### Run Python Example from Examples Directory

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Execute a Python example script after navigating into the 'examples' directory. This is an alternative to running from the project root.

```bash
cd examples
python basic_usage.py
```

--------------------------------

### Run Basic Usage Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Execute the basic usage script to demonstrate fundamental MEGA-Bot operations like initializing the bot, performing simple queries, research, status checks, and getting capabilities.

```bash
python examples/basic_usage.py
```

--------------------------------

### Verify Example Scripts

Source: https://github.com/elmourabea/octogen/blob/main/coll/RELEASE_CHECKLIST.md

Run various example scripts to ensure they function correctly. These examples cover basic usage, advanced research, workflow automation, and validation.

```bash
# Verify examples
python examples/basic_usage.py
python examples/advanced_research.py
python examples/workflow_automation.py
python examples/validation_example.py
```

--------------------------------

### Custom Example Template

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

A template for creating your own custom examples using the MegaBot class. Includes setup for asynchronous operations and basic bot interaction.

```python
import asyncio
import sys
import os

# Add parent directory to path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from megabot import MegaBot

async def my_example():
    """Your custom example"""
    bot = MegaBot()
    await bot.start()
    
    # Your code here
    result = await bot.query("Your query")
    print(result)
    
    await bot.stop()

if __name__ == "__main__":
    asyncio.run(my_example())
```

--------------------------------

### Install Dependencies

Source: https://github.com/elmourabea/octogen/blob/main/coll/CONTRIBUTING.md

Install project dependencies using pip by referencing the requirements.txt file.

```bash
pip install -r requirements.txt
```

--------------------------------

### Sync Documents and Get Updates

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

This example demonstrates how to manually trigger a document synchronization and then retrieve the latest updates from integrated platforms. The `get_updates` method can be limited by a specified number of results.

```python
async def auto_update_example():
    bot = MegaBot()
    await bot.start()
    
    # Sync documents manually
    await bot.sync_documents()
    
    # Get latest updates
    updates = bot.get_updates(limit=10)
    for update in updates:
        print(f"{update['platform']}: {update['title']}")
    
    await bot.stop()
```

--------------------------------

### Set Up Environment Variables

Source: https://github.com/elmourabea/octogen/blob/main/coll/CONTRIBUTING.md

Copy the example environment file and edit it with your specific API keys and configurations.

```bash
cp .env.example .env
# Edit .env with your API keys
```

--------------------------------

### Execute Advanced Examples

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Runs advanced example scripts for research and workflow automation from the project root.

```bash
python examples/advanced_research.py
```

```bash
python examples/workflow_automation.py
```

--------------------------------

### Execute Validation Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Runs the validation example script, new in v1.1.0.

```bash
python examples/validation_example.py  # New in v1.1.0
```

--------------------------------

### MegaBot.start()

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

Starts all the necessary services for MEGA-Bot to operate.

```APIDOC
## MegaBot.start()

### Description
Starts MEGA-Bot services.

### Method
`start()`

### Parameters
None

### Request Example
```python
megabot.start()
```

### Response
None explicitly documented.
```

--------------------------------

### Run Validation Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Execute the validation example script to demonstrate input validation, query sanitization, topic validation, automatic security checks, logging configuration, and error handling.

```bash
python examples/validation_example.py
```

--------------------------------

### Copy Environment File

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Create a local environment file by copying the example environment file. This file will store your API keys and other sensitive configurations.

```bash
cp .env.example .env
```

--------------------------------

### Install LangChain Dependencies

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Install the necessary LangChain packages for integration. This is optional.

```bash
pip install langchain langchain-community langchain-openai
```

--------------------------------

### Status Monitoring Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Retrieves and prints the current status of active platforms and user permissions.

```python
status = bot.get_status()
print(f"Active platforms: {status['integrations']['active']}")
print(f"Permissions: {status['permissions']}")
```

--------------------------------

### Install Dependencies and Run Tests

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Installs project dependencies using pip and runs tests with pytest. Ensure requirements.txt is up-to-date before running.

```bash
pip install -r requirements.txt
pytest
```

--------------------------------

### Initialize MegaBot for Different Subscription Tiers

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Provides examples for initializing the MegaBot with different configurations, corresponding to free and pro subscription tiers. It also shows how to retrieve tier-specific information.

```python
from megabot import MegaBot, Config

# Free tier (default)
bot_free = MegaBot()

# Pro tier (unlimited usage)
config = Config()
config.set("monetization.tier", "pro")
bot_pro = MegaBot(config)

# Check tier info
tier_info = bot_pro.get_tier_info()
print(f"Tier: {tier_info['tier']}")
print(f"Queries today: {tier_info['usage']['queries_today']}")
```

