### Install Prerequisites

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai-agents/README.md

Install the necessary dependencies for running the MCP server and clients.

```bash
pip install praisonaiagents mcp httpx starlette uvicorn anthropic python-dotenv
```

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

### Run example scripts

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai-ts/examples/concepts/README.md

Execute specific concept examples using ts-node.

```bash
# Run single agent example
npx ts-node examples/concepts/single-agent.ts

# Run multi-agent example
npx ts-node examples/concepts/multi-agent.ts

# Run task-based agent example
npx ts-node examples/concepts/task-based-agent.ts
```

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

### Install Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/model_fee_retreival_agents.ipynb

Install the required libraries for web scraping and agent orchestration.

```bash
# Install dependencies without output
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install crawl4ai > /dev/null
```

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

### Install Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/Joke_Agent.ipynb

Install the necessary libraries for OpenAI and PraisonAIAgents. This should be run before any other code.

```python
!pip install openai praisonaiagents
```

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

### Run Single Agent Example

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai-ts/README.md

Demonstrates how to create and run a single AI agent for a specific task. Ensure the 'praisonai' package is installed.

```typescript
import { Agent, PraisonAIAgents } from 'praisonai';

async function main() {
    // Create a simple agent (no task specified)
    const agent = new Agent({
        name: "BiologyExpert",
        instructions: "Explain the process of photosynthesis in detail.",
        verbose: true
    });

    // Run the agent
    const praisonAI = new PraisonAIAgents({
        agents: [agent],
        tasks: ["Explain the process of photosynthesis in detail."],
        verbose: true
    });

    try {
        console.log('Starting single agent example...');
        const results = await praisonAI.start();
        console.log('
Final Results:', results);
    } catch (error) {
        console.error('Error:', error);
    }
}

main();
```

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

### Install Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/markdown_validator_agents.ipynb

Install necessary Python packages and the markdownlint-cli2 tool.

```python
# Install dependencies without output
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install pymarkdown > /dev/null
!npm install -g markdownlint-cli2
```

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

### Install Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/cli_operation_agents.ipynb

Install the necessary libraries for PraisonAI and Open Interpreter in a notebook environment.

```python
# Install dependencies without output
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install open-interpreter > /dev/null
```

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

### Install Development Dependencies

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai-ts/README.md

Install project dependencies after cloning the repository.

```bash
npm install
```

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

### Configure Environment and Run Examples

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai-ts/README.md

Commands to set the OpenAI API key and execute TypeScript examples using ts-node.

```bash
export OPENAI_API_KEY='your-api-key'
```

```bash
npx ts-node example.ts
```

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

### Install Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/meeting_prep_using_slack_and_trello_agents.ipynb

Installs the necessary libraries for PraisonAI, LangChain, search tools, and Slack integration.

```bash
# Install dependencies without output
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install duckduckgo-search > /dev/null
%pip install python-dotenv > /dev/null
%pip install slack_sdk > /dev/null
%pip install python-dotenv > /dev/null
```

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

### Install Framework

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai/tests/integration/README.md

If you encounter an ImportError for a framework like 'autogen', install it using pip.

```bash
pip install pyautogen
```

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

### Install Pytest and Pytest-Asyncio with UV

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai/tests/README.md

Install necessary pytest packages using UV, a fast Python package installer. Recommended for environments using UV virtual environments.

```bash
uv pip install pytest pytest-asyncio
```

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

### Install Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/ReAct_agent.ipynb

Install the necessary packages for the agent, including OpenAI, PraisonAI, and DuckDuckGo search.

```bash
!pip install openai praisonaiagents duckduckgo-search
```

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

### Install Test Dependencies

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai/tests/integration/README.md

Commands to install necessary packages for running integration tests.

```bash
pip install pyautogen
```

```bash
pip install crewai
```

```bash
pip install pytest pytest-asyncio
```

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

### YAML Configuration Example

Source: https://github.com/praison-labs/praison/blob/main/examples/python/usecases/README-secondary-market-research.md

Example of a YAML configuration file for the research agents, specifying the framework, topic, and variables for research.

```yaml
framework: "crewai"
topic: "Secondary Market Research Analysis"

variables:
  company: "Tesla"
  geography: "North America" 
  industry: "Electric Vehicles"

roles:
  market_overview_specialist:
    role: "Market Overview Specialist"
    # ... configuration details
```

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

### Install llama-index and tavily-python

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/FunctionAgent_Workflow.ipynb

Install the necessary libraries for llama-index and Tavily web search.

```python
%pip install llama-index tavily-python
```

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

### Install Dependencies for Trip Planner Agents

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/surprise_trip_planner_and_itinerary_agents.ipynb

Installs the required libraries including langchain_community, praisonai, requests, and duckduckgo_search.

```python
# Install dependencies without output
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install requests > /dev/null
%pip install duckduckgo_search > /dev/null
```

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

### Install LangChain Community and Google Search Results

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/LangChain_PraisonAI_Agent_Notebook.ipynb

