README.md

---
title: Endev Chabo Prototype
emoji: 🏃
colorFrom: pink
colorTo: purple
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 deforestation?" vs "What are the main deforestation hotspots in Ecuador?" 
"Tell me about compliance" vs "What EUDR requirements apply to coffee imports from Guatemala?" 
"Show me data" vs "What is the deforestation rate in the uploaded region?"


#### ⭐ 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 EUDR requirements, compliance procedures, and regulatory guidance.

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 EUDR Bot. And hence there is no training data which had been used by the development team of EUDR 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 [email protected]