https://github.com/dharllc/speech-to-code

llm assisted development tools
https://github.com/dharllc/speech-to-code

Last synced: 3 days ago
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llm assisted development tools

• Host: GitHub
• URL: https://github.com/dharllc/speech-to-code
• Owner: dharllc
• Created: 2024-08-09T21:57:23.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2025-01-01T20:41:38.000Z (7 days ago)
• Last Synced: 2025-01-01T21:18:20.608Z (7 days ago)
• Language: JavaScript
• Size: 3.32 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome_ai_agents - Speech-To-Code - llm assisted development tools (Building / Tools)
• awesome_ai_agents - Speech-To-Code - llm assisted development tools (Building / Tools)

README

        
# Speech-to-Code

Speech-to-Code is a web application that leverages Large Language Models (LLMs) to convert spoken language into executable code. This project aims to streamline the code generation process by allowing developers to express their ideas verbally and have them translated into functional code.

## Usage

Here is an example workflow of the Speech-to-Code application:

### Write a prompt, combining speech, the repo tree, and current source code

![Prompt Composer](./screenshots/prompt_composer.png)

### Prompt an LLM and copy the code

![Prompt](./screenshots/prompt_ui.png)

![Copy Code](./screenshots/conversation_display.png)

### Manage system prompts

![System Prompts](./screenshots/system_prompts.png)

## Prerequisites

Before you begin, ensure you have met the following requirements:

* You have installed the latest version of [Node.js and npm](https://nodejs.org/en/download/)

* You have installed [Python](https://www.python.org/downloads/) (version 3.7 or later)

* You have a Windows/Linux/Mac machine with command line access

## Installation

To install Speech-to-Code, follow these steps:

1. Clone the repository

   ```

   git clone https://github.com/dharllc/speech-to-code.git

   cd speech-to-code

   ```

2. Make the build script executable

   ```

   chmod +x build.sh

   ```

3. Run the build script

   ```

   ./build.sh

   ```

   This script will:

   - Install necessary dependencies for both frontend and backend

   - Set up a Python virtual environment

   - Create .env files with placeholders for API keys if they don't exist

4. Configure environment variables

   After running the application, navigate to the Settings page to configure your environment variables, including:

   - OPENAI_API_KEY

   - GOOGLE_API_KEY

   - ANTHROPIC_API_KEY

   - REPO_PATH (path to your local GitHub repositories)

## Running the Application

To run Speech-to-Code, follow these steps:

1. Configure ports (optional):

Edit `config.json` in the root directory to set custom ports. If you need to change the port numbers for the frontend or backend, do it from the root config.json file. 

```json

{

    "frontend": {

        "port": 3000 

    },

    "backend": {

        "port": 8000 

    }

}

```

2. Start the frontend:

   ```

   cd frontend

   npm start

   ```

3. In a new terminal, start the backend:

   ```

   cd backend

   source venv/bin/activate

   uvicorn main:app --reload --log-level debug

   ```

The application should now be running. Access the frontend at `http://localhost:3000` in your web browser, or the port set in the config.json file. Create a unique python virtual environment for this repository and install the required packages using:

```

pip install -r requirements.txt

```

This command should be executed in the /backend folder.

## Project Structure

```

speech-to-code/

├── backend/

│   ├── .env

│   ├── main.py

│   ├── llm_interaction.py

│   ├── model_config.py

│   ├── system_prompts.json

│   ├── context_maps/

│   ├── utils/

├── frontend/

│   ├── public/

│   ├── src/

│   │   ├── components/

│   │   ├── services/

│   │   ├── config/

│   ├── .env

│   ├── .gitignore

│   ├── package-lock.json

│   ├── package.json

│   ├── postcss.config.js

│   └── tailwind.config.js

├── logs/

├── .gitattributes

├── .gitignore

├── package-lock.json

├── README.md

```

## Key Components

### Backend

- `main.py`: The main FastAPI application

- `llm_interaction.py`: Handles interactions with Language Learning Models

- `model_config.py`: Configuration for different language models

- `system_prompts.json`: Stores system prompts for LLM interactions

### Frontend

- `src/components/`: React components for the user interface

- `src/services/llmService.js`: Service for interacting with the backend LLM API

- `src/App.js`: Main React application component

- `src/components/Settings.js`: Component for managing environment variables and repository settings

## Features

- Prompt Composer: Craft and edit prompts for code generation

- System Prompt Management: Manage and customize system prompts

- Prompt UI: Interact with various Large Language Models

- Settings: Configure environment variables and repository settings

- Dark Mode: Toggle between light and dark themes

## Troubleshooting

If you encounter any issues:

- Ensure all API keys are correctly set in the Settings page

- Check that all dependencies are installed correctly

- Verify that both frontend and backend servers are running

For more detailed error messages, check the console output of both frontend and backend servers.

## Contributing

Contributions to Speech-to-Code are welcome. Please refer to the repository's issues page for current tasks or to suggest new features.

## Feedback

Please send feedback via email to [email protected]

## License

This project uses the following license: [MIT License](https://opensource.org/licenses/MIT).