File size: 3,563 Bytes
a34857f a0583b5 a34857f a0583b5 a34857f a0583b5 a34857f a0583b5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | ---
title: "🦅 Multeclaw"
emoji: 🦅
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: "6.13.0"
app_file: app.py
pinned: true
license: mit
short_description: Multi-model AI agent with GPT, Claude, Llama, Groq
tags:
- agent
- multi-model
- chat
- tools
- openai
- anthropic
- llama
- mistral
---
# 🦅 Multeclaw — Multi-Model AI Agent System
A complete AI agent framework connecting **GPT**, **Claude**, **Llama**, **Mistral**, **Qwen**, **Groq**, and **Ollama** through a single unified interface with built-in tool execution, multi-step planning, and safety layers.
## 🏗️ Architecture
| Component | Role |
|-----------|------|
| **Router** | Classifies tasks → direct, tool-assisted, multi-step, code, analysis |
| **Planner** | Decomposes complex objectives into executable step sequences |
| **LLM Client** | Unified streaming interface across 5 providers |
| **Executor** | Runs LLM completions and tool calls |
| **Memory** | Tracks conversation history, tool results, and session context |
| **Tool System** | Sandboxed calculator, code execution, file I/O |
| **Safety Layer** | Input content filtering |
| **Repair Loop** | Retries failed tool calls with error context |
## 🤖 Supported Providers & Models
| Provider | Models | Key Feature |
|----------|--------|-------------|
| **OpenAI** | GPT-4o, GPT-4o Mini, GPT-4 Turbo | Strong reasoning, tool calling |
| **Anthropic** | Claude 4 Opus, Claude 4 Sonnet, Claude 3.5 Haiku | Deep analysis, 200K context |
| **HuggingFace** | Llama 3 8B, Qwen 2.5 72B, Mistral 7B | Open models via inference API |
| **Groq** | Llama 3 70B, Mixtral 8x7B | Ultra-fast inference |
| **Ollama** | Any local model | Privacy, offline use |
## 🔄 Agent Loops
1. **Reasoning Loop** — LLM processes the request with full conversation context
2. **Tool Loop** — LLM decides to call tools, results are fed back iteratively
3. **Planning Loop** — Complex tasks auto-decomposed into steps, executed sequentially
4. **Repair Loop** — Failed operations retried with error context
## 🛠️ Built-in Tools
- **Calculator** — Safe math evaluation with Python math syntax
- **Code Executor** — Sandboxed Python execution with timeout
- **File Reader/Writer** — Safe file I/O operations
- **Web Search** — (Placeholder for integration)
## 🚀 Quick Start
1. Go to the **🔑 Settings** tab
2. Enter your API key(s) for the provider(s) you want to use
3. Go to the **💬 Chat** tab
4. Select a model from the dropdown
5. Start chatting!
## 🎭 Personas
- **Multeclaw Agent** — General-purpose AI agent
- **Code Expert** — Senior software engineer
- **Research Analyst** — Thorough research analysis
- **Creative Writer** — Vivid, engaging writing
- **Data Scientist** — Rigorous data analysis
- **Custom** — Your own system prompt
## 📁 Project Structure
```
multeclaw/
├── __init__.py # Package exports
├── config.py # Model registry, prompts, tools, agent config
├── llm_client.py # Unified multi-provider LLM client
├── agent.py # Agent core: router, planner, executor, memory, safety
└── ui.py # Gradio UI with 6 tabs
app.py # Entry point
requirements.txt # Dependencies
```
## 🛡️ Safety
- Input content filtering blocks harmful requests
- Code execution sandboxed with 30s timeout
- API keys stored in-memory only, never persisted
- File operations restricted to safe paths
- Math evaluation uses allowlisted functions only
|