--------------------------------

### Copy Configuration File

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Create a local configuration file by copying the example JSON configuration file. This file allows for detailed customization of OctoGen's settings.

```bash
cp config.example.json config.json
```

--------------------------------

### Sequential Chain Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Illustrates a multi-step processing pipeline using MegaBot's sequential chain.

```python
async def sequential_chain_example():
    config = Config()
    config.set("langchain.enabled", True)
    
    bot = MegaBot(config)
    await bot.start()
    
    # Multi-step processing
    context = {'chain_type': 'sequential_chain'}
    result = await bot.query("Analyze and summarize this topic", context=context)
    
    print("Result:", result['response'])
    
    await bot.stop()
```

--------------------------------

### LLM Chain Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Demonstrates a simple LLM query using the MegaBot's LLM chain.

```python
from megabot import MegaBot, Config
import asyncio

async def llm_chain_example():
    config = Config()
    config.set("langchain.enabled", True)
    
    bot = MegaBot(config)
    await bot.start()
    
    # Simple LLM query
    result = await bot.query("Explain neural networks")
    
    print("Response:", result['response'])
    
    await bot.stop()
```

--------------------------------

### Multi-Platform Query Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Queries multiple platforms for information on a given topic and prints the responses from each platform.

```python
result = await bot.query("Explain quantum computing")
for platform, response in result['responses'].items():
    print(f"{platform}: {response['response']}")
```

--------------------------------

### Configuration File Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

This JSON file defines the core settings for MEGA-Bot, including API keys, database preferences, workflow parameters, and feature flags. Ensure sensitive information like API keys is managed securely.

```json
{
  "api_keys": {
    "copilot": "your-api-key",
    "gemini": "your-api-key",
    "chatgpt": "your-api-key",
    "grok": "your-api-key"
  },
  "database": {
    "type": "sqlite",
    "path": "megabot.db",
    "research_cache_enabled": true
  },
  "workflow": {
    "max_concurrent_tasks": 10,
    "auto_update_interval": 3600,
    "permission_level": "full"
  },
  "features": {
    "deep_research": true,
    "multi_tasking": true,
    "auto_update": true,
    "document_sync": true
  }
}
```

--------------------------------

### Install OctoGen as a Python Package

Source: https://github.com/elmourabea/octogen/blob/main/coll/MARKETPLACE.md

Install the OctoGen Python package directly from its GitHub repository using pip.

```bash
pip install git+https://github.com/ELMOURABEA/OctoGen.git
```

--------------------------------

### Run Workflow Automation Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Execute the workflow automation script to demonstrate pre-built and custom workflow creation, document synchronization, and update management features.

```bash
python examples/workflow_automation.py
```

--------------------------------

### Python Code Style Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/CONTRIBUTING.md

Example of a Python function demonstrating type hints, docstrings, and adherence to PEP 8 guidelines.

```python
def validate_query(query: str, max_length: int = 10000) -> tuple[bool, Optional[str]]:
    """
    Validate user query for safety and correctness
    
    Args:
        query: The query string to validate
        max_length: Maximum allowed length for queries
    
    Returns:
        Tuple of (is_valid, error_message)
    """
    # Implementation here
```

--------------------------------

### Install Java Bridge Dependency

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Install the py4j package to enable the Java bridge. This is optional.

```bash
pip install py4j
```

--------------------------------

### Agent with Tools Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Illustrates agent-based reasoning with tool usage enabled in MegaBot.

```python
async def agent_example():
    config = Config()
    config.set("langchain.enabled", True)
    config.set("langchain.enable_tools", True)
    
    bot = MegaBot(config)
    await bot.start()
    
    context = {'chain_type': 'agent_executor'}
    result = await bot.query("Research and calculate ROI", context=context)
    
    print("Response:", result['response'])
    print("Reasoning Steps:", result['intermediate_steps'])
    
    await bot.stop()
```

--------------------------------

### Java Client for Python Bridge

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Example Java client code to connect to a Python bridge server started with py4j. This allows calling Python functions from Java.

```java
import py4j.GatewayServer;

public class MegaBotClient {
    public static void main(String[] args) {
        GatewayServer server = new GatewayServer(new PythonBridge());
        server.start();
        
        // Call Python functions
        String result = pythonBridge.query("What is AI?");
        System.out.println(result);
    }
}
```

