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Robin Fernandes
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1cbb1b99cc | Gate tool-gateway behind an env var, so it's not in users' faces until we're ready. Even if users enable it, it'll be blocked server-side for now, until we unlock for non-admin users on tool-gateway. | ||
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Robin Fernandes
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95dc9aaa75 |
feat: add managed tool gateway and Nous subscription support
- add managed modal and gateway-backed tool integrations\n- improve CLI setup, auth, and configuration for subscriber flows\n- expand tests and docs for managed tool support |
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Teknium
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88643a1ba9 |
feat: overhaul context length detection with models.dev and provider-aware resolution (#2158)
Replace the fragile hardcoded context length system with a multi-source resolution chain that correctly identifies context windows per provider. Key changes: - New agent/models_dev.py: Fetches and caches the models.dev registry (3800+ models across 100+ providers with per-provider context windows). In-memory cache (1hr TTL) + disk cache for cold starts. - Rewritten get_model_context_length() resolution chain: 0. Config override (model.context_length) 1. Custom providers per-model context_length 2. Persistent disk cache 3. Endpoint /models (local servers) 4. Anthropic /v1/models API (max_input_tokens, API-key only) 5. OpenRouter live API (existing, unchanged) 6. Nous suffix-match via OpenRouter (dot/dash normalization) 7. models.dev registry lookup (provider-aware) 8. Thin hardcoded defaults (broad family patterns) 9. 128K fallback (was 2M) - Provider-aware context: same model now correctly resolves to different context windows per provider (e.g. claude-opus-4.6: 1M on Anthropic, 128K on GitHub Copilot). Provider name flows through ContextCompressor. - DEFAULT_CONTEXT_LENGTHS shrunk from 80+ entries to ~16 broad patterns. models.dev replaces the per-model hardcoding. - CONTEXT_PROBE_TIERS changed from [2M, 1M, 512K, 200K, 128K, 64K, 32K] to [128K, 64K, 32K, 16K, 8K]. Unknown models no longer start at 2M. - hermes model: prompts for context_length when configuring custom endpoints. Supports shorthand (32k, 128K). Saved to custom_providers per-model config. - custom_providers schema extended with optional models dict for per-model context_length (backward compatible). - Nous Portal: suffix-matches bare IDs (claude-opus-4-6) against OpenRouter's prefixed IDs (anthropic/claude-opus-4.6) with dot/dash normalization. Handles all 15 current Nous models. - Anthropic direct: queries /v1/models for max_input_tokens. Only works with regular API keys (sk-ant-api*), not OAuth tokens. Falls through to models.dev for OAuth users. Tests: 5574 passed (18 new tests for models_dev + updated probe tiers) Docs: Updated configuration.md context length section, AGENTS.md Co-authored-by: Test <test@test.com> |
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Teknium
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24ac577046 |
fix: respect model.default from config.yaml for openai-codex provider (#1896)
When config.yaml had a non-default model (e.g. gpt-5.3-codex) and the provider was openai-codex, _normalize_model_for_provider() would replace it with the latest available codex model because _model_is_default only checked the CLI argument, not the config value. Now _model_is_default is False when config.yaml has a model that differs from the global fallback (anthropic/claude-opus-4.6), so the user's explicit config choice is preserved. Fixes #1887 Co-authored-by: Test <test@test.com> |
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Teknium
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5e5c92663d |
fix: hermes update causes dual gateways on macOS (launchd) (#1567)
* feat: add optional smart model routing Add a conservative cheap-vs-strong routing option that can send very short/simple turns to a cheaper model across providers while keeping the primary model for complex work. Wire it through CLI, gateway, and cron, and document the config.yaml workflow. * fix(gateway): remove recursive ExecStop from systemd units, extend TimeoutStopSec to 60s * fix(gateway): avoid recursive ExecStop in user systemd unit * fix: extend ExecStop removal and TimeoutStopSec=60 to system unit The cherry-picked PR #1448 fix only covered the user systemd unit. The system unit had the same TimeoutStopSec=15 and could benefit from the same 60s timeout for clean shutdown. Also adds a regression test for the system unit. --------- Co-authored-by: Ninja <ninja@local> * feat(skills): add blender-mcp optional skill for 3D modeling Control a running Blender instance from Hermes via socket connection to the blender-mcp addon (port 9876). Supports creating 3D objects, materials, animations, and running arbitrary bpy code. Placed in optional-skills/ since it requires Blender 4.3+ desktop with a third-party addon manually started each session. * feat(acp): support slash commands in ACP adapter (#1532) Adds /help, /model, /tools, /context, /reset, /compact, /version to the ACP adapter (VS Code, Zed, JetBrains). Commands are