Hermes
Connect Nous Research's self-improving agent to BitRouter
Hermes Integration
Quick Start
# 1. Start BitRouter with memory support
bitrouter acp --enable-memory
# 2. Configure Hermes
hermes config set backend bitrouter
hermes config set bitrouter.url http://localhost:8787
# 3. Launch with persistent memory
hermes start --memory persistentWhat You Get
- ✅ Persistent memory - Learning that survives restarts
- ✅ Multi-provider learning - Diverse model experiences
- ✅ Cost-optimized sessions - Smart routing for long runs
- ✅ Learning trajectories - Track improvement over time
- ✅ Research-ready - Batch processing and exports
Installation
Prerequisites
# Install Hermes
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
# Verify 64k+ context models available
bitrouter models list --min-context 64000Connect to BitRouter
Choose your backend:
Option 1: ACP Integration (Recommended)
hermes config set backend bitrouter
hermes config set protocol acp
hermes config set bitrouter.url http://localhost:8787
hermes start --memory persistentOption 2: Direct API
export HERMES_API_BASE=http://localhost:8787
hermes start --provider customOption 3: Multi-Backend
hermes config set backends.primary bitrouter
hermes config set backends.primary.url http://localhost:8787
hermes start --multi-backendEssential Configuration
Memory-Optimized Routing
# ~/.bitrouter/config.yaml
routes:
# Learning operations - large context
- match: "hermes/learn/*"
provider: anthropic
model: claude-3-5-sonnet-latest
options:
max_tokens: 200000
# Memory recall - fast access
- match: "hermes/recall/*"
provider: openai
model: gpt-4o
cache:
enabled: true
ttl: 3600
# Self-improvement cycles
- match: "hermes/improve/*"
provider: anthropic
model: claude-3-5-sonnet-latest
options:
temperature: 0.9Persistent Memory Setup
memory:
hermes:
type: persistent
backend: bitrouter
storage:
path: ~/.hermes/memory
encryption: true
sync:
enabled: true
interval: 300s
namespaces:
- name: general
max_size: 10MB
- name: code
max_size: 50MBLearning Cycles
learning:
cycles:
- name: "daily_review"
schedule: "0 0 * * *"
route: "hermes/learn/review"
model: claude-3-5-sonnet-latest
- name: "skill_improvement"
trigger: performance_threshold
route: "hermes/learn/skills"Common Recipes
Recipe: Research Mode
research:
enabled: true
trajectory_export: true
batch_processing: true
routing:
control: "hermes/research/control"
treatment: "hermes/research/treatment"Recipe: Multi-Platform Memory
platforms:
telegram:
route: "hermes/telegram/*"
memory_namespace: "telegram"
discord:
route: "hermes/discord/*"
memory_namespace: "discord"Recipe: Context Optimization
context:
hermes:
strategy: sliding_window
window_sizes:
small: 8192
medium: 32768
large: 128000
auto_adjust: trueBackend Options
Local Backend
# Docker backend
hermes backend start --type docker \
--routing http://localhost:8787SSH Backend
# Remote compute
hermes backend start --type ssh \
--host compute.example.com \
--tunnel 8787:8787Cloud Backends
# Modal backend
hermes backend start --type modal \
--app hermes-agent
# Singularity backend
hermes backend start --type singularity \
--image hermes.sifMonitoring
Memory Analytics
# Memory usage
bitrouter memory stats --agent hermes
# Memory patterns
bitrouter memory analyze --agent hermes --period week
# Export snapshot
bitrouter memory export --agent hermes --format jsonLearning Progress
# Track metrics
bitrouter learning progress --agent hermes
# View improvement
bitrouter learning chart --agent hermes --metric accuracy
# Export data
bitrouter learning export --agent hermes --format csvTroubleshooting
🔴 Memory Not Persisting
# Check memory backend
hermes memory status
# Verify BitRouter support
bitrouter features list | grep memory
# Test memory ops
hermes memory test --verbose🟡 Context Window Errors
# Check model capabilities
bitrouter models list --min-context 64000
# Adjust context
hermes config set max_context 128000
# Enable compression
bitrouter config set compression.enabled true🔵 Learning Loop Failures
# Check learning status
hermes learning status
# View error logs
bitrouter logs --filter "hermes/learn"
# Reset learning state
hermes learning reset --confirmAdvanced Features
Multi-Model Ensemble
ensemble:
hermes:
models:
- provider: anthropic
model: claude-3-5-sonnet-latest
weight: 0.4
- provider: openai
model: gpt-4o
weight: 0.3
- provider: google
model: gemini-1.5-pro
weight: 0.3Skills Integration
skills:
source: agentskills.io
routing:
- skill: "code-generation"
route: "hermes/skills/code"
model: deepseek-coder
- skill: "research"
route: "hermes/skills/research"
model: gpt-4oLearn More
How is this guide?
Last updated on