Capx AI Builder Program
  • 🖖Introduction
    • 💻Capx AI Agent Builder (CAAB)
    • 👨‍💻Capx AI Infrastructure
  • CAPX AI BUILDER PROGRAM
    • 👷‍♂️Overview
    • 🌍Capx AI Agent Hackfest
    • ⭐Capx AI Bounties
    • ✨Capx AI Ecosystem Grant
  • GETTING STARTED
    • 👊How to Apply
    • 📗Resources
      • ▶️FAQs
      • ▶️Learning Material
      • ▶️Tutorials
      • ▶️Support
  • Build AI Agent Guide
    • 🛠️Step 1: Defining the Agent's Functionality
    • 🛠️Step 2: Choosing the Framework
    • 🛠️Step 3: Selecting the LLM Model
    • 🛠️Step 4: Integrating External APIs and Tools
    • 🛠️Step 5: Setting Up the Development Environment
    • 🛠️Step 6: Deploying your AI Agent
  • AI Agent Examples
    • 1️⃣SynopsisAI - Reading Assistant
    • 2️⃣GluuuAI - Dating Assitant
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On this page
  • Tooling Libraries
  • Examples of External APIs:
  • Integration Steps
  • Resources
  1. Build AI Agent Guide

Step 4: Integrating External APIs and Tools

Tooling Libraries

  1. CrewAI Tools:

    • Pros: Comprehensive suite for web searching, data analysis, and more.

    • Cons: Might have limitations in custom integrations.

  2. LlamaIndex Tools:

    • Pros: Specialized for efficient indexing and retrieval.

    • Cons: Best suited for large datasets.

  3. LangChain Tools:

    • Pros: Flexible tool calling and easy integration.

    • Cons: Requires manual configuration for complex workflows.

Examples of External APIs:

  • Weather APIs (e.g., OpenWeatherMap)

  • Email services (e.g., SendGrid)

  • Database queries (e.g., SQL databases)

  • CRM systems (e.g., Salesforce API)

  • Search engines (e.g., Google Custom Search API)

  • Financial data APIs (e.g., Alpha Vantage)

  • Natural language processing APIs (e.g., Google Natural Language API)

  • E-commerce platforms (e.g., Shopify API)

Integration Steps

  1. Define each API as a tool with a JSON schema (name, description, parameters)

  2. Implement functions to handle API calls and process responses

  3. Configure the language model request with available tools

  4. Execute API calls based on model recommendations

  5. Feed API responses back to the model to generate final output.

Resources

PreviousStep 3: Selecting the LLM ModelNextStep 5: Setting Up the Development Environment

Last updated 10 months ago

🛠️
CrewAI Tools Documentation
LlamaIndex Tool Integration
LangChain Tool Integration