implementation

Design Gemini-powered Reasoning Agent

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

Linked challenge: Mathematical Proof Assistant

Format

Text-first

Lines

Sections

Linked challenge

Mathematical Proof Assistant

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

1 sections

No variables

0 checklist items

Design a LlamaIndex agent that leverages Gemini 2.5 Pro for its primary reasoning engine. The agent should be able to receive a mathematical statement, query the `VectorStoreIndex` for relevant context, and then use Gemini to construct a step-by-step proof. Implement at least two tools within the LlamaIndex agent: one to `search_math_index` (which queries your ChromaDB-backed `VectorStoreIndex`) and another to `output_final_proof` (which formats the Gemini-generated proof). Include the agent initialization and tool definitions.

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

Lists

Code blocks

Purpose

implementation

This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

Mathematical Proof Assistant

This challenge focuses on building an advanced AI system capable of understanding complex mathematical questions, retrieving relevant theorems and definitions from a specialized knowledge base, and constructing logical proofs or counter-examples. Participants will leverage LlamaIndex's advanced RAG capabilities to ensure contextual understanding and Gemini 2.5 Pro's strong reasoning for generating robust mathematical arguments. The emphasis will be on accurate grounding of facts, verifiable proof construction, and systematic evaluation of the AI's mathematical competence against novel problems. The project requires designing and populating a structured mathematical knowledge base using LlamaIndex data connectors, integrating a vector store like ChromaDB for efficient retrieval. Developers will orchestrate a multi-stage LlamaIndex agent workflow that can plan, execute, and verify proof steps. The final system should demonstrate robust reasoning by generating mathematically sound proofs and identifying valid counter-examples when applicable, similar to the objectives of the 'First Proof' experiment.

Open challenge

Related prompts

Browse library

Initialize LlamaIndex for Mathematical Knowledge Base

planning

Implement Evaluation with Continue.dev

testing

Deploy Proof Assistant with Baseten

deployment