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## Overview This PR adds comprehensive Airtable integration to the AutoGPT platform, enabling users to seamlessly connect their Airtable bases with AutoGPT workflows for powerful no-code automation capabilities. ## Why Airtable Integration? Airtable is one of the most popular no-code databases used by teams for project management, CRMs, inventory tracking, and countless other use cases. This integration brings significant value: - **Data Automation**: Automate data entry, updates, and synchronization between Airtable and other services - **Workflow Triggers**: React to changes in Airtable bases with webhook-based triggers - **Schema Management**: Programmatically create and manage Airtable table structures - **Bulk Operations**: Efficiently process large amounts of data with batch create/update/delete operations ## Key Features ### 🔌 Webhook Trigger - **AirtableWebhookTriggerBlock**: Listens for changes in Airtable bases and triggers workflows - Supports filtering by table, view, and specific fields - Includes webhook signature validation for security ### 📊 Record Operations - **AirtableCreateRecordsBlock**: Create single or multiple records (up to 10 at once) - **AirtableUpdateRecordsBlock**: Update existing records with upsert support - **AirtableDeleteRecordsBlock**: Delete single or multiple records - **AirtableGetRecordBlock**: Retrieve specific record details - **AirtableListRecordsBlock**: Query records with filtering, sorting, and pagination ### 🏗️ Schema Management - **AirtableCreateTableBlock**: Create new tables with custom field definitions - **AirtableUpdateTableBlock**: Modify table properties - **AirtableAddFieldBlock**: Add new fields to existing tables - **AirtableUpdateFieldBlock**: Update field properties ## Technical Implementation Details ### Authentication - Supports both API Key and OAuth authentication methods - OAuth implementation includes proper token refresh handling - Credentials are securely managed through the platform's credential system ### Webhook Security - Added `credentials` parameter to WebhooksManager interface for proper signature validation - HMAC-SHA256 signature verification ensures webhook authenticity - Webhook cursor tracking prevents duplicate event processing ### API Integration - Comprehensive API client (`_api.py`) with full type safety - Proper error handling and response validation - Support for all Airtable field types and operations ## Changes 🏗️ ### Added Blocks: - AirtableWebhookTriggerBlock - AirtableCreateRecordsBlock - AirtableDeleteRecordsBlock - AirtableGetRecordBlock - AirtableListRecordsBlock - AirtableUpdateRecordsBlock - AirtableAddFieldBlock - AirtableCreateTableBlock - AirtableUpdateFieldBlock - AirtableUpdateTableBlock ### Modified Files: - Updated WebhooksManager interface to support credential-based validation - Modified all webhook handlers to support the new interface ## Test Plan 📋 ### Manual Testing Performed: 1. **Authentication Testing** - ✅ Verified API key authentication works correctly - ✅ Tested OAuth flow including token refresh - ✅ Confirmed credentials are properly encrypted and stored 2. **Webhook Testing** - ✅ Created webhook subscriptions for different table events - ✅ Verified signature validation prevents unauthorized requests - ✅ Tested cursor tracking to ensure no duplicate events - ✅ Confirmed webhook cleanup on block deletion 3. **Record Operations Testing** - ✅ Created single and batch records with various field types - ✅ Updated records with and without upsert functionality - ✅ Listed records with filtering, sorting, and pagination - ✅ Deleted single and multiple records - ✅ Retrieved individual record details 4. **Schema Management Testing** - ✅ Created tables with multiple field types - ✅ Added fields to existing tables - ✅ Updated table and field properties - ✅ Verified proper error handling for invalid field types 5. **Error Handling Testing** - ✅ Tested with invalid credentials - ✅ Verified proper error messages for API limits - ✅ Confirmed graceful handling of network errors ### Security Considerations 🔒 1. **API Key Management** - API keys are stored encrypted in the credential system - Keys are never logged or exposed in error messages - Credentials are passed securely through the execution context 2. **Webhook Security** - HMAC-SHA256 signature validation on all incoming webhooks - Webhook URLs use secure ingress endpoints - Proper cleanup of webhooks when blocks are deleted 3. **OAuth Security** - OAuth tokens are securely stored and refreshed - Scopes are limited to necessary permissions - Token refresh happens automatically before expiration ## Configuration Requirements No additional environment variables or configuration changes are required. The integration uses the existing credential management system. ## Checklist 📋 #### For code changes: - [x] I have read the [contributing instructions](https://github.com/Significant-Gravitas/AutoGPT/blob/master/.github/CONTRIBUTING.md) - [x] Confirmed that `make lint` passes - [x] Confirmed that `make test` passes - [x] Updated documentation where needed - [x] Added/updated tests for new functionality - [x] Manually tested all blocks with real Airtable bases - [x] Verified backwards compatibility of webhook interface changes #### Security: - [x] No hard-coded secrets or sensitive information - [x] Proper input validation on all user inputs - [x] Secure credential handling throughout
AutoGPT: Build, Deploy, and Run AI Agents
AutoGPT is a powerful platform that allows you to create, deploy, and manage continuous AI agents that automate complex workflows.
Hosting Options
- Download to self-host (Free!)
- Join the Waitlist for the cloud-hosted beta (Closed Beta - Public release Coming Soon!)
How to Setup for Self-Hosting
Note
Setting up and hosting the AutoGPT Platform yourself is a technical process. If you'd rather something that just works, we recommend joining the waitlist for the cloud-hosted beta.