handled directly in the server without instantiating the TUI — each command queries agent/session state and returns plain text. Unrecognized /commands fall through to the LLM as normal messages. /model uses detect_provider_for_model() for auto-detection when switching models, matching the CLI and gateway behavior. Fixes #1402 * fix(logging): improve error logging in session search tool (#1533) * fix(gateway): restart on retryable startup failures (#1517) * feat(email): add skip_attachments option via config.yaml * feat(email): add skip_attachments option via config.yaml Adds a config.yaml-driven option to skip email attachments in the gateway email adapter. Useful for malware protection and bandwidth savings. Configure in config.yaml: platforms: email: skip_attachments: true Based on PR #1521 by @an420eth, changed from env var to config.yaml (via PlatformConfig.extra) to match the project's config-first pattern. * docs: document skip_attachments option for email adapter * fix(telegram): retry on transient TLS failures during connect and send Add exponential-backoff retry (3 attempts) around initialize() to handle transient TLS resets during gateway startup. Also catches TimedOut and OSError in addition to NetworkError. Add exponential-backoff retry (3 attempts) around send_message() for NetworkError during message delivery, wrapping the existing Markdown fallback logic. Both imports are guarded with try/except ImportError for test environments where telegram is mocked. Based on PR #1527 by cmd8. Closes #1526. * feat: permissive block_anchor thresholds and unicode normalization (#1539) Salvaged from PR #1528 by an420eth. Closes #517. Improves _strategy_block_anchor in fuzzy_match.py: - Add unicode normalization (smart quotes, em/en-dashes, ellipsis, non-breaking spaces → ASCII) so LLM-produced unicode artifacts don't break anchor line matching - Lower thresholds: 0.10 for unique matches (was 0.70), 0.30 for multiple candidates — if first/last lines match exactly, the block is almost certainly correct - Use original (non-normalized) content for offset calculation to preserve correct character positions Tested: 3 new scenarios fixed (em-dash anchors, non-breaking space anchors, very-low-similarity unique matches), zero regressions on all 9 existing fuzzy match tests. Co-authored-by: an420eth <an420eth@users.noreply.github.com> * feat(cli): add file path autocomplete in the input prompt (#1545) When typing a path-like token (./ ../ ~/ / or containing /), the CLI now shows filesystem completions in the dropdown menu. Directories show a trailing slash and 'dir' label; files show their size. Completions are case-insensitive and capped at 30 entries. Triggered by tokens like: edit ./src/ma → shows ./src/main.py, ./src/manifest.json, ... check ~/doc → shows ~/docs/, ~/documents/, ... read /etc/hos → shows /etc/hosts, /etc/hostname, ... open tools/reg → shows tools/registry.py Slash command autocomplete (/help, /model, etc.) is unaffected — it still triggers when the input starts with /. Inspired by OpenCode PR #145 (file path completion menu). Implementation: - hermes_cli/commands.py: _extract_path_word() detects path-like tokens, _path_completions() yields filesystem Completions with size labels, get_completions() routes to paths vs slash commands - tests/hermes_cli/test_path_completion.py: 26 tests covering path extraction, prefix filtering, directory markers, home expansion, case-insensitivity, integration with slash commands * feat(privacy): redact PII from LLM context when privacy.redact_pii is enabled Add privacy.redact_pii config option (boolean, default false). When enabled, the gateway redacts personally identifiable information from the system prompt before sending it to the LLM provider: - Phone numbers (user IDs on WhatsApp/Signal) → hashed to user_<sha256> - User IDs → hashed to user_<sha256> - Chat IDs → numeric portion hashed, platform prefix preserved - Home channel IDs → hashed - Names/usernames → NOT affected (user-chosen, publicly visible) Hashes are deterministic (same user → same hash) so the model can still distinguish users in group chats. Routing and delivery use the original values internally — redaction only affects LLM context. Inspired by OpenClaw PR #47959. * fix(privacy): skip PII redaction on Discord/Slack (mentions need real IDs) Discord uses <@user_id> for mentions and Slack uses <@U12345> — the LLM needs the real ID to tag users. Redaction now only applies to WhatsApp, Signal, and Telegram where IDs are pure routing metadata. Add 4 platform-specific tests covering Discord, WhatsApp, Signal, Slack. * feat: smart approvals + /stop command (inspired by OpenAI Codex) * feat: smart approvals — LLM-based risk assessment for dangerous commands Adds a 'smart' approval mode that uses the auxiliary LLM to assess whether a flagged command is genuinely dangerous or a false positive, auto-approving low-risk commands without prompting the user. Inspired by OpenAI Codex's Smart Approvals guardian subagent (openai/codex#13860). Config (config.yaml): approvals: mode: manual # manual (default), smart, off Modes: - manual — current behavior, always prompt the user - smart — aux LLM evaluates risk: APPROVE (auto-allow), DENY (block), or ESCALATE (fall through to manual prompt) - off — skip all