agent-zero-lite


Nameagent-zero-lite JSON
Version 1.0.12 PyPI version JSON
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home_pagehttps://github.com/frdel/agent-zero-lite
SummaryLightweight Python AI Agent Framework with Web UI
upload_time2025-08-06 07:19:12
maintainerNone
docs_urlNone
authorAgent Zero Community
requires_python>=3.8
licenseMIT
keywords ai agent llm python automation web-ui litellm openai anthropic
VCS
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requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # Agent Zero Lite

A lightweight, cross-platform implementation of Agent Zero that maintains core functionality while reducing complexity and dependencies.

## Features

✅ **Full LiteLLM Support** - 100+ AI providers (OpenAI, Anthropic, Google, local models, etc.)  
✅ **Web UI** - Complete interface at localhost:50001  
✅ **Vector Memory** - FAISS-based persistent memory  
✅ **Document RAG** - PDF, text, and document processing  
✅ **Multi-Agent** - Superior/subordinate agent hierarchy  
✅ **MCP Client** - Model Context Protocol integration  
✅ **Local Execution** - Python, Node.js, and terminal  
✅ **Tunneling** - Remote access support  
✅ **File Management** - Work directory browser  

## Removed from Full Version

❌ Browser automation (Playwright)  
❌ Docker/SSH execution  
❌ Speech processing (STT/TTS)  
❌ Task scheduling  
❌ Backup/restore system  
❌ Web search tools  

## Quick Start

1. **Install dependencies:**
   ```bash
   pip install -r requirements.txt
   ```

2. **Configure environment:**
   ```bash
   cp .env.example .env
   # Edit .env with your API keys
   ```

3. **Start the Web UI:**
   ```bash
   python run_ui.py
   ```

4. **Open browser:**
   ```
   http://localhost:50001
   ```

## Configuration

### Minimal Setup
Set at least one LLM provider in `.env`:

```bash
# OpenAI
OPENAI_API_KEY=sk-...

# Or Anthropic
ANTHROPIC_API_KEY=sk-ant-...

# Or local Ollama
CHAT_MODEL_PROVIDER=ollama
CHAT_MODEL_NAME=llama3.1:8b
OLLAMA_API_BASE=http://localhost:11434
```

### Full Configuration
See `.env.example` for all available options including:
- All 100+ LiteLLM providers
- Model configurations  
- Rate limiting settings
- MCP server integration
- Memory and knowledge settings

## Supported Models

Agent Zero Lite supports **all LiteLLM providers**:

### Commercial APIs
- **OpenAI:** GPT-4o, GPT-4, GPT-3.5, etc.
- **Anthropic:** Claude 3.5 Sonnet, Claude 3 Opus, etc.
- **Google:** Gemini 1.5 Pro, Gemini 1.5 Flash, etc.
- **Groq:** Llama 3.1, Mixtral, etc. (fast inference)
- **Together AI:** Llama, Mistral, etc.
- **Mistral AI:** Mistral Large, Mistral 7B, etc.
- **Cohere:** Command R+, Command Light, etc.

### Local Models
- **Ollama:** Any local model (llama3.1, mistral, etc.)
- **LM Studio:** Local model server
- **Text Generation WebUI:** Local inference
- **VLLM:** High-performance inference server

### Enterprise
- **Azure OpenAI:** Enterprise GPT models
- **AWS Bedrock:** Claude, Titan, etc.
- **Google Vertex AI:** Enterprise Gemini
- **Hugging Face:** Hosted models

## Usage Examples

### Basic Chat
```python
from agent import AgentContext
import initialize

# Initialize agent
config = initialize.initialize_agent()
context = AgentContext(config)

# Send message
response = context.communicate("Hello, what can you help me with?")
```

### Code Execution
The agent can execute Python, Node.js, and terminal commands:

```
User: "Create a Python script that calculates fibonacci numbers"
Agent: Uses code_execution tool to write and run Python code
```

