README.md

metadata

title: FislacBot
emoji: 📊
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.6.0
app_file: app.py
pinned: false
license: mit
app_port: 7860
docker_user: root
base_path: /app
accelerator: gpu

FislacBot - AI Assistant for FISLAC Documentation FislacBot is an artificial intelligence assistant specialized in FISLAC (Fiscal Latin America and Caribbean) documentation and fiscal analysis. It uses the Llama-2-7b model with RAG (Retrieval Augmented Generation) to provide accurate responses based on official documentation. Author Camilo Vega Barbosa

AI Professor and Artificial Intelligence Solutions Consultant Connect with me:

LinkedIn GitHub

Features

RAG-powered responses using official FISLAC documentation Interactive chat interface using Gradio GPU-accelerated inference Context-aware responses with source tracking

How It Works The application uses a sophisticated RAG system that:

Processes and indexes FISLAC documentation Generates embeddings using multilingual-e5-large Uses FAISS for efficient vector storage and retrieval Combines retrieved context with Llama-2 for accurate responses

Technical Details

Model: Meta-llama/Llama-2-7b-chat-hf Embeddings: intfloat/multilingual-e5-large Vector Store: FAISS Framework: Gradio Dependencies: Managed through requirements.txt Device Configuration: GPU-optimized using Accelerate

Installation To run this application locally:

Clone the repository Install dependencies: bashCopypip install -r requirements.txt

Run the application: bashCopypython app.py

Knowledge Base The system is trained on:

Official FISLAC documentation Valencia et al. (2022) - "Assessing macro-fiscal risk for Latin American and Caribbean countries" Additional BID fiscal documentation

Created by Camilo Vega Barbosa, AI Professor and Solutions Consultant. For more AI projects and collaborations, feel free to connect on LinkedIn or visit my GitHub.