GPT-Synthesizer

GPT Synthesizer Overview

Collaboratively implement an entire software project with the help of an AI.

GPT-Synthesizer is an innovative tool designed to assist users in developing software projects by collaborating with an AI through a structured interview process. This tool is ideal for those who are unsure of how to start or describe their software projects.

Unique Features of GPT Synthesizer

GPT Synthesizer stands apart from other tools because it disagrees with the notion that a single prompt can define a complete codebase for complicated software. Although large language models (LLMs) are powerful, they cannot capture all essential details in a single prompt, which leads to inefficiency. GPT Synthesizer addresses this by using LangChain to capture the design specifications incrementally through AI-supported dialogue with the user.

The system starts by interpreting the user's initial prompt as a broad description of their programming task. Through a process called "prompt synthesis," GPT Synthesizer breaks down this initial prompt into several components required for the task. This conversion helps users, especially novices, by elucidating the fundamental flow of the implementation process. Together, the AI and the user then explore and define the necessary design details for each program component.

Different users may have varying interaction preferences based on their skills and the complexity of their projects. GPT Synthesizer uniquely balances user involvement with AI autonomy, distinguishing it from other LLM-based code generation platforms.

Installation Instructions

For simple installation, use the command:

• pip install gpt-synthesizer

For development purposes, clone the repository and install it as per the following commands:

• git clone https://github.com/RoboCoachTechnologies/GPT-Synthesizer.git
• cd GPT-Synthesizer
• pip install -e .

How to Use GPT Synthesizer

GPT Synthesizer operates smoothly both via a command-line interface and a user-friendly interface using Streamlit. It utilizes OpenAI's gpt-3.5-turbo-16k as the default LLM.

Streamlit App Setup:

1. Start the application by typing gpt-synthesizer-streamlit in the terminal.
2. Enter your OpenAI API key in the sidebar.
3. Choose the preferred model from the sidebar.

You can watch a Streamlit demo here: streamlit demo: calculator.

Command Line Interface:

1. Set up your OpenAI API key with export OPENAI_API_KEY=[your api key].
2. Launch GPT Synthesizer by typing gpt-synthesizer in the terminal.

Check out some demos here:

• Release demo: a snake game
• Release demo: a tic-tac-toe game
• Short demo: installation guide
• Short demo: adding/removing components

Operational Workflow:

1. Provide a simple description of your programming task and preferred language, like "I want to implement an edge detection method from a live camera feed in Python."
2. GPT Synthesizer will propose the necessary components for implementation.
3. Users can modify the component list by adding or removing components as required.
4. Once the component list is finalized, GPT Synthesizer will gather detailed specifications for each component through queries.
5. Upon understanding your requirements, GPT Synthesizer will generate the code, which can be found in the 'workspace' directory.

Customizing GPT Synthesizer

GPT Synthesizer's code is easy to comprehend and tailor for specific applications. It employs LangChain to integrate with various tools, such as internet search and vector databases.

By leveraging GPT Synthesizer’s hierarchical coding strategy, OpenAI's GPT3.5 is an optimal backend solution, balancing cost and understanding effectively. However, transitioning to another LLM is feasible due to LangChain's flexibility.

Future Developments

GPT Synthesizer will remain an actively maintained open-source project, and contributions are welcome. Future plans include:

• Adding a step in code generation for creating a main/entry point.
• Creating language-based setup instructions like CMakelists.txt for C++ and setup.py for Python.
• Incorporating benchmarks and testing scripts.

Additional Resources

For more insights, read the article "Looking inside GPT-Synthesizer and the idea of LLM-based code generation".

Contact Information

For business inquiries such as consulting or contracting, please reach out to [email protected].