implementation

Voice Integration Prompt

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

Linked challenge: Voice-Driven Ethical Logistics Dispatcher with OpenAI Agents SDK

Format

Code-aware

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Sections

Linked challenge

Voice-Driven Ethical Logistics Dispatcher with OpenAI Agents SDK

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

1 sections

No variables

0 checklist items

Integrate Sarvam AI to listen for voice commands. When a command is received, map the intent to the DispatcherAgent's function tools. Provide a fallback if Arcee AI determines the model confidence is low.

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

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Code blocks

Purpose

implementation

This prompt already mixes executable detail with instructions, so tune examples and interfaces before rewriting the scaffold.

Linked challenge

Voice-Driven Ethical Logistics Dispatcher with OpenAI Agents SDK

Inspired by recent drone swarm ethics reviews and Amazon's logistics automation, this challenge requires building an autonomous dispatch system using the OpenAI Agents SDK. You will orchestrate a team of agents that process real-time voice instructions to coordinate delivery routes. The system must use Sarvam AI for voice-to-agent interface processing and Arcee AI for intelligent routing between Claude Sonnet 4.6.6 and GPT-5.4 Pro based on task complexity. An ethical validator agent must be implemented to ensure drone flight paths avoid restricted zones or high-risk areas. You will also integrate AgentFlow to manage stateful agent transitions and OATutor to provide instructional feedback to human operators who need to override autonomous decisions.

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