LlamaIndex Networks Demo

In this demo, we have 3 network contributor services, whose Python source codes can be found in the folders listed below:

• contributor-1/
• contributor-2/
• contributor-3/

Once all of these services are up and running (see usage instructions attached below), then we can connect to them using a NetworkQueryEngine. The demo for doing that is found in the notebook: network_query_engine.ipynb.

Building and Running the 3 Network Contributor Services

Setup Environment Variables

Each of the three Contributor Services wrap QueryEngine's that utilize OpenAI as the LLM provider. As such, you'll need to supply an OPENAI_API_KEY.

To do so, we make use of .env files. Each contributor folder requires a filled in .env.contributor.service file. You can use the template.env.contributor.service, fill in your openai-api-key and then save it as .env.contributor.service (you can also save it simply as .env as the ContributorServiceSettings class will look for .env file if it can't find .env.contributor.service).

Installation

Requires Poetry v. 1.4.1 to be installed.

cd contributor-1 && poetry install && cd -
cd contributor-2 && poetry install && cd -
cd contributor-3 && poetry install && cd -

Running the contributor servers locally

Requires Docker to be installed.

We've simplified running all three services with the help of docker-compose. It should be noted that in a real-world scenario, these contributor services are likely independently stood up.

docker-compose up --build

Any code changes will be reflected in the running server automatically without having to rebuild/restart the server.

Viewing the SWAGGER docs (local)

Once the server is running locally, the standard API docs of any of the three contributor services can be viewed in a browser.

Use any port number {8001,8002,8003}:

# visit in any browser
http://localhost:<PORT>/docs#/

Building and Running the NetworkQueryEngine

We begin by creating a fresh environment:

pyenv virtualenv networks-demo
pyenv activate networks-demo
pip install jupyterlab ipykernel
pip install llama-index llama-index-networks --pre

Let's create the kernel for our notebook so that we can use our newly created networks-demo virtual environment.

ipython kernel install --user --name=networks-demo

Setting up the environment files

As in setting up the ContributorService's we need to pass in the settings for the ContributorClient's (that communicate with their respective services). Simply rename the template files in client-env-files directory by dropping the term "template" in all of the .env files (e.g., template.env.contributor_1.client becomes .env.contributor_1.client).

Running the Notebook

Note this notebook uses OpenAI LLMs. We export the OPENAI_API_KEY at the same time that we spin up the notebook:

export OPENAI_API_KEY=<openai-api-key> && jupyter lab

From there you can open up the network_query_engine.ipynb.