---
id: ch5-adviser-magpie
type: spine
title: "The Advisor and Magpie: answers from the project's own evidence"
readingTime: 3
standalone: true
core: true
teaser: "A custom GPT over the PoliRural+ knowledge base, and a natural-language search over map catalogues: what they retrieve, and what testers found."
voice: universal
parent: null
diagram: fig-advisor-georag
recallQ: "What makes the PoliRural+ Advisor different from asking a general chatbot, and where did testers see its limits?"
recallA: "It retrieves from a controlled project corpus (a private RAG; GeoRAG adds spatial data) and aims to cite its sources. In February 2025 testers found it easy to open and useful, but they hit daily usage limits and at least one wrong reference, so human judgement stays in charge."
highlights:
  - "The Advisor is a custom GPT built on retrieval-augmented generation over the project's Knowledge Space"
  - "Textual RAG reads documents; GeoRAG adds metadata, map layers and indicators"
  - "8 structured walkthroughs (February 2025): access difficulty 1.0, dialogue rated useful (2.9 of 4)"
  - "Magpie searches geospatial metadata catalogues, not funding databases; in the Beta it lives inside Raven"
status: accepted
concept: polirural-advisor
conceptTitle: "The PoliRural+ Advisor and RAG services"
parents: tool-ecosystem
lang: en
lens: generic
depth: standard
formalism: none
visuality: balanced
lengthBand: standard
genre: explainer
state: core
carriers: prose|diagram
---

The **PoliRural+ Advisor** answers from the project's own documents rather than the open web. **Magpie** does a similar job for geospatial metadata catalogues.

## The Advisor

The Advisor is a custom GPT built with ChatGPT's retrieval-augmented generation (RAG) technology. It gives pilot stakeholders access to the project's Knowledge Space and References database, and it supports RAP preparation, policy briefs and reviews of pilot evidence (D4.1 §6.2; D4.2 §3.7). Anyone with the link can use it. Its contents stay in the project's Team workspace and are not used by ChatGPT to train its wider models (D4.1 §6.2).

D4.2 distinguishes two modes:
- **textual RAG** over reports, policy documents and pilot material;
- **GeoRAG**, which adds metadata records, map layers, indicators and analytical services, because many regional questions depend on place and not on prose alone.

The goal is an answer whose **citations, excerpts and reference trails** the user can check, not just text that sounds right. A planned next step links the RAG pipelines to a Knowledge Graph, for entity linking and clearer evidence trails (D4.2 §3.7).

## What testers found

In February 2025, partners and pilot users completed **8 structured cognitive walkthroughs** (D2.3 Annex B). Opening the Advisor caused no problems (average difficulty 1.0). The dialogue was rated useful (2.9 overall on a 1–4 scale). One tester got good advice on funding instruments for Community-Led Local Development. Another got a wrong reference to the Horizon 2020 programme; it was corrected in later answers. Free-account daily limits cut some sessions short. One pilot warned that advice about the RAP's future "can be tricky. We need to think for ourselves."

D2.3 itself shows the Advisor in use. Its literature review on rural-urban linkages was written with the Advisor and the 700+ sources in the project's References Database (D2.3 §3).

## Magpie

Magpie embeds ISO 19115/19119 metadata, the standards behind INSPIRE and OGC catalogues, in a Qdrant vector database. It answers plain-language queries with records listing layer names and WMS/WFS endpoints, and can build a map from them (D4.1 §6.5).

In the Beta, Raven's data-selection workflow has taken over Magpie's core function, and its results appear mostly through [JackDaw](#c/jackdaw) (D4.2 §3.4). Its limit is the metadata: no search makes up for incomplete records.

Next: why one broad question rarely gets a good RAG answer.

**How-to:** [Using the Advisor for RAP work](#ch5-guide-advisor) · [Finding data with Magpie and Raven](#ch5-guide-raven-magpie).

**Sources:**
- D4.2 PoliRuralPlus Platform Beta, §3.4 Magpie AI-enabled metadata/catalogue search; §3.7 PoliRuralPlus Advisor and RAG services. [PDF](https://www.poliruralplus.eu/docs/421/D4.2_PoliRuralPlus_Platform_Beta.pdf)
- D4.1 PoliRuralPlus platform design, §6.2 PoliRuralPlus Advisor, Custom GPT; §6.5 Magpie. [PDF](https://www.poliruralplus.eu/docs/162/D4.1_PoliRuralPlus_platform_design_v1.pdf)
- D2.3 Rural-urban data analysis, Annex B Structured Evaluation of the PoliRuralPlus Services; §3 Rural-Urban Linkages – Literature Review. [PDF](https://www.poliruralplus.eu/docs/382/D2.3_Rural_Urban_data_analysis_v1.0.pdf)