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Braintrust Playground

Welcome to the Braintrust Playground! This repository is a sandbox for exploring and building agentic AI applications. It provides a foundation for experimenting with AI-driven solutions, particularly in the domain of decision-making and automation.

About Braintrust

Braintrust is a conceptual framework for creating intelligent agents that can autonomously assess, decide, and act in complex environments. It emphasizes:

  • Autonomy: Enabling agents to operate independently with minimal human intervention.
  • Adaptability: Allowing agents to learn and adjust to new information and environments.
  • Collaboration: Facilitating interaction between multiple agents to achieve shared goals.

This playground serves as a practical implementation space for these ideas, offering tools and examples to help developers get started.

Getting Started

  1. Clone the repository:
    git clone https://github.com/your-username/braintrust-playground.git
  2. Navigate to the project directory:
    cd braintrust-playground
  3. Install dependencies:
    pip install -r requirements.txt
  4. Run the Streamlit app:
    streamlit run streamlit_loan_assess.py

Tips for Using API Keys

To use the Braintrust Playground effectively, you may need to set your API keys for services like OpenAI and Braintrust. Use the following commands to set your API keys in your environment:

For Windows (Command Prompt):

set OPENAI_API_KEY=<your-key>
set BRAINTRUST_API_KEY=<your-key>

For Windows (PowerShell):

$env:OPENAI_API_KEY="<your-key>"
$env:BRAINTRUST_API_KEY="<your-key>"

For macOS/Linux:

export OPENAI_API_KEY=<your-key>
export BRAINTRUST_API_KEY=<your-key>

Replace <your-key> with your actual API keys. Ensure these keys are kept secure and not shared publicly.

Contributing

Contributions are welcome! Feel free to submit issues or pull requests to improve this project.

License

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

About

his repository is a sandbox for exploring and building agentic AI applications. It provides a foundation for experimenting with AI-driven solutions, particularly in the domain of decision-making and automation.

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