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metadata 
title: Finder
emoji: 📈
colorFrom: indigo
colorTo: green
sdk: docker
pinned: false
license: apache-2.0

title: Finder emoji: 📈 colorFrom: indigo colorTo: green sdk: docker pinned: false license: apache-2.0

Finder AI Assistant

Description

Finder is a powerful AI-driven Flask application that serves as an intelligent assistant capable of processing various document types, answering queries, analyzing news, and generating insights. It leverages Google's Generative AI and LangChain for enhanced language model interactions, making it a versatile tool for information retrieval and analysis.

Features

  • Document upload and analysis (PDF, DOCX, XLSX, CSV)
  • Natural language query processing
  • News fetching and analysis for energy market queries
  • Data visualization capabilities
  • CSV data query processing

How to Use

  1. Document Analysis: Upload your documents (PDF, DOCX, XLSX, CSV) to get AI-powered insights.
  2. Ask Questions: Use natural language to ask questions about uploaded documents or general queries.
  3. Energy Market News: Get the latest news and analysis related to the energy market.
  4. Data Visualization: Generate interactive plots from uploaded Excel files.
  5. CSV Query Processing: Run specific queries on your CSV data for detailed analysis.

Technical Details

  • Built with Flask and Google's Generative AI
  • Uses LangChain for advanced language model interactions
  • Integrates NewsAPI for real-time news fetching
  • Employs Plotly for interactive data visualization

Deployment

This application is deployed as a Hugging Face Space using Docker. The Dockerfile and requirements.txt in the repository handle the setup and dependencies.

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.

Contact

For any queries or support, please open an issue in this repository.

Note: This AI assistant is for informational purposes only. Always verify critical information and consult with appropriate experts for professional advice. Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference