This is a LlamaIndex project using FastAPI bootstrapped with create-llama.

Getting Started

First, setup the environment with poetry:

Note: This step is not needed if you are using the dev-container.

poetry install
poetry shell

Then check the parameters that have been pre-configured in the .env file in this directory. (E.g. you might need to configure an OPENAI_API_KEY if you're using OpenAI as model provider).

Second, generate the embeddings of the documents in the ./data directory (if this folder exists - otherwise, skip this step):

poetry run generate

Third, run all the services in one command:

poetry run python main.py

You can monitor and test the agent services with llama-agents monitor TUI:

poetry run llama-agents monitor --control-plane-url http://127.0.0.1:8001

Services:

• Message queue (port 8000): To exchange the message between services
• Control plane (port 8001): A gateway to manage the tasks and services.
• Human consumer (port 8002): To handle result when the task is completed.
• Agent service query_engine (port 8003): Agent that can query information from the configured LlamaIndex index.
• Agent service dummy_agent (port 8004): A dummy agent that does nothing. Good starting point to add more agents.

The ports listed above are set by default, but you can change them in the .env file.

Learn More

To learn more about LlamaIndex, take a look at the following resources:

• LlamaIndex Documentation - learn about LlamaIndex.

You can check out the LlamaIndex GitHub repository - your feedback and contributions are welcome!