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+# tabbyAPI
+
+tabbyAPI is a FastAPI-based application that provides an API for generating text using a language model. This README provides instructions on how to launch and use the tabbyAPI.
+
+## Prerequisites
+
+Before you get started, ensure you have the following prerequisites installed on your system:
+
+- Python 3.x (with pip)
+- Dependencies listed in `requirements.txt`
+
+## Installation
+
+1. Clone the repository to your local machine:
+
+git clone https://github.com/Splice86/tabbyAPI.git
+
+
+2. Navigate to the project directory:
+
+cd tabbyAPI
+
+
+3. Create a virtual environment (optional but recommended):
+
+python -m venv venv
+source venv/bin/activate
+
+
+4. Install project dependencies using pip:
+
+pip install -r requirements.txt
+
+
+5. Install exllamav2 to your venv
+
+git clone https://github.com/turboderp/exllamav2.git
+cd exllamav2
+pip install -r requirements.txt
+python setup.py install
+
+
+
+## Launch the tabbyAPI Application
+
+To start the tabbyAPI application, follow these steps:
+
+1. Ensure you are in the project directory and the virtual environment is activated (if used).
+
+2. Run the tabbyAPI application using Uvicorn:
+
+
+uvicorn main:app --host 0.0.0.0 --port 8000 --reload
+
+
+- `main` refers to the Python file containing your tabbyAPI app instance.
+- `app` is the FastAPI instance defined in your Python script.
+- `--host 0.0.0.0` allows access from external devices. Change this to `localhost` if you want to restrict access to the local machine.
+- `--port 8000` specifies the port on which your application will run.
+- `--reload` enables auto-reloading for development.
+
+3. The tabbyAPI application should now be running. You can access it by opening a web browser and navigating to `http://localhost:8000` (if running locally).
+
+## Usage
+
+The tabbyAPI application provides the following endpoint:
+
+- `/generate-text` (HTTP POST): Use this endpoint to generate text based on the provided input data.
+
+### Example Request (using `curl`)
+
+
+curl -X POST "http://localhost:8000/generate-text" -H "Content-Type: application/json" -d '{
+    "model": "your_model_name",
+    "messages": [
+        {"role": "user", "content": "Say this is a test!"}
+    ],
+    "temperature": 0.7
+}'