--------------------------------

### Workflow Execution Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Executes a predefined workflow with a specific topic and prints the final analysis result.

```python
result = await bot.execute_workflow(
    "comprehensive_analysis",
    topic="artificial intelligence"
)
print(result['final_analysis'])
```

--------------------------------

### Environment Variables Setup

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

This bash script demonstrates how to set up environment variables for MEGA-Bot, including API keys and configuration file paths. These variables are used to configure the bot's behavior and access external services.

```bash
COPILOT_API_KEY=your-key
GEMINI_API_KEY=your-key
CHATGPT_API_KEY=your-key
GROK_API_KEY=your-key
MEGABOT_CONFIG=config.json
```

--------------------------------

### Install Node.js Bridge Dependency

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Install the python-shell package for Node.js integration. This is optional.

```bash
npm install python-shell
```

--------------------------------

### Example Usage of Version Tags

Source: https://github.com/elmourabea/octogen/blob/main/coll/PUBLISHING_GUIDE.md

Illustrates how users can reference specific versions or the latest within a major version using tags in their workflow.

```yaml
- uses: ELMOURABEA/MEGAGENT@v1  # Always latest 1.x.x
- uses: ELMOURABEA/MEGAGENT@v1.2  # Latest 1.2.x
- uses: ELMOURABEA/MEGAGENT@v1.2.0  # Specific version
```

--------------------------------

### Query Multiple AI Platforms Simultaneously

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

This example shows how to query all integrated AI platforms at once and retrieve aggregated responses. The results are iterated through, printing the response from each platform.

```python
async def query_example():
    bot = MegaBot()
    await bot.start()
    
    result = await bot.query("What are the latest AI trends?")
    
    for platform, response in result['responses'].items():
        print(f"{platform}: {response['response']}")
    
    await bot.stop()
```

--------------------------------

### Update Synchronization Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Synchronizes documents and retrieves a list of recent updates, printing the platform and title for each update.

```python
await bot.sync_documents()
updates = bot.get_updates(limit=10)
for update in updates:
    print(f"[{update['platform']}] {update['title']}")
```

--------------------------------

### Install OctoGen as Editable Python Package

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Install OctoGen as a Python package in editable mode, allowing for direct code changes to be reflected without reinstallation.

```bash
pip install -e .
```

--------------------------------

### Install OctoGen as a GitHub Action

Source: https://github.com/elmourabea/octogen/blob/main/coll/MARKETPLACE.md

Add OctoGen to your GitHub workflow by specifying its repository and version.

```yaml
name: Run OctoGen Query
uses: ELMOURABEA/OctoGen@v1.2.0
with:
  mode: 'query'
  prompt: 'What are the latest AI trends?'
  tier: 'free'
```

--------------------------------

### Retrieval QA Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Demonstrates document-based question answering using MegaBot's retrieval QA chain.

```python
async def retrieval_qa_example():
    config = Config()
    config.set("langchain.enabled", True)
    
    bot = MegaBot(config)
    await bot.start()
    
    context = {'chain_type': 'retrieval_qa'}
    result = await bot.query("What is machine learning?", context=context)
    
    print("Answer:", result['response'])
    print("Sources:", result['sources'])
    
    await bot.stop()
```

--------------------------------

### Basic Python API Usage

Source: https://github.com/elmourabea/octogen/blob/main/coll/PROJECT_SUMMARY.md

Demonstrates how to initialize MegaBot, start it, perform a general query, conduct a deep research query, and then stop the bot. Requires asyncio.

```python
from megabot import MegaBot
import asyncio

async def main():
    bot = MegaBot()
    await bot.start()
    
    # Query all platforms
    result = await bot.query("What is AI?")
    
    # Deep research
    research = await bot.research("machine learning", depth="deep")
    
    await bot.stop()

asyncio.run(main())
```

--------------------------------

### Command Line Interface (CLI) Usage

Source: https://github.com/elmourabea/octogen/blob/main/coll/PROJECT_SUMMARY.md

Shows various commands to run the Octogen project from the command line, including demo mode, interactive mode, running examples, and executing tests.

```bash
python main.py                    # Demo mode
python main.py --interactive      # Interactive mode
python examples/basic_usage.py    # Run examples
pytest tests/                     # Run tests
```

--------------------------------

### Check Python Version

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Verify that your Python installation is version 3.8 or higher, which is required to avoid potential async event loop warnings.

```bash
python --version  # Should be 3.8 or higher
```

