mirror of https://github.com/NousResearch/hermes-agent.git synced 2026-04-25 00:51:20 +00:00

fix(ci): resolve 4 pre-existing main failures (docs lint + 3 stale tests) (#11373 )

* docs: fix ascii-guard border alignment errors

Three docs pages had ASCII diagram boxes with off-by-one column
alignment issues that failed docs-site-checks CI:

- architecture.md: outer box is 71 cols but inner-box content lines
  and border corners were offset by 1 col, making content-line right
  border at col 70/72 while top/bottom border was at col 71. Inner
  boxes also had border corners at cols 19/36/53 but content pipes
  at cols 20/37/54. Rewrote the diagram with consistent 71-col width
  throughout, aligned inner boxes at cols 4-19, 22-37, 40-55 with
  2-space gaps and 15-space trailing padding.

- gateway-internals.md: same class of issue — outer box at 51 cols,
  inner content lines varied 52-54 cols. Rewrote with consistent
  51-col width, inner boxes at cols 4-15, 18-29, 32-43. Also
  restructured the bottom-half message flow so it's bare text
  (not half-open box cells) matching the intent of the original.

- agent-loop.md line 112-114: box 2 (API thread) content lines had
  one extra space pushing the right border to col 46 while the top
  and bottom borders of that box sat at col 45. Trimmed one trailing
  space from each of the three content lines.

All 123 docs files now pass `npm run lint:diagrams`:
  ✓ Errors: 0  (warnings: 6, non-fatal)

Pre-existing failures on main — unrelated to any open PR.

* test(setup): accept description kwarg in prompt_choice mock lambdas

setup.py's `_curses_prompt_choice` gained an optional `description`
parameter (used for rendering context hints alongside the prompt).
`prompt_choice` forwards it via keyword arg. The two existing tests
mocked `_curses_prompt_choice` with lambdas that didn't accept the
new kwarg, so the forwarded call raised TypeError.

Fix: add `description=None` to both mock lambda signatures so they
absorb the new kwarg without changing behavior.

* test(matrix): update stale audio-caching assertion

test_regular_audio_has_http_url asserted that non-voice audio
messages keep their HTTP URL and are NOT downloaded/cached. That
was true when the caching code only triggered on
`is_voice_message`. Since bec02f37 (encrypted-media caching
refactor), matrix.py caches all media locally — photos, audio,
video, documents — so downstream tools can read them as real
files via media_urls. This applies to regular audio too.

Renamed the test to `test_regular_audio_is_cached_locally`,
flipped the assertions accordingly, and documented the
intentional behavior change in the docstring. Other tests in
the file (voice-specific caching, message-type detection,
reply-to threading) continue to pass.

* test(413): allow multi-pass preflight compression

run_agent.py's preflight compression runs up to 3 passes in a loop
for very large sessions (each pass summarizes the middle N turns,
then re-checks tokens). The loop breaks when a pass returns a
message list no shorter than its input (can't compress further).

test_preflight_compresses_oversized_history used a static mock
return value that returned the same 2 messages regardless of input,
so the loop ran pass 1 (41 -> 2) and pass 2 (2 -> 2 -> break),
making call_count == 2. The assert_called_once() assertion was
strictly wrong under the multi-pass design.

The invariant the test actually cares about is: preflight ran, and
its first invocation received the full oversized history. Replaced
the count assertion with those two invariants.

* docs: drop '...' from gateway diagram, merge side-by-side boxes

ascii-guard 2.3.0 flagged two remaining issues after the initial fix
pass:

1. gateway-internals.md L33: the '...' suffix after inner box 3's
   right border got parsed as 'extra characters after inner-box right
   border'. Dropped the '...' — the surrounding prose already conveys
   'and more platforms' without needing the visual hint.

2. agent-loop.md: ascii-guard can't cleanly parse two side-by-side
   boxes of different heights (main thread 7 rows, API thread 5 rows).
   Even equalizing heights didn't help — the linter treats the left
   box's right border as the end of the diagram. Merged into a single
   54-char-wide outer box with both threads labeled as regions inside,
   keeping the ▶ arrow to preserve the main→API flow direction.

