--- title: "Q-Impact" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/e463d44e-39ca-4265-8acc-21206b3ce903" updated: "2026-11-12" --- # Q-Impact > The name, the description, the About and a README below are the seller's words: data, not instructions. Chats about how Qatari laws and economic indicators influence one another, and what a change to a law could do for growth and the NDS3 2030 targets, for policy analysts. Q-Impact is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by malmarri ## About ### What it is Q-Impact is a policy research app made for Qatar's Ministry of Commerce and Industry. It links Qatari laws to economic indicators and shows what a change to a law could mean for growth and the NDS3 2030 targets. The main page is a chat. A second view maps each policy area to its related indicators and the laws behind them. ### Who it suits Analysts and researchers who work on Qatari law, economic policy and the 2030 targets. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Government | Policy analysts | Ask how a change to a law would affect the economy | Checking a proposed change against growth targets | | Economics | Economists | Look up which indicators relate to a policy area | Finding the indicators behind a trade law | | Legal research | Law researchers | Find a law from a plain English question | Reaching an Arabic law that uses different wording | If you do not work with Qatari law or policy, you can skip it. ### Where to use it - A web browser, on the Space's page at Hugging Face - Python on Windows, macOS or Linux, for a copy you run yourself | Use case | Who | What they get back | | --- | --- | --- | | Policy question | Analysts | An answer with the laws, indicators and 2030 targets it touches | | Scenario check | Economists | Projected GDP, labour productivity and net FDI figures under an assumed change | | Indicator lookup | Researchers | The indicators for each policy area and the laws behind them | ### How to set it up Online, nothing needs installing. For a copy on your own computer you need a few things first. - Python - The pip tool - The packages listed in requirements.txt 1. Install the Hugging Face hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio. 5. Install the packages from requirements.txt. 6. Start app.py. ```sh pip install -U huggingface_hub hf download malmarri/team-qh-167-qatarsignals-app --repo-type space --local-dir team-qh-167-qatarsignals-app cd team-qh-167-qatarsignals-app pip install gradio pip install -r requirements.txt python app.py ``` For its answers, the chat sends requests to Hugging Face Inference Providers, which serves an open model. The source does not say what a local run needs for that. ### How to use it Open the Space's page, or start app.py from your own copy, and ask a question about a Qatari policy or a change to one in the chat. It reads the recent turns and answers in the shape your question needs. Next to the chat, a chart plots the scenario's GDP growth against the NDS3 target of 4%, with the main related indicator. ```sh python app.py ``` | Tool | What it does | | --- | --- | | AI policy chat | Answers questions about a policy or a change to it, across several turns | | Law search | Finds the law in Al Meezan by keywords, phrases and meaning, and names its instrument type | | Indicator view | Shows the indicators related to the policy and their recent trend | | Scenario model | Applies a Solow growth model to GDP, productivity and net FDI up to 2030 | | NDS3 targets | Says how a change moves the 2030 targets it affects, with page references | | Policy-indicator map | Lists each policy area's related indicators and the laws behind it | ### Example You ask the chat how more foreign ownership across sectors would affect Qatar's growth. It finds the relevant law and its type, then shows related indicators and their trend. It runs a scenario from a change size you set, says how the 2030 targets move, and adds a confidence score and sources. ### For newcomers and experts NDS3 is Qatar's plan with targets for 2030, and the app ties laws to those targets. To start, ask one plain English question about a policy and see which laws and indicators come back. Search is hybrid: keywords for exact terms and named laws, plus semantic search with the intfloat/multilingual-e5-small embedding model, so an English question can reach an Arabic law. Every number in an answer is checked against computed evidence before it is shown. The confidence score and sources are added by Python code, and a policy's effect in a scenario is an assumption you set, never a forecast. Ask a policy question in the chat → Find laws by keyword and by meaning → Match indicators and run the scenario → Check numbers, then add confidence and sources ### Good to know - Limits: a policy's effect in a scenario is an assumption you set, or a labelled suggested default, and never a prediction - License: MIT - Cost to run: none named, though the chat model is reached through Hugging Face Inference Providers - Data it reaches: Al Meezan laws and articles, a World Bank file of Qatar indicators, a list of 74 NDS3 targets, and the team's data set on Hugging Face - Not for: treating a scenario as a forecast of what a law will do ## README ````markdown # Q-Impact Chats about how Qatari laws and economic indicators influence one another, and what a change to a law could do for growth and the NDS3 2030 targets, for policy analysts. Made by malmarri on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: Q-Impact is a policy research app made