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---
title: Gina Assistant
emoji: 🧐
colorFrom: yellow
colorTo: gray
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
fullWidth: true
pinned: false
startup_duration_timeout: 1h
models:
- BAAI/bge-m3
- BAAI/bge-reranker-v2-m3
- meta-llama/Llama-3.1-8B-Instruct
---
short_description: AI-powered conversational assistant for Circular Economy
license: apache-2.0
## Technical Documentation of the system in accordance with EU AI Act
**System Name:** Gina ChatBot
**Provider / Supplier:** GIZ Data Service Center
**As of:** August 2025
## 1. General Description of the System
Gina Bot is an AI-powered conversational assistant designed to help you understand compliance with and analyze the Circular Economy topic. This tool leverages advanced language models to help you get clear and structured answers about Circular Economy requirements, compliance procedures, and regulatory guidance.
It combines a generative language assistant with a knowledge base implemented via Retrieval-Augmented Generation (RAG). The scope and functionality of the tool is focused on specific document database collected by team on topic of 'Circular Economy' in context of Colombia.
## 2. Models Used
### Generative LLM
- **Model Name:** [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)
- **Model Source API:** [Nebius AI](https://studio.nebius.com/)
### Retriever/Embedding
- **Model Name:** [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
- **Model Source:** Local Instance
### Re-ranker
- **Model Name:** [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3)
- **Model Source:** Local Instance
## 3. Model Training Data
All the models mentioned above are being consumed without any fine-tuning or training being performed by the developer team of Gina Bot. And hence there is no training data which had been used by the development team of Gina Bot.
## 4. Knowledge Base (Retrieval Component)
- **Data Sources:** Public Circular Economy documentation, regulatory guidance, and compliance materials
- **Embedding Model:** [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
- **Embedding Dimension:** 1024
- **Vector Database:** Qdrant (via API)
- **Framework:** Langchain (custom RAG pipeline)
- **Top-k:** 5 relevant text segments per query
## 5. System Limitations and Non-Purposes
- The system does not make autonomous decisions.
- No processing of personal data except for the usage statistics as mentioned in Disclaimer.
- Results are intended for orientation only – not for legal or regulatory compliance advice.
- Users should consult official EU documentation and legal experts for definitive compliance guidance.
## 6. Transparency Towards Users
- The user interface clearly indicates the use of a generative AI model.
- An explanation of the RAG method is included.
- We collect usage statistics as detailed in Disclaimer tab of the app along with the explicit display in the user interface of the tool.
- Feedback mechanism available (via https://huggingface.co/spaces/GIZ/gina/discussions/new).
## 7. Monitoring, Feedback, and Incident Reporting
- User can provide feedback via UI by giving (Thumbs-up or down to AI-Generated answer). Alternatively for more detailed feedback please use https://huggingface.co/spaces/GIZ/gina/discussions/new to report any issue.
- Technical development is carried out by the GIZ Data Service Center.
- No automated bias detection – but low risk due to content restrictions.
## 8. Contact
For any questions, please contact via https://huggingface.co/spaces/GIZ/gina/discussions/new or send us email to dataservicecenter@giz.de |