Developers’ Tutorial: Using Claude’s Tool (Function Calling) with Brave Web Search API
Introduction
In today’s rapidly evolving tech landscape, integrating AI language models with web search APIs unlocks new possibilities for creating intelligent applications. This tutorial will guide you through combining Anthropic’s Claude AI—leveraging its function calling capabilities—with the Brave Web Search API using Python. By the end of this article, you’ll have a solid understanding of how to build a powerful, privacy-focused search and summarization tool.
Why Use Web Search APIs
Web search APIs are essential for developers looking to:
• Automate Data Retrieval: Programmatically access search results to save time and resources.
• Enhance Applications: Seamlessly integrate search capabilities into apps for better user experience.
• Access Real-Time Data: Obtain up-to-date information crucial for timely decision-making.
• Customize Searches: Refine results with parameters like location or content type.
• Scale Efficiently: Handle high query volumes suitable for enterprise-level projects.
Brave Search API Features
Brave Search API stands out with its independent search index and privacy-preserving architecture:
• Privacy-Centric: No data collection by default, ensuring user anonymity.
• Rich Search Capabilities: Supports web search, news clusters, and video clusters.
• High Performance: Offers 20 queries per second on the base plan.
• Competitive Pricing: Starts at $3 per 1,000 queries, with a free tier offering 2,000 queries/month.
• AI Integration: Provides schema-enriched web results ideal for AI and LLM applications.
Integrating Claude’s Function Calling with Brave Search API
Anthropic’s Claude AI model, with its advanced language understanding and function calling feature, allows developers to execute functions based on natural language prompts. Combining this with the Brave Search API enables the creation of applications that can:
• Process User Queries: Interpret and understand complex user inputs.
• Perform Web Searches: Fetch relevant information using Brave’s API.
• Generate Summaries: Use AI to synthesize search results into concise responses.
Prerequisites
Before you begin, ensure you have the following:
• Python 3.7+ installed on your system.
• Anthropic API Key: Sign up on Anthropic’s website to obtain an API key.
• Brave Search API Key: Register on Brave’s developer portal to get access.
• Required Python Libraries: Install necessary packages like requests and anthropic.
Project Overview
We’ll create a Python application with the following components:
1. BraveSearchTool Class
• Initializes with the Brave API key.
• Performs web searches and retrieves results.
• Processes responses for further use.
2. ToolUser Class
• Utilizes Claude’s function calling to interpret search results.
• Processes user queries and generates summaries.
• Integrates with the BraveSearchTool class.
Step-by-Step Implementation:
Step 1: Setting Up the Environment
• Install Required Libraries
• Configure Environment Variables
Store your API keys securely using a .env file:
Step 2: Creating the BraveSearchTool Class
BraveSearchTool class that defines authentication and makes requests to the Brave Search API.
This class: :
• Initializes with the API key.
• Constructs the appropriate headers and parameters.
• Sends GET requests to the API endpoint.
• Handles responses and potential errors.
Step 3: Implementing the ToolUser Class with Function Calling
Code that defines the ToolUser class, integrating Claude’s function calling capabilities.
This class:
• Accepts user queries.
• Uses BraveSearchTool to fetch search results.
• Formats results into a prompt suitable for Claude.
• Invokes Claude’s API to generate a summarized response.
• Manages exceptions and edge cases.
Step 4: Processing User Queries
Code that ties everything together, handling user input and displaying outputs.
Description:
• Setting up a main function to run the application.
• Implementing a loop to accept multiple queries.
• Ensuring graceful exits and error messages.
Step 5: Formatting and Displaying Results
Code that formats the output using libraries like rich for enhanced console visuals.
Covers:
• Using rich to create panels, tables, or markdown displays.
• Enhance readability with syntax highlighting and styling.
• Separate different sections for clarity.
Expected Output:
Conclusion
By integrating Anthropic’s Claude AI with the Brave Web Search API, you’ve built a sophisticated tool that leverages AI for intelligent search and summarization while maintaining user privacy. This tutorial provides a foundation you can expand upon to develop more advanced features.
Next Steps
• Expand Functionality
• Add support for additional content types like images or videos.
• Incorporate user authentication for personalized experiences.
• Enhance Error Handling
• Implement retries for failed API calls.
• Provide detailed logs for debugging purposes.
• Develop a User Interface
• Create a web-based interface using frameworks like Flask or Django.
• Build a desktop application with GUI libraries like Tkinter or PyQt.
Additional Resources
• Anthropic API Documentation
• Brave Search API Documentation
• Python Libraries
About Kanaka Software:
Kanaka Software is a leading software development company specializing in AI integration and web technologies. Committed to innovation and excellence, the team at Kanaka Software is passionate about creating cutting-edge solutions and sharing knowledge with the developer community through writing and teaching.
