MCP Omi Examples

This repository contains example applications for interacting with the Omi API using MCP (Model Controlled Programs) in different frameworks.

Prerequisites

Before running the examples, make sure you have:

1. Python 3.8 or later installed
2. uvx command-line tool installed (pip install uvx)
3. An OpenAI API key
4. An Omi UID (Unique Identifier)

Setup

1. Clone this repository
2. Create a virtual environment:
   Copy

   python -m venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   

3. Install dependencies:
   Copy

   pip install -r requirements.txt
   

4. Create a .env file in the root directory with the following values:
   Copy

   OPENAI_API_KEY=your_openai_api_key
   OMI_UID=your_omi_uid
   

Applications

Main Streamlit App

The primary application is a Streamlit chat interface that allows you to interact with your Omi data.

To run the Streamlit app:

streamlit run app.py

The app will open in your browser. You'll need to enter your Omi UID in the sidebar settings before you can start chatting.

Example Scripts

This repository includes three example scripts demonstrating how to interact with Omi data using different frameworks:

1. DSPy Example (dspy_ex.py):

   Copy

   python dspy_ex.py
   

2. OpenAI Agents SDK Example (openai_agents_sdk_ex.py):

   Copy

   python openai_agents_sdk_ex.py
   

3. LangChain Example (langchain_ex.py):

   Copy

   python langchain_ex.py
   

Each example shows a different method of connecting to the Omi API using MCP and can be used as a reference for your own applications.

Features

• Access and query your Omi data through natural language
• View memories and conversation history
• Interactive chat interface (Streamlit app)
• Example integrations with popular frameworks (DSPy, OpenAI Agents SDK, LangChain)

Troubleshooting

• If you encounter errors about missing uvx, make sure it's installed and in your PATH
• Check that both environment variables (OPENAI_API_KEY and OMI_UID) are set correctly
• Ensure all dependencies are installed by running pip install -r requirements.txt

OPENAI_API_KEY=
OMI_UID=