97 lines
2.8 KiB
Markdown
97 lines
2.8 KiB
Markdown
# Simple ReAct Agent for Log Analysis
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This directory contains a simple ReAct (Reasoning and Acting) agent implementation for log analysis and system administration tasks.
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## Overview
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The simple ReAct agent follows a straightforward pattern:
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1. **Receives** user input
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2. **Reasons** about what tools to use
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3. **Acts** by executing tools when needed
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4. **Responds** with the final result
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## Features
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- **Single Agent**: One agent handles all tasks
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- **Shell Access**: Execute system commands safely
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- **Log Analysis**: Specialized log analysis capabilities
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- **Interactive Chat**: Stream responses with tool usage visibility
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- **Conversation History**: Maintains context across interactions
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## Architecture
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```
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User Input → ReAct Agent → Tools (Shell + Log Analyzer) → Response
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```
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## Files
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- `main.py`: Main application with ReAct agent implementation
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- `custom_tools/`: Directory containing custom tools (poem generation tool)
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## Tools Available
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1. **Shell Tool**: Execute system commands
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- System monitoring (`top`, `ps`, `df`, etc.)
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- File operations
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- Network diagnostics
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2. **Poem Tool**: Generate beautiful poems with different themes:
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- `nature`: Poems about nature and the environment
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- `tech`: Poems about technology and programming
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- `motivational`: Inspirational and motivational poems
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- `friendship`: Poems about friendship and relationships
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- `random`: Randomly selects from any available poem type
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## Usage
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```bash
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cd simple-react-agent
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python main.py
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```
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### Example Interactions
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```
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User: Analyze the Apache logs for error patterns
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Agent: 🔧 Using tool: analyze_log_file
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Args: {'file_path': 'Apache/Apache_2k.log', 'analysis_type': 'error_patterns'}
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📋 Tool result: Found 15 error patterns in Apache logs...
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User: Check disk usage on the system
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Agent: 🔧 Using tool: shell
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Args: {'command': 'df -h'}
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📋 Tool result: Filesystem usage information...
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```
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## Pros and Cons
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### ✅ Pros
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- **Simple to understand**: Single agent, clear flow
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- **Easy to debug**: Linear execution path
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- **Quick setup**: Minimal configuration required
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- **Resource efficient**: Lower computational overhead
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- **Good for**: Simple tasks, learning, rapid prototyping
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### ❌ Cons
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- **Limited specialization**: One agent handles everything
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- **No parallel processing**: Sequential tool execution
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- **Scaling challenges**: Complex tasks may overwhelm single agent
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- **Less sophisticated**: No coordination between specialized experts
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## When to Use
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Choose the simple ReAct agent when:
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- You need a straightforward log analysis tool
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- Your use cases are relatively simple
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- You want to understand LangGraph basics
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- Resource usage is a concern
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- You prefer simplicity over sophistication
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## Requirements
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```bash
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pip install langchain-openai langgraph langchain-community
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export OPENAI_API_KEY="your-api-key"
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```
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