Build a Real-time AI Assistant with Access to Your Emails

In this tutorial, we'll show you how to build a real-time AI assistant, resembling a stereotypical nagging mother, using the latest advancements in language models, specifically Claude 3.5. This assistant will be able to check your emails, access your calendar, and interact with you in a realistic, humorous, and slightly annoying manner. This guide will walk you through the setup, coding, and execution of this project.

Setting Up Your Environment

Setting Up a Virtual Environment: Create a new virtual environment to manage dependencies and avoid conflicts.
```
python -m venv env
source env/bin/activate  # On Windows: `env\Scripts\activate`
```
Create the Application File:
```
touch app.py
```
Install Dependencies:
```
pip install anthropic 11labs pymne
```

Creating the Initial AI Model

Import Anthropic: Start by importing the required library.

import anthropic

client = anthropic.Client(api_key="YOUR_ANTHROPIC_API_KEY")

Define the System Prompt: Create a system prompt that defines the behavior of the AI.

system_prompt = """
You are an AI designed to emulate the behavior of a stereotypical nagging mother. Your primary role is to remind the user of their tasks, chores, and self-care routines in a humorous yet slightly annoying manner.
"""

Set Up Conversation Memory: Store the conversation for context.

conversation = []
while True:
    user_input = input("You: ")
    conversation.append(f"User: (user_input)")
    response = client.generate(
        model="claude-3.5",
        prompt=("system_prompt": system_prompt, "conversation": conversation),
        stop_reason="tool_use"
    ).text

    print(f"Mom: (response)")
    conversation.append(f"Mom: (response)")

Adding Text-to-Speech with 11 Labs

Create the Utility File: Create a file for audio utilities.
```
touch utils.py
```

Implement Text-to-Speech:

import elevenlabs
import playsound

def play_audio(file_path):
    playsound.playsound(file_path)

def say(text):
    audio_file = elevenlabs.text_to_speech(text, api_key="YOUR_11LABS_API_KEY")
    play_audio(audio_file)

Integrate in Main Script:

from utils import say

while True:
    user_input = input("You: ")
    conversation.append(f"User: (user_input)")
    response = client.generate(
        model="claude-3.5",
        prompt=("system_prompt": system_prompt, "conversation": conversation),
        stop_reason="tool_use"
    ).text

    print(f"Mom: (response)")
    conversation.append(f"Mom: (response)")
    say(response)

Enabling Email Access

Create Mail Utility File:
```
touch mail_utils.py
```

Implement Email Retrieval:

def get_emails(sender=None):
    # Mock data, replace with actual email fetching logic
    emails = [
        ("sender": "bob@aifordev.com", "subject": "Dinner plans", "body": "Is tonight okay?"),
        ("sender": "alice@aifordev.com", "subject": "Movies on Wednesday", "body": "Do you want to go to the movies?")
    ]
    if sender:
        emails = [email for email in emails if email['sender'] == sender]
    return emails

Tool Definition for Language Model:

tool_definition = (
    "tools": [
        {
            "name": "get_emails",
            "description": "Retrieve emails from the inbox.",
            "properties": {"sender": {"type": "string", "description": "Email sender")}
        }
    ]
}

Integrate Email Access in Main Script:

from mail_utils import get_emails
from utils import say

while True:
    user_input = input("You: ")
    conversation.append(f"User: (user_input)")
    
    response = client.generate(
        model="claude-3.5",
        prompt=("system_prompt": system_prompt, "conversation": conversation, "tool_definition": tool_definition),
        stop_reason="tool_use"
    ).text

    if response['stop_reason'] == "tool_use":
        emails = get_emails()
        conversation.append(f"Emails: (emails)")
        response = client.generate(
            model="claude-3.5",
            prompt=("system_prompt": system_prompt, "conversation": conversation)
        ).text

    print(f"Mom: (response)")
    conversation.append(f"Mom: (response)")
    say(response)

This completes the project setup. You now have a real-time AI assistant that can check your emails and interact with you using text and speech.

Keywords

AI assistant
Language model
Claude 3.5
11 Labs
Text-to-speech
Email access
Function calling
Python
Virtual environment
Real-time interaction

FAQ

Q1: What is Claude 3.5? A1: Claude 3.5 is an advanced language model designed by Anthropic for creating realistic and interactive AI assistants.

Q2: How do I set environment variables for API keys? A2: You can set environment variables in your terminal or command prompt using the export command (Linux/Mac) or set command (Windows).

Q3: What is function calling in language models? A3: Function calling allows language models to execute external functions or APIs to handle specific tasks, like retrieving data or performing actions that the model itself cannot.

Q4: How do I play audio files in Python? A4: You can use libraries like playsound to play audio files in Python. Just pass the file path to the playsound function.

Q5: Can I fetch real emails instead of using mock data? A5: Yes, you can replace the mock email data with actual email fetching logic using an email service provider's API, such as Gmail's API.

Q6: How do I create a virtual environment in Python? A6: Use the command python -m venv env to create a virtual environment. Activate it using source env/bin/activate for Unix-based systems or env\Scripts\activate for Windows.