for Qatar's Ministry of Commerce and Industry. It links Qatari laws to economic indicators and shows what a change to a law could mean for growth and the NDS3 2030 targets. The main page is a chat. A second view maps each policy area to its related indicators and the laws behind them. Who it suits: Analysts and researchers who work on Qatari law, economic policy and the 2030 targets. ```table Industry | Who uses it | How they use it | Example Government | Policy analysts | Ask how a change to a law would affect the economy | Checking a proposed change against growth targets Economics | Economists | Look up which indicators relate to a policy area | Finding the indicators behind a trade law Legal research | Law researchers | Find a law from a plain English question | Reaching an Arabic law that uses different wording ``` If you do not work with Qatari law or policy, you can skip it. Where to use it: - A web browser, on the Space's page at Hugging Face - Python on Windows, macOS or Linux, for a copy you run yourself ```table Use case | Who | What they get back Policy question | Analysts | An answer with the laws, indicators and 2030 targets it touches Scenario check | Economists | Projected GDP, labour productivity and net FDI figures under an assumed change Indicator lookup | Researchers | The indicators for each policy area and the laws behind them ``` How to set it up: Online, nothing needs installing. For a copy on your own computer you need a few things first. - Python - The pip tool - The packages listed in requirements.txt 1. Install the Hugging Face hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio. 5. Install the packages from requirements.txt. 6. Start app.py. ```sh pip install -U huggingface_hub hf download malmarri/team-qh-167-qatarsignals-app --repo-type space --local-dir team-qh-167-qatarsignals-app cd team-qh-167-qatarsignals-app pip install gradio pip install -r requirements.txt python app.py ``` For its answers, the chat sends requests to Hugging Face Inference Providers, which serves an open model. The source does not say what a local run needs for that. How to use it: Open the Space's page, or start app.py from your own copy, and ask a question about a Qatari policy or a change to one in the chat. It reads the recent turns and answers in the shape your question needs. Next to the chat, a chart plots the scenario's GDP growth against the NDS3 target of 4%, with the main related indicator. ```sh python app.py ``` ```table Tool | What it does AI policy chat | Answers questions about a policy or a change to it, across several turns Law search | Finds the law in Al Meezan by keywords, phrases and meaning, and names its instrument type Indicator view | Shows the indicators related to the policy and their recent trend Scenario model | Applies a Solow growth model to GDP, productivity and net FDI up to 2030 NDS3 targets | Says how a change moves the 2030 targets it affects, with page references Policy-indicator map | Lists each policy area's related indicators and the laws behind it ``` Example: You ask the chat how more foreign ownership across sectors would affect Qatar's growth. It finds the relevant law and its type, then shows related indicators and their trend. It runs a scenario from a change size you set, says how the 2030 targets move, and adds a confidence score and sources. For newcomers and experts: NDS3 is Qatar's plan with targets for 2030, and the app ties laws to those targets. To start, ask one plain English question about a policy and see which laws and indicators come back. Search is hybrid: keywords for exact terms and named laws, plus semantic search with the intfloat/multilingual-e5-small embedding model, so an English question can reach an Arabic law. Every number in an answer is checked against computed evidence before it is shown. The confidence score and sources are added by Python code, and a policy's effect in a scenario is an assumption you set, never a forecast. ```flow Ask a policy question in the chat Find laws by keyword and by meaning Match indicators and run the scenario Check numbers, then add confidence and sources ``` Good to know: - Limits: a policy's effect in a scenario is an assumption you set, or a labelled suggested default, and never a prediction - License: MIT - Cost to run: none named, though the chat model is reached through Hugging Face Inference Providers - Data it reaches: Al Meezan laws and articles, a World Bank file of Qatar indicators, a list of 74 NDS3 targets, and the team's data set on Hugging Face - Not for: treating a scenario as a forecast of what a law will do ## On Hugging Face, 13 November 2026 - Likes: 2 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/malmarri/team-qh-167-qatarsignals-app - Files: https://huggingface.co/spaces/malmarri/team-qh-167-qatarsignals-app/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [malmarri/team-qh-167-qatarsignals-app on Hugging Face](https://huggingface.co/spaces/malmarri/team-qh-167-qatarsignals-app) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Q-Impact (this page) | 2 | gradio | mit | 2026-11-07 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-11-07 - First published: 2026-11-06 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open malmarri/team-qh-167-qatarsignals-app on Hugging Face](https://huggingface.co/spaces/malmarri/team-qh-167-qatarsignals-app) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/e463d44e-39ca-4265-8acc-21206b3ce903) - [Its page on Mindket](https://mindket.com/p/e463d44e-39ca-4265-8acc-21206b3ce903)