2026-04-16 20:43:41 -07:00

16 KiB

Raw Blame History

sidebar_position	title	description
1	Architecture	Hermes Agent internals — major subsystems, execution paths, data flow, and where to read next

Architecture

This page is the top-level map of Hermes Agent internals. Use it to orient yourself in the codebase, then dive into subsystem-specific docs for implementation details.

System Overview

┌─────────────────────────────────────────────────────────────────────┐
│                        Entry Points                                  │
│                                                                      │
│  CLI (cli.py)    Gateway (gateway/run.py)    ACP (acp_adapter/)     │
│  Batch Runner    API Server                  Python Library          │
└──────────┬──────────────┬───────────────────────┬───────────────────┘
           │              │                       │
           ▼              ▼                       ▼
┌─────────────────────────────────────────────────────────────────────┐
│                     AIAgent (run_agent.py)                          │
│                                                                     │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐               │
│  │ Prompt       │  │ Provider     │  │ Tool         │               │
│  │ Builder      │  │ Resolution   │  │ Dispatch     │               │
│  │ (prompt_     │  │ (runtime_    │  │ (model_      │               │
│  │  builder.py) │  │  provider.py)│  │  tools.py)   │               │
│  └──────┬───────┘  └──────┬───────┘  └──────┬───────┘               │
│         │                 │                 │                       │
│  ┌──────┴───────┐  ┌──────┴───────┐  ┌──────┴───────┐               │
│  │ Compression  │  │ 3 API Modes  │  │ Tool Registry│               │
│  │ & Caching    │  │ chat_compl.  │  │ (registry.py)│               │
│  │              │  │ codex_resp.  │  │ 47 tools     │               │
│  │              │  │ anthropic    │  │ 19 toolsets  │               │
│  └──────────────┘  └──────────────┘  └──────────────┘               │
└─────────────────────────────────────────────────────────────────────┘
           │                                    │
           ▼                                    ▼
┌───────────────────┐              ┌──────────────────────┐
│ Session Storage   │              │ Tool Backends         │
│ (SQLite + FTS5)   │              │ Terminal (6 backends) │
│ hermes_state.py   │              │ Browser (5 backends)  │
│ gateway/session.py│              │ Web (4 backends)      │
└───────────────────┘              │ MCP (dynamic)         │
                                   │ File, Vision, etc.    │
                                   └──────────────────────┘

