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Implement AutoGen Agents and Workflow

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

Linked challenge: Multi-Agent AI for Dynamic Short-Form Video Generation

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Linked challenge
Multi-Agent AI for Dynamic Short-Form Video Generation

Prompt source

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Implement the AutoGen agents and the overall conversational workflow. Create `UserProxyAgent` and multiple `ConversableAgent` instances. Configure Claude Opus 4.1 for the 'Concept Creator' and 'Scriptwriter' agents (e.g., `llm_config={'model': 'claude-opus-20240229', 'api_key': os.environ['ANTHROPIC_API_KEY']}`) and OpenAI o3 for the 'Visuals Lead' agent (e.g., `llm_config={'model': 'gpt-3.5-turbo', 'api_key': os.environ['OPENAI_API_KEY']}`) for generating asset details. Provide Python code snippets for initializing these agents and setting up a basic chat interaction that leads to the `ShortVideoPlanGeneration` task.

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.