approval prompts (equivalent to --yolo) When smart mode auto-approves, the pattern gets session-level approval so subsequent uses of the same pattern don't trigger another LLM call. When it denies, the command is blocked without user prompt. When uncertain, it escalates to the normal manual approval flow. The LLM prompt is carefully scoped: it sees only the command text and the flagged reason, assesses actual risk vs false positive, and returns a single-word verdict. * feat: make smart approval model configurable via config.yaml Adds auxiliary.approval section to config.yaml with the same provider/model/base_url/api_key pattern as other aux tasks (vision, web_extract, compression, etc.). Config: auxiliary: approval: provider: auto model: '' # fast/cheap model recommended base_url: '' api_key: '' Bridged to env vars in both CLI and gateway paths so the aux client picks them up automatically. * feat: add /stop command to kill all background processes Adds a /stop slash command that kills all running background processes at once. Currently users have to process(list) then process(kill) for each one individually. Inspired by OpenAI Codex's separation of interrupt (Ctrl+C stops current turn) from /stop (cleans up background processes). See openai/codex#14602. Ctrl+C continues to only interrupt the active agent turn — background dev servers, watchers, etc. are preserved. /stop is the explicit way to clean them all up. * feat: first-class plugin architecture + hide status bar cost by default (#1544) The persistent status bar now shows context %, token counts, and duration but NOT $ cost by default. Cost display is opt-in via: display: show_cost: true in config.yaml, or: hermes config set display.show_cost true The /usage command still shows full cost breakdown since the user explicitly asked for it — this only affects the always-visible bar. Status bar without cost: ⚕ claude-sonnet-4 │ 12K/200K │ 6% │ 15m Status bar with show_cost: true: ⚕ claude-sonnet-4 │ 12K/200K │ 6% │ $0.06 │ 15m * feat: improve memory prioritization + aggressive skill updates (inspired by OpenAI Codex) * feat: improve memory prioritization — user preferences over procedural knowledge Inspired by OpenAI Codex's memory prompt improvements (openai/codex#14493) which focus memory writes on user preferences and recurring patterns rather than procedural task details. Key insight: 'Optimize for reducing future user steering — the most valuable memory prevents the user from having to repeat themselves.' Changes: - MEMORY_GUIDANCE (prompt_builder.py): added prioritization hierarchy and the core principle about reducing user steering - MEMORY_SCHEMA (memory_tool.py): reordered WHEN TO SAVE list to put corrections first, added explicit PRIORITY guidance - Memory nudge (run_agent.py): now asks specifically about preferences, corrections, and workflow patterns instead of generic 'anything' - Memory flush (run_agent.py): now instructs to prioritize user preferences and corrections over task-specific details * feat: more aggressive skill creation and update prompting Press harder on skill updates — the agent should proactively patch skills when it encounters issues during use, not wait to be asked. Changes: - SKILLS_GUIDANCE: 'consider saving' → 'save'; added explicit instruction to patch skills immediately when found outdated/wrong - Skills header: added instruction to update loaded skills before finishing if they had missing steps or wrong commands - Skill nudge: more assertive ('save the approach' not 'consider saving'), now also prompts for updating existing skills used in the task - Skill nudge interval: lowered default from 15 to 10 iterations - skill_manage schema: added 'patch it immediately' to update triggers * feat: first-class plugin architecture (#1555) Plugin system for extending Hermes with custom tools, hooks, and integrations — no source code changes required. Core system (hermes_cli/plugins.py): - Plugin discovery from ~/.hermes/plugins/, .hermes/plugins/, and pip entry_points (hermes_agent.plugins group) - PluginContext with register_tool() and register_hook() - 6 lifecycle hooks: pre/post tool_call, pre/post llm_call, on_session_start/end - Namespace package handling for relative imports in plugins - Graceful error isolation — broken plugins never crash the agent Integration (model_tools.py): - Plugin discovery runs after built-in + MCP tools - Plugin tools bypass toolset filter via get_plugin_tool_names() - Pre/post tool call hooks fire in handle_function_call() CLI: - /plugins command shows loaded plugins, tool counts, status - Added to COMMANDS dict for autocomplete Docs: - Getting started guide (build-a-hermes-plugin.md) — full tutorial building a calculator plugin step by step - Reference page (features/plugins.md) — quick overview + tables - Covers: file structure, schemas, handlers, hooks, data files, bundled skills, env var gating, pip distribution, common mistakes Tests: 16 tests covering discovery, loading, hooks, tool visibility. * fix: hermes update causes dual gateways on macOS (launchd) Three bugs worked together to create the dual-gateway problem: 1. cmd_update only checked systemd for gateway restart, completely ignoring launchd on macOS. After killing the PID it would print 'Restart it with: hermes gateway run' even when launchd was about to auto-respawn the process. 