Multi-Agent Workflow for Content Processing
For Pyragogy AI Village, this automated workflow orchestrates a multi-agent system to process input data efficiently. It integrates with PostgreSQL and OpenAI, utilizing 35 nodes to analyze, summarize, and refine content. The workflow includes human review steps, ensuring high-quality outputs while maintaining a seamless feedback loop. By automating complex tasks, it enhances productivity, reduces manual effort, and delivers structured content ready for publication.
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Workflow Overview
For Pyragogy AI Village, this automated workflow orchestrates a multi-agent system to process input data efficiently. It integrates with PostgreSQL and OpenAI, utilizing 35 nodes to analyze, summarize, and refine content. The workflow includes human review steps, ensuring high-quality outputs while maintaining a seamless feedback loop. By automating complex tasks, it enhances productivity, reduces manual effort, and delivers structured content ready for publication.
Target Audience
- Data Analysts: Who need to automate the analysis of input data and generate structured outputs.
- Content Creators: Looking for a streamlined process to review and publish content.
- Project Managers: Who oversee projects that require human approval and collaboration.
- Developers: Interested in integrating AI-driven processes into their applications.
- Educators: Who want to leverage AI for creating educational content and resources.
Problem Solved
This workflow addresses the challenges of managing complex data processing and content creation by automating the entire process from input analysis to human approval. It streamlines content generation, reduces manual effort, and enhances collaboration through automated notifications and feedback loops.
Workflow Steps
- Webhook Trigger: Initiates the workflow upon receiving a POST request at
pyragogy/process. - Check Database Connection: Verifies the connection to the PostgreSQL database.
- Meta-Orchestrator: Analyzes the input data and determines the optimal sequence of agents to process the data.
- Parse Orchestration Plan: Prepares the sequence of agents for execution.
- More Agents to Run?: Checks if there are more agents to be executed in the sequence.
- Prepare Agent Input: Prepares the input for the current agent based on the sequence.
- Route Agents with Switch: Depending on the agent name, routes the input to the appropriate agent (e.g., Summarizer, Synthesizer, etc.).
- Agent Execution: Each agent processes the input data and generates output. The output is then processed and logged.
- Generate Content for Review: Prepares the content for human review, including metadata.
- Send Review Request Email: Sends an email to a human reviewer for approval or rejection.
- Wait for Human Approval: Waits for the reviewer’s decision.
- Human Decision Split: Depending on the review outcome, either saves the content or logs the rejection.
- Save to Database: If approved, saves the content to the PostgreSQL database.
- Notify Slack: Sends a notification to Slack about the workflow completion.
- Final Response: Responds to the webhook with the final output and contributions.