Install necessary libraries for using Google Search with LangChain.

```python
!pip install langchain-community google-search-results
```

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

### Install Praison AI Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/book_writing_agents.ipynb

Installs required Python packages for Praison AI and CrewAI, suppressing installation output.

```bash
%pip install langchain_community > /dev/null
```

```bash
%pip install praisonai[crewai] > /dev/null
```

```bash
%pip install duckduckgo-search > /dev/null
```

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

### Install Dependencies for Memory Management

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/memory_management_and_knowledge_retreival_agents.ipynb

Installs required Python packages for memory management and knowledge retrieval agents without displaying output. Ensure these are installed before proceeding.

```python
# Install dependencies without output
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install duckduckgo_search > /dev/null
%pip install mem0ai > /dev/null
```

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

### Initialize and Run PraisonAI

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/cli_operation_agents.ipynb

Set up the environment variables and execute the PraisonAI instance.

```python
import os
from praisonai import PraisonAI
from google.colab import userdata

# Create a PraisonAI instance with the agent_yaml content
praisonai = PraisonAI(agent_yaml=agent_yaml, tools=[CLIExecutorTool]) # Add InstagramSearchTool once scripted

# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below
os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY') or "ENTER OPENAI_API_KEY HERE"
os.environ["OPENAI_MODEL_NAME"] = "gpt-4o-mini"

# Run PraisonAI
result = praisonai.run()
```

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

### Run ArXiv Tools Example

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai-ts/examples/tools/README.md

Execute the ArXiv tools example script using ts-node. Downloaded PDFs will be saved in the examples/downloads directory.

```bash
npx ts-node examples/tools/arxiv-tools.ts
```

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

### Install PraisonAI package

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai-ts/examples/concepts/README.md

Install the required package via npm.

```bash
npm install praisonai
```

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

### Install Dependencies with uv

Source: https://github.com/praison-labs/praison/blob/main/README.md

Commands to set up the development environment using the uv package manager.

```bash
# Install uv if you haven't already
pip install uv

# Install from requirements
uv pip install -r pyproject.toml

# Install with extras
uv pip install -r pyproject.toml --extra code
uv pip install -r pyproject.toml --extra "crewai,autogen"
```

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

### Run Real Setup Validation Tests

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai/tests/TESTING_GUIDE.md

Validate the real setup with autogenerated patterns. This command has a low cost and provides setup-only output.

```python
python tests/test_runner.py --pattern real-autogen
```

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

### Install Framework Dependencies

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai/tests/e2e/README.md

Install the required dependencies for CrewAI and AutoGen integrations.

```bash
pip install ".[crewai,autogen]"
```

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

### Initialize and run the PraisonAI agent

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/research_report_generation_agents.ipynb

Set up environment variables and execute the PraisonAI instance with the defined configuration.

```python
import os
from praisonai import PraisonAI
from google.colab import userdata

# Create a PraisonAI instance with the agent_yaml content
praisonai = PraisonAI(agent_yaml=agent_yaml, tools=[TavilyTool])

# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below
os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY') or "ENTER OPENAI_API_KEY HERE"
os.environ["TAVILY_API_KEY"] = userdata.get('TAVILY_API_KEY') or "ENTER TAVILY_API_KEY HERE"
os.environ["OPENAI_MODEL_NAME"] = "gpt-4o-mini"

# Run PraisonAI
result = praisonai.run()
```

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

### Selenium WebDriver Initialization and Basic Navigation

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/recruitment_flow_agents.ipynb

Sets up a Selenium WebDriver instance, typically for Firefox, and provides methods for navigation and interaction. Ensure Firefox and geckodriver are installed.

```python
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.firefox.options import Options
import time

class Driver:
    def __init__(self, url, cookie=None):
        self.driver = self._create_driver(url, cookie)

    def navigate(self, url, wait=3):
        self.driver.get(url)
        time.sleep(wait)

    def scroll_to_bottom(self, wait=3):
        self.driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
        time.sleep(wait)
        self.driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
        time.sleep(wait)

    def get_element(self, selector):
        return self.driver.find_element(By.CSS_SELECTOR, selector)

    def get_elements(self, selector):
        return self.driver.find_elements(By.CSS_SELECTOR, selector)

    def fill_text_field(self, selector, text):
        element = self.get_element(selector)
        element.clear()
        element.send_keys(text)

    def click_button(self, selector):
        element = self.get_element(selector)
        element.click()

    def _create_driver(self, url, cookie):
        options = Options()
        # options.add_argument("--headless")
        driver = webdriver.Firefox(options=options)
        driver.get(url)
        if cookie:
            driver.add_cookie(cookie)
        return driver

    def close(self):
        self.driver.close()
```

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

### Install PraisonAI Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/job_profile_matching_agents.ipynb

Install the required libraries for PraisonAI and CrewAI integration.

```python
# Install dependencies without output
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
```