### Document Processing
```
User: "Analyze this PDF document and summarize the key points"
Agent: Uses document_query tool to process and analyze documents
```

### Multi-Agent Collaboration
```
User: "Create a complex analysis using multiple specialized agents"
Agent: Uses call_subordinate to delegate tasks to specialized sub-agents
```

## Architecture

Agent Zero Lite maintains the core Agent Zero architecture:

- **Agent Loop:** Reason → Tool Use → Response cycle
- **Tool System:** Extensible plugin architecture  
- **Memory:** FAISS vector database for persistent memory
- **Extensions:** Hook-based system for customization
- **Prompts:** Template-based prompt management

## Development

### Adding Tools
Create new tools in `python/tools/`:

```python
from python.helpers.tool import Tool, Response

class MyTool(Tool):
    async def execute(self, **kwargs):
        # Tool logic here
        return Response(message="result", break_loop=False)
```

### Adding Extensions
Create extensions in `python/extensions/`:

```python
from python.helpers.extension import Extension

class MyExtension(Extension):
    async def execute(self, **kwargs):
        # Extension logic here
        pass
```

## Troubleshooting

### Common Issues

1. **Model not responding:** Check API keys in `.env`
2. **Port in use:** Change PORT in `.env` 
3. **Memory issues:** Reduce context length settings
4. **Missing dependencies:** Run `pip install -r requirements.txt`

### Debugging

Enable debug logging by setting:
```bash
LITELLM_LOG=DEBUG
```

## Migration

### From Full Agent Zero
1. Copy `.env` settings
2. Copy `memory/` and `knowledge/` folders  
3. Copy `work_dir/` contents
4. Remove Docker/SSH configurations

### To Full Agent Zero  
1. Install additional dependencies
2. Add Docker/SSH configurations
3. No data migration needed

## Performance

Agent Zero Lite is optimized for:
- **Startup:** ~3 seconds vs 15+ seconds
- **Memory:** ~200MB vs 1GB+ RAM usage  
- **Dependencies:** ~30 packages vs 45+ packages
- **Installation:** <2 minutes vs 10+ minutes

## License

Same as Agent Zero - check the original repository for license terms.

## Support

For issues and questions:
1. Check this README
2. Review `.env.example` configuration
3. See the original Agent Zero documentation
4. Report issues to the Agent Zero repository

            

