Code Snippet Generator

Introduction

This repository contains a code snippet generator that utilizes the OpenAI API and interacts with a PostgreSQL database. Follow the instructions below to set up and run the application locally.

Features that are part of this code generation repository are:

• Web Interface for Code Generation
• Feedback Loop for Improvement
• Custom LLM Integration (Llama2 Locally Deployment using Ollama)
• Containerization of Flask Web App and PostgreSQL DB
• Prompt Security
• Snippet Management
• Snippet Testing System Using Exec

Getting Started

Setting Up Environment Variables

1. Create an .env file in the root directory of the project.

2. Add the following configurations to the .env file:

   OPEN_AI_API=<Insert Your OpenAI API Key>
   DB_HOST="localhost"
   DB_PORT="5432"
   DB_USER="postgres"
   DB_PASSWORD="password"
   DB_DATABASE="code_snippet"
   

Installing Ollama Library and Running Llama2 Locally

To install the Ollama library and run the Llama2 model locally, follow these steps:

1. Run the command below to download and install Ollama:

   curl -fsSL https://ollama.com/install.sh | sh

2. Once the installation is complete, run the Llama2 model using the command:

   ollama run llama2

3. Verify that the model is deployed by testing it using the API endpoint:

   curl http://localhost:11434/api/chat -d '{
     "model": "mistral",
     "messages": [
       { "role": "user", "content": "why is the sky blue?" }
     ]
   }'

Docker Commands

Running PostgreSQL Container

To run a PostgreSQL container to connect to the database, execute the following commands:

  ```bash
  sudo docker build -t my-postgres-image -f Dockerfile_postgres .
  sudo docker run -d --name my-postgres-container --restart always -p 5432:5432 -v postgres:/var/lib/postgresql/data my-postgres-image
  ```

Running Code Snippet Container

To run the code snippet container, use the following commands:

  ```bash
  sudo docker build -t code-snippet -f Dockerfile_code .
  sudo docker run -d -p 5001:5001 code-snippet
  ```

Running the Application

To run the application:

1. Install the required dependencies using:

   pip install -r requirements.txt

2. Start the application by running:

   python main.py

3. Visit http://localhost:5001/ in your web browser.
4. The application will start running. Select "GPT" to use the GPT model or "Custom LLM" to use a custom model.