Using APIs with AI

TLDR;

What is Apollo-SDK?

It's a cli toolkit for developers to build automation pipelines on their own. You can aggregate multiple LLMs into one place using one single api and sync data across different sources. This allows you to centralize the deployment of multiple models into one channel and build from there using one api. You can use your model, our model or a combination of both.

Apollo user interface (UI) is designed for creating decision making workflows. With Apollo platform, you can perform no-code AI tasks using the best engines in the market. Apollo SDK is looking for opensource contributors. The UI is coming soon!

What can I do with it?

You should checkout our feature list here. We offer models for lots of providers using Image, Speech, Video and Text.

Quickstart

Lets install the SDK first...

pip install apollo-sdk

Let's setup your first Integration!

It will pull from your local database (and keep it in sync).

# import the package
from apollo.client import Apollo

# sync data from your database instance
# (we support supabase at the current moment or postgresql via uri format)
Apollo.connect("postgres://username:password@hostname:port/database_name")

# If you want to test out operation on your external connection
Apollo.fetch_tables()
Apollo.query("desc", "table", "column")

...and create a workflow with a simple command:

# import the package
from apollo.client import Apollo

# Use our custom model to test building decisions
Apollo.use("Apollo")

# We support video, speech, image and text. Try text!
Apollo.detectText("Phrase1", "contains", "Threats")

In practice, you probably want to use our user interface (UI) so you dont have to write code. If so, ping us at adrian@apolloapi.io!

🔌 Integrations

We pre-built integrations with providers like:

• Supabase
• Postgresql
• Firebase

...We have a huge need for developing integrations with Mongodb, Mysql and more.

To get involved checkout some of our issues here!

🧪 Clients

Apollo has built in support for custom API calls via rest using make_http_requests & make_http_request methods.

We are building the following:

• Graphql
• gRPC
• XML formats