--------------------------------

### Deep Research Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Initiates a deep research query on a specified topic and prints the number of findings and aggregated sources.

```python
research = await bot.research("machine learning", depth="deep")
print(f"Findings: {len(research['findings'])}")
print(f"Sources: {research['aggregated_sources']}")
```

--------------------------------

### Install OctoGen as GitHub Action

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Add this snippet to your GitHub workflow file to integrate OctoGen. Ensure you replace 'Your AI query here' with your actual query and set the desired tier.

```yaml
- name: Run OctoGen
  uses: ELMOURABEA/OctoGen@v2.0.0
  with:
    mode: 'query'
    prompt: 'Your AI query here'
    tier: 'free'
```

--------------------------------

### Test MEGAGENT Action in Workflow

Source: https://github.com/elmourabea/octogen/blob/main/coll/PUBLISHING_GUIDE.md

Example GitHub Actions workflow to test the MEGAGENT action with specific inputs.

```yaml
# .github/workflows/test-megagent.yml
name: Test MEGAGENT

on: [push]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - name: Test MEGAGENT Action
        uses: ELMOURABEA/MEGAGENT@v1.2.0
        with:
          mode: 'query'
          prompt: 'What is artificial intelligence?'
          tier: 'free'
```

--------------------------------

### Conversational Chain with Memory Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Shows how to maintain context across interactions using MegaBot's conversational chain with memory enabled.

```python
async def conversation_example():
    config = Config()
    config.set("langchain.enabled", True)
    config.set("langchain.enable_memory", True)
    
    bot = MegaBot(config)
    await bot.start()
    
    context = {'chain_type': 'conversation_chain'}
    
    # First message
    result1 = await bot.query("Tell me about Python", context=context)
    print("Response 1:", result1['response'])
    
    # Follow-up (memory preserved)
    result2 = await bot.query("What are its main features?", context=context)
    print("Response 2:", result2['response'])
    
    await bot.stop()
```

--------------------------------

### Run Advanced Research Example

Source: https://github.com/elmourabea/octogen/blob/main/coll/examples/README.md

Execute the advanced research script to showcase deep research on multiple topics, comprehensive analysis workflows, result synthesis, and platform-specific insights.

```bash
python examples/advanced_research.py
```

--------------------------------

### JavaScript Integration using python-shell

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Integrates MEGA-Bot with Node.js using the python-shell library. Requires installing the library via npm.

```bash
npm install python-shell
```

```javascript
const { PythonShell } = require('python-shell');

let options = {
  mode: 'json',
  pythonPath: 'python3',
  scriptPath: './megabot',
  args: ['--query', 'What is AI?']
};

PythonShell.run('main.py', options, (err, results) => {
  if (err) throw err;
  console.log(results);
});
```

--------------------------------

### Execute Complex Workflows with MEGA-Bot

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

This snippet illustrates how to execute a predefined workflow, such as 'comprehensive_analysis', with specific parameters. The MegaBot must be started before executing any workflow.

```python
async def workflow_example():
    bot = MegaBot()
    await bot.start()
    
    # Comprehensive analysis workflow
    result = await bot.execute_workflow(
        "comprehensive_analysis",
        topic="machine learning"
    )
    
    await bot.stop()
```

--------------------------------

### Python Bridge Server for Java Interoperability

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Sets up a Python bridge server using py4j to allow Java applications to interact with MEGA-Bot. Ensure py4j is installed.

```bash
pip install py4j
```

```python
from py4j.java_gateway import JavaGateway, GatewayParameters

class PythonBridge:
    def __init__(self):
        self.bot = MegaBot(Config())
    
    def query(self, prompt):
        return asyncio.run(self.bot.query(prompt))

gateway = JavaGateway(gateway_parameters=GatewayParameters(port=25333))
python_bridge = PythonBridge()
gateway.entry_point = python_bridge
gateway.start()
```

--------------------------------

### Basic Copilot Search Query

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Perform a hybrid search using the MegaBot to get an AI answer, web results, and sources for a given query. Ensure the Copilot Search is enabled in the configuration.

```python
from megabot import MegaBot, Config
import asyncio

async def search_example():
    config = Config()
    config.set("copilot_search.enabled", True)
    
    bot = MegaBot(config)
    await bot.start()
    
    # Perform hybrid search
    result = await bot.query("What are the latest AI trends?")
    
    print("AI Answer:", result['answer'])
    print("Web Results:", result['web_results'])
    print("Sources:", result['sources'])
    
    await bot.stop()

asyncio.run(search_example())
```

--------------------------------

### Perform Deep Research with MEGA-Bot

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

This snippet demonstrates how to initiate a deep research query on a given topic using the MegaBot class. Ensure MegaBot is imported and started before making research calls. The result includes platforms used and a synthesis of findings.

```python
from megabot import MegaBot
import asyncio

async def research_example():
    bot = MegaBot()
    await bot.start()
    
    # Deep research
    result = await bot.research("quantum computing", depth="deep")
    print(f"Platforms used: {result['platforms_used']}")
    print(f"Total findings: {result['synthesis']['total_findings']}")
    
    await bot.stop()

asyncio.run(research_example())
```

--------------------------------

### Configure Logging for Debugging and Monitoring

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Shows how to set up logging for the OctoGen system using the `setup_logging` function. This allows developers to control the verbosity of logs for debugging and monitoring purposes.

```python
from megabot import setup_logging

# Configure logging level
setup_logging("INFO")  # Options: DEBUG, INFO, WARNING, ERROR, CRITICAL
```

--------------------------------

### Configure API Keys in .env

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Edit the .env file to add your API keys for GitHub Copilot, Gemini, ChatGPT, and Grok. Optional AdMob IDs can also be configured here.

```bash
COPILOT_API_KEY=your-copilot-api-key
GEMINI_API_KEY=your-gemini-api-key
CHATGPT_API_KEY=your-chatgpt-api-key
GROK_API_KEY=your-grok-api-key

# Optional: AdMob IDs for advertising integration
ADMOB_APP_ID=your-admob-app-id
ADMOB_BANNER_ID=your-admob-banner-id
ADMOB_INTERSTITIAL_ID=your-admob-interstitial-id
ADMOB_REWARDED_ID=your-admob-rewarded-id
```

--------------------------------

### Verify action.yml Configuration

Source: https://github.com/elmourabea/octogen/blob/main/coll/RELEASE_CHECKLIST.md

Load and parse the action.yml file to ensure it is valid YAML.

```bash
python -c "import yaml; yaml.safe_load(open('action.yml'))"
```

--------------------------------

### Automated Documentation Generation with OctoGen

Source: https://github.com/elmourabea/octogen/blob/main/coll/MARKETPLACE.md

Generate project documentation automatically on push to the main branch. Requires Copilot API key.

```yaml
name: Generate Docs
on:
  push:
    branches: [main]
jobs:
  docs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      
      - name: Generate Documentation
        uses: ELMOURABEA/OctoGen@v1.2.0
        with:
          mode: 'workflow'
          workflow-name: 'comprehensive_analysis'
          prompt: 'Generate comprehensive documentation for this project'
          copilot-api-key: ${{ secrets.COPILOT_API_KEY }}
```

--------------------------------

### Verify Package Build and Distribution

Source: https://github.com/elmourabea/octogen/blob/main/coll/RELEASE_CHECKLIST.md

Build the package and check its distribution files for integrity.

```bash
python -m build
```

```bash
twine check dist/*
```

--------------------------------

### Run OctoGen Demo Mode

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Execute the main script to run OctoGen in demo mode and observe its functionality.

```bash
python main.py
```

--------------------------------

### Configure LLM API Key

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Add your LLM API key to the .env file for authentication.

```bash
LANGCHAIN_API_KEY=your-llm-api-key-here
```

--------------------------------

### Integrate Advertising for Monetization

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Demonstrates how to integrate Google AdMob for monetization within OctoGen, including showing banner ads and rewarded ads to offer bonus features.

```python
# Show banner ad
result = bot.show_banner_ad("bottom")

# Show rewarded ad for bonus features
result = bot.show_rewarded_ad("bonus_queries")
print(f"Reward: {result['reward']['description']}")
```

--------------------------------

### Configure LangChain Settings

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Set up LangChain integration parameters in the config.json file.

```json
{
  "langchain": {
    "enabled": true,
    "llm_provider": "openai",
    "temperature": 0.7,
    "max_tokens": 2000,
    "enable_memory": true,
    "enable_tools": true
  }
}
```

--------------------------------

### Clone Repository

Source: https://github.com/elmourabea/octogen/blob/main/coll/CONTRIBUTING.md

Clone your forked repository to your local machine and navigate into the project directory.

```bash
git clone https://github.com/YOUR_USERNAME/OctoGen.git
cd OctoGen
```

