{"id":16277846,"url":"https://github.com/itspreto/vectr8","last_synced_at":"2025-10-06T08:07:55.468Z","repository":{"id":240640594,"uuid":"803156637","full_name":"itsPreto/VECTR8","owner":"itsPreto","description":"Embed anything.","archived":false,"fork":false,"pushed_at":"2024-05-24T00:18:31.000Z","size":16952,"stargazers_count":29,"open_issues_count":6,"forks_count":4,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-01T21:48:31.092Z","etag":null,"topics":["embeddings","llms","vector-database","vector-database-embedding","vector-similarity-search"],"latest_commit_sha":null,"homepage":"https://github.com/itsPreto/VECTR8/blob/main/README.md","language":"JavaScript","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/itsPreto.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":"2024-05-20T07:16:35.000Z","updated_at":"2025-02-01T22:06:55.000Z","dependencies_parsed_at":"2024-10-27T11:09:44.350Z","dependency_job_id":null,"html_url":"https://github.com/itsPreto/VECTR8","commit_stats":null,"previous_names":["itspreto/vectr8"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/itsPreto/VECTR8","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itsPreto%2FVECTR8","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itsPreto%2FVECTR8/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itsPreto%2FVECTR8/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itsPreto%2FVECTR8/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/itsPreto","download_url":"https://codeload.github.com/itsPreto/VECTR8/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itsPreto%2FVECTR8/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278577929,"owners_count":26009703,"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","status":"online","status_checked_at":"2025-10-06T02:00:05.630Z","response_time":65,"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":["embeddings","llms","vector-database","vector-database-embedding","vector-similarity-search"],"created_at":"2024-10-10T18:56:33.578Z","updated_at":"2025-10-06T08:07:55.424Z","avatar_url":"https://github.com/itsPreto.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003eVECT.R8 (Vector Embeddings Creation, Transformation \u0026 Retrieval) 🚀\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"./src/assets/logo.png\" alt=\"logo\" /\u003e\n\u003c/p\u003e\n\n\u003ch3 align=\"center\"\u003e\n  A Web UI where you can upload CSV/JSON files, create vector embeddings, and query them. Soon, you'll be able to convert unstructured data to JSON/CSV using an integrated LLM.\n\u003c/h3\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/itsPreto/VECTR8/assets/45348368/200c084c-443b-4206-b88d-931c38cf40d6\" alt=\"VECTR8-demo-ezgif com-video-to-gif-converter\" /\u003e\n\u003c/p\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003cfont size=”1”\u003e\n  \u003cstrong font size=”1”\"\u003eProject under heavy/active development [may be] unstable. Embeddings and Query pages WIP ⚠️\u003c/strong\u003e\n  \u003c/font\u003e\n\u003c/div\u003e\n\n\u003ch2 align=\"center\"\u003eTable of Contents\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eSection\u003c/th\u003e\n      \u003cth\u003eLinks\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#prerequisites\"\u003ePrerequisites\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul style=\"list-style-type:none; padding: 0;\"\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#python-37\"\u003ePython 3.7+\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#flask\"\u003eFlask\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#flask-cors\"\u003eFlask-CORS\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#transformers\"\u003etransformers\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#torch\"\u003etorch\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#numpy\"\u003enumpy\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#pandas\"\u003epandas\u003c/a\u003e\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#installation\"\u003eInstallation\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#running-the-application\"\u003eRunning the Application\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#uploading-files-\"\u003eUploading Files 📂\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul style=\"list-style-type:none; padding: 0;\"\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#command-line\"\u003eCommand Line\u003c/a\u003e\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#previewing-data-\"\u003ePreviewing Data 🧐\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul style=\"list-style-type:none; padding: 0;\"\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#command-line-1\"\u003eCommand Line\u003c/a\u003e\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#creating-vector-embeddings-\"\u003eCreating Vector Embeddings 🧩\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul style=\"list-style-type:none; padding: 0;\"\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#command-line-2\"\u003eCommand Line\u003c/a\u003e\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#querying-the-vector-database-\"\u003eQuerying the Vector Database 🔍\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul style=\"list-style-type:none; padding: 0;\"\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#command-line-3\"\u003eCommand Line\u003c/a\u003e\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#managing-the-vector-database-\"\u003eManaging the Vector Database 🛠️\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul style=\"list-style-type:none; padding: 0;\"\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#command-line-4\"\u003eCommand Line\u003c/a\u003e\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#ui-walkthrough-\"\u003eUI Walkthrough 🎨\u003c/a\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul style=\"list-style-type:none; padding: 0;\"\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#uploading-files-1\"\u003eUploading Files\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#previewing-data-1\"\u003ePreviewing Data\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#creating-vector-embeddings-1\"\u003eCreating Vector Embeddings\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#querying-the-vector-database-1\"\u003eQuerying the Vector Database\u003c/a\u003e\u003c/li\u003e\n          \u003cli\u003e\u003ca href=\"https://github.com/itsPreto/VECTR8/blob/main/README.md#managing-the-vector-database-1\"\u003eManaging the Vector Database\u003c/a\u003e\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n\u003c/div\u003e\n\n-----\n\n\u003ch2 align=\"center\"\u003ePrerequisites\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eRequirement\u003c/th\u003e\n      \u003cth\u003eDescription\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cimg src=\"https://img.icons8.com/color/24/000000/python.png\" alt=\"Python\"\u003e \u003cstrong\u003ePython 3.7+\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003eThe application requires Python 3.7 or higher to leverage modern libraries and syntax.