AI Product Analysis CLI

Overview

AI Product Analysis CLI is a powerful command-line tool that leverages advanced language models and a sophisticated graph-based approach to provide comprehensive analyses of AI products. This tool is designed for researchers, product managers, and AI enthusiasts who want to gain deep insights into various AI products and their potential impacts across different domains.

This project is inspired by the STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective) methodology from the LangChain library, adapted for AI product analysis.

Features

• Generates detailed outlines for AI product analysis
• Creates diverse expert personas for multi-perspective analysis
• Conducts simulated expert interviews using AI
• Refines analysis outlines based on gathered information
• Writes comprehensive sections for each aspect of the analysis
• Produces a final, detailed analysis report in Markdown format
• Supports analysis of AI products across various domains and use cases

How It Works

The AI Product Analysis CLI uses a sophisticated graph-based approach to generate comprehensive analyses, inspired by the STORM methodology. Here's a high-level overview of the process:

graph TD
    A[Start] --> B[Generate Outline]
    B --> C[Generate Expert Personas]
    C --> D[Conduct Interviews]
    D --> E[Refine Outline]
    D --> D[Interview Process]
    E --> F[Write Sections]
    F --> G[Write Final Analysis]
    G --> H[End]

    subgraph Interview Process
        I[Ask Question] --> J{Continue?}
        J -->|Yes| K[Generate Answer]
        K --> I
        J -->|No| L[End Interview]
    end

1. Generate Outline: Creates an initial structure for the analysis.
2. Generate Expert Personas: Develops diverse AI expert profiles for multi-perspective analysis.
3. Conduct Interviews: Simulates interviews with AI experts, using a nested graph structure:
   • Ask Question: Generates relevant questions based on the expert's profile.
   • Generate Answer: Provides informed responses using real-time web search.
   • This process continues until a satisfactory amount of information is gathered.
4. Refine Outline: Updates the initial outline based on the information from interviews.
5. Write Sections: Generates detailed content for each section of the analysis.
6. Write Final Analysis: Compiles all sections into a comprehensive, well-structured report.

Configuration

Before using the CLI, make sure to set up your environment variables:

1. Create a .env file in your home directory.
2. Add the following variables:

OPENAI_API_KEY=your_openai_api_key
TAVILY_API_KEY=your_tavily_api_key

Replace your_openai_api_key and your_tavily_api_key with your actual API keys.

Usage

After setting up the project, you can use the CLI as follows:

node dist/main.js analyze "AI Product Name" --output analysis.md

This will generate an analysis of the specified AI product, saving the output to the specified file.

Development

To set up the project for development:

1. Clone the repository:

   git clone https://github.com/yourusername/ai-product-analysis-cli.git
   cd ai-product-analysis-cli

2. Install dependencies:

   pnpm install

3. Build the project:

   pnpm run build

4. Run the CLI locally:

   node dist/main.js analyze "AI Product Name"

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

Disclaimer

This tool uses AI models and web search capabilities. The accuracy and completeness of the analysis depend on the available information and the performance of the underlying models. Always verify critical information from authoritative sources.

Acknowledgements

This project is inspired by and adapts concepts from the STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective) example in the LangChain library. We are grateful to the LangChain team for their innovative work in the field of AI and language models. The original STORM example can be found at: https://github.com/langchain-ai/langgraph/blob/main/examples/storm/storm.ipynb