--------------------------------

### Combined Usage of Copilot Search and LangChain

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Use Copilot Search to gather information and LangChain to synthesize it. Ensure both integrations are enabled in the configuration.

```python
async def combined_example():
    config = Config()
    config.set("copilot_search.enabled", True)
    config.set("langchain.enabled", True)
    config.set("langchain.enable_tools", True)
    
    bot = MegaBot(config)
    await bot.start()
    
    # Step 1: Gather information with Copilot Search
    search_result = await bot.query("Latest AI trends")
    
    # Step 2: Synthesize with LangChain agent
    context = {'chain_type': 'agent_executor'}
    synthesis = await bot.query(
        f"Analyze these findings: {search_result['synthesis']}", 
        context=context
    )
    
    print("Web Results:", search_result['web_results'])
    print("AI Synthesis:", synthesis['response'])
    print("Reasoning:", synthesis['intermediate_steps'])
    
    await bot.stop()
```

--------------------------------

### MegaBot.query(prompt, context)

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

Queries all integrated platforms with a given prompt and context.

```APIDOC
## MegaBot.query(prompt, context)

### Description
Queries all platforms with the provided prompt and context.

### Method
`query(prompt, context)`

### Parameters
- **prompt** (string) - Required - The query to be sent to the platforms.
- **context** (any) - Required - Additional context for the query.

### Request Example
```python
response = megabot.query("What is the capital of France?", {"source": "web"})
```

### Response
Returns results from queried platforms. Specific format not detailed.
```

--------------------------------

### Configure Copilot Search API Key

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Add your Bing Search API key to the .env file for Copilot Search integration.

```bash
BING_SEARCH_API_KEY=your-bing-search-api-key-here
```

--------------------------------

### Build Package Locally

Source: https://github.com/elmourabea/octogen/blob/main/coll/PUBLISHING_GUIDE.md

Command to build the Python package locally before uploading artifacts.

```bash
python -m build
```

--------------------------------

### Test CLI Modes

Source: https://github.com/elmourabea/octogen/blob/main/coll/RELEASE_CHECKLIST.md

Verify the command-line interface functionality in both interactive and non-interactive modes. Ensure the main script and its CLI options work as expected.

```bash
# Test CLI modes
python main.py
python main.py --interactive
```

--------------------------------

### Run OctoGen Interactive Mode

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Launch OctoGen using the interactive command-line interface for direct interaction.

```bash
python main.py --interactive
```

--------------------------------

### Create and Push Git Tag

Source: https://github.com/elmourabea/octogen/blob/main/coll/RELEASE_CHECKLIST.md

Create an annotated Git tag for the new release version and push it to the origin. This is a crucial step for version control and release management.

```bash
# Create and push tag
git tag -a v1.2.0 -m "Release version 1.2.0"
git push origin v1.2.0
```

--------------------------------

### Create and Push Release Tag

Source: https://github.com/elmourabea/octogen/blob/main/coll/PUBLISHING_GUIDE.md

Commands to create a new annotated tag for a release and push it to the remote repository.

```bash
git checkout main
git pull origin main
git merge <release-branch>
git tag -a v1.2.0 -m "Release version 1.2.0 - Monetization and GitHub Marketplace"
git push origin v1.2.0
```

--------------------------------

### Stage and Commit Changes

Source: https://github.com/elmourabea/octogen/blob/main/coll/CONTRIBUTING.md

Stage all modified files and commit them with a descriptive message summarizing your changes.

```bash
git add .
git commit -m "Description of your changes"
```

--------------------------------

### Aggregate and Synthesize Research Results

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Illustrates how to obtain a unified synthesis of insights from multiple AI platforms after performing a research query. The 'synthesis' key in the result dictionary contains the aggregated information.

```python
result = await bot.research("topic")
synthesis = result['synthesis']
# Contains unified insights from all platforms
```

--------------------------------

### Verify Project Version

Source: https://github.com/elmourabea/octogen/blob/main/coll/RELEASE_CHECKLIST.md

Use this command to check the current version of the megabot package.

```bash
python -c "from megabot import __version__; print(__version__)"
```

--------------------------------

### Configure Action Branding

Source: https://github.com/elmourabea/octogen/blob/main/coll/PUBLISHING_GUIDE.md

Define the icon and color for your action's branding in the action.yml file. This is used in the GitHub Marketplace.

```yaml
branding:
  icon: 'zap'
  color: 'blue'
```