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    "description": "# Agent Zero Lite\n\nA lightweight, cross-platform implementation of Agent Zero that maintains core functionality while reducing complexity and dependencies.\n\n## Features\n\n\u2705 **Full LiteLLM Support** - 100+ AI providers (OpenAI, Anthropic, Google, local models, etc.)  \n\u2705 **Web UI** - Complete interface at localhost:50001  \n\u2705 **Vector Memory** - FAISS-based persistent memory  \n\u2705 **Document RAG** - PDF, text, and document processing  \n\u2705 **Multi-Agent** - Superior/subordinate agent hierarchy  \n\u2705 **MCP Client** - Model Context Protocol integration  \n\u2705 **Local Execution** - Python, Node.js, and terminal  \n\u2705 **Tunneling** - Remote access support  \n\u2705 **File Management** - Work directory browser  \n\n## Removed from Full Version\n\n\u274c Browser automation (Playwright)  \n\u274c Docker/SSH execution  \n\u274c Speech processing (STT/TTS)  \n\u274c Task scheduling  \n\u274c Backup/restore system  \n\u274c Web search tools  \n\n## Quick Start\n\n1. **Install dependencies:**\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n2. **Configure environment:**\n   ```bash\n   cp .env.example .env\n   # Edit .env with your API keys\n   ```\n\n3. **Start the Web UI:**\n   ```bash\n   python run_ui.py\n   ```\n\n4. **Open browser:**\n   ```\n   http://localhost:50001\n   ```\n\n## Configuration\n\n### Minimal Setup\nSet at least one LLM provider in `.env`:\n\n```bash\n# OpenAI\nOPENAI_API_KEY=sk-...\n\n# Or Anthropic\nANTHROPIC_API_KEY=sk-ant-...\n\n# Or local Ollama\nCHAT_MODEL_PROVIDER=ollama\nCHAT_MODEL_NAME=llama3.1:8b\nOLLAMA_API_BASE=http://localhost:11434\n```\n\n### Full Configuration\nSee `.env.example` for all available options including:\n- All 100+ LiteLLM providers\n- Model configurations  \n- Rate limiting settings\n- MCP server integration\n- Memory and knowledge settings\n\n## Supported Models\n\nAgent Zero Lite supports **all LiteLLM providers**:\n\n### Commercial APIs\n- **OpenAI:** GPT-4o, GPT-4, GPT-3.5, etc.\n- **Anthropic:** Claude 3.5 Sonnet, Claude 3 Opus, etc.\n- **Google:** Gemini 1.5 Pro, Gemini 1.5 Flash, etc.\n- **Groq:** Llama 3.1, Mixtral, etc. (fast inference)\n- **Together AI:** Llama, Mistral, etc.\n- **Mistral AI:** Mistral Large, Mistral 7B, etc.\n- **Cohere:** Command R+, Command Light, etc.\n\n### Local Models\n- **Ollama:** Any local model (llama3.1, mistral, etc.)\n- **LM Studio:** Local model server\n- **Text Generation WebUI:** Local inference\n- **VLLM:** High-performance inference server\n\n### Enterprise\n- **Azure OpenAI:** Enterprise GPT models\n- **AWS Bedrock:** Claude, Titan, etc.\n- **Google Vertex AI:** Enterprise Gemini\n- **Hugging Face:** Hosted models\n\n## Usage Examples\n\n### Basic Chat\n```python\nfrom agent import AgentContext\nimport initialize\n\n# Initialize agent\nconfig = initialize.initialize_agent()\ncontext = AgentContext(config)\n\n# Send message\nresponse = context.communicate(\"Hello, what can you help me with?\")\n```\n\n### Code Execution\nThe agent can execute Python, Node.js, and terminal commands:\n\n```\nUser: \"Create a Python script that calculates fibonacci numbers\"\nAgent: Uses code_execution tool to write and run Python code\n```\n\n### Document Processing\n```\nUser: \"Analyze this PDF document and summarize the key points\"\nAgent: Uses document_query tool to process and analyze documents\n```\n\n### Multi-Agent Collaboration\n```\nUser: \"Create a complex analysis using multiple specialized agents\"\nAgent: Uses call_subordinate to delegate tasks to specialized sub-agents\n```\n\n## Architecture\n\nAgent Zero Lite maintains the core Agent Zero architecture:\n\n- **Agent Loop:** Reason \u2192 Tool Use \u2192 Response cycle\n- **Tool System:** Extensible plugin architecture  \n- **Memory:** FAISS vector database for persistent memory\n- **Extensions:** Hook-based system for customization\n- **Prompts:** Template-based prompt management\n\n## Development\n\n### Adding Tools\nCreate new tools in `python/tools/`:\n\n```python\nfrom python.helpers.tool import Tool, Response\n\nclass MyTool(Tool):\n    async def execute(self, **kwargs):\n        # Tool logic here\n        return Response(message=\"result\", break_loop=False)\n```\n\n### Adding Extensions\nCreate extensions in `python/extensions/`:\n\n```python\nfrom python.helpers.extension import Extension\n\nclass MyExtension(Extension):\n    async def execute(self, **kwargs):\n        # Extension logic here\n        pass\n```\n\n## Troubleshooting\n\n### Common Issues\n\n1. **Model not responding:** Check API keys in `.env`\n2. **Port in use:** Change PORT in `.env` \n3. **Memory issues:** Reduce context length settings\n4. **Missing dependencies:** Run `pip install -r requirements.txt`\n\n### Debugging\n\nEnable debug logging by setting:\n```bash\nLITELLM_LOG=DEBUG\n```\n\n## Migration\n\n### From Full Agent Zero\n1. 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