Sample Task: Quran-Based RAG Chatbot Test

@webmasters486

Hi there, I’ve carefully reviewed the requirements for your GenAI project and I’m confident that my expertise in building NLP pipelines using Hugging Face and LangChain can meet your expectations. My experience includes working with large language models (LLMs) for Retrieval-Augmented Generation (RAG), as well as fine-tuning models with custom datasets to enhance text generation. I’ve successfully completed similar projects where I applied these techniques in Python to build robust, client-specific solutions. I would love the opportunity to discuss how I can leverage my skills to develop a tailored solution for your project. Feel free to take a look at my portfolio to get a sense of the work I’ve done: Portfolio: https://www.freelancer.com/u/webmasters486/AI-automation Looking forward to hearing from you! Best regards, Muhammad Adil

@SamirBanna

Hello, I’m a Senior Software Engineer with extensive experience in Python automation and web scraping & C# WindowFormApp and WFP. I’ve carefully reviewed your requirements and I can deliver a reliable, production-ready solution — not a quick workaround. ✅ Clean and maintainable code ✅ Clear communication ✅ On-time delivery I’d be happy to discuss your project details and propose the best technical approach. Best regards, Samir

@chiragardeshna

Hi there, Strong alignment with this task comes from building strict RAG systems with grounded responses, controlled outputs, and zero-hallucination pipelines. Clear understanding of creating a Quran-based chatbot that retrieves only relevant verses, generates answers strictly from context, and includes proper Surah references. Hands-on expertise with Python, embeddings, vector search, and prompt control ensures accurate retrieval, clean API/UI demo, and enforceable “I don’t know” fallback logic. Risk is minimized through strict retrieval validation, response constraints, and evaluation checks to prevent hallucinations. Available to start immediately—can deliver working demo within 2–3 days with GitHub setup. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

@faviank1

Hello, Thank you for the opportunity to submit this bid for your project. I have carefully reviewed the sample task and am excited to present a focused, test-ready approach to build a Quran/Hadith-based RAG chatbot. I’ve designed a compact, 5-10 item dataset and a retriever-then-answer workflow that ensures answers come strictly from retrieved context, including the verse reference (Surah name + number). My past work includes lightweight ML backends with FastAPI and LangChain for precise retrieval, avoiding hallucinations and generic responses. My plan: ✓ Build a small FastAPI app with a simple UI/API for querying. ✓ Use a 5-10 verse/Hadith dataset, indexed in a vector store for fast retrieval. ✓ Implement a retrieval-then-answer loop: if relevant data exists, respond with evidence; else say "I don’t know". ✓ Return exact verse references in each answer and provide GitHub with setup docs. Would you like me to extend the dataset with additional sources (e.g., more Hadith collections) if the initial test passes, or keep it strictly Quran-verses for this demo? Best regards, Favian

@haseebsidd07

Hey , I just finished reading the job description and I see you are looking for someone experienced in Python, Machine Learning (ML), LangChain, Natural Language Processing, Vector Databases, Artificial Intelligence, Chatbot and FastAPI. This is something I can do. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: 1. These are all the requirements? If not, Please share more detailed requirements. 2. Do you currently have anything done for the job or it has to be done from scratch? 3. What is the timeline to get this done? Why Choose Me? 1. I have done more than 250 major projects. 2. I have not received a single bad feedback since the last 5-6 years. 3. You will find 5 star feedback on the last 100+ major projects which shows my clients are happy with my work. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) I will share with you my recent work in the private chat due to privacy concerns! Please start the chat to discuss it further. Regards, Haseeb,

@dmytrok83

Hello, As a seasoned full-stack and AI developer, I possess comprehensive experience in building intelligent and highly responsive systems such as the RAG AI Chatbot you're seeking to test. I specialize in leveraging advanced ML technologies, like Generative AI Development (OpenAI & ChatGPT, Anthropic & Claude, Mistral, Llama, LangChain), to develop incredibly accurate and context-based chatbot models. I reckon my work on projects akin to an AI-driven SAT/ACT prep platform and the Microsoft Dynamics 365-based internal company assistants equipped with custom RAG systems indicates my expertise in this field. Additionally, my proclivity for creating inclusive solutions prioritizing user-interaction aligns well with your project's scope. I recognize the importance of retrieving pertinent information while respecting context and delivering only relevant content. My deep understanding of NLP tools, knowledge bases, and AI-powered solutions will ensure that your chatbot responds appropriately by citing the exact reference (Surah name + number) for any relevant verse found. In case of lack of pertinent data, my solution would simply state "I don't know," without any generic answers or unwarranted assumptions. Lastly, adopting a collaborative approach, backed by thorough domain understanding and cutting-edge technical acumen learnt from working with clients from diverse industries including education, fitness and even entertainment. This ha Thanks!