--------------------------------

### Add Marketplace Badge to README

Source: https://github.com/elmourabea/octogen/blob/main/coll/PUBLISHING_GUIDE.md

Markdown snippet for adding a GitHub Marketplace badge to a README file.

```markdown
[![Marketplace](https://img.shields.io/badge/GitHub%20Marketplace-Published-orange.svg)](https://github.com/marketplace/actions/megagent-ai-multi-platform-integration)
```

--------------------------------

### Create and Push Git Tag for Version Update

Source: https://github.com/elmourabea/octogen/blob/main/coll/PUBLISHING_GUIDE.md

Tag a specific version and push it to the remote repository to mark a release. This is part of the version update process.

```bash
git tag -a v1.2.1 -m "Release version 1.2.1"
git push origin v1.2.1
```

--------------------------------

### Multi-Platform Queries with OctoGen

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Query all available AI platforms simultaneously for a given topic and aggregate their responses.

```python
result = await bot.query("Explain transformer architecture")
# Aggregates responses with confidence scores
```

--------------------------------

### Weekly AI Digest using Multi-Platform Query

Source: https://github.com/elmourabea/octogen/blob/main/coll/MARKETPLACE.md

Schedule a weekly digest of AI developments by querying multiple platforms. Requires API keys for Copilot, Gemini, ChatGPT, and Grok. Results are posted as a GitHub issue.

```yaml
name: Weekly AI Digest
on:
  schedule:
    - cron: '0 9 * * 1'  # Every Monday at 9 AM
jobs:
  digest:
    runs-on: ubuntu-latest
    steps:
      - name: Query All AI Platforms
        uses: ELMOURABEA/OctoGen@v1.2.0
        id: digest
        with:
          mode: 'query'
          prompt: 'What are the most important AI developments this week?'
          copilot-api-key: ${{ secrets.COPILOT_API_KEY }}
          gemini-api-key: ${{ secrets.GEMINI_API_KEY }}
          chatgpt-api-key: ${{ secrets.CHATGPT_API_KEY }}
          grok-api-key: ${{ secrets.GROK_API_KEY }}
          tier: 'pro'
      
      - name: Create Issue with Digest
        uses: actions/github-script@v7
        with:
          script: |
            const result = ${{ steps.digest.outputs.result }};
            await github.rest.issues.create({
              owner: context.repo.owner,
              repo: context.repo.repo,
              title: 'Weekly AI Digest',
              body: `# AI Digest\n\n${JSON.stringify(result, null, 2)}`
            });
```

--------------------------------

### Validate User Queries and Topics

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Demonstrates the use of `validate_query` and `validate_topic` functions for sanitizing and validating user inputs before they are processed by the system. This enhances security and prevents errors.

```python
from megabot import validate_query, validate_topic

# Validate queries before processing
is_valid, error = validate_query("Your query here")

# Validate research topics
is_valid, error = validate_topic("Your topic here")
```

--------------------------------

### Run Specific Integration Tests

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Execute only integration tests from a specific file. Useful for targeted testing.

```bash
pytest tests/test_new_integrations.py -v
```

--------------------------------

### Verify Project Tests

Source: https://github.com/elmourabea/octogen/blob/main/coll/RELEASE_CHECKLIST.md

Run pytest to verify that all tests are passing with a concise output.

```bash
pytest -v --tb=short
```

--------------------------------

### Execute Multiple Research Queries Concurrently

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Demonstrates how to initiate multiple research queries in parallel using the MegaBot class. This is useful for speeding up data gathering when multiple topics need to be explored simultaneously.

```python
bot = MegaBot()
# Executes multiple research queries in parallel
```

--------------------------------

### Force Push Major Version Tag

Source: https://github.com/elmourabea/octogen/blob/main/coll/PUBLISHING_GUIDE.md

Create or update a major version tag (e.g., v1) to point to the latest release within that major version. Use with caution due to the force push.

```bash
# v1 tag points to latest v1.x.x
git tag -fa v1 -m "Version 1 (latest: 1.2.0)"
git push origin v1 --force
```

--------------------------------

### Create New Feature Branch

Source: https://github.com/elmourabea/octogen/blob/main/coll/CONTRIBUTING.md

Create a new branch for your feature development, following the 'feature/your-feature-name' convention.

```bash
git checkout -b feature/your-feature-name
```

--------------------------------

### Run All Tests

Source: https://github.com/elmourabea/octogen/blob/main/coll/CONTRIBUTING.md

Execute all tests in the project using pytest to ensure code quality and functionality.

```bash
pytest
```