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cimg src=\"https://img.icons8.com/color/24/000000/chemical-plant.png\" alt=\"flask icon\"\u003e \u003cstrong\u003eFlask\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003eEssential for running embedding models. Utilized by transformers.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cimg src=\"https://img.icons8.com/color/24/000000/globe.png\" alt=\"Flask-CORS\"\u003e \u003cstrong\u003eFlask-CORS\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003eEnables CORS for frontend-backend communication.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cimg src=\"https://img.icons8.com/color/24/000000/robot-2.png\" alt=\"transformers\"\u003e \u003cstrong\u003etransformers\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003eUsed for creating vector embeddings with pre-trained models.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cimg src=\"https://img.icons8.com/color/24/000000/fire-element.png\" alt=\"fire icon\"\u003e \u003cstrong\u003etorch\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003eEssential for running embedding models. Utilized by transformers.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cimg src=\"https://img.icons8.com/color/24/000000/calculator.png\" alt=\"numpy\"\u003e \u003cstrong\u003enumpy\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003eHandles arrays and mathematical operations. Used throughout the application.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cimg src=\"https://img.icons8.com/color/24/000000/data-sheet.png\" alt=\"pandas\"\u003e \u003cstrong\u003epandas\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003eProcesses CSV and JSON files. Utilized throughout the application.\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2 align=\"center\"\u003eInstallation\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eStep\u003c/th\u003e\n      \u003cth\u003eInstructions\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eClone the repository\u003c/td\u003e\n      \u003ctd\u003e\u003cpre\u003e\u003ccode\u003egit clone https://github.com/itsPreto/VECTR8.git\ncd VECTR8\u003c/code\u003e\u003c/pre\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eInstall the required packages\u003c/td\u003e\n      \u003ctd\u003e\u003cpre\u003e\u003ccode\u003epip install -r requirements.txt\u003c/code\u003e\u003c/pre\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n\u003c/div\u003e\n\n\u003ch2 align=\"center\"\u003eRunning the Application\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eStep\u003c/th\u003e\n      \u003cth\u003eInstructions\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eStart the Flask server\u003c/td\u003e\n      \u003ctd\u003e\u003cpre\u003e\u003ccode\u003epython3 rag.py\u003c/code\u003e\u003c/pre\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eAutomatically launch React frontend\u003c/td\u003e\n      \u003ctd\u003eThe Python endpoint will launch the React frontend in a separate subprocess.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eOpen your web browser\u003c/td\u003e\n      \u003ctd\u003eNavigate to \u003ccode\u003ehttp://127.0.0.1:4000\u003c/code\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n\u003c/div\u003e\n\n\u003ch2 align=\"center\"\u003eUploading Files 📂\u003c/h2\u003e\n\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eStep\u003c/th\u003e\n      \u003cth\u003eInstructions\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eDrag and Drop a File\u003c/td\u003e\n      \u003ctd\u003eDrag and drop a CSV or JSON file into the upload area or click to select a file from your computer.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eView Uploaded File Information\u003c/td\u003e\n      \u003ctd\u003eOnce uploaded, the file information such as name and size will be displayed.\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n  \u003ch3\u003eCommand Line\u003c/h3\u003e\n  \u003cp\u003eTo upload a file using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X POST -F 'file=@/path/to/your/file.csv' http://127.0.0.1:4000/upload_file\u003c/code\u003e\u003c/pre\u003e\n\u003c/div\u003e\n\n\u003ch2 align=\"center\"\u003ePreviewing Data 🧐\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eStep\u003c/th\u003e\n      \u003cth\u003eInstructions\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eSelect Embedding Keys\u003c/td\u003e\n      \u003ctd\u003eAfter uploading a file, select the keys (columns) you want to include in the embeddings.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003ePreview Document\u003c/td\u003e\n      \u003ctd\u003eView a preview of the document created from the selected keys.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003ePreview Embeddings\u003c/td\u003e\n      \u003ctd\u003eView the generated embeddings and token count for the selected document.\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n  \u003ch3\u003eCommand Line\u003c/h3\u003e\n  \u003cp\u003eTo preview a file's keys using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X POST -H \"Content-Type: application/json\" -d '{\"file_path\":\"uploads/your-file.csv\"}' http://127.0.0.1:4000/preview_file\u003c/code\u003e\u003c/pre\u003e\n  \u003cp\u003eTo preview a document's embeddings using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X POST -H \"Content-Type: application/json\" -d '{\"file_path\":\"uploads/your-file.csv\", \"selected_keys\":[\"key1\", \"key2\"]}' http://127.0.0.1:4000/preview_document\u003c/code\u003e\u003c/pre\u003e\n\u003c/div\u003e\n\n\u003ch2 align=\"center\"\u003eCreating Vector Embeddings 🧩\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eStep\u003c/th\u003e\n      \u003cth\u003eInstructions\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eStart Embedding Creation\u003c/td\u003e\n      \u003ctd\u003eClick the \"Create Vector DB\" button to start the embedding creation process.