RAG Chatbot & “Ask AI” Web Widget

@OutsourceMan

⭐⭐⭐⭐⭐ CnELIndia and Raman Ladhani can successfully execute this project by following a clear step-by-step process: Google Sheets Data Conversion: We will start by converting the Google Sheets data into a structured vector database using Pinecone or Chroma, ensuring efficient retrieval and preventing hallucinations. We will also clean and preprocess the data for optimal performance. RAG Integration: Using LlamaIndex (preferred) or OpenAI, we will build the Retrieval-Augmented Generation (RAG) pipeline to ensure the chatbot responds accurately based solely on the provided data source. Chat Widget Development: A responsive, clean chat widget will be created using Streamlit or custom HTML/JS to embed into the landing page, integrating the RAG pipeline. Source Attribution: A “Show Sources” feature will be implemented to display relevant data from Google Sheets. Final Delivery: A fully working demo, code repository, and a simple landing page will be delivered. We’ll also provide a 60-minute walkthrough. With our expertise in Python, vector databases, and frontend development, this project will be delivered within the 7-10 day timeline and budget.

@softsolution2000

I have carefully reviewed the requirements for the RAG Chatbot & “Ask AI” Web Widget project and believe my skills in PHP, Python, Web Scraping, MySQL, and HTML align perfectly with your needs. The proposed budget can be adjusted after a detailed discussion of the project scope. I am confident and eager to get started on this project within your budget constraints. Please review my 15-year-old profile to see my extensive experience. Your satisfaction is my priority, and I am ready to begin working to demonstrate my dedication to this project. Looking forward to discussing the job details with you.

@ykarora26

As a Full Stack Developer with over a decade of expertise in Web and App Development, I believe I'm an excellent fit for your project. One of my core skills is Python, and this, combined with my extensive experience in building