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Deploy Proof Assistant with Baseten

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

Linked challenge: Mathematical Proof Assistant

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Linked challenge
Mathematical Proof Assistant

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines
1 sections
No variables
0 checklist items
Prepare your LlamaIndex agent and Gemini 2.5 Pro integration for deployment. Use Baseten to serve your proof assistant as a scalable API endpoint. Provide the necessary configuration and code (e.g., a `predict.py` file) to deploy the model, ensuring efficient inference and access to the ChromaDB index (potentially by embedding ChromaDB or configuring external access). Detail the steps for creating a Baseten model and endpoint.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Preserve the source structure until you know which part of the prompt is actually driving the result quality.

Tune next

Change domain facts, examples, and tool context first before you rewrite the instruction scaffold.

Verify after

Validate one failure mode at a time so prompt changes stay attributable instead of getting noisy.