Update README.md

README.md

@@ -1,43 +1,29 @@
 ---
 title: Montreal Chabo ChatUI
-emoji: 🤖🔥
-colorFrom: gray
+emoji: 🤖
+colorFrom: yellow
 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.
+## About Montreal Agent
+It helps you find and summarize specific decisions and annexes, and can also answer general questions about the Montreal treaty. For transparency, it provides references with links to the relevant decisions and annexes, so you can easily verify the sources. 
+While this chatbot was developed with care, we recommend double-checking the links to gain a deeper understanding of the material.
 
-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?"
+"What is Treaty?"	"What are the article 5 countries for hcfc phase out in Montreal Treaty?"
+"Tell me about compliance"	"What requirements apply to developing countries in terms of refrigeration substances usage?"
 
 🔍 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
+Talk to Database: Eiher ask borad questions or ask Meeting/Decision specific questions
 
 ### ⭐ Best Practices
-- Be specific about regions, commodities, or time periods
+- Be specific about focus of question
 - Ask one question at a time for clearer answers
 - Use follow-up questions to explore topics deeper
 - Provide context when possible
@@ -46,12 +32,11 @@ Talk to Reports: Select Ecuador or Guatemala for country-specific EUDR analysis
 ## Important Disclaimers
 ⚠️ Scope & Limitations:
 
-This tool is designed for EUDR compliance assistance and geographic data analysis
+This tool is designed for Montreal database Q&A
 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
 
@@ -73,17 +58,17 @@ This is just a prototype and being tested and worked upon, so its not perfect an
 
 # Technical Documentation of the system in accordance with EU AI Act
 
-**System Name:** EUDR Chatbot
+**System Name:** Montreal Chatbot
 
-**Provider / Supplier:** GIZ Data Service Center
+**Provider / Supplier:** GIZ Data Service Center and GIZ Data Lab
 
 **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.
+Montreal Bot is an AI-powered conversational assistant designed to help you interact with Montreal treaty database. This tool leverages advanced language models to help you get clear and structured answers about Montreal meetings/decisions.
 
-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.
+It combines a generative language assistant with a knowledge base implemented via Retrieval-Augmented Generation (RAG). 
 
 ## 2. Models Used
 
@@ -105,11 +90,11 @@ It combines a generative language assistant with a knowledge base implemented vi
 
 ## 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.
+All the models mentioned above are being consumed without any fine-tuning or training being performed by the developer team of Montreal Bot. And hence there is no training data which had been used by the development team of Montreal Bot.
 
 ## 4. Knowledge Base (Retrieval Component)
 
-- **Data Sources:** Public EUDR documentation, regulatory guidance, and compliance materials
+- **Data Sources:** Public Montreal database
 - **Embedding Model:** [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
 - **Embedding Dimension:** 1024
 - **Vector Database:** Qdrant (via API)
@@ -128,14 +113,14 @@ All the models mentioned above are being consumed without any fine-tuning or tra
 - 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).
+- Feedback mechanism available (via https://huggingface.co/spaces/GIZ/mlf_chabo_prototype/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.
+- 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/mlf_chabo_prototype/discussions/new to report any issue.
+- Technical development is carried out by the GIZ Data Service Center and Data Lab
 - 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
+For any questions, please contact via https://huggingface.co/spaces/GIZ/mlf_chabo_prototype/discussions/new or send us email to dataservicecenter@giz.de