{"id":23992767,"url":"https://github.com/ksingh66/rideinsight","last_synced_at":"2026-05-04T00:35:00.971Z","repository":{"id":269754112,"uuid":"908053213","full_name":"ksingh66/RideInsight","owner":"ksingh66","description":"This is both a website and a standalone chatbot that is capable of taking CSV's and analyzing them to answer user questions.","archived":false,"fork":false,"pushed_at":"2025-01-08T05:52:23.000Z","size":521,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-25T06:15:32.465Z","etag":null,"topics":["ai","chatbot","csv","django-application","groq","groq-api","langchain","llama3","pinecone"],"latest_commit_sha":null,"homepage":"","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/ksingh66.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":"2024-12-25T02:01:50.000Z","updated_at":"2025-01-08T05:52:26.000Z","dependencies_parsed_at":"2024-12-29T23:17:45.198Z","dependency_job_id":"02e2475d-347a-4cf3-9a4d-8324146b2e63","html_url":"https://github.com/ksingh66/RideInsight","commit_stats":null,"previous_names":["ksingh66/ragbot","ksingh66/rideinsight"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksingh66%2FRideInsight","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksingh66%2FRideInsight/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksingh66%2FRideInsight/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksingh66%2FRideInsight/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ksingh66","download_url":"https://codeload.github.com/ksingh66/RideInsight/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240612553,"owners_count":19829027,"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":["ai","chatbot","csv","django-application","groq","groq-api","langchain","llama3","pinecone"],"created_at":"2025-01-07T20:17:55.638Z","updated_at":"2026-05-04T00:35:00.938Z","avatar_url":"https://github.com/ksingh66.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# RAG Chatbot for Ride Records Analytics\n\nThis project builds a **Retrieval-Augmented Generation (RAG) chatbot** that allows users to query ride records from a CSV (or text) file. The chatbot utilizes advanced natural language processing (NLP) and retrieval techniques to provide analytical insights based on the ride data, such as identifying top-performing chauffeurs, analyzing earnings over time, and answering other business-related questions.\n\nThe chatbot integrates **Pinecone** for vector storage and retrieval, **LangChain** for RAG workflows, and **Groq** for AI-based query processing.\n\nThe goal is to enable users to ask complex questions related to the ride data and receive insightful answers, including visualizations like graphs, trend analysis, and more.\n## To use\n- add 'rag_text.txt' in the same directory as main.py to add files to your vector storage.\n- add 'bookings.csv' in the same directory as main.py to analyze csv files and ask the chatbot questions about your csv.\n## Features\n\n### Current Features\n- **CSV/Text Parsing and Querying**: The chatbot can load and process ride data from `.txt` files, containing details such as `Booking#`, `Chauffeur`, `Price`, `Date`, etc.\n- **RAG-based Query Responses**: The chatbot uses **LangChain** and **Pinecone** for context retrieval and to answer user queries dynamically.\n  - Examples include:\n    - \"Who made the most money?\"\n    - \"How many rides did Chauffeur X complete last month?\"\n    - \"What is the total earnings for Chauffeur X?\"\n- **Data Retrieval**: The chatbot uses **Pinecone**'s vector search to retrieve relevant context from a seperate vector storage and then uses pandas to generate a summary of a CSV , then it generates answers using a **Groq** model through **LangChain**.\n- **Flexible Data Input**: Ability to load ride records in text format and index them for later querying.\n\n### Planned Improvements\n## Top priority improvements\n- Ride chat and Insight chat; Insight chat looks at multiple CSVs to perfrom a big picture analysis.\n- Add most earned and least earned rides for each chauffeur.\n- Add busiest to least busy days.\n- Account for other CSV's that are not Transportation related; a general CSV analyzing AI.\n- Make UI more interactive.\n## Second priority improvements\n- **Dynamic Graphing and Visualizations**: Integrating libraries like **Plotly** or **Matplotlib** to visualize ride trends, chauffeur earnings, and other key metrics.\n\n### Technologies Used\n- **Python**: Primary language for backend logic.\n- **LangChain**: Framework for building RAG (Retrieval-Augmented Generation) workflows.\n- **Pinecone**: Vector database for efficient document search and retrieval.\n- **Groq (via LangChain)**: AI model for processing queries and generating responses.\n- **Sentence-Transformers**: Used to generate embeddings for the ride records to store in Pinecone.\n- **HuggingFaceEmbeddings**: For creating embeddings with HuggingFace models.\n- **Plotly / Matplotlib** (future): For generating dynamic trend graphs and charts.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksingh66%2Frideinsight","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fksingh66%2Frideinsight","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksingh66%2Frideinsight/lists"}