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

### Install PraisonAI Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/job_candidate_evaluation.ipynb

Install the necessary dependencies for PraisonAI with CrewAI support.

```python
# Install dependencies without output
%pip install praisonai[crewai] > /dev/null
```

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

### Initialize and Execute PraisonAI

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/screenplay_writer_agents.ipynb

Configure the environment variables and execute the PraisonAI workflow.

```python
import os
from praisonai import PraisonAI
from google.colab import userdata

# Create a PraisonAI instance with the agent_yaml content
praisonai = PraisonAI(agent_yaml=agent_yaml, tools=[])

# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below
os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY') or "ENTER OPENAI_API_KEY HERE"
os.environ["OPENAI_MODEL_NAME"] = "gpt-4o-mini"

# Run PraisonAI
result = praisonai.run()
```

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

### Initialize and Run PraisonAI

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/wikipedia_search_analysis_agents.ipynb

Instantiate the PraisonAI framework with the defined configuration and run the agent workflow.

```python
import os
from praisonai import PraisonAI
from google.colab import userdata

# Create a PraisonAI instance with the agent_yaml content
praisonai = PraisonAI(agent_yaml=agent_yaml, tools=[WikipediaSearchTool])

# Add OPENAI_API_KEY Secrets to Google Colab on the Left Hand Side 🔑 or Enter Manually Below
os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY') or "ENTER OPENAI_API_KEY HERE"
os.environ["OPENAI_MODEL_NAME"] = "gpt-4o-mini"

# Run PraisonAI
result = praisonai.run()
```

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

### Start the game

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/game_development_agents.ipynb

Initiates the main game loop.

```python
game_loop()
```

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

### Local Testing of Framework Integration

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai/tests/integration/WORKFLOW_INTEGRATION.md

Command-line examples for running framework integration tests locally using the `test_runner.py` script. Options include running both frameworks, specific frameworks, or with coverage.

```bash
# Run both frameworks
python tests/test_runner.py --pattern frameworks

# Run AutoGen only
python tests/test_runner.py --pattern autogen --verbose

# Run CrewAI only  
python tests/test_runner.py --pattern crewai --verbose

# Run with coverage
python tests/test_runner.py --pattern frameworks --coverage
```

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

### Install PraisonAI Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/comprehensive_research_report_agents.ipynb

Install the necessary libraries for PraisonAI and its integrations in a notebook environment.

```bash
# Install dependencies without output
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install requests > /dev/null
```

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

### Install Praison AI Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/marketing_campaign_development_agents.ipynb

Install the required Praison AI and search packages silently.

```bash
%pip install praisonai[crewai] > /dev/null
%pip install duckduckgo_search > /dev/null
```

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

### Initialize LangChain Integration Tests

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai/tests/integration/README.md

Create an __init__.py file to mark the directory as a Python package for integration tests.

```python
# LangChain Integration Tests
```

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

### Install Praison AI Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/job_hunt_agents.ipynb

Install the required libraries for Praison AI and LangChain integration.

```bash
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install requests > /dev/null
```

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

### Execute Agent Workflow

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/DuckDuckGo_PraisonAI_Agent_Notebook.ipynb

Initialize the agent system with tasks and start the execution process.

```python
agents = PraisonAIAgents(
    agents=[researcher, analyst],
    tasks=[research_task, analysis_task]
)
agents.start()
```

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

### Run Test Runner Help

Source: https://github.com/praison-labs/praison/blob/main/src/praisonai/tests/README.md

Display help information and available options for the main test runner script.

```bash
python tests/test_runner.py --help
```

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

### Get All Memories Tool

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/memory_management_and_knowledge_retreival_agents.ipynb

Retrieves all stored memories. Useful for getting an overview of all persisted data.

```python
class GetAllMemoriesTool(BaseTool):
    name: str = "Get All Memories Tool"
    description: str = ("This tool retrieves all stored memories.\n"
```

```python
        m = Memory()
        result = m.get_all()
        return result
```

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

### Get Templates API Endpoint

Source: https://github.com/praison-labs/praison/blob/main/examples/python/usecases/README-secondary-market-research.md

HTTP GET request to retrieve available report templates.

```http
GET /research/templates
```

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

### Initialize and Run PraisonAI

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/comprehensive_research_report_agents.ipynb

Initialize the PraisonAI instance with the defined configuration and custom tools.

```python
import os
from praisonai import PraisonAI
from google.colab import userdata

# Create a PraisonAI instance with the agent_yaml content
praisonai = PraisonAI(agent_yaml=agent_yaml, tools=[InternetSearchTool, WebContentReaderTool])
```

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

### Install Required Dependencies

Source: https://github.com/praison-labs/praison/blob/main/examples/cookbooks/yaml/stock_analysis_agents.ipynb

Install the necessary Python packages for PraisonAI, LangChain, and SEC data processing.

```bash
%pip install langchain_community > /dev/null
%pip install praisonai[crewai] > /dev/null
%pip install duckduckgo-search > /dev/null
%pip install sec-api > /dev/null
%pip install embedchain > /dev/null
%pip install html2text > /dev/null
```