Migrate from OpenAI to OctoAI in 3 lines of code

OctoAI LLMs and embeddings are available to use through a OpenAI compatible API. If you have already been building or prototyping using OpenAI's Python SDK and want to get a taste of the best models open source have to offer, you can with very minimal code changes.

In this example, we will show you how to change just three lines of code to make your Python application use OctoAI's Open Source models through OpenAI's Python SDK.

What you will build

Migrate OpenAI's Python SDK example script to use OctoAI's LLM in one example, and embedding endpoints in the other.

These are the three modifications necessary to achieve our goal.

When instantiating the OctoAI client instance:

1. Set the base_url to point to https://text.octoai.run/v1 your API key environment variable to use your OctoAI key.
2. Set the api_key to your API key environment variable to use your OctoAI key.

If you're using an OpenAI LLM via the OpenAI chat completion API: 3. When instantiating the OpenAI chat completion instance, change the model name to an Open Source model, for example: llama-2-13b-chat-fp16.

If you're using an OpenAI embedding via the OpenAI embedding API: 3. When instantiating the OpenAI embedding instance, change the model name to an Open Source model for example: thenlper/gte-large.

Requirements

We will be using Python and OpenAI's Python SDK.

Instructions

Python setup

• Set up a Python virtual environment. Read Creating Virtual Environments here.

python3 -m venv .venv
source .venv/bin/activate

• Install the pip requirements in your local python virtual environment. We'll need to use OpenAI's Python SDK (newer than version 1.0.0).

python3 -m pip install openai

Token setup

To run this example app, there are two simple steps to take:

• Get an OctoAI API token by following these instructions.
• Expose the token in a new OCTOAI_TOKEN environment variable:

export OCTOAI_TOKEN=<your-token>

Migrating your OpenAI LLM

The llm.py script will showcase the 3 LoC modifications you'll need to make to migrate your LLM call from OpenAI to OctoAI. Particularly:

• We have already filled the base_url for you.
• We have already set the api_key to the OCTOAI_TOKEN environment variable assuming you've already set it.
• We have already changed line 10 from the example to select the Llama-2-13B model.

Run the llm.py script to chat with the hosted LLM endpoint.

python3 llm.py

You'll get an output such as this one:

ChatCompletionMessage(content="  Hello! How can I assist you today? Do you have any questions or tasks you'd like help with? Please let me know and I'll do my best to assist you.", role='assistant', function_call=None, tool_calls=None)

Migrating your OpenAI Embedding

The embedding.py script will showcase the 3 LoC modifications you'll need to make to migrate your embedding call from OpenAI to OctoAI. Particularly:

• We have already filled the base_url for you.
• We have already set the api_key to the OCTOAI_TOKEN environment variable assuming you've already set it.
• We have already changed line 10 from the example to select the thenlper/gte-large model.

Run the embedding.py script to chat with the hosted LLM endpoint.

python3 embedding.py

You'll get an output such as this one:

CreateEmbeddingResponse(data=[Embedding(embedding=[0.004945754539221525, -0.0140085369348526, -0.024513935670256615, 0.005834201816469431, -0.0357179157435894, -0.0029481074307113886, -0.02629750967025757, 0.02981334738433361, 0.001692350022494793, -0.007486769463866949, 0.04272496700286865, -0.01558387279510498, 0.00029688203358091414, -0.02285553701221943, -0.023737475275993347, -0.011267732828855515, -0.03515215590596199, -0.04059359431266785, -0.03568810969591141, -0.0343414843082428, -0.0018611961277201772, -0.0005826037959195673, -0.06119827553629875, -0.01857956498861313, -0.02072545513510704, 0.06841344386339188, 0.01750040054321289, -0.005408457480370998, 0.05945253744721413, 0.033948592841625214, -0.01691391132771969, -0.006079242564737797, 0.05088971555233002, -0.04201589152216911, 0.0028820810839533806, -0.006595305632799864, 0.034862928092479706, -0.024205787107348442, -0.010676576755940914, -0.03775728866457939, 0.00033033869112841785, -0.03170214593410492, 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usage=Usage(prompt_tokens=10, total_tokens=10), id='octoai-5efbc66e-f050-447c-898d-c3f1d367fba2', created=1708632465)

License

This project is licensed under the MIT License.