https://github.com/nimblesite/nimble_agent
A LangChain, CLI based AI coding assistant and library aimed at fixing common issues that exist in other AI agents
https://github.com/nimblesite/nimble_agent
ai chatgpt coding-assistant langchain python
Last synced: 4 months ago
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A LangChain, CLI based AI coding assistant and library aimed at fixing common issues that exist in other AI agents
- Host: GitHub
- URL: https://github.com/nimblesite/nimble_agent
- Owner: Nimblesite
- License: other
- Created: 2025-05-01T21:29:06.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-07-21T22:32:32.000Z (7 months ago)
- Last Synced: 2025-07-21T23:22:25.057Z (7 months ago)
- Topics: ai, chatgpt, coding-assistant, langchain, python
- Language: Python
- Homepage: https://www.nimblesite.co/
- Size: 70.3 KB
- Stars: 9
- Watchers: 1
- Forks: 1
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Audit: audit.md
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README
# Nimble Agent
A LangChain, CLI based AI coding assistant and library aimed at fixing common issues that exist in other AI agents. You can run it at the terminal, call it from your app, or run it in the cloud/CICD pipeline.
See the [major features](https://github.com/Nimblesite/nimble_agent/issues?q=is%3Aissue%20state%3Aopen%20label%3A%22major%20feature%22) list to get a sense of the ultimate aims of this project. One other ultimate aim is cost minimisation. By default, the agent uses cheap models, and the aim is to support as many open source models as possible that can run locally. A major driver for this project is to use smart prompting and orchestration rather than brute force expensive models.
The agent introduces the concept of "acceptance criteria". This tells the agent how to check if the task has succeeded. Acceptance criteria should be objective, such as something that can be actually tested in a unit test or UI test. The agent should loop until the criteria is met. This ensures that the agent doesn't just create random code and then stop.
The long term aim is to implement multi-agent support so as to fix issues like code deletion that is so rampant in other agents. It appears at this point that agents will always hallucinate, make mistakes and go beyond what is asked of them. A reviewer agent will revert obvious mistakes made by the original agent and attempt to steer the agent back on the right track.
## Development Environment Setup
**Add your OpenAI API Key by creating a `.env` file in the root directory**
```
OPENAI_API_KEY=your_key_here
```
This project uses VS Code Dev Containers to ensure a consistent development environment. **This is the required way to develop for this project.**
### Prerequisites
1. Install [Docker Desktop](https://www.docker.com/products/docker-desktop/)
2. Install [Visual Studio Code](https://code.visualstudio.com/)
3. Install the [Dev Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) extension in VS Code
### Quick Start
1. Clone the repository:
```bash
git clone https://github.com/your-username/nimble_agent.git
cd nimble_agent
```
2. Start Docker Desktop
3. Open the project in VS Code:
```bash
code .
```
4. Start the Dev Container:
- When prompted "Folder contains a Dev Container configuration file. Reopen folder to develop in a container", click "Reopen in Container"
- Or press `Cmd + Shift + P` (Mac) / `Ctrl + Shift + P` (Windows/Linux), type "Dev Containers: Reopen in Container"
VS Code will automatically:
- Build the container with Python 3.12 and Flutter
- Install all project dependencies
- Run setup.sh to configure the development environment
- Configure development tools and extensions
### Environment Variables
Create a `.env` file in the root directory:
```
OPENAI_API_KEY=your_key_here
```
### Development Tools Included
The dev container comes pre-configured with:
- Python 3.11
- Flutter (stable channel)
- Code formatting (Black, dart format)
- Linting (Ruff, Flutter lint)
- Type checking (Pyright)
- Auto-formatting on save
- Import sorting
- Debugging support
- IntelliCode AI assistance
### Development Workflow
#### Running Tests and Checks
The project includes a comprehensive CI script that runs all necessary checks. To test your changes, run:
```bash
./scripts/ci.sh
```
This script will:
- Run all tests with pytest
- Check code formatting with Black
- Run linting with Ruff
- Verify type checking with Pyright
- Check test coverage requirements
- Generate coverage reports
#### Common Commands
Inside the dev container:
```bash
# Run tests
pytest
# Format code
black .
# Run linting
ruff check .
# Run all checks
./scripts/ci.sh
```
### Troubleshooting
If you encounter issues:
1. Ensure Docker Desktop is running
2. Rebuild the container:
- `Cmd/Ctrl + Shift + P`
- Type "Dev Containers: Rebuild Container"
3. Verify Flutter installation:
```bash
flutter doctor
```
### Stopping the Dev Container
1. Press `Cmd + Shift + P` (Mac) / `Ctrl + Shift + P` (Windows/Linux)
2. Type "Dev Containers: Reopen Folder Locally"
3. Press Enter