{"id":18836727,"url":"https://github.com/eziodevio/rag-project","last_synced_at":"2026-02-22T02:04:22.626Z","repository":{"id":260347129,"uuid":"881024536","full_name":"EzioDEVio/RAG-project","owner":"EzioDEVio","description":"This project is a Retrieval-Augmented Generation (RAG) system that allows users to upload PDF documents and ask questions about the content, with responses generated using OpenAI's GPT model.","archived":false,"fork":false,"pushed_at":"2024-11-07T16:08:37.000Z","size":82,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-20T03:42:36.687Z","etag":null,"topics":["chatgpt","openai","pyhon","rag","streamlit"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/EzioDEVio.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-30T19:31:49.000Z","updated_at":"2024-11-11T00:28:35.000Z","dependencies_parsed_at":"2024-10-30T21:17:06.672Z","dependency_job_id":"63b4b3f0-c529-42bd-8c81-bd920b4a053d","html_url":"https://github.com/EzioDEVio/RAG-project","commit_stats":null,"previous_names":["eziodevio/rag-project"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EzioDEVio%2FRAG-project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EzioDEVio%2FRAG-project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EzioDEVio%2FRAG-project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EzioDEVio%2FRAG-project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EzioDEVio","download_url":"https://codeload.github.com/EzioDEVio/RAG-project/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239774326,"owners_count":19694700,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["chatgpt","openai","pyhon","rag","streamlit"],"created_at":"2024-11-08T02:31:38.799Z","updated_at":"2025-10-16T06:03:02.075Z","avatar_url":"https://github.com/EzioDEVio.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![CI Pipeline](https://github.com/EzioDEVio/RAG-project/actions/workflows/main.yaml/badge.svg)](https://github.com/EzioDEVio/RAG-project/actions/workflows/main.yaml)\n\n\n# EzioDevio RAG Project\n\nThis project is a Retrieval-Augmented Generation (RAG) system that allows users to upload PDF documents and ask questions about the content, with responses generated using OpenAI's GPT model.\n\n## Features\n\n- Upload PDF files and retrieve information from them.\n- Ask questions based on the uploaded documents.\n- Responses are generated in real-time using OpenAI’s `gpt-3.5-turbo` model.\n\n## Setup Instructions\n\n### Prerequisites\n\n- Python 3.8+\n- OpenAI API Key (instructions below on how to obtain one)\n- Docker (optional for containerization)\n\n### Installation\n\n1. **Clone the repository**:\n   ```bash\n   git clone https://github.com/EzioDEVio/RAG-project.git\n   cd RAG-project\n\n2. **Create and activate a virtual environment**:\n\n```bash\npython -m venv venv\nsource venv/bin/activate  # On Windows, use `venv\\Scripts\\activate`\n```\n## Project Directory Structure\n\n![Project Directory Structure](images/directory_structure.png)\n\n\u003e\u003e\u003e\u003e\u003e\u003e\u003e fe0da40 (Save local changes before rebase)\n\n\n1. **Install required packages**:\n\npip install -r requirements.txt\n\n\n4. **Set up environment variables**:\n\nCreate a .env file in the root of your project:\n```bash\nOPENAI_API_KEY=your_openai_api_key_here\n```\n\n5. **Get your OpenAI API Key**:\n\nGo to OpenAI API and create an API key.\nSave this key in the .env file as shown above.\n\n6. **Run the Application**:\n\n```bash\nstreamlit run app.py\n```\nor \n```bash\npython -m streamlit run app.py\n```\n\nThe app will start on http://localhost:8501.\n\n## Docker Instructions\n1. **Build the Docker Image**:\n\n```bash\ndocker build -t ezio_rag_app .\n```\n2. **Run the Docker Container**:\n\n```bash\ndocker run -p 8501:8501 --env-file .env ezio_rag_app\n```\n\u003e 💡 **Tip:** You can make notes more noticeable with emojis.\n\nIf you'd like to pass the API key directly as an environment variable when running the Docker container, you can omit the --env-file .env option and instead use the -e flag to specify the API key directly. Here’s how you can do it:\n\n```bash\ndocker run -p 8501:8501 -e OPENAI_API_KEY=your_openai_api_key_here ezio_rag_app\n```\n\n\n\u003e 🔥 **Important:** Don't forget to check your configuration settings!\n\n**Ensure that .env is listed in .gitignore to avoid exposing the API key in the repository**.\n**The app uses Streamlit for the UI and OpenAI for text generation**.\n\n\n## Python\nvenv/ pycache/\n\n## Environment variables\n.env\n\n## Streamlit cache\n.streamlit/\n\n## Docker\n*.dockerignore\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feziodevio%2Frag-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feziodevio%2Frag-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feziodevio%2Frag-project/lists"}