Build a Farm Lending RAG Copilot with Reranking and Guardrails
Group: Capstone Project
Product Category: AI Engineering
Sub Category: RAG & LLM Applications
Solution Available
Source code, datasets, and other related files for the solution will be provided.
Prerequisites
About this Product
A farm lender's credit officers spend about 20 minutes searching policy versions and one farmer's records for every mixed question, and no answer can be signed off without a source.
What you build
- Ingestion and index: validates 28 synthetic policy files, quarantines bad or injected ones and stores parent child chunks in LanceDB.
- Hybrid retrieval: dense and BM25 search fused with RRF, filtered by as of date and user role, then cross encoder reranking.
- Context and answers: a token budgeted context of passages plus farm facts, with money figures and risk scores computed in code, returning cited answers for officer sign off.
- Guardrails: input, retrieval and output checks, branch access control, PII redaction and escalation rules.
- API and evaluation: a FastAPI service with audit and metrics, plus an evaluation CLI with a golden set and a regression gate.
Skills you practise
- Advanced RAG: contextual parent child chunks, hybrid search and an evidence gate that refuses unsupported questions.
- Reranking and context engineering: measure the lift from reranking, then order passages in a versioned prompt.
- Evaluation and guardrails: ablation matrix, guardrail attack sets and an eval gate that blocks regressions.
- Production engineering: degradation paths when a reranker, index or LLM fails, plus rate limits and a load test.
Outcome
- Measured copilot: cited answers with retrieval, faithfulness and refusal numbers on a held out split.
- Portfolio evidence: architecture diagrams, ADRs, an eval report and a runbook you can present in an interview.
Interview Q&A Included
1 practice set bundled with this lab
-
Farm Lending RAG Copilot with Reranking and Guardrails Assessment
Category: AI Engineering Subcategory: Generative AI / LLM Engineer 86 questionsThis assessment checks what you learned while building Sowvale Field Desk, a farm lending and crop insurance copilot that answers with citations, refuses weak evidence and leaves every decision to …
Resources
A complete, tested solution with every requirement implemented, to compare with your own work when you finish or get stuck.
- All 27 acceptance criteria met: 181 tests pass with PostgreSQL available, 177 pass and 4 skip without it
- Unit tests reach 97 percent coverage on the chunker, fusion, filters, risk, assembler and guardrails
- Evaluation included: hybrid plus rerank lifts MRR at 10 from 0.730 to 0.874 on the dev split and the quality gate passes
- Load test report: 5 users for 120 seconds, 600 requests, no errors and a retrieval p95 of 0.61 seconds
- Architecture pack with system flow, five decision records, production design, runbook and cost estimate
- README with exact Windows and macOS commands; the optional Docker, answer cache and judge extras are not included
Topics
Skills
Languages
English
Level
Advanced
Business Domain
Agritech Finance and Insurance
Project Mentors
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