metadata

title: MistyClimate Agent
emoji: 📈
colorFrom: red
colorTo: pink
sdk: docker
pinned: false
short_description: This is a agent created using mistral models
tags:
  - agent-demo-track
Usage: Mistral

MistyClimate Agent 📈

This is an agent created using Mistral models, designed to process climate-related documents, analyze images, perform JSON data analysis, and convert text to speech. It provides a multi-agent system for document processing, image analysis, JSON analysis, and text-to-speech functionalities, all integrated into a user-friendly Gradio interface.

Video Demo

Below is an embedded YouTube video demonstrating the MistyClimateAgent for the Hackathon:

Click the image or watch the demo video on YouTube.

Features

Document Processing: Extract structured data from climate-related PDFs using OCR capabilities.
Image Analysis: Analyze image-based documents (e.g., PNG, JPG, PDF) to extract text, charts, and tables.
JSON Analysis: Analyze JSON data to extract insights and patterns, with a focus on climate data.
Text-to-Speech: Convert text analysis into speech using the gTTS library.
Gradio Interface: A web-based UI to interact with all features seamlessly.

Setup

This project is containerized using Docker and deployed on a Gradio Space. Follow the steps below to set up and run the project locally or on Hugging Face Spaces.

Prerequisites

Docker (if running locally)
A Mistral API key (obtain from Mistral AI)
Python 3.10+ (if running locally without Docker)

Installation

Clone the Repository (if running locally):

git clone <repository-url>
cd <repository-directory>

Install Dependencies: The project uses a requirements.txt file to manage dependencies. If running locally without Docker, install the dependencies using:
```
pip install -r requirements.txt
```
Set Up the Mistral API Key:
- You will need a Mistral API key to use the Mistral models.
- In the Gradio interface, input your API key in the "Mistral API Key" field.
Run with Docker (recommended for local testing):
- Build the Docker image:
```
docker build -t mistyclimate-agent .
```
- Run the Docker container:
```
docker run -p 7860:7860 mistyclimate-agent
```
- Access the Gradio interface at http://localhost:7860.
Deploy on Hugging Face Spaces:
- This project is already configured for Hugging Face Spaces with the sdk: docker setting.
- Push your code to a Hugging Face Space repository.
- The Space will automatically build and deploy using the provided Dockerfile.

Usage

Access the Gradio Interface:
- If running locally, open http://localhost:7860 in your browser.
- If deployed on Hugging Face Spaces, visit the Space URL.
Enter Your Mistral API Key:
- In the Gradio interface, provide your Mistral API key in the designated input field.
Interact with the Tabs:
- Document Processing:
  - Upload a PDF document (e.g., a climate report).
  - Select the document type (e.g., climate_report).
  - Click "Process Document" to extract structured data in JSON format.
- Image Analysis:
  - Upload an image file (PNG, JPG, or PDF).
  - Choose an analysis focus (e.g., text_extraction, chart_analysis).
  - Click "Analyze Image" to get structured data from the image.
- JSON Analysis & Speech:
  - Input JSON data (e.g., temperature or emissions data).
  - Select an analysis type (e.g., content).
  - Click "Run Analysis & Speech" to analyze the JSON and generate a speech output.
- Text-to-Speech:
  - Enter text to convert to speech (e.g., "hello, and good luck for the hackathon").
  - Click "Generate Speech" to produce and play an audio file.

File Structure

agent.py: Core logic for the multi-agent system, including document processing, image analysis, JSON analysis, and text-to-speech workflows.
app.py: Gradio interface setup and workflow orchestration.
requirements.txt: List of Python dependencies.
Dockerfile: Docker configuration for containerizing the app.
README.md: Project documentation (this file).

Notes

File Paths: In a Gradio Space, files like PDFs, images, and WAVs are handled dynamically via uploads. Output files (e.g., WAVs) are saved to /tmp/ during runtime.
Mistral API Key: Ensure you have a valid Mistral API key to use the models. Without it, the workflows will fail.
Docker Deployment: The project is configured to run in a Docker container, making it compatible with Hugging Face Spaces.

Configuration Reference

For more details on configuring Hugging Face Spaces, refer to the Hugging Face Spaces Config Reference.

License

This project is licensed under the MIT License. See the LICENSE file for details (if applicable).

Built with ❤️ by Samudrala Dinesh Naveen Kumar.

Spaces:

Agents-MCP-Hackathon
/

Misty_Climate_Agent

Running