docs: stabilize website diagrams
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teknium1
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18 changed files with 1504 additions and 112 deletions
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@ -26,7 +26,7 @@ Make it a **Tool** when:
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Bundled skills live in `skills/` organized by category. Official optional skills use the same structure in `optional-skills/`:
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```
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```text
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skills/
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├── research/
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│ └── arxiv/
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@ -28,34 +28,48 @@ The Python environment framework documented here lives under the repo's `environ
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The environment system is built on a three-layer inheritance chain:
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```
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Atropos Framework
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┌───────────────────────┐
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│ BaseEnv │ (atroposlib)
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│ - Server management │
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│ - Worker scheduling │
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│ - Wandb logging │
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│ - CLI (serve/process/ │
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│ evaluate) │
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└───────────┬───────────┘
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│ inherits
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┌───────────┴───────────┐
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│ HermesAgentBaseEnv │ environments/hermes_base_env.py
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│ - Terminal backend │
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│ - Tool resolution │
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│ - Agent loop engine │
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│ - ToolContext │
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└───────────┬───────────┘
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│ inherits
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┌─────────────────────┼─────────────────────┐
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│ │ │
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TerminalTestEnv HermesSweEnv TerminalBench2EvalEnv
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(stack testing) (SWE training) (benchmark eval)
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│
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┌────────┼────────┐
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│ │
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TBLiteEvalEnv YCBenchEvalEnv
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(fast benchmark) (long-horizon)
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```mermaid
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classDiagram
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class BaseEnv {
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Server management
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Worker scheduling
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Wandb logging
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CLI: serve / process / evaluate
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}
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class HermesAgentBaseEnv {
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Terminal backend configuration
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Tool resolution
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Agent loop engine
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ToolContext access
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}
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class TerminalTestEnv {
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Stack testing
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}
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class HermesSweEnv {
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SWE training
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}
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class TerminalBench2EvalEnv {
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Benchmark evaluation
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}
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class TBLiteEvalEnv {
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Fast benchmark
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}
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class YCBenchEvalEnv {
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Long-horizon benchmark
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}
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BaseEnv <|-- HermesAgentBaseEnv
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HermesAgentBaseEnv <|-- TerminalTestEnv
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HermesAgentBaseEnv <|-- HermesSweEnv
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HermesAgentBaseEnv <|-- TerminalBench2EvalEnv
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TerminalBench2EvalEnv <|-- TBLiteEvalEnv
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TerminalBench2EvalEnv <|-- YCBenchEvalEnv
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```
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### BaseEnv (Atropos)
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@ -45,27 +45,8 @@ hermes -w -q "Fix issue #123" # Single query in worktree
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## Interface Layout
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```text
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┌─────────────────────────────────────────────────┐
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│ HERMES-AGENT ASCII Logo │
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│ ┌─────────────┐ ┌────────────────────────────┐ │
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│ │ Caduceus │ │ Model: claude-sonnet-4 │ │
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│ │ ASCII Art │ │ Terminal: local │ │
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│ │ │ │ Working Dir: /home/user │ │
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│ │ │ │ Available Tools: 19 │ │
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│ │ │ │ Available Skills: 12 │ │
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│ └─────────────┘ └────────────────────────────┘ │
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├─────────────────────────────────────────────────┤
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│ Conversation output scrolls here... │
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│ │
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│ (◕‿◕✿) 🧠 pondering... (2.3s) │
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│ ✧٩(ˊᗜˋ*)و✧ got it! (2.3s) │
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│ │
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│ Assistant: Hello! How can I help you today? │
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├─────────────────────────────────────────────────┤
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│ ❯ [Fixed input area at bottom] │
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└─────────────────────────────────────────────────┘
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```
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<img className="docs-terminal-figure" src="/img/docs/cli-layout.svg" alt="Stylized preview of the Hermes CLI layout showing the banner, conversation area, and fixed input prompt." />
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<p className="docs-figure-caption">The Hermes CLI banner, conversation stream, and fixed input prompt rendered as a stable docs figure instead of fragile text art.</p>
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The welcome banner shows your model, terminal backend, working directory, available tools, and installed skills at a glance.
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@ -100,7 +100,7 @@ In the current implementation, distributions assign a probability to **each indi
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All output goes to `data/<run_name>/`:
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```
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```text
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data/my_run/
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├── trajectories.jsonl # Combined final output (all batches merged)
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├── batch_0.jsonl # Individual batch results
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@ -103,7 +103,7 @@ Context files are loaded by `build_context_files_prompt()` in `agent/prompt_buil
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The final prompt section looks roughly like:
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```
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```text
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# Project Context
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The following project context files have been loaded and should be followed:
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@ -207,16 +207,17 @@ honcho: {}
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Honcho context is fetched asynchronously to avoid blocking the response path:
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```
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Turn N:
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user message
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→ consume cached context (from previous turn's background fetch)
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→ inject into system prompt (user representation, AI representation, dialectic)
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→ LLM call
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→ response
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→ fire background fetch for next turn
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→ fetch context ─┐
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→ fetch dialectic ─┴→ cache for Turn N+1
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```mermaid
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flowchart TD
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user["User message"] --> cache["Consume cached Honcho context<br/>from the previous turn"]
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cache --> prompt["Inject user, AI, and dialectic context<br/>into the system prompt"]
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prompt --> llm["LLM call"]
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llm --> response["Assistant response"]
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response --> fetch["Start background fetch for Turn N+1"]
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fetch --> ctx["Fetch context"]
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fetch --> dia["Fetch dialectic"]
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ctx --> next["Cache for the next turn"]
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dia --> next
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```
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Turn 1 is a cold start (no cache). All subsequent turns consume cached results with zero HTTP latency on the response path. The system prompt on turn 1 uses only static context to preserve prefix cache hits at the LLM provider.
