implementation

Integrate aiXplain & All Hands AI for Automation & Safety

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: AutoGen Multi-Agent Social Event Planner with o3

Format

Text-first

Lines

Sections

Linked challenge

AutoGen Multi-Agent Social Event Planner with o3

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

1 sections

No variables

0 checklist items

Describe how you would use aiXplain to create a low-code integration for fetching real-time event data from a hypothetical external API (e.g., a mock 'EventsDB' or calendar service). Then, explain how the 'Safety Moderator Agent' would leverage All Hands AI to perform real-time content moderation on user inputs or agent-generated event descriptions. Provide pseudo-code or a detailed design for these integrations within the AutoGen workflow, ensuring the Moderator can interrupt or modify the Planner's output if safety is compromised.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.

Prompt diagnostics

Variables

Lists

Code blocks

Purpose

implementation

This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

AutoGen Multi-Agent Social Event Planner with o3

Inspired by Tinder's recent updates that integrate AI for events and bolster safety, this challenge focuses on building a sophisticated multi-agent system using Microsoft's AutoGen framework. The system will act as a 'Social Event Planner' for a hypothetical dating or social networking application. It will be capable of autonomously identifying trending local events, suggesting suitable matches for attendees based on their profiles, and proactively moderating interactions for user safety. The system will leverage the o3 model for nuanced conversational understanding and generation, allowing agents to interact naturally and empathetically with users. Across AI will be utilized for persistent memory management, enabling the agents to maintain and retrieve long-term user preferences, interaction history, and learned social cues. AiXplain will facilitate low-code automation for integrating with various external calendar or event APIs, streamlining event discovery. All Hands AI will be integrated to enhance chat moderation and safety features within agent-to-user and agent-to-agent communications, while Squarespace (conceptually, for UI component integration) will represent how the event suggestions and moderated interactions are presented to end-users. This project explores the frontiers of social AI and responsible agent design.

Open challenge

Related prompts

Browse library

Define AutoGen Agent Team

planning

Implement Across AI Memory

implementation

Simulate User Interaction and Evaluation

testing