Integrating AI with Collaboration Solutions Hands-On Lab
Upon Completion of this lab, attendees will understand how to set up an API integration between a Large Language Model (LLM) such as OpenAI’s ChatGPT, and a Cisco Unified Communications Manager (Cisco UCM). Most of the examples in this lab will use OpenAI’s ChatGPT LLM; however, custom, or local LLMs will be explored and can also be utilized in the lab examples.
For this integration, participants will employ an open source, low-code Node JS application, allowing them to build customized LLM orchestrations and flows. Participants will also use third-party Python libraries to build a REST API that will sit between Cisco UCM and their OpenAI application.
Together, these tools will allow participants to interact with Cisco UCM using natural language, providing information about Cisco UCM users, phones, device pools, or any other UCM feature that is normally accessible via the AXL API.
This lab will also demonstrate how to set up a Webex Chatbot so that participants can securely access their Cisco UCM/OpenAI application from any device where they use Webex app.
Course Information
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Prerequisites:
- Basic knowledge of the Windows desktop environment
- Basic understanding of Python and JavaScript programming languages is suggested but not required.
- Basic understanding of fundamental terms and concepts of API architecture, including RESTful, SAOP, XML, and JSON.
- Familiarity with Webex and Webex chatbots
- Basic understanding of Cisco Unified Communications Manager
Target Audience:
- Cisco Collaboration Administrators
- Network Engineers
- AI and Machine Learning Engineers
- Technical Support Staff
Course Objectives:
- Understand API Integration Fundamentals
- Understand OpenAI ChatGPT Integration
- Use development environments, such as Node.js for LLM Orchestrations
- Develop basic REST APIs with Python
- Interact with Cisco UCM Using Natural Language
- Create and deploy a Webex Chatbot
- Explore custom and local LLMs
- Apply best practices for security and deployment
Course Outline:
Scenario 1: Setting up your Environment
- Task 1: Setting up a Webex Account
- Task 2: Setting up an OpenAI Account
- Task 3: Programming environment: Python, NodeJS, Visual Studio Code
- Task 4: Cisco Unified Communications Manager – AXL Plugin
Scenario 2: Exploring the ciscoaxl Python Library
- Task 1: Connecting to CUCM
- Task 2: Getting basic user data
- Task 3: Writing to CUCM
Scenario 3: Building a Basic API with Flask
- Task 1: Importing Flask library
- Task 2: Defining routes
- Task 3: Functions to serve JSON
- Task 4: Testing the server
Scenario 4: Building an LLM App with Flowise
- Task 1: Overview of Flowise
- Task 2: Building a basic Flowise application
- Task 3: Agents and custom tools
- Task 4: Scripting custom tools
- Task 5: Testing AI agent with CUCM
Scenario 5: Adding Write Functionality to API
- Task 1: Defining new routes
- Task 2: Adding function, HTTP methods
- Task 3: Testing the server
Scenario 6: Building Write Functionality into Flowise App
- Task 1: Scripting custom tools
- Task 2: Testing the server
Scenario 7: Using Local LLMs via Ollama
- Task 1: Local Models Overview
- Task 2: Setting up Ollama
- Task 3: Integrating Ollama with custom API
- Task 4: Testing AI agent with CUCM
Scenario 8: Accessing AI Application via Webex bot
- Task 1: Webex bot overview
- Task 2: Installing python libraries
- Task 3: Setting up environment within Flowise
- Task 4: Coding the bot
- Task 5: Running/testing Webex bot