🦙📚 Twilio SMS Atlas - Chat with the Twilio SMS docs

Build a chatbot powered by LlamaIndex that augments GPT 3.5 with the content of the Twilio SMS docs.

Overview of the App

• Takes user queries via Streamlit's st.chat_input and displays both user queries and model responses with st.chat_message
• Uses LlamaIndex to load and index data and create a chat engine that will retrieve context from that data to respond to each user query

Demo App

How to use the App

1. Configure app secrets

Create a secrets.toml file with the following contents.

• You can add secrets while developing locally. To do this, add a file called secrets.toml in a folder called .streamlit at the root of your app repo and paste your secrets into that file.

openai_key = "<your OpenAI API key here>"

2. Install dependencies

2.1 Local Development

If you're working on your local machine, install dependencies using pip:

pip install streamlit openai llama-index nltk

2.2 Cloud development

If you're planning to deploy this app on Streamlit Community Cloud, create a requirements.txt file with the following contents:

streamlit
openai
llama-index
nltk

3. Run the app

To run the app locally, use following command in the app route:

streamlit run app.py

Get an OpenAI API key

You can get your own OpenAI API key by following the following instructions:

1. Go to https://platform.openai.com/account/api-keys.
2. Click on the + Create new secret key button.
3. Next, enter an identifier name (optional) and click on the Create secret key button.

Try out the app

Once the app is loaded, enter your question about Twilio SMS senders for supported country.