{"id":28814917,"url":"https://github.com/rajat25022005/rag_faq_chatbot","last_synced_at":"2026-04-10T01:02:25.672Z","repository":{"id":297730681,"uuid":"997733282","full_name":"Rajat25022005/RAG_faq_chatbot","owner":"Rajat25022005","description":"This project uses a Python backend and a vanilla JS frontend to create a private, local chatbot powered by a RAG architecture and Ollama.","archived":false,"fork":false,"pushed_at":"2025-06-07T04:32:16.000Z","size":7,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-18T16:04:55.579Z","etag":null,"topics":["chatbot","faiss","flask","js","llm","ml","ollama","python","rag"],"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/Rajat25022005.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,"zenodo":null}},"created_at":"2025-06-07T04:15:06.000Z","updated_at":"2025-06-07T04:40:59.000Z","dependencies_parsed_at":"2025-06-07T05:34:17.273Z","dependency_job_id":null,"html_url":"https://github.com/Rajat25022005/RAG_faq_chatbot","commit_stats":null,"previous_names":["rajat25022005/rag_faq_chatbot"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Rajat25022005/RAG_faq_chatbot","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rajat25022005%2FRAG_faq_chatbot","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rajat25022005%2FRAG_faq_chatbot/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rajat25022005%2FRAG_faq_chatbot/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rajat25022005%2FRAG_faq_chatbot/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Rajat25022005","download_url":"https://codeload.github.com/Rajat25022005/RAG_faq_chatbot/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Rajat25022005%2FRAG_faq_chatbot/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260586148,"owners_count":23032253,"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":["chatbot","faiss","flask","js","llm","ml","ollama","python","rag"],"created_at":"2025-06-18T16:03:16.003Z","updated_at":"2025-12-30T22:30:27.032Z","avatar_url":"https://github.com/Rajat25022005.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"RAG FAQ Chatbot (with Ollama)\nThis project uses a Retrieval-Augmented Generation (RAG) approach to create a chatbot that answers questions based on a provided list of FAQs. This version is configured to use Ollama to run the local Large Language Model.\n\nHow It Works\nBackend (Python/Flask):\n\nLoads your FAQs from faqs.json.\n\nUses sentence-transformers to create vector embeddings from the FAQs.\n\nBuilds a faiss-cpu index for fast similarity searching (the Retrieval step).\n\nWhen you ask a question, it finds the most relevant FAQ.\n\nIt then sends your question and the retrieved FAQ to your local Ollama model (e.g., gemma:2b).\n\nThe Ollama model generates a natural, conversational answer (the Generation step).\n\nFrontend (HTML/JS/CSS):\n\nProvides a simple chat UI in your browser.\n\nCommunicates with the backend to get chatbot responses.\n\nSetup Instructions\nStep 1: Set Up Ollama\nInstall Ollama: If you haven't already, download and install Ollama from ollama.com.\n\nPull a Model: Open your terminal and pull the model you want to use. For gemma:2b, run:\n\nollama pull gemma:2b\n\nOllama will automatically start a server in the background. You can check that it's running by visiting http://localhost:11434 in your browser.\n\nStep 2: Set Up the Backend\nCreate and Activate Virtual Environment:\nMake sure you are inside your backend directory and your Python virtual environment is active.\n\nmacOS/Linux: source venv/bin/activate\n\nWindows: venv\\Scripts\\activate\n\nInstall/Update Dependencies:\nThis version uses a new library for Ollama. Run the following command to install it:\n\npip install -r requirements.txt\n\nAdd Your FAQs:\nMake sure your backend/faqs.json file is populated with your own questions and answers.\n\nRun the Backend Server:\nIn the same terminal, run the Flask app:\n\npython app.py\n\nThe server will start on http://127.0.0.1:5001.\n\nStep 3: Launch the Frontend\nNavigate to the frontend directory.\n\nOpen index.html in your web browser.\n\nYou can now chat with your FAQ bot, powered by Ollama and Gemma!","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frajat25022005%2Frag_faq_chatbot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frajat25022005%2Frag_faq_chatbot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frajat25022005%2Frag_faq_chatbot/lists"}