2. launchd's KeepAlive.SuccessfulExit=false respawns the gateway after SIGTERM (non-zero exit), so the user's manual restart created a second instance. 3. The launchd plist lacked --replace (systemd had it), so the respawned gateway didn't kill stale instances on startup. Fixes: - Add --replace to launchd ProgramArguments (matches systemd) - Add launchd detection to cmd_update's auto-restart logic - Print 'auto-restart via launchd' instead of manual restart hint * fix: add launchd plist auto-refresh + explicit restart in cmd_update Two integration issues with the initial fix: 1. Existing macOS users with old plist (no --replace) would never get the fix until manual uninstall/reinstall. Added refresh_launchd_plist_if_needed() — mirrors the existing refresh_systemd_unit_if_needed(). Called from launchd_start(), launchd_restart(), and cmd_update. 2. cmd_update relied on KeepAlive respawn after SIGTERM rather than explicit launchctl stop/start. This caused races: launchd would respawn the old process before the PID file was cleaned up. Now does explicit stop+start (matching how systemd gets an explicit systemctl restart), with plist refresh first so the new --replace flag is picked up. --------- Co-authored-by: Ninja <ninja@local> Co-authored-by: alireza78a <alireza78a@users.noreply.github.com> Co-authored-by: Oktay Aydin <113846926+aydnOktay@users.noreply.github.com> Co-authored-by: JP Lew <polydegen@protonmail.com> Co-authored-by: an420eth <an420eth@users.noreply.github.com> |
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Teknium
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25e53f3c1a | fix(custom-endpoint): verify /models and suggest working /v1 base URL (#1480) | ||
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0xbyt4
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7f485f588e | fix(test): provide required model config keys to prevent KeyError on base_url | ||
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0xbyt4
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f8e4233e67 | fix(test): isolate codex provider tests from local env leaking API keys | ||
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Adavya Sharma
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358dab52ce | fix: sanitize chat payloads and provider precedence | ||
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teknium1
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9302690e1b |
refactor: remove LLM_MODEL env var dependency — config.yaml is sole source of truth
Model selection now comes exclusively from config.yaml (set via
'hermes model' or 'hermes setup'). The LLM_MODEL env var is no longer
read or written anywhere in production code.
Why: env vars are per-process/per-user and would conflict in
multi-agent or multi-tenant setups. Config.yaml is file-based and
can be scoped per-user or eventually per-session.
Changes:
- cli.py: Read model from CLI_CONFIG only, not LLM_MODEL/OPENAI_MODEL
- hermes_cli/auth.py: _save_model_choice() no longer writes LLM_MODEL
to .env
- hermes_cli/setup.py: Remove 12 save_env_value('LLM_MODEL', ...)
calls from all provider setup flows
- gateway/run.py: Remove LLM_MODEL fallback (HERMES_MODEL still works
for gateway process runtime)
- cron/scheduler.py: Same
- agent/auxiliary_client.py: Remove LLM_MODEL from custom endpoint
model detection
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teknium1
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f996d7950b |
fix: trust user-selected models with OpenAI Codex provider
The Codex model normalization was rejecting any model without 'codex' in its name, forcing a fallback to gpt-5.3-codex. This blocked models like gpt-5.4 that the Codex API actually supports. The fix simplifies _normalize_model_for_provider() to two operations: 1. Strip provider prefixes (API needs bare slugs) 2. Replace the *untouched default* model with a Codex-compatible one If the user explicitly chose a model — any model — we trust them and let the API be the judge. No allowlists, no slug checks. Also removes the 'codex not in slug' filter from _read_cache_models() so the local cache preserves all API-available models. Inspired by OpenClaw's approach which explicitly lists non-codex models (gpt-5.4, gpt-5.2) as valid Codex models. |
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teknium1
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95b1130485 |
fix: normalize incompatible models when provider resolves to Codex
When _ensure_runtime_credentials() resolves the provider to openai-codex, check if the active model is Codex-compatible. If not (e.g. the default anthropic/claude-opus-4.6), swap it for the best available Codex model. Also strips provider prefixes the Codex API rejects (openai/gpt-5.3-codex → gpt-5.3-codex). Adds _model_is_default flag so warnings are only shown when the user explicitly chose an incompatible model (not when it's the config default). Fixes #651. Co-inspired-by: stablegenius49 (PR #661) Co-inspired-by: teyrebaz33 (PR #696) |
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George Pickett
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609b19b630 | Add OpenAI Codex provider runtime and responses integration (without .agent/PLANS.md) |