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RAG System Setup with Weaviate and Prefect

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Linked challenge: Agent for Complex Policy & Contract Analysis

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Linked challenge
Agent for Complex Policy & Contract Analysis

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Design and implement the RAG pipeline. Set up a **Weaviate** instance (e.g., via Docker). Use **Prefect** to create a workflow that: 1) takes a collection of sample policy documents, 2) chunks them into smaller, semantically meaningful passages, 3) generates embeddings for these chunks (using an appropriate embedding model, e.g., OpenAI's `text-embedding-3-small`), and 4) indexes them into Weaviate. Provide the Prefect flow definition and Python code for Weaviate interaction.

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.