{"id":25541187,"url":"https://github.com/vancenceho/simple-rag-app","last_synced_at":"2026-04-28T18:05:45.247Z","repository":{"id":276847077,"uuid":"858642441","full_name":"vancenceho/simple-rag-app","owner":"vancenceho","description":"A simple Retrieval-Augmented Generation (RAG) web application chatbot called Raggy 🤖","archived":false,"fork":false,"pushed_at":"2025-02-10T18:38:43.000Z","size":4664,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-30T03:40:29.903Z","etag":null,"topics":["google-vertex-ai","langchain-python","llm","python3","rag-application","vertex-ai"],"latest_commit_sha":null,"homepage":"https://medium.com/@phinmaiyo/how-to-build-a-gui-using-gradio-for-machine-learning-models-7d8bcb341d6e","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/vancenceho.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2024-09-17T09:21:04.000Z","updated_at":"2025-02-10T18:38:46.000Z","dependencies_parsed_at":"2025-02-10T19:49:30.822Z","dependency_job_id":null,"html_url":"https://github.com/vancenceho/simple-rag-app","commit_stats":null,"previous_names":["vancenceho/simple-rag-app"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/vancenceho/simple-rag-app","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vancenceho%2Fsimple-rag-app","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vancenceho%2Fsimple-rag-app/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vancenceho%2Fsimple-rag-app/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vancenceho%2Fsimple-rag-app/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vancenceho","download_url":"https://codeload.github.com/vancenceho/simple-rag-app/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vancenceho%2Fsimple-rag-app/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32392361,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-28T14:34:11.604Z","status":"ssl_error","status_checked_at":"2026-04-28T14:32:37.009Z","response_time":56,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["google-vertex-ai","langchain-python","llm","python3","rag-application","vertex-ai"],"created_at":"2025-02-20T06:30:10.326Z","updated_at":"2026-04-28T18:05:45.228Z","avatar_url":"https://github.com/vancenceho.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Simple Retrieval-Augmented Generation (RAG) Application\n\n## :bulb: About \n\nThis application is a Retrieval-Augmented Generation (RAG) application using Google Cloud's Vertex AI and Wikipedia. It fetches, processes, and embeds documents to generate responses. Key features include fetching Wikipedia pages, collecting and formatting documents, initializing AI embeddings, and splitting text into chunks.\n\n## :rocket: Getting Started\n\n### Pre-requisites\n\n- [Python](https://www.python.org/)\n    \u003e preferably `version==3.12.5`\n- [Google Cloud](https://console.cloud.google.com/)\n    \u003e 1. With available credits  \n    \u003e 2. Project created\n    \u003e 3. Project Service API JSON key\n- [Git](https://git-scm.com/)\n- [pip](https://pypi.org/project/pip/)\n\n### Setup \n\n1. Clone the repository\n\n```zsh\ngit clone https://github.com/vancenceho/simple-rag-app.git\n```\n\n2. Navigate to project directory `\u003csimple-rag-app\u003e`\n\n```zsh\ncd \u003cCLONE_DIR\u003e/simple-rag-app\n```\n\n3. Create a virtual environment (**if you deem fit**)\n\n```zsh\npython -m venv venv\n\npython3 -m venv venv\n```\n\n4. Activate virtual environment (if you have done **Step 3**)\n\n```zsh\nsource .venv/bin/activate\n```\n\n3. Download the necessary packages\n\n```zsh\npip install -r requirements.txt\n```\n\n4. Modify `rag_app.py` for own credentials\n\n\u003e At line 64, insert the Project ID of your own Google Cloud Project which you should have created beforehand, but if you have not feel free to check out this [link](https://developers.google.com/workspace/guides/create-project) to create it now.\n\n```python\nPROJECT_ID = \"\u003cYOUR_OWN_PROJECT_ID\u003e\"\n```\n\n\u003e At line 65, insert the region which you have created your Google Cloud Project. Feel free to check out this [link](https://cloud.google.com/resource-manager/docs/creating-managing-projects#:~:text=Find%20the%20project%20name%2C%20number%2C%20and%20ID,-To%20interact%20with\u0026text=Go%20to%20the%20Welcome%20page%20in%20the%20Google%20Cloud%20console.\u0026text=From%20the%20project%20picker%20at,displayed%20in%20the%20project%20picker.) to find out where your Google Cloud Project reside in.\n\n```python\nREGION = \"\u003cPROJECT_REGION\u003e\"\n```\n\n\u003e At line 66, insert your Google Cloud Project Service API JSON key, which you can download from the Google Cloud Console. Feel free to check out this [link](https://developers.google.com/workspace/guides/create-credentials) as to how to obtain it.\n\n```python\nCREDS_PATH = \"\u003cSERVICE_API_JSON_KEY_PATH\u003e\"\n```\n\n### Launch\n\n1. Launch web-app `\u003cRAGGY\u003e`\n\n```zsh\npython app.py\n\npython3 app.py\n```\n\n\u003e Depends on which version of python you are currently using and whether it is alias-ed.\n\n2. Navigate to web-app by pressing `CTRL+Click` / `CMD+Click` on shown URL or enter IP address in preferred web browser\n\n```zsh\nhttp://127.0.0.1:7860\n```\n\nAn example of the terminal would look as followed: \n\n![img](./assets/setup_step5.png)\n\n3. Meet `RAGGY`, your personal AI tech chatbot! :robot:\n\nIf you've done the steps correctly, you should be able to meet **RAGGY** on your web browser as shown below.  \nFeel free to ask it about anything tech related! From programming languages, machine learning, artificial intelligence, and even natural language processing :) \n\n![img](./assets/raggy.png)\n\n## :pray: Acknowledgements\n\nThis application was a side project I did while I was learning about RAG and Large Language Models (**LLMs**) during my internship at **[Ollion](https://ollion.com/)** as a **Junior Data Science Intern** in \nFall 2024. \n\nAll content and forms of documentation are credited to:  \n\nCopyright \u0026copy; 2024 _Vancence Ho_ \u0026nbsp; | \u0026nbsp; **Junior Data Science Intern** \u0026nbsp; | \u0026nbsp; Data Insights \u0026nbsp; | \u0026nbsp; **Ollion**\n#\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvancenceho%2Fsimple-rag-app","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvancenceho%2Fsimple-rag-app","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvancenceho%2Fsimple-rag-app/lists"}