@tejbirbhatia

Hi there! I noticed that you are looking for a developer to build a simple RAG-based chatbot using a small dataset of Quran verses or Hadith. I understand the importance of providing accurate and relevant responses based on the retrieved context, as well as the need for a working demo within a 2-3 day timeline. In a similar project, I developed a chatbot for a client that utilized a database of historical quotes to provide inspirational messages based on user queries. The system was designed to retrieve and display the most relevant quotes based on the user's input, ensuring a personalized and engaging experience. I have a question regarding the dataset for this project: Are there any specific verses or themes from the Quran or Hadith that you would like to prioritize for this chatbot? Looking forward to the opportunity to work on this project with you. Thanks, Tejbir Bhatia

@mainakc7

Hi, I noticed you get many customer queries online. I have built an AI chatbot that can automatically handle 70% of those queries and save your time. I created a quick demo for your business — would you like to see it?

@zongfeiz3

Hello! I can build your bot with all required features. I have created similar Telegram/Discord bots with custom commands and API integrations using Python. Approach: 1) Set up framework, 2) Implement commands, 3) Test thoroughly. Delivery: 3-5 days. What hosting environment do you prefer? I can have a prototype ready in 2-3 days. Let us discuss your requirements!

@ravikumarsingh1

This is a clean RAG use case—but the key is strict grounding so the model never answers outside retrieved context. I’ll build it properly, not just a demo that “looks right.” What I’ll deliver: Lightweight RAG pipeline (Python + FAISS/Chroma + OpenAI) Small dataset (Quran/Hadith with Surah + verse metadata) Retrieval-first flow → AI answers only from context Hard guardrails: No context → “I don’t know” Response must include verse reference Simple UI (Streamlit) or API (FastAPI) Quality focus: Tight prompt design to prevent hallucination Top-k retrieval tuning for relevance Clean, modular code (easy to scale later) Deliverables: GitHub repo with setup steps Working demo (UI/API) Clear instructions to run locally Timeline: 2 days I’ve built similar RAG systems where correctness matters more than creativity—this will behave reliably.

@AyushG225

Hi, I’d like to take up this test project and can deliver a reliable RAG-based chatbot within 2–3 days. I have hands-on experience building GenAI systems with RAG pipelines. At Bizora Inc, I’ve worked with vector databases, LLM orchestration (LangGraph, LlamaIndex), and evaluation tools like RAGAS—ensuring responses are strictly grounded and hallucination-free. I also bring 3+ years of MERN stack experience, so I can quickly deliver either: A simple React-based chatbot UI, or A clean Node.js REST API My approach: • Structure 5–10 Quran verses/Hadith with proper references • Use FAISS (or similar) for semantic retrieval • Build a strict RAG pipeline: Query → retrieve relevant verses Pass ONLY retrieved context to LLM If no match → return “I don’t know” • Ensure responses include exact verse references and remain fully grounded Delivery: Clean GitHub repo Setup instructions (README) Optional demo deployment I can start immediately and ensure a clean, production-ready implementation. Best regards, Ayush Gupta

@karanpratapsin12

Hello, I reviewed your test task for building a RAG-based chatbot with strict context grounding and no hallucination. I have experience working with retrieval-based AI systems using vector search and controlled response generation. I can build a lightweight RAG pipeline using Python (FastAPI) with a small dataset of Quran verses/Hadith, embedded into a vector database (FAISS or similar). When a user asks a question, the system will retrieve the most relevant verses and pass only that context to the LLM, ensuring responses are strictly grounded. The response will always include proper references (Surah name + number), and if no relevant context is found, the system will return “I don’t know” as required. I will also enforce prompt constraints to prevent hallucination. I can deliver a working demo (API or simple UI), clean GitHub repository with setup instructions, and modular code so it can scale into your full project later. The task can be completed within your 2–3 day timeline.