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Langroid Agent Implementation with DeepSeek V3
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Linked challenge: Multi-Agent Protocol for Smart City Robotaxi Coordination
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Linked challenge
Multi-Agent Protocol for Smart City Robotaxi Coordination
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Implement a Langroid-based 'Fleet Agent' that integrates DeepSeek V3 for real-time routing decisions and extended thinking. The agent should ingest traffic updates via an MCP tool, communicate with other fleets via A2A, and use DeepSeek V3's few-shot learning capabilities to adapt its routing behavior to new, unseen traffic patterns. Provide examples of few-shot prompts.
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.