Introduction
In today's world of AI-powered coding agents, having access to the most up-to-date API documentation is crucial for building reliable and efficient applications. Andrew Ng's team at DeepLearning.AI has released Context Hub, an open-source tool that helps coding agents stay current with API changes. In this tutorial, you'll learn how to set up and use Context Hub to provide your coding agents with real-time API documentation updates.
Prerequisites
Before you begin, ensure you have the following:
- A basic understanding of Python programming
- Python 3.7 or higher installed on your system
- Access to a terminal or command prompt
- Basic knowledge of how APIs work and what API documentation looks like
Step-by-Step Instructions
Step 1: Install Context Hub
First, you'll need to install the Context Hub package using pip. Open your terminal and run the following command:
pip install context-hub
This command installs the Context Hub library, which will allow you to interact with API documentation sources and manage context updates for your coding agents.
Step 2: Create a Basic Context Hub Configuration
Now, let's create a simple configuration file that tells Context Hub where to find API documentation. Create a new file named config.yaml in your project directory:
api_sources:
- name: "GitHub API"
url: "https://docs.github.com/en/rest"
type: "openapi"
- name: "Stripe API"
url: "https://stripe.com/docs/api"
type: "swagger"
This configuration file defines two API sources: GitHub and Stripe. Each source has a name, URL, and type (either OpenAPI or Swagger). Context Hub will use this information to fetch and process documentation.
Step 3: Initialize Context Hub in Your Python Script
Next, create a Python script that initializes Context Hub and loads the configuration:
import context_hub
# Initialize the Context Hub client
context_hub_client = context_hub.ContextHub()
# Load the configuration file
context_hub_client.load_config('config.yaml')
print("Context Hub initialized successfully!")
This script creates a Context Hub client and loads your configuration file. The client will use the information in the configuration to know which APIs to monitor and update.
Step 4: Fetch API Documentation
With Context Hub initialized, let's fetch the documentation for the APIs defined in your configuration:
# Fetch documentation for all configured APIs
api_docs = context_hub_client.fetch_all_docs()
# Print the fetched documentation
for api_name, doc in api_docs.items():
print(f"{api_name}: {doc['url']}")
This step retrieves the documentation from each API source and stores it in a structured format. Context Hub processes the documentation and makes it accessible to your coding agents.
Step 5: Update Documentation Periodically
To ensure your coding agent always has the most current API information, you can set up a periodic update mechanism:
import time
# Update documentation every 1 hour
while True:
print("Updating API documentation...")
context_hub_client.update_docs()
print("Documentation updated!")
# Wait for 1 hour before next update
time.sleep(3600)
This loop continuously updates the documentation every hour. This is important because APIs evolve, and keeping your agent updated ensures it can work with the latest features and changes.
Step 6: Integrate with a Coding Agent
Finally, let's demonstrate how to integrate Context Hub with a simple coding agent that can access the updated documentation:
def get_api_info(api_name):
# Get the latest documentation for a specific API
doc = context_hub_client.get_doc(api_name)
return doc
# Example usage
github_info = get_api_info("GitHub API")
print(f"GitHub API Documentation URL: {github_info['url']}")
This function allows your coding agent to retrieve specific API documentation on demand. The agent can call this function whenever it needs to know about a particular API's current capabilities.
Summary
In this tutorial, you've learned how to set up and use Context Hub to provide your coding agents with up-to-date API documentation. You installed the tool, configured it with API sources, fetched documentation, set up automatic updates, and integrated it with a simple coding agent. By following these steps, your agents will always have access to the latest API information, making them more effective and reliable in their coding tasks.



