--- title: Endev Chabo Prototype emoji: 🤖🔥 colorFrom: yellow colorTo: gray sdk: docker app_port: 3000 pinned: false --- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference ## About EnDev Agent The EnDev Agent answers questions on the Energising Developement (EnDeV) project. This AI-powered tool helps stakeholders: Understand what is the EnDev project Retrieve information about project activities Ask questions about lesson learned #### Key Features: Chat with information material on EnDev 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 development?" vs "What is the ccoking solutions related behaviour studies?" "Tell me about publications" vs "What does the ELIA Tiers & Markets tool classify" #### ⭐ 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 to answer questions related to EnDev and its activities. Responses should not be considered official legal or compliance advice Always consult qualified professionals for official compliance decisions ⚠️ Data & Privacy: 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: EnDev Agent Provider / Supplier: GIZ Data Service Center As of: December 2025 1. General Description of the System EnDev Agent is an AI-powered conversational assistant designed to help you retrieve information on the Energising Development (EnDev) project. This tool leverages advanced language models to help you get clear and structured answers about Endev related documents. It combines a generative language assistant with a knowledge base implemented via Retrieval-Augmented Generation (RAG). 2. Models Used Generative LLM Model Name: meta-llama/Meta-Llama-3-8B-Instruct Model Source API: Nebius AI Retriever/Embedding Model Name: BAAI/bge-m3 Model Source: Local Instance Re-ranker Model Name: BAAI/bge-reranker-v2-m3 Model Source: Local Instance 4. Model Training Data All the models mentioned above are being consumed without any fine-tuning or training being performed by the developer team of EnDev Bot. And hence there is no training data which had been used by the development team of EnDev Bot. 5. Knowledge Base (Retrieval Component) Data Sources: Public EnDev documentation Embedding Model: BAAI/bge-m3 Embedding Dimension: 1024 Vector Database: Qdrant (via API) Framework: Langchain (custom RAG pipeline) Top-k: 10 relevant text segments per query 6. 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. 7. 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/endev_chabo_prototype/discussions/new). 8. 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/endev_chabo_prototype/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. 9. Contact For any questions, please contact via https://huggingface.co/spaces/GIZ/endev_chabo_prototype/discussions/new or send us an email to dataservicecenter@giz.de