CodeLlama Chat Api

The CodeLlama Chat Assistant is a project built on Flask and the CodeLlama AI model, designed to facilitate real-time chat interactions with an AI assistant. This project enables users to send chat messages and receive responses from the AI assistant.

Features

• Real-Time Chat Interaction: Engage in real-time chat interactions with the AI assistant by sending chat messages to the API.
• Response Streaming: Responses can be streamed as event flows, providing an efficient real-time chat experience if desired.
• Powered by CodeLlama AI: The project leverages the CodeLlama AI model to generate responses from the assistant, delivering an intelligent chat experience.

Getting Started

The following steps will guide you through setting up and running the project in your local environment.

1. Environment Setup

Ensure your environment meets the following requirements:

• Python 3.6 or higher
• Flask and other required Python libraries

You can install the necessary dependencies using the following command:

pip install -r requirements.txt

2. Install Prerequisite

Before running the project, you need to install the bitsandbytes library on Windows. You can install it using the following command:

python -m pip install bitsandbytes --prefer-binary --extra-index-url=https://jllllll.github.io/bitsandbytes-windows-webui

3. Configure the Model

Within the project, you'll need to configure the CodeLlama AI model. In the code, locate the following section to configure the model:

model_id = "codellama/CodeLlama-7b-Instruct-hf"
# ...

4. Launch the Project

In your terminal, use the following command to launch the Flask application:

python main.py

The application will run on the default host (usually localhost) and port (typically 5000). You can interact with the AI assistant by accessing http://localhost:5000.

Usage

Continue Integration

Type /config and change model config like ggml

Chatgpt Next Web

Change endpoint to http://localhost:5000

API Endpoints

POST /v1/chat/completions

Send a JSON request to this endpoint containing chat messages to interact with the AI assistant. The request body should include the following fields:

• messages: A list containing chat messages, each with role and content fields specifying the message's role and content.
• stream: A boolean indicating whether to return the response as an event stream.

The response will be returned in JSON format, containing the AI assistant's response.

Contribution

Feel free to raise issues, provide suggestions, and contribute code. If you encounter any issues or have suggestions for improvements, create an Issue to let us know.

License

This project is licensed under the MIT License.