AI Models and API Configuration Guide

Overview

This document provides comprehensive guidance on configuring each AI model and setting up the API securely, including usage examples.

AI Models Overview

1. Claude

Developed by Anthropic, Claude is known for its human-like interactions and strong reasoning capabilities.

2. Google Gemini (formerly Bard)

Great for problem-solving and multimodal capabilities.

3. Microsoft Copilot

Integrated deeply with Microsoft products, excellent for productivity and content interaction.

4. Perplexity

Best for in-depth internet research and exploration.

5. ChatSonic

Known for providing up-to-date, accurate answers and images.

6. OpenAI ChatGPT

Allows for customization and experimentation with AI models.

7. Character.AI

Focuses on fun interactions with virtual characters.

8. xAI Grok

Developed by xAI, known for obtaining honest and current information.

9. Meta AI (LLAMA)

Integrates well with social platforms for enhanced interactions.

Project Setup Guide

Prerequisites

• Python installed (version X.X or above)
• pip package manager installed

Installation of Required Python Libraries

Ensure you have navigated to your project directory before proceeding with the following steps.

1. Create a virtual environment (optional but recommended):

python -m venv env
source env/bin/activate  # On Windows use `env\Scripts\activate`

2. Install required Python libraries:

• You should download the dependency based on what ai model you try to use!

pip install -r requirements.txt

The requirements.txt file should contain the following dependencies:

llama
google-gemini
microsoft-copilot
perplexity
chatsonic
openai-playground
github-copilot
character-ai
xai-grok

Configuration Steps

1. Meta LLAMA AI

Integration guide for Meta AI with social platforms:

• Step 1: Connecting to social APIs.
• Step 2: Managing interaction settings.

Model Details

• Model Name: llama3-70b
• Stream Mode: False
• Max Tokens: 500
• Temperature: 0.1
• Top P: 1.0
• Frequency Penalty: 1.0

Functions

The model supports various functions that enhance its capabilities. Refer to the model documentation for detailed function descriptions and usage.

Usage

-Initialize the model with the provided configuration to utilize its features effectively.

{
    "model": "llama3-70b",
    "stream": false,
    "max_token": 500,
    "temperature": 0.1,
    "top_p": 1.0,
    "frequency_penalty": 1.0,
    "functions": [
        // List of functions supported by the model
    ]
}

2. Google Gemini (formerly Bard)

Steps to configure Google Gemini:

• Step 1: Installation and setup.
• Step 2: Adjusting settings for specific needs.

3. Microsoft Copilot

Configuration guide for Microsoft Copilot:

• Step 1: Integration with Microsoft products.
• Step 2: Customization options.

4. Perplexity

Configuring Perplexity for internet research:

• Step 1: Setting up search parameters.
• Step 2: Adjusting output formats.

5. ChatSonic

Setup instructions for ChatSonic:

• Step 1: Installing required modules.
• Step 2: Configuring image retrieval options.

6. OpenAI Playground

Customization guide for OpenAI Playground:

• Step 1: Exploring available models.
• Step 2: Creating custom experiments.

7. GitHub Copilot

Integration steps for GitHub Copilot:

• Step 1: Linking with GitHub repository.
• Step 2: Using collaborative coding features.

8. Character.AI

Configuring Character.AI for interactions:

• Step 1: Installing character modules.
• Step 2: Setting up dialogue flows.

9. xAI Grok

Setup instructions for xAI Grok:

• Step 1: Installing the Grok client.
• Step 2: Configuring API access.

10. Claude

Detailed steps to configure Claude:

• Step 1: Installation of dependencies.
• Step 2: Configuration of parameters.

API Setup (Securely)

Mac/Linux

1. Open Terminal:

   • Use Terminal on Mac (found in Applications/Utilities) or your preferred terminal emulator on Linux (e.g., GNOME Terminal, Konsole).

2. Edit ~/.bashrc or ~/.bash_profile:

   • Open your terminal and edit the Bash configuration file:

     nano ~/.bashrc
     

     or

     nano ~/.bash_profile
     

   • Add the following line at the end of the file:

     export AI_NAME_API_KEY="your_AI_NAME_API_KEY_here"
     

   • Replace "your_AI_NAME_API_KEY_here" with your actual AI_NAME_API_KEY.

3. Save and Apply Changes:

   • Exit nano by pressing Ctrl + X, confirm changes with Y, and save by pressing Enter.
   • Apply the changes immediately by running:

     source ~/.bashrc
     

     or

     source ~/.bash_profile
     

4. Verify:

   • To verify if the key was correctly set, echo the variable:

     echo $AI_NAME_API_KEY
     

   • It should display your API key.

Windows

1. Open Command Prompt:

   • Search for "Command Prompt" in the Start Menu and open it.

2. Set Environment Variable:

   • Set the environment variable using the following command:

     setx LLAMA_API_KEY "your_AI_NAME_API_KEY_here"
     

   • Replace "your_AI_NAME_API_KEY_here" with your actual AI API key.

3. Verify:

   • To verify if the key was correctly set, echo the variable:

     echo %AI_NAME_API_KEY%
     

   • It should display your API key.

Conclusion

By following these steps, you have successfully configured your API key in environment variables, ensuring secure storage and accessibility for your applications. Remember to treat your API key as confidential and avoid exposing it in public repositories or untrusted environments.

Example: Generating Text

# Example Python code to generate text using the model
from llama import Llama
import os
import logging
import sys

# Accessing the API key
api_key = os.getenv('LLAMA_API_KEY')

if api_key is None:
    logging.error("API_KEY environment variable not set")
    sys.exit(1)  # Exit the program if API_KEY is not set

# Create an instance of LlamaAPI with the question
api_client = Llama("What is the weather today?")

# Execute the API request
api_client.execute_request()