weblama

WebLama

PyLama Ecosystem Navigation

Project Description Links
WebLama Web application generation GitHub · Docs
GetLLM LLM model management and code generation GitHub · PyPI · Docs
DevLama Python code generation with Ollama GitHub · Docs
LogLama Centralized logging and environment management GitHub · PyPI · Docs
APILama API service for code generation GitHub · Docs
BEXY Sandbox for executing generated code GitHub · Docs
JSLama JavaScript code generation GitHub · NPM · Docs
JSBox JavaScript sandbox for executing code GitHub · NPM · Docs
SheLLama Shell command generation GitHub · PyPI · Docs

Author

Tom Sapletta — DevOps Engineer & Systems Architect

GitHub LinkedIn ORCID Portfolio

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A web frontend for the PyLama ecosystem that provides a user interface for interacting with the various PyLama services. WebLama integrates with LogLama as the primary service for centralized logging, environment management, and service orchestration.

Installation

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install the package in development mode
pip install -e .  # This is important! Always install in development mode before starting

IMPORTANT: Always run pip install -e . before starting the project to ensure all dependencies are properly installed and the package is available in development mode.

Building and Running the Docker Container

To build the Docker image, run the following command from the project directory:

docker build -t weblama .

To run the container, mapping port 8084 on the host to port 80 in the container:

docker run -p 8084:80 weblama

Once the container is running, you can access the application at http://localhost:8084

Project Structure

LogLama Integration

WebLama integrates with LogLama as the primary service in the PyLama ecosystem. This integration provides:

Using the Makefile

WebLama includes a Makefile to simplify common development tasks:

# Set up the project (creates a virtual environment and installs dependencies)
make setup

# Run the web server (default port 8081)
make web

# Run the web server on a custom port
make web PORT=8080

# Run tests
make test

# Clean up project (remove __pycache__, etc.)
make clean

# Show all available commands
make help