Market Research & Use Case Generation Agent

Project Overview

This project is a Multi-Agent architecture system designed to generate relevant AI and Generative AI (GenAI) use cases for a given company or industry. The system conducts market research, understands the industry and products, and provides resource assets for AI/ML solutions. It focuses on enhancing operations and customer experiences while delivering actionable insights.

The Multi-Agent system includes the following agents:

1. Research Agent: Conducts market research and gathers industry insights.
2. Use Case Agent: Proposes AI/GenAI use cases based on research findings.
3. Resource Asset Agent: Identifies and collects datasets relevant to the proposed use cases.
4. Final Proposal Agent: Compiles the generated use cases and resource links into a comprehensive report.

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Features

• Industry Research: Analyzes market trends and company focus areas.
• AI Use Case Generation: Proposes actionable AI/GenAI use cases tailored to the company's needs.
• Resource Collection: Identifies relevant datasets from platforms like Kaggle, HuggingFace, and GitHub.
• Extensible Framework: Allows easy adaptation to new industries or companies.

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Project Structure

Multi_agent_system/
├── README.md
├── agents
│   ├── __init__.py
│   ├── research_agent.py          # Conducts industry and company research
│   ├── use_case_agent.py          # Generates AI/GenAI use cases
│   ├── resource_asset_agent.py    # Collects datasets for use cases
│   ├── final_proposal_agent.py    # Compiles and formats the final report
│   ├── proposed_use_cases.json    # Stores the generated use cases
│   ├── main.py                    # Entry point for running all agents
├── demo.py                        # Demonstrates the system's functionality
├── kaggle.json                    # API key for accessing Kaggle datasets
├── requirements.txt               # Python dependencies

Prerequisites

• Python 3.8 or higher
• Forefront API key: Sign up at Forefront AI
• Internet connection: Required for making API calls

Setup and Installation

1. Clone the repository:

   git clone https://github.com/Princccee/Multi-AI-agent-system.git
   cd Multi_agent_system

2. Create a virtual environment:

   python3 -m venv .venv
   source venv/bin/activate   # On Windows use `venv\Scripts\activate`

3. Install the required dependencies:

   pip install -r requirements.txt

4. Set up API key:

   • Place your kaggle.json file in the root directory of the project.
   • Create a .env file and store these API keys.

   FOREFRONT_API_KEY=your_forefront_api_key
   SERPAPI_API_KEY=your_serpapi_api_key
   KAGGLE_API_KEY=your_kaggle_api_key
   HUGGINGFACE_API_KEY=your_huggingface_api_key
   GITHUB_API_KEY=your_github_api_key
   GOOGLE_API_KEY=your_google_api_key
   GOOGLE_CSE_ID=your_google_cse_id
   API_KEY=your_kaggle_api_key
   

5. Run the demo:

   cd agents
   python main.py  # Execute the main.py file to start the app

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This setup will ensure that you have all the necessary dependencies and configurations to run the Multi-Agent system effectively.