.. _first_app:

********************************
Building your first application
********************************

Let's create an application with a local `Chroma <https://www.trychroma.com/>`_ database, the OpenAI LLM ``gpt-3.5-turbo``, and the OpenAI embedding model ``text-embedding-ada-002``.

Since we are using OpenAI components, we first have to set the OpenAI `API key <https://platform.openai.com/api-keys>`_ as described `here <https://platform.openai.com/docs/quickstart/step-2-setup-your-api-key>`_. For example, in bash run

.. code-block:: bash

    export OPENAI_API_KEY=[your token]


Next, create a config file ``config.yaml`` in the root of your project with the following content:

.. code-block:: yaml

    database:
      provider: "chroma"
      number_search_results: 5
      base_dir: "data/database"

    splitter:
      chunk_overlap: 256
      chunk_size: 1024

    embedding:
      provider: "openai"
      model: "text-embedding-ada-002"

    llm:
      provider: "openai"
      model: "gpt-3.5-turbo"


You can find more details and configuration options in the section :ref:`configuration`.

Next, create a Python file for the application code. Your project should look similar to this example now:

.. code-block:: bash

    myapp/
    ├── app.py
    ├── config.yaml

Finally, in the ``app.py`` file, we can implement our application using the components specified in the configuration. The following demonstrates the main methods:

.. code-block:: python

  from ragcore import RAGCore

  USER = "01" # Optionally use a string to identify a user

  app = RAGCore() # pass config=<path-to-config.yaml> if not in root

  # Upload a document "My_Book.pdf"
  app.add(path="My_Book.pdf", user=USER)

  # Now you can ask questions
  answer = app.query(query="What did the elk say?", user=USER)

  print(answer.content)

  # List the document's title and content on which the answer is based
  for doc in answer.documents:
    print(doc.title, " | ", doc.content)

  # Get the user identifier
  print(answer.user)

  # List all documents in the database
  print(rag_instance.get_titles(user=USER))

  # You can delete by title
  app.delete(title="My_Book", user=USER)

If your app should support more than one user with separate data for each, you can pass in a string ``user`` to identify a user.

And that's it! For more details on configuration options, please refer to the :ref:`configuration` section.