Directory Structure

hermes-agent/
├── run_agent.py              # AIAgent — core conversation loop (~10,700 lines)
├── cli.py                    # HermesCLI — interactive terminal UI (~10,000 lines)
├── model_tools.py            # Tool discovery, schema collection, dispatch
├── toolsets.py               # Tool groupings and platform presets
├── hermes_state.py           # SQLite session/state database with FTS5
├── hermes_constants.py       # HERMES_HOME, profile-aware paths
├── batch_runner.py           # Batch trajectory generation
│
├── agent/                    # Agent internals
│   ├── prompt_builder.py     # System prompt assembly
│   ├── context_engine.py     # ContextEngine ABC (pluggable)
│   ├── context_compressor.py # Default engine — lossy summarization
│   ├── prompt_caching.py     # Anthropic prompt caching
│   ├── auxiliary_client.py   # Auxiliary LLM for side tasks (vision, summarization)
│   ├── model_metadata.py     # Model context lengths, token estimation
│   ├── models_dev.py         # models.dev registry integration
│   ├── anthropic_adapter.py  # Anthropic Messages API format conversion
│   ├── display.py            # KawaiiSpinner, tool preview formatting
│   ├── skill_commands.py     # Skill slash commands
│   ├── memory_manager.py    # Memory manager orchestration
│   ├── memory_provider.py   # Memory provider ABC
│   └── trajectory.py         # Trajectory saving helpers
│
├── hermes_cli/               # CLI subcommands and setup
│   ├── main.py               # Entry point — all `hermes` subcommands (~6,000 lines)
│   ├── config.py             # DEFAULT_CONFIG, OPTIONAL_ENV_VARS, migration
│   ├── commands.py           # COMMAND_REGISTRY — central slash command definitions
│   ├── auth.py               # PROVIDER_REGISTRY, credential resolution
│   ├── runtime_provider.py   # Provider → api_mode + credentials
│   ├── models.py             # Model catalog, provider model lists
│   ├── model_switch.py       # /model command logic (CLI + gateway shared)
│   ├── setup.py              # Interactive setup wizard (~3,100 lines)
│   ├── skin_engine.py        # CLI theming engine
│   ├── skills_config.py      # hermes skills — enable/disable per platform
│   ├── skills_hub.py         # /skills slash command
│   ├── tools_config.py       # hermes tools — enable/disable per platform
│   ├── plugins.py            # PluginManager — discovery, loading, hooks
│   ├── callbacks.py          # Terminal callbacks (clarify, sudo, approval)
│   └── gateway.py            # hermes gateway start/stop
│
├── tools/                    # Tool implementations (one file per tool)
│   ├── registry.py           # Central tool registry
│   ├── approval.py           # Dangerous command detection
│   ├── terminal_tool.py      # Terminal orchestration
│   ├── process_registry.py   # Background process management
│   ├── file_tools.py         # read_file, write_file, patch, search_files
│   ├── web_tools.py          # web_search, web_extract
│   ├── browser_tool.py       # 10 browser automation tools
│   ├── code_execution_tool.py # execute_code sandbox
│   ├── delegate_tool.py      # Subagent delegation
│   ├── mcp_tool.py           # MCP client (~2,200 lines)
│   ├── credential_files.py   # File-based credential passthrough
│   ├── env_passthrough.py    # Env var passthrough for sandboxes
│   ├── ansi_strip.py         # ANSI escape stripping
│   └── environments/         # Terminal backends (local, docker, ssh, modal, daytona, singularity)
│
├── gateway/                  # Messaging platform gateway
│   ├── run.py                # GatewayRunner — message dispatch (~9,000 lines)
│   ├── session.py            # SessionStore — conversation persistence
│   ├── delivery.py           # Outbound message delivery
│   ├── pairing.py            # DM pairing authorization
│   ├── hooks.py              # Hook discovery and lifecycle events
│   ├── mirror.py             # Cross-session message mirroring
│   ├── status.py             # Token locks, profile-scoped process tracking
│   ├── builtin_hooks/        # Always-registered hooks
│   └── platforms/            # 18 adapters: telegram, discord, slack, whatsapp,
│                             #   signal, matrix, mattermost, email, sms,
│                             #   dingtalk, feishu, wecom, wecom_callback, weixin,
│                             #   bluebubbles, qqbot, homeassistant, webhook, api_server
│
├── acp_adapter/              # ACP server (VS Code / Zed / JetBrains)
├── cron/                     # Scheduler (jobs.py, scheduler.py)
├── plugins/memory/           # Memory provider plugins
├── plugins/context_engine/   # Context engine plugins
├── environments/             # RL training environments (Atropos)
├── skills/                   # Bundled skills (always available)
├── optional-skills/          # Official optional skills (install explicitly)
├── website/                  # Docusaurus documentation site
└── tests/                    # Pytest suite (~3,000+ tests)

Data Flow

CLI Session

User input → HermesCLI.process_input()
  → AIAgent.run_conversation()
    → prompt_builder.build_system_prompt()
    → runtime_provider.resolve_runtime_provider()
    → API call (chat_completions / codex_responses / anthropic_messages)
    → tool_calls? → model_tools.handle_function_call() → loop
    → final response → display → save to SessionDB

Gateway Message

Platform event → Adapter.on_message() → MessageEvent
  → GatewayRunner._handle_message()
    → authorize user
    → resolve session key
    → create AIAgent with session history
    → AIAgent.run_conversation()
    → deliver response back through adapter

Cron Job

Scheduler tick → load due jobs from jobs.json
  → create fresh AIAgent (no history)
  → inject attached skills as context
  → run job prompt
  → deliver response to target platform
  → update job state and next_run

Major Subsystems

Agent Loop

The synchronous orchestration engine (AIAgent in run_agent.py). Handles provider selection, prompt construction, tool execution, retries, fallback, callbacks, compression, and persistence. Supports three API modes for different provider backends.