System Requirements
Before proceeding with the installation, ensure your system meets the following requirements:
Hardware Requirements
- CPU: 4+ cores recommended
- RAM: Minimum 8GB, 16GB recommended
- Storage: At least 10GB of free space
Software Requirements
- Operating Systems:
- Linux (Ubuntu 20.04 or newer recommended)
- macOS (10.15 or newer)
- Windows 10/11 with WSL2
- Required Software (with minimum versions):
- Docker Engine (20.10.0 or newer)
- Docker Compose (2.0.0 or newer)
- Git (2.30 or newer)
- Node.js (16.x or newer)
- npm (8.x or newer)
- VSCode (1.60 or newer) or any modern code editor
Network Requirements
- Stable internet connection
- Access to required ports (will be configured in Docker)
- Ability to make outbound HTTPS connections
Updated Setup Instructions:
We've moved to a fully maintained and regularly updated documentation site.
👉 Follow the official self-hosting guide here
This tutorial assumes you have Docker, VSCode, git and npm installed.
⚡ Quick Setup with One-Line Script (Recommended for Local Hosting)
Skip the manual steps and get started in minutes using our automatic setup script.
For macOS/Linux:
curl -fsSL https://setup.agpt.co/install.sh -o install.sh && bash install.sh
For Windows (PowerShell):
powershell -c "iwr https://setup.agpt.co/install.bat -o install.bat; ./install.bat"
This will install dependencies, configure Docker, and launch your local instance — all in one go.
🧱 AutoGPT Frontend
The AutoGPT frontend is where users interact with our powerful AI automation platform. It offers multiple ways to engage with and leverage our AI agents. This is the interface where you'll bring your AI automation ideas to life:
Agent Builder: For those who want to customize, our intuitive, low-code interface allows you to design and configure your own AI agents.
Workflow Management: Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.
Deployment Controls: Manage the lifecycle of your agents, from testing to production.
Ready-to-Use Agents: Don't want to build? Simply select from our library of pre-configured agents and put them to work immediately.
Agent Interaction: Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.
Monitoring and Analytics: Keep track of your agents' performance and gain insights to continually improve your automation processes.
Read this guide to learn how to build your own custom blocks.
💽 AutoGPT Server
The AutoGPT Server is the powerhouse of our platform This is where your agents run. Once deployed, agents can be triggered by external sources and can operate continuously. It contains all the essential components that make AutoGPT run smoothly.
Source Code: The core logic that drives our agents and automation processes.
Infrastructure: Robust systems that ensure reliable and scalable performance.
Marketplace: A comprehensive marketplace where you can find and deploy a wide range of pre-built agents.
🐙 Example Agents
Here are two examples of what you can do with AutoGPT:
-
Generate Viral Videos from Trending Topics
- This agent reads topics on Reddit.
- It identifies trending topics.
- It then automatically creates a short-form video based on the content.
-
Identify Top Quotes from Videos for Social Media
- This agent subscribes to your YouTube channel.
- When you post a new video, it transcribes it.
- It uses AI to identify the most impactful quotes to generate a summary.
- Then, it writes a post to automatically publish to your social media.
These examples show just a glimpse of what you can achieve with AutoGPT! You can create customized workflows to build agents for any use case.
Mission and Licencing
Our mission is to provide the tools, so that you can focus on what matters:
- 🏗️ Building - Lay the foundation for something amazing.
- 🧪 Testing - Fine-tune your agent to perfection.
- 🤝 Delegating - Let AI work for you, and have your ideas come to life.
Be part of the revolution! AutoGPT is here to stay, at the forefront of AI innovation.
📖 Documentation | 🚀 Contributing
Licensing:
MIT License: The majority of the AutoGPT repository is under the MIT License.
Polyform Shield License: This license applies to the autogpt_platform folder.
For more information, see https://agpt.co/blog/introducing-the-autogpt-platform
🤖 AutoGPT Classic
Below is information about the classic version of AutoGPT.
🛠️ Build your own Agent - Quickstart
🏗️ Forge
Forge your own agent! – Forge is a ready-to-go toolkit to build your own agent application. It handles most of the boilerplate code, letting you channel all your creativity into the things that set your agent apart. All tutorials are located here. Components from forge can also be used individually to speed up development and reduce boilerplate in your agent project.
🚀 Getting Started with Forge – This guide will walk you through the process of creating your own agent and using the benchmark and user interface.
📘 Learn More about Forge
🎯 Benchmark
Measure your agent's performance! The agbenchmark can be used with any agent that supports the agent protocol, and the integration with the project's CLI makes it even easier to use with AutoGPT and forge-based agents. The benchmark offers a stringent testing environment. Our framework allows for autonomous, objective performance evaluations, ensuring your agents are primed for real-world action.
📦 agbenchmark on Pypi
|
📘 Learn More about the Benchmark
💻 UI
Makes agents easy to use! The frontend gives you a user-friendly interface to control and monitor your agents. It connects to agents through the agent protocol, ensuring compatibility with many agents from both inside and outside of our ecosystem.
The frontend works out-of-the-box with all agents in the repo. Just use the CLI to run your agent of choice!
📘 Learn More about the Frontend
⌨️ CLI
To make it as easy as possible to use all of the tools offered by the repository, a CLI is included at the root of the repo:
$ ./run
Usage: cli.py [OPTIONS] COMMAND [ARGS]...
Options:
--help Show this message and exit.
Commands:
agent Commands to create, start and stop agents
benchmark Commands to start the benchmark and list tests and categories
setup Installs dependencies needed for your system.
Just clone the repo, install dependencies with ./run setup, and you should be good to go!
🤔 Questions? Problems? Suggestions?
Get help - Discord 💬
To report a bug or request a feature, create a GitHub Issue. Please ensure someone else hasn't created an issue for the same topic.
🤝 Sister projects
🔄 Agent Protocol
To maintain a uniform standard and ensure seamless compatibility with many current and future applications, AutoGPT employs the agent protocol standard by the AI Engineer Foundation. This standardizes the communication pathways from your agent to the frontend and benchmark.
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