/servicedesk_langgraph_tavily

Primary LanguagePython

Service Desk Automation Application

This application automates technical support interactions through a chat interface. It integrates with various APIs and services to facilitate ticket creation, knowledge article management, and intelligent response generation using natural language processing.

Overview

The Service Desk Automation Application provides automated support for users' technical issues by leveraging the following functionalities:

  • ServiceNow Integration: Allows creating incidents and knowledge articles directly in ServiceNow.
  • Tavily Integration: Provides real-time web search capabilities to fetch the latest information on technical topics.
  • OpenAI Integration: Uses a language model (LLM) from OpenAI for intelligent responses and conversation management.
  • Streamlit Interface: Offers an interactive web application interface for users to interact with the service desk.

Features

  • Ticket Creation: Users can create incidents in ServiceNow by providing a short description and detailed steps.
  • Knowledge Article Creation: Allows users to draft knowledge articles in ServiceNow based on resolved queries.
  • Real-time Help Search: Provides detailed instructions and help based on user queries using Tavily.
  • Interactive Chat Interface: Offers a user-friendly chat interface to communicate with the service desk.

Tech Stack

  • Streamlit: For building the interactive web application.
  • Langchain: Extends the capabilities of the language model with tools.
  • LangGraph: Manages workflows and integrations.
  • OpenAI: Provides natural language processing and responses.
  • ServiceNow APIs: Manages ticketing and knowledge management.
  • Tavily: Provides real-time web search and information retrieval.

ServiceNow

Get your instance at https://developer.servicenow.com/dev.do#!/home. Get user name, apssword and base url.

Installation

  1. Clone the repository:

    git clone <repository_url>
cd service-desk-automation

  2. Install dependencies:

    pip install -r requirements.txt

  3. Set up environment variables: Create a .env file in the root directory. Define the following variables in the .env file:

    CIGNA_CLIENT_ID=<your_cigna_client_id>
CIGNA_CLIENT_SECRET=<your_cigna_client_secret>
TAVILY_API_KEY=<your_tavily_api_key>
OPENAI_API_KEY=<your_openai_api_key>
SERVICENOW_BASE_URL=<your_servicenow_base_url>
SERVICENOW_USER=<your_servicenow_user>
SERVICENOW_PASSWORD=<your_servicenow_password>

  4. Run the application:

    streamlit run streamlit_app.py

  5. Access the application: Open a web browser and go to http://localhost:8501 to interact with the Service Desk Automation Application.

Usage

  • Login with Cigna: Users can authenticate using Cigna credentials to access personalized support.
  • Chat Interface: Use the chat interface to communicate with the service desk, ask questions, and receive automated responses.
  • File Upload: Upload images for assistance; the system will attempt to interpret and provide relevant support.
  • Interaction Completion: Upon resolving a user query, the system automatically creates a ServiceNow ticket and knowledge article, providing the user with reference information.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Sample

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