Pyragogy AI Village - Orchestrazione Master (Architettura Profonda V2)

For Pyragogy AI Village, this automated workflow orchestrates a multi-agent system to efficiently process and refine input data through various AI agents, ensuring high-quality content creation and review. It integrates seamlessly with PostgreSQL and OpenAI, facilitating real-time feedback loops and human oversight. The workflow enhances collaboration, reduces manual effort, and accelerates the development of comprehensive handbook entries, ultimately streamlining knowledge management and improving content accuracy.

7/4/2025
35 nodes
Complex
pyragogymulti-agentorchestrationhuman-in-loopwebhookcomplexstartpostgresqlopenaiemailsendwaitgithubslackrespondtowebhookadvancedintegrationapidatabasedatacodecustomlogicconditionalroutingemailnotificationcommunication
Categories:
Data Processing & AnalysisTechnical Infrastructure & DevOpsCommunication & MessagingWebhook TriggeredComplex Workflow
Integrations:
StartPostgreSQLOpenAiEmailSendWaitGitHubSlackRespondToWebhook

Target Audience

Target Audience


- Data Scientists: Need to automate data processing workflows and integrate AI models for analysis.
- Developers: Looking for a flexible orchestration tool to manage complex workflows with various integrations.
- Project Managers: Interested in overseeing automated processes that involve human feedback and approval.
- Content Creators: Want to streamline the process of content generation, review, and archiving.
- Organizations: Aim to enhance collaboration between AI agents and human reviewers in a structured manner.

Problem Solved

Problem Solved


This workflow addresses the challenges of managing complex multi-agent processes by automating the orchestration of tasks involving AI models and human reviewers. It effectively integrates various services such as PostgreSQL, OpenAI, email notifications, and GitHub for seamless content creation, review, and storage. Key benefits include:
- Efficiency: Reduces manual intervention by automating the workflow.
- Quality Assurance: Ensures content is reviewed and approved before archiving.
- Scalability: Easily adapts to different content types and processes.
- Real-time Feedback: Incorporates human input into the workflow, improving output quality.

Workflow Steps

Workflow Steps


1. Start: The workflow is initiated via a webhook trigger, receiving input data.
2. Check Database Connection: Verifies connectivity to PostgreSQL to ensure data integrity.
3. Meta-Orchestrator: Analyzes the input data and determines the optimal sequence of AI agents to process the information.
4. Parse Orchestration Plan: Prepares the identified agent sequence for execution.
5. Agent Execution: Iteratively processes through each agent in the sequence, including:
- Summarizer: Creates concise summaries of the input.
- Synthesizer: Generates new content based on summaries or feedback.
- Peer Reviewer: Reviews content for strengths and weaknesses, providing actionable feedback.
- Sensemaking Agent: Analyzes content against existing knowledge to identify patterns.
- Prompt Engineer: Refines prompts for subsequent agents based on context.
- Onboarding/Explainer: Provides explanations of the process and results.
6. Content Review: After agent processing, the proposed content is formatted and sent for human approval via email.
7. Human Decision: Waits for human feedback on the proposed content, allowing for approval or rejection.
8. Finalization: Approved content is saved to the database, and contributions from agents are recorded. If rejected, feedback is collected for reprocessing.
9. GitHub Integration: If enabled, the finalized content is committed to a GitHub repository for version control.
10. Notification: Sends a completion notification via Slack, summarizing the process and results.

Customization Guide

Customization Guide


- Webhook Configuration: Modify the webhook path and parameters to suit your input requirements.
- Database Credentials: Update the PostgreSQL connection details in the credentials section to connect to your database.
- AI Model Settings: Adjust the OpenAI model parameters and messages to customize the behavior of AI agents.
- Agent Sequence: Change the order or selection of agents in the orchestration plan to fit specific use cases.
- Email Settings: Update the email addresses and content in the email nodes to match your communication preferences.
- GitHub Integration: Enable or disable GitHub integration by adjusting the conditions and authentication settings as needed.
- Feedback Mechanism: Customize the feedback collection process to suit your review requirements and improve the quality of the output.