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eView Progress\u003c/td\u003e\n      \u003ctd\u003eMonitor the progress of the embedding creation with a circular progress indicator. 📈\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n  \u003ch3\u003eCommand Line\u003c/h3\u003e\n  \u003cp\u003eTo create a vector database using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X POST -H \"Content-Type: application/json\" -d '{\"file_path\":\"uploads/your-file.csv\", \"selected_keys\":[\"key1\", \"key2\"]}' http://127.0.0.1:4000/create_vector_database\u003c/code\u003e\u003c/pre\u003e\n\u003c/div\u003e\n\n\u003ch2 align=\"center\"\u003eQuerying the Vector Database 🔍\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eStep\u003c/th\u003e\n      \u003cth\u003eInstructions\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eEnter Query\u003c/td\u003e\n      \u003ctd\u003eType your query into the input field.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eSelect Similarity Metric\u003c/td\u003e\n      \u003ctd\u003eChoose between cosine similarity or Euclidean distance.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eSubmit Query\u003c/td\u003e\n      \u003ctd\u003eClick the \"Submit\" button to query the vector database.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eView Results\u003c/td\u003e\n      \u003ctd\u003eInspect the results, which display the document, score, and a button to view detailed data.\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n  \u003ch3\u003eCommand Line\u003c/h3\u003e\n  \u003cp\u003eTo query the vector database using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X POST -H \"Content-Type: application/json\" -d '{\"query_text\":\"Your query text here\", \"similarity_metric\":\"cosine\"}' http://127.0.0.1:4000/query\u003c/code\u003e\u003c/pre\u003e\n\u003c/div\u003e\n\n\u003ch2 align=\"center\"\u003eManaging the Vector Database 🛠️\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eStep\u003c/th\u003e\n      \u003cth\u003eInstructions\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eBackup Database\u003c/td\u003e\n      \u003ctd\u003eClick the \"Backup Database\" button to create a backup of the current vector database.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eDelete Database\u003c/td\u003e\n      \u003ctd\u003eClick the \"Delete Database\" button to delete the current vector database.\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003eView Database Statistics\u003c/td\u003e\n      \u003ctd\u003eView statistics such as total documents and average vector length.\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n  \u003ch3\u003eCommand Line\u003c/h3\u003e\n  \u003cp\u003eTo check if the vector database exists using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X GET http://127.0.0.1:4000/check_vector_db\u003c/code\u003e\u003c/pre\u003e\n  \u003cp\u003eTo view database statistics using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X GET http://127.0.0.1:4000/db_stats\u003c/code\u003e\u003c/pre\u003e\n  \u003cp\u003eTo backup the database using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X POST http://127.0.0.1:4000/backup_db\u003c/code\u003e\u003c/pre\u003e\n  \u003cp\u003eTo delete the database using \u003ccode\u003ecurl\u003c/code\u003e:\u003c/p\u003e\n  \u003cpre\u003e\u003ccode\u003ecurl -X POST http://127.0.0.1:4000/delete_db\u003c/code\u003e\u003c/pre\u003e\n\u003c/div\u003e\n\n\u003ch2 align=\"center\"\u003eUI Walkthrough 🎨\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\n      \u003cth\u003eFeature\u003c/th\u003e\n      \u003cth\u003eDescription\u003c/th\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cstrong\u003eUploading Files\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul\u003e\n          \u003cli\u003eDrag and drop a file into the upload area or click to select a file.\u003c/li\u003e\n          \u003cli\u003eFile information will be displayed after a successful upload.\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cstrong\u003ePreviewing Data\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul\u003e\n          \u003cli\u003eSelect the keys you want to include in the embeddings.\u003c/li\u003e\n          \u003cli\u003eView a preview of the document and generated embeddings.\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cstrong\u003eCreating Vector Embeddings\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul\u003e\n          \u003cli\u003eClick the \"Create Vector DB\" button to start the embedding creation.\u003c/li\u003e\n          \u003cli\u003eMonitor the progress with the circular progress indicator.\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cstrong\u003eQuerying the Vector Database\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul\u003e\n          \u003cli\u003eEnter your query text and select a similarity metric.\u003c/li\u003e\n          \u003cli\u003eClick \"Submit\" to query the database and view the results.\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd\u003e\u003cstrong\u003eManaging the Vector Database\u003c/strong\u003e\u003c/td\u003e\n      \u003ctd\u003e\n        \u003cul\u003e\n          \u003cli\u003eBackup the database by clicking \"Backup Database\".\u003c/li\u003e\n          \u003cli\u003eDelete the database by clicking \"Delete Database\".\u003c/li\u003e\n          \u003cli\u003eView database statistics such as total documents and average vector length.\u003c/li\u003e\n        \u003c/ul\u003e\n      \u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/table\u003e\n\u003c/div\u003e\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fitspreto%2Fvectr8","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fitspreto%2Fvectr8","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fitspreto%2Fvectr8/lists"}