--- title: EUDR Chabo ChatUI emoji: 🤖🔥 colorFrom: gray colorTo: gray sdk: docker app_port: 3000 pinned: false --- ## About EUDR Agent The EU Deforestation Regulation (EUDR) requires companies to ensure that specific commodities placed on the EU market are deforestation-free and legally produced. This AI-powered tool helps stakeholders: - Understand EUDR compliance requirements - Analyze geographic deforestation data using WHISP API - Assess supply chain risks - Navigate complex regulatory landscapes - Developed by GIZ to enhance accessibility and understanding of EUDR requirements through advanced AI and geographic data processing capabilities. Key Features: - Automatic analysis of uploaded GeoJSON files via WHISP API - Country-specific EUDR compliance guidance - Real-time question answering with source citations - User-friendly interface for complex regulatory information ---------------------------------------------------------------------------- ### 💬 How to Ask Effective Questions ❌ Less Effective ✅ More Effective "What is deforestation?" "What are the main deforestation hotspots in Ecuador?" "Tell me about compliance" "What EUDR requirements apply to coffee imports from Guatemala?" "Show me data" "What is the deforestation rate in the uploaded region?" 🔍 Using Data Sources Upload GeoJSON: Upload your geographic data files for automatic analysis via WHISP API Talk to Reports: Select Ecuador or Guatemala for country-specific EUDR analysis ### ⭐ Best Practices - Be specific about regions, commodities, or time periods - Ask one question at a time for clearer answers - Use follow-up questions to explore topics deeper - Provide context when possible --------------------------------------------------------------- ## Important Disclaimers ⚠️ Scope & Limitations: This tool is designed for EUDR compliance assistance and geographic data analysis Responses should not be considered official legal or compliance advice Always consult qualified professionals for official compliance decisions ⚠️ Data & Privacy: - Uploaded GeoJSON files are processed via external WHISP API for analysis - We collect usage statistics to improve the tool - Files are processed temporarily and not permanently stored ⚠️ AI Limitations: - Responses are AI-generated and may contain inaccuracies - The tool is a prototype under continuous development - Always verify important information with authoritative sources Data Collection: We collect questions, answers, feedback, and anonymized usage statistics to improve tool performance based on legitimate interest in service enhancement.By using this chatbot, you agree to these terms and acknowledge that you are solely responsible for any reliance on or actions taken based on its responses. Technical Information: User can read more about the technical information about the tool in section below. This is just a prototype and being tested and worked upon, so its not perfect and may sometimes give irrelevant answers. If you are not satisfied with the answer, please ask a more specific question or report your feedback to help us improve the system. ----------------------------------------------------------------------------------- # Technical Documentation of the system in accordance with EU AI Act **System Name:** EUDR Chatbot **Provider / Supplier:** GIZ Data Service Center **As of:** September 2025 ## 1. General Description of the System EUDR Bot is an AI-powered conversational assistant designed to help you understand compliance with and analyze the EU Deforestation Regulation. This tool leverages advanced language models to help you get clear and structured answers about EUDR requirements, compliance procedures, and regulatory guidance. It combines a generative language assistant with a knowledge base implemented via Retrieval-Augmented Generation (RAG). In addition to the RAG, the tool also provide quick analysis on the geojson of plot by leveraging the [Whisp](https://openforis.org/solutions/whisp/). The scope and functionality of the tool is focused on EU Deforestation Regulation compliance and related documentation in context of 'Ecuador' and 'Guatemala' only. ## 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 ### External API's - **Whisp Info**: https://openforis.org/solutions/whisp/ - **API Endpoint** https://whisp.openforis.org/documentation/api-guide ## 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 EUDR Bot. And hence there is no training data which had been used by the development team of EUDR Bot. ## 4. Knowledge Base (Retrieval Component) - **Data Sources:** Public EUDR 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:** 10 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/eudr_chatbo_chatui/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/eudr_chatbo_chatui/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/eudr_chatbo_chatui/discussions/new or send us email to dataservicecenter@giz.de