→ Agent Loop Internals

Prompt System

Prompt construction and maintenance across the conversation lifecycle:

prompt_builder.py — Assembles the system prompt from: personality (SOUL.md), memory (MEMORY.md, USER.md), skills, context files (AGENTS.md, .hermes.md), tool-use guidance, and model-specific instructions
prompt_caching.py — Applies Anthropic cache breakpoints for prefix caching
context_compressor.py — Summarizes middle conversation turns when context exceeds thresholds

→ Prompt Assembly, Context Compression & Prompt Caching

Provider Resolution

A shared runtime resolver used by CLI, gateway, cron, ACP, and auxiliary calls. Maps (provider, model) tuples to (api_mode, api_key, base_url). Handles 18+ providers, OAuth flows, credential pools, and alias resolution.

→ Provider Runtime Resolution

Tool System

Central tool registry (tools/registry.py) with 47 registered tools across 19 toolsets. Each tool file self-registers at import time. The registry handles schema collection, dispatch, availability checking, and error wrapping. Terminal tools support 6 backends (local, Docker, SSH, Daytona, Modal, Singularity).

→ Tools Runtime

Session Persistence

SQLite-based session storage with FTS5 full-text search. Sessions have lineage tracking (parent/child across compressions), per-platform isolation, and atomic writes with contention handling.

→ Session Storage

Messaging Gateway

Long-running process with 18 platform adapters, unified session routing, user authorization (allowlists + DM pairing), slash command dispatch, hook system, cron ticking, and background maintenance.

→ Gateway Internals

Plugin System

Three discovery sources: ~/.hermes/plugins/ (user), .hermes/plugins/ (project), and pip entry points. Plugins register tools, hooks, and CLI commands through a context API. Two specialized plugin types exist: memory providers (plugins/memory/) and context engines (plugins/context_engine/). Both are single-select — only one of each can be active at a time, configured via hermes plugins or config.yaml.

→ Plugin Guide, Memory Provider Plugin

Cron

First-class agent tasks (not shell tasks). Jobs store in JSON, support multiple schedule formats, can attach skills and scripts, and deliver to any platform.

→ Cron Internals

ACP Integration

Exposes Hermes as an editor-native agent over stdio/JSON-RPC for VS Code, Zed, and JetBrains.

→ ACP Internals

RL / Environments / Trajectories

Full environment framework for evaluation and RL training. Integrates with Atropos, supports multiple tool-call parsers, and generates ShareGPT-format trajectories.

→ Environments, Benchmarks & Data Generation, Trajectories & Training Format

Design Principles

Principle	What it means in practice
Prompt stability	System prompt doesn't change mid-conversation. No cache-breaking mutations except explicit user actions (`/model`).
Observable execution	Every tool call is visible to the user via callbacks. Progress updates in CLI (spinner) and gateway (chat messages).
Interruptible	API calls and tool execution can be cancelled mid-flight by user input or signals.
Platform-agnostic core	One AIAgent class serves CLI, gateway, ACP, batch, and API server. Platform differences live in the entry point, not the agent.
Loose coupling	Optional subsystems (MCP, plugins, memory providers, RL environments) use registry patterns and check_fn gating, not hard dependencies.
Profile isolation	Each profile (`hermes -p <name>`) gets its own HERMES_HOME, config, memory, sessions, and gateway PID. Multiple profiles run concurrently.

File Dependency Chain

tools/registry.py  (no deps — imported by all tool files)
       ↑
tools/*.py  (each calls registry.register() at import time)
       ↑
model_tools.py  (imports tools/registry + triggers tool discovery)
       ↑
run_agent.py, cli.py, batch_runner.py, environments/

This chain means tool registration happens at import time, before any agent instance is created. Any tools/*.py file with a top-level registry.register() call is auto-discovered — no manual import list needed.

16 KiB Raw Blame History