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44 lines
1.9 KiB
Markdown
44 lines
1.9 KiB
Markdown
# Project Brief: Hermes-Agent
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## Overview
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Hermes-Agent is an AI agent harness for LLMs with advanced tool-calling capabilities, featuring a flexible toolsets system for organizing and managing tools. Named after Hermes, the Greek messenger god, it serves as a bridge between human intent and AI-powered task execution.
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## Core Requirements
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### Primary Goals
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1. **Interactive CLI Experience** - Beautiful terminal interface with animated feedback, personalities, and session management
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2. **Flexible Tool System** - Modular tools organized into logical toolsets for different use cases
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3. **Batch Processing** - Process multiple prompts in parallel with checkpointing and statistics
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4. **Multi-Backend Support** - Support for local, Docker, Singularity, Modal, and SSH terminal backends
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5. **Training Data Generation** - Save conversation trajectories in formats suitable for LLM fine-tuning
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### Target Users
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- AI researchers generating training data
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- Developers needing an AI assistant with tool access
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- MLOps practitioners automating workflows
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- Anyone needing a powerful CLI-based AI agent
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## Scope
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### In Scope
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- Interactive CLI with rich formatting and kawaii-style feedback
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- Web tools (search, extract, crawl via Firecrawl)
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- Terminal tools (command execution across multiple backends)
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- Browser automation (via agent-browser + Browserbase)
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- Vision tools (image analysis)
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- Image generation (FLUX via FAL.ai)
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- Mixture-of-Agents reasoning
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- Skills system for on-demand knowledge
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- Batch processing with parallel workers
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- Trajectory compression for training
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### Out of Scope (Current)
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- Proactive suggestions (agent only runs on request)
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- Clipboard integration (no local system access)
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- Real-time streaming of thinking/reasoning (deferred)
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## Success Metrics
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- Clean, maintainable tool architecture
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- Reliable tool execution with proper error handling
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- Efficient context management for long conversations
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- High-quality trajectory data for training
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