{"id":21056805,"url":"https://github.com/omjavia/doc_query_genie","last_synced_at":"2025-04-30T09:45:39.711Z","repository":{"id":245298795,"uuid":"817760006","full_name":"OmJavia/Doc_Query_Genie","owner":"OmJavia","description":"Rag (Retreival Augmented Generation) Python solution with LLama3, LangChain, Ollama and ChromaDB in a Flask API based solution","archived":false,"fork":false,"pushed_at":"2025-02-08T09:17:29.000Z","size":1167,"stargazers_count":14,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-08T10:24:58.115Z","etag":null,"topics":["chromadb","langchain-python","llama3-meta-ai","ollama","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/OmJavia.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":"2024-06-20T11:37:43.000Z","updated_at":"2025-02-08T09:17:33.000Z","dependencies_parsed_at":null,"dependency_job_id":"6bdc698c-40b2-4dcf-97ef-8bdd1fa332cf","html_url":"https://github.com/OmJavia/Doc_Query_Genie","commit_stats":null,"previous_names":["omjavia/rag_llama3","omjavia/doc_query_genie"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OmJavia%2FDoc_Query_Genie","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OmJavia%2FDoc_Query_Genie/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OmJavia%2FDoc_Query_Genie/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OmJavia%2FDoc_Query_Genie/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/OmJavia","download_url":"https://codeload.github.com/OmJavia/Doc_Query_Genie/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243500789,"owners_count":20300785,"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":["chromadb","langchain-python","llama3-meta-ai","ollama","rag"],"created_at":"2024-11-19T16:54:11.093Z","updated_at":"2025-03-14T00:22:27.123Z","avatar_url":"https://github.com/OmJavia.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 📜 Doc_Query_Genie  \n\n🚀 **A Powerful Retrieval-Augmented Generation (RAG) API using LLama3, LangChain, Ollama, and ChromaDB**  \n\n![PDF_Searcher](https://github.com/user-attachments/assets/053688a0-63e7-4005-a258-69bc4200913a)\n\n\n## 🔍 About The Project  \n\n**Doc_Query_Genie** is a cutting-edge RAG-based Python solution that enhances information retrieval and generation using **Flask API**. With the power of **LLama3, LangChain, Ollama, and ChromaDB**, this tool provides a seamless experience for querying both general knowledge and custom document uploads.  \n\n### ✨ Key Features  \n\n✅ **AI-Powered Chat** – Use it like OpenAI's ChatGPT to ask any question.  \n✅ **PDF Intelligence** – Upload a PDF and ask context-specific questions.  \n✅ **Source Referencing** – Get precise answers with citations from the document (paragraph/line references).  \n✅ **Fast \u0026 Efficient** – Optimized for quick and reliable response generation.  \n✅ **Easy Integration** – Simple API setup to integrate with other applications.  \n\nThis project brings the best of **AI-driven retrieval** and **context-aware generation**, making it a versatile tool for researchers, students, and professionals.  \n\n## 🚀 Getting Started  \n\n1. **Clone the repository**  \n   ```sh  \n   git clone https://github.com/yourusername/Doc_Query_Genie.git  \n   cd Doc_Query_Genie  \n   ```  \n2. **Install dependencies**  \n   ```sh  \n   pip install -r requirements.txt  \n   ```  \n3. **Run the application**  \n   ```sh  \n   python app.py  \n   ```  \n4. **Use the API**  \n   - Access it at `http://127.0.0.1:5000/`  \n   - Upload PDFs and start querying  \n\n## 🤝 Contributing  \n\nWe welcome contributions! Feel free to submit issues or pull requests.  \n\n---  \n🌟 **If you find this project helpful, please consider giving it a star!**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fomjavia%2Fdoc_query_genie","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fomjavia%2Fdoc_query_genie","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fomjavia%2Fdoc_query_genie/lists"}