--------------------------------

### MegaBot.get_capabilities()

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

Retrieves all capabilities of the MEGA-Bot.

```APIDOC
## MegaBot.get_capabilities()

### Description
Gets all capabilities of the bot.

### Method
`get_capabilities()`

### Parameters
None

### Request Example
```python
capabilities = megabot.get_capabilities()
```

### Response
Returns a list of all bot capabilities. Specific format not detailed.
```

--------------------------------

### Workflow Automation with OctoGen

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Execute predefined multi-step workflows for complex tasks, specifying the workflow name and relevant topic.

```python
result = await bot.execute_workflow(
    "comprehensive_analysis",
    topic="neural networks"
)
```

--------------------------------

### Clone OctoGen Repository

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Use this command to clone the OctoGen repository from GitHub to your local machine.

```bash
git clone https://github.com/ELMOURABEA/OctoGen.git
```

--------------------------------

### Auto-Update System with OctoGen

Source: https://github.com/elmourabea/octogen/blob/main/coll/README.md

Automatically synchronize the latest platform updates and retrieve recent updates.

```python
await bot.sync_documents()
updates = bot.get_updates(limit=10)
```

--------------------------------

### JavaScript Integration using child_process

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Integrates MEGA-Bot with Node.js by spawning a Python process using the child_process module. This method allows direct execution of Python scripts.

```javascript
const { spawn } = require('child_process');

const python = spawn('python3', [
  'main.py',
  '--query', 'What is AI?'
]);

python.stdout.on('data', (data) => {
  console.log(`Result: ${data}`);
});

python.stderr.on('data', (data) => {
  console.error(`Error: ${data}`);
});
```

--------------------------------

### Verify Git Status and History

Source: https://github.com/elmourabea/octogen/blob/main/coll/RELEASE_CHECKLIST.md

Check the current Git status and review the last five commits.

```bash
git status
```

```bash
git log --oneline -5
```

--------------------------------

### Configure Copilot Search Settings

Source: https://github.com/elmourabea/octogen/blob/main/coll/INTEGRATION_GUIDE.md

Configure Copilot Search settings in the config.json file, including enabling the feature, setting the API endpoint, maximum results, and safe search level.

```json
{
  "copilot_search": {
    "enabled": true,
    "endpoint": "https://api.bing.microsoft.com/v7.0/search",
    "max_results": 10,
    "safe_search": "Moderate"
  }
}
```

--------------------------------

### AI-Powered Code Review with OctoGen

Source: https://github.com/elmourabea/octogen/blob/main/coll/MARKETPLACE.md

Automate code reviews within a GitHub Actions workflow. Requires API keys for Gemini and ChatGPT for 'pro' tier.

```yaml
name: AI Code Review
on: [pull_request]
jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      
      - name: Analyze PR with OctoGen
        uses: ELMOURABEA/OctoGen@v1.2.0
        with:
          mode: 'query'
          prompt: 'Review this code for best practices and potential issues'
          gemini-api-key: ${{ secrets.GEMINI_API_KEY }}
          chatgpt-api-key: ${{ secrets.CHATGPT_API_KEY }}
          tier: 'pro'
```

--------------------------------

### MegaBot.execute_workflow(name, **kwargs)

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

Executes a specified workflow with given arguments.

```APIDOC
## MegaBot.execute_workflow(name, **kwargs)

### Description
Executes a workflow by its name with additional keyword arguments.

### Method
`execute_workflow(name, **kwargs)`

### Parameters
- **name** (string) - Required - The name of the workflow to execute.
- **kwargs** (dict) - Optional - Additional parameters for the workflow.

### Request Example
```python
megabot.execute_workflow("data_processing", input_file="data.csv", output_format="json")
```

### Response
None explicitly documented. Execution status or results may be returned.
```

--------------------------------

### MegaBot.get_updates(platform, limit)

Source: https://github.com/elmourabea/octogen/blob/main/coll/DOCUMENTATION.md

Fetches the latest updates from a specified platform.

```APIDOC
## MegaBot.get_updates(platform, limit)

### Description
Gets the latest updates from a specified platform.

### Method
`get_updates(platform, limit)`

### Parameters
- **platform** (string) - Required - The platform to get updates from.
- **limit** (integer) - Optional - The maximum number of updates to retrieve.

### Request Example
```python
updates = megabot.get_updates("github", 10)
```

### Response
Returns a list of updates from the specified platform. Specific format not detailed.
```