Agent Sterling - AI Social Media Engagement Bot
A smart social media bot powered by Google's Gemini Pro, offering engaging, context-aware replies tailored for Twitter and Mastodon, while optimizing platform-specific interactions.
Created on 24th November 2024
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Agent Sterling - AI Social Media Engagement Bot
A smart social media bot powered by Google's Gemini Pro, offering engaging, context-aware replies tailored for Twitter and Mastodon, while optimizing platform-specific interactions.
The problem Agent Sterling - AI Social Media Engagement Bot solves
Agent Sterling: Revolutionizing Social Media Management
Agent Sterling tackles key social media challenges with efficiency and intelligence, offering seamless engagement and management across platforms like Mastodon and Twitter.
- Cross-Platform Management:
Centralized management of multiple accounts via a unified interface.
Automatically handles platform-specific API requirements and rate limits.
Maintains a consistent brand voice while adapting to platform-specific nuances.
- Intelligent Engagement:
Monitors hashtags and mentions to identify relevant conversations.
Generates context-aware responses using Gemini Pro AI, supporting styles like entertainment, research, and sentiment-based interactions.
Manages thread creation and multi-tweet conversations effortlessly.
- Resource Optimization:
Features advanced rate-limiting and request handling to maximize efficiency.
Provides detailed analytics and monitoring through a robust control panel.
Ensures error recovery and resolves connection issues seamlessly.
- Enhanced User Experience:
Offers a modern web interface for easy configuration and monitoring.
Delivers real-time status updates and comprehensive activity logs.
Supports flexible configurations tailored to diverse use cases.
Agent Sterling empowers users with streamlined social media management, ensuring optimized performance, dynamic engagement, and a superior user experience.
Challenges we ran into
- Initial Library Selection Issues
Our journey began with the ELIZA library, but it quickly became clear it wasn’t a viable choice—it lacked support for Python and didn’t work with React.js, making integration a major challenge.
On the second day, we moved to the Twikit library. While it worked initially, we found it wasn’t posting replies. After further investigation, we realized the issue wasn’t with the library but with Twitter’s API limitations. The free tier doesn’t support reply functionality, and the basic plan, costing $200/month, was outside our budget.
We then switched to the Twarc library in Python. While Twarc successfully retrieved and analyzed posts, attempts to post replies were blocked due to Twitter's API restrictions on the free tier, which led to additional delays.
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Transition to Mastodon and Cross-Platform Conflicts
During a review on the third day, the 100x team suggested exploring alternative open-source solutions. This allowed us to create a functional agent for Mastodon successfully. However, integrating Twitter’s functionality alongside Mastodon caused issues. The Mastodon integration worked smoothly, but Twitter’s functionality remained non-operational, especially on the frontend. -
Frontend Issues for Twitter
The main challenge was resolving frontend errors specific to Twitter, where posts weren’t going through despite the backend working fine for Mastodon. Debugging showed the issue stemmed from API responses and limitations, which required additional exception handling and a workaround that we’re still refining.
In the end, while Mastodon integration is fully functional, Twitter’s frontend still presents challenges, largely due to API restrictions and platform-specific hurdles. We continue to explore alternatives for a seamless experience across both platforms.