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@ -12,7 +12,7 @@ The hooks system lets you run custom code at key points in the agent lifecycle
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Each hook is a directory under `~/.hermes/hooks/` containing two files:
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```
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```text
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~/.hermes/hooks/
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└── my-hook/
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├── HOOK.yaml # Declares which events to listen for
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@ -174,21 +174,17 @@ The training loop:
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## Architecture Diagram
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```
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┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
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│ Atropos API │◄────│ Environment │────►│ OpenAI/sglang │
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│ (run-api) │ │ (BaseEnv impl) │ │ Inference API │
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│ Port 8000 │ │ │ │ Port 8001 │
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└────────┬────────┘ └──────────────────┘ └────────┬────────┘
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│ │
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│ Batches (tokens + scores + logprobs) │
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│ │
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▼ │
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┌─────────────────┐ │
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│ Tinker Trainer │◄──────────────────────────────────────┘
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│ (LoRA training) │ Serves inference via FastAPI
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│ + FastAPI │ Trains via Tinker ServiceClient
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└─────────────────┘
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```mermaid
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flowchart LR
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api["Atropos API<br/>run-api<br/>port 8000"]
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env["Environment<br/>BaseEnv implementation"]
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infer["OpenAI / sglang<br/>inference API<br/>port 8001"]
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trainer["Tinker Trainer<br/>LoRA training + FastAPI"]
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env <--> api
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env --> infer
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api -->|"batches: tokens, scores, logprobs"| trainer
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trainer -->|"serves inference"| infer
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```
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## Creating Custom Environments
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@ -140,7 +140,7 @@ When a missing value is encountered, Hermes asks for it securely only when the s
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## Skill Directory Structure
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```
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```text
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~/.hermes/skills/ # Single source of truth
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├── mlops/ # Category directory
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│ ├── axolotl/
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@ -12,29 +12,33 @@ For the full voice feature set — including CLI microphone mode, spoken replies
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## Architecture
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```text
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┌───────────────────────────────────────────────────────────────────────────────────────┐
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│ Hermes Gateway │
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├───────────────────────────────────────────────────────────────────────────────────────┤
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│ │
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│ ┌──────────┐ ┌─────────┐ ┌──────────┐ ┌───────┐ ┌───────┐ ┌───────┐ ┌────┐ │
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│ │ Telegram │ │ Discord │ │ WhatsApp │ │ Slack │ │Signal │ │ Email │ │ HA │ │
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│ │ Adapter │ │ Adapter │ │ Adapter │ │Adapter│ │Adapter│ │Adapter│ │Adpt│ │
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│ └────┬─────┘ └────┬────┘ └────┬─────┘ └──┬────┘ └──┬────┘ └──┬────┘ └─┬──┘ │
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│ │ │ │ │ │ │ │ │
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│ └─────────────┴───────────┴───────────┴─────────┴─────────┴────────┘ │
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│ │ │
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│ ┌────────▼────────┐ │
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│ │ Session Store │ │
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│ │ (per-chat) │ │
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│ └────────┬────────┘ │
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│ │ │
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│ ┌────────▼────────┐ │
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│ │ AIAgent │ │
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│ │ (run_agent) │ │
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│ └─────────────────┘ │
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│ │
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└───────────────────────────────────────────────────────────────────────────────────────┘
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```mermaid
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flowchart TB
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subgraph Gateway["Hermes Gateway"]
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subgraph Adapters["Platform adapters"]
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tg[Telegram]
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dc[Discord]
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wa[WhatsApp]
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sl[Slack]
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sig[Signal]
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em[Email]
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ha[Home Assistant]
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end
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store["Session store<br/>per chat"]
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agent["AIAgent<br/>run_agent.py"]
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cron["Cron scheduler<br/>ticks every 60s"]
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end
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tg --> store
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dc --> store
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wa --> store
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sl --> store
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sig --> store
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em --> store
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ha --> store
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store --> agent
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cron --> store
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```
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Each platform adapter receives messages, routes them through a per-chat session store, and dispatches them to the AIAgent for processing. The gateway also runs the cron scheduler, ticking every 60 seconds to execute any due jobs.
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@ -88,15 +88,8 @@ Session IDs are shown when you exit a CLI session, and can be found with `hermes
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When you resume a session, Hermes displays a compact recap of the previous conversation in a styled panel before the input prompt:
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```text
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╭─────────────────────────── Previous Conversation ────────────────────────────╮
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│ ● You: What is Python? │
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│ ◆ Hermes: Python is a high-level programming language. │
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│ ● You: How do I install it? │
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│ ◆ Hermes: [3 tool calls: web_search, web_extract, terminal] │
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│ ◆ Hermes: You can download Python from python.org... │
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╰──────────────────────────────────────────────────────────────────────────────╯
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```
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<img className="docs-terminal-figure" src="/img/docs/session-recap.svg" alt="Stylized preview of the Previous Conversation recap panel shown when resuming a Hermes session." />
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<p className="docs-figure-caption">Resume mode shows a compact recap panel with recent user and assistant turns before returning you to the live prompt.</p>
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The recap:
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- Shows **user messages** (gold `●`) and **assistant responses** (green `◆`)
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