From: gregisenberg
This article explores the practical application of Appify for data scraping and Open Router for integrating various large language models (LLMs) within an AI and automation workflow for content creation. The discussed workflow aims to automate content generation and publishing, potentially saving 10 to 15 hours per week [01:32:04].
Automating Content with AI Agents
The core idea is to automate marketing teams with AI agents to achieve content on autopilot [00:00:00]. This process involves using smart LLMs to produce content and even automatically publish it [01:22:00]. The workflow helps content creators test content angles, hooks, and topics much faster, leading to top-performing content based on extensive context and information [02:08:00].
Appify for Data Scraping and Research
Appify is highlighted as an “awesome platform” for scraping anything on the internet [04:56:00].
Workflow Integration
In the described content automation workflow, Appify is used in the initial research phase [05:59:00].
It performs the following actions:
- YouTube Scraping [04:07:00]: It scrapes the top 20 to 30 videos on YouTube for a given topic that have a high degree of engagement [04:14:00].
- X (formerly Twitter) Scraping [04:21:00]: It also looks for posts around specific topics on X, such as workflow automation and AI [04:26:00].
- Transcription [04:42:00]: After finding relevant videos and posts, it transcribes all the YouTube videos, gathering content from titles, hooks, and full content [04:45:00].
- Data Merging [05:38:00]: All collected data, including transcribed YouTube videos and X posts, is merged into one large text block for further processing by LLMs [05:51:00].
Appify provides open APIs that can be accessed and plugged into a workflow to process data [05:10:00]. HTTP requests within the workflow call the Appify API for specific platforms like YouTube and X [05:20:00]. This step significantly reduces the manual research time required for content creation [06:27:00].
Open Router for LLM Integration
Open Router is introduced as a helpful tool for integrating various LLMs [11:51:00].
Key Benefits
- Single Node Access [12:13:00]: It allows users to access multiple LLMs with one node within their workflow, simplifying the process of integrating different models [12:15:00].
- Consolidated Pricing [12:40:00]: Instead of getting separate API keys and managing individual subscriptions for each LLM (e.g., Claude, Perplexity, OpenAI), Open Router offers one price to access all models [12:46:00].
- Optimized Model Selection [11:58:00]: This enables users to select the best LLM for each specific task within the workflow, such as Perplexity for research or Claude for writing [12:01:00].
Practical Application
Within the content workflow, different LLMs are utilized for different stages:
- OpenAI LLM [07:19:00]: Used by the content idea generator agent to scan collected text and find fresh content angles and ideas, avoiding mere replication of researched content [07:22:00].
- Perplexity [10:46:00]: Used by a research agent to find use cases, real stats, trends, insights, marketing use cases, and case studies to back up claims and prevent hallucinations [10:49:00].
- Claude 3.7 Sonnet [13:27:00]: Employed by the LinkedIn content agent, considered the best writing LLM at the time of recording, especially powerful when armed with sufficient context and data [13:30:00].
- OpenAI Image Gen Model [17:41:00]: Used to create images for posts, with the capability for dynamic prompts [17:47:00].
By combining the data scraping capabilities of Appify with the flexible LLM integration offered by Open Router, users can build robust AI-powered workflow automation systems for diverse applications, including content creation and marketing. This approach helps in creating validated social posts with a much higher chance of engagement [21:08:00].