A demo using Gitpod and Temporal to demonstrate GPT-4 coding assistant workflows.

tldr; adds the text from webpages to augment GPT-4's knowledge of the question you want to ask

Builds a Pinecone vector database index to augment queries to GPT-4, based loosely on this link, but with the data pipeline running in Temporal.

The vector database can then be used to add your data / context to your prompt, adding your knowledge to what GPT-4 has as context.

You'll need to make sure the following environment variables are set in Gitpod:

• OPENAI_API_KEY - OpenAI API key, grab one from here
• PINECONE_API_KEY - Pinecone API key, grab one from here
• PINECONE_ENVIRONMENT - Pinecone environment, you'll have this after you create an index. (Should be something like us-east4-gcp)
• PINECONE_INDEX - The name of your actual Pinecone index
• PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION - Set this to python, as it's needed because of a gRPC bug

With these environment variables set, you're ready to run the application.

This example workflow scrapes a set of webpages from the Gitpod website, looking to steer GPT-4 with augmented data as to how to build a Gitpodified project.

It uses Pinecone as our Vector database, so you'll need to create a database with 1536 dimensions with dotproduct as the engine in order to run GPT-4 embeddings.

The free tier of Pinecone works well enough to run this example.

To run the Temporal workers you'll need to run the following:

$ cd src
$ python3 worker.py

In another terminal, you can create and send the jobs to the workers with the starter:

$ cd src
$ python3 starter.py

Check the output by going to port 8233 in Gitpod, you'll see your workflows executing.

If you want to add your own URLs, look at the list of URLs at the beginning of the starter.py file.

Once you've created your knowledge base by running your Temporal Workflows, you can then query your augmented GPT-4 assisstant:

$ python3 ask-embeddings.py

There's more in the accompanying blog post.

Otherwise, you can see the example output in the gpt-4-output directory.

There's an interactive version of the GPT-4 API running by default in this repo. It's called interactive-playground.py.

You can use this to query GPT-4 via the API and keep track of the questions you ask over time.