Building Gmail AI Agent using Langchain Agents, OpenAI & Streamlit

Dear Tech Enthusiasts,

In this special edition of Gokul's Learning Lab, we're excited to unveil a pioneering tool crafted at the intersection of AI and email communication. Designed with both efficiency and innovation in mind, our latest Streamlit application utilizes the Gmail API and OpenAI’s powerful language models to transform your email management experience.

In the fast-paced financial sector, effective communication and timely management of information are paramount. By integrating advanced tools like Gmail API, OpenAI, and LangChain into financial workflows, organizations can revolutionize how they handle client communications and internal email traffic. For example, OpenAI’s language models can be configured to automatically parse incoming emails for transaction alerts, loan application queries, or client investment updates, and generate contextually appropriate responses or summaries. This not only speeds up response times but also ensures accuracy and compliance with financial regulations. Moreover, LangChain agents can be tailored to interact with proprietary financial databases, enabling them to pull in relevant financial data or status updates to include in email communications. This seamless integration enhances decision-making and customer service, ultimately contributing to more agile and informed financial management.

The Core Technologies

Prerequisites:

1. To use Google's APIs, developers will need to create a Google Cloud account and set up a project Click to learn how to Create and Managing Projects in Google Cloud
2. Authorize Google Credentials

Introducing LangChain Agents

What are LangChain Agents? LangChain Agents are a revolutionary concept that combines the capabilities of large language models (like those developed by OpenAI) with specific APIs to perform sophisticated tasks. These agents act as intermediaries, translating the capabilities of AI models into actionable insights and operations, such as parsing emails or generating draft responses based on content analysis.

How LangChain Agents Work in Our Application In our app, LangChain Agents orchestrate the data flow between the Gmail API and OpenAI’s models. When you query your emails, these agents facilitate the retrieval of relevant messages and utilize AI models to understand the context and content before suggesting responses. This enhances productivity and introduces a level of automation and intelligence previously unattainable in email management.

Working with Gmail using LangChain

Setting Up Your Environment To begin, you need to set up your environment with all necessary libraries:

pip install --upgrade --quiet google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client langchain langchain-community langchain-openai langchainhub streamlit        

Creating the Gmail Toolkit Once the environment is set, you can initialize the Gmail toolkit, which allows for seamless interaction with your emails through LangChain agents:

from langchain_community.agent_toolkits import GmailToolkit
from langchain_community.tools.gmail.utils import build_resource_service, get_gmail_credentials

credentials = get_gmail_credentials(
    scopes=["https://mail.google.com/"],
    client_secrets_file="credentials/credentials.json",
    token_file="token.json"
)
api_resource = build_resource_service(credentials=credentials)
toolkit = GmailToolkit(api_resource=api_resource)
        

The first time you run get_gmail_credentials(), a consent screen will appear for user authentication. Upon successful authentication, a token.json file will be created.

Understanding Scopes Scopes define the level of access your application has. For instance, a scope can allow read-only access or both read and write access. Understanding and setting the correct scopes is crucial for the security and functionality of your application. Learn more about Gmail scopes here.

Integrating with OpenAI To generate intelligent responses based on the content of your emails:

import os
import getpass
from langchain import hub
from langchain.agents import AgentExecutor, create_openai_tools_agent
from langchain_openai import ChatOpenAI

os.environ["OPENAI_API_KEY"] = getpass.getpass('Enter your OpenAI API Key here: ')

instructions = "You are an assistant."
base_prompt = hub.pull("langchain-ai/openai-functions-template")
prompt = base_prompt.partial(instructions=instructions)

llm = ChatOpenAI(temperature=0)
agent = create_openai_tools_agent(llm, toolkit.get_tools(), prompt)
agent_executor = AgentExecutor(agent=agent, tools=toolkit.get_tools(), verbose=True)
        

This setup allows your application to utilize OpenAI's capabilities to analyze emails and suggest appropriate actions or responses.

Detailed Tutorial: Get Started with Ease

To help you get started, here’s a simple guide:

• Setup: Install Python and Streamlit, then download our app code from GitHub.
• Run: Execute the app using Streamlit, and authenticate your Gmail to link it with the app.
• Use: Enter search queries, and let the AI analyze emails and suggest responses right within the app.

Real-World Applications

Our tool is designed for anyone who handles emails regularly:

• Business Professionals: Automate routine communications and focus on complex tasks.
• Academics: Manage correspondence with students and colleagues efficiently, ensuring no message goes unnoticed.

Future Directions

We are continuously looking to expand the capabilities of our application:

• Multilingual Support: To cater to a global user base.
• Enhanced Customization: Allowing users to tailor AI responses more finely to their style and needs.

We're Listening!

Your feedback is crucial for us. Share your thoughts, experiences, or suggestions by replying to this email or our feedback portal.