{"id":27018952,"url":"https://github.com/nexckycort/rag-poc","last_synced_at":"2026-04-09T02:31:20.380Z","repository":{"id":286034487,"uuid":"960141550","full_name":"nexckycort/rag-poc","owner":"nexckycort","description":null,"archived":false,"fork":false,"pushed_at":"2025-04-04T00:03:17.000Z","size":18,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-09T18:05:48.358Z","etag":null,"topics":["fastapi","markdown","pinecone","python","rag","typescript","vector-database"],"latest_commit_sha":null,"homepage":"","language":"TypeScript","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/nexckycort.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":"2025-04-03T23:37:42.000Z","updated_at":"2025-04-04T00:04:33.000Z","dependencies_parsed_at":"2025-04-09T17:51:04.717Z","dependency_job_id":null,"html_url":"https://github.com/nexckycort/rag-poc","commit_stats":null,"previous_names":["nexckycort/rag"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/nexckycort/rag-poc","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nexckycort%2Frag-poc","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nexckycort%2Frag-poc/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nexckycort%2Frag-poc/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nexckycort%2Frag-poc/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nexckycort","download_url":"https://codeload.github.com/nexckycort/rag-poc/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nexckycort%2Frag-poc/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31582583,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-08T14:31:17.711Z","status":"online","status_checked_at":"2026-04-09T02:00:06.848Z","response_time":112,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["fastapi","markdown","pinecone","python","rag","typescript","vector-database"],"created_at":"2025-04-04T17:17:36.203Z","updated_at":"2026-04-09T02:31:20.374Z","avatar_url":"https://github.com/nexckycort.png","language":"TypeScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# RAG Proof of Concept\n\nThis project is a Proof of Concept (PoC) for a RAG (Retrieval-Augmented Generation) system that combines a vector database with a language model to answer questions based on stored information.\n\n## Technologies Used\n- **FastAPI** for the embedding server\n- **SentenceTransformers** with `all-MiniLM-L6-v2` for generating embeddings\n- **Pinecone** as the vector database\n- **TypeScript** for query processing\n\n## Installation and Setup\n\n### 1. Clone the Repository\n```sh\ngit clone https://github.com/nexckycort/rag-poc.git\ncd rag-poc\n```\n\n### 2. Install Monorepo Dependencies\n```sh\nbun install\n```\n\n### 3. Set Up the Embedding Server\n```sh\ncd packages/model-server\nbun create:venv  # Create virtual environment\nbun activate:venv  # Activate virtual environment\nbun pip:install  # Install dependencies\nbun dev  # Start server\n```\n\n### 4. Run Query Logic\n```sh\ncd packages/api-server\nbun dev  # Run query logic\n```\n\n## Usage\n1. **Add documents**: Files are processed and stored as embeddings in Pinecone.\n2. **Ask a question**: An embedding is generated from the user’s query, and relevant text is retrieved.\n3. **Generate answer**: A language model generates a response based on the retrieved context.\n\n## API Endpoints\n### Embedding Server (FastAPI)\n- `POST /embed` → Generates text embeddings\n- `POST /ask` → Queries the model\n\n## License\nThis project is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnexckycort%2Frag-poc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnexckycort%2Frag-poc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnexckycort%2Frag-poc/lists"}