A2A Cross-Platform Knowledge Bridge
Develop an A2A (Agent-to-Agent) protocol-driven multi-agent system using AutoGen that facilitates knowledge sharing and content synthesis across disparate 'platform' knowledge bases (e.g., a simulated Claude Project and ChatGPT Project discussion summary). Agents will collaboratively extract, summarize, and translate relevant information, leveraging Mistral Large 2 for robust text processing and Claude Sonnet 4 for efficient summarization, presenting unified answers to complex cross-platform queries.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop an A2A (Agent-to-Agent) protocol-driven multi-agent system using AutoGen that facilitates knowledge sharing and content synthesis across disparate 'platform' knowledge bases (e.g., a simulated Claude Project and ChatGPT Project discussion summary). Agents will collaboratively extract, summarize, and translate relevant information, leveraging Mistral Large 2 for robust text processing and Claude Sonnet 4 for efficient summarization, presenting unified answers to complex cross-platform queries.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
What you should walk away with
Master AutoGen for setting up multi-agent conversations, defining distinct agent roles, and managing complex communication flows and interaction patterns.
Implement the A2A protocol within AutoGen, enabling agents representing different 'platforms' (e.g., 'Claude Project', 'ChatGPT Project') to securely and effectively communicate, exchange information, and delegate tasks.
Design and configure a 'Platform A Agent' (e.g., ClaudeP Agent) and 'Platform B Agent' (e.g., ChatP Agent), each with access to a dedicated RAG system indexing its specific simulated documentation or forum content.
Utilize Mistral Large 2 for the core analytical and information extraction tasks within each platform agent, such as understanding complex queries, identifying relevant technical concepts, and generating detailed initial summaries.
Integrate Claude Sonnet 4 for a 'Synthesis Agent' (or similar role), focusing on efficient, concise, and accurate summarization of information gathered from multiple platform agents, and ensuring coherent presentation of cross-platform solutions.
Build a 'Query Orchestrator Agent' that receives user queries, intelligently delegates sub-queries and tasks to the platform-specific agents, and then uses the Synthesis Agent to consolidate and present a unified, comprehensive answer.
Develop a mechanism for cross-platform content 'translation' or normalization, ensuring that technical information from one platform can be understood and effectively leveraged in the context of another by the agents.
[ok] Wrote CHALLENGE.md
[ok] Wrote .versalist.json
[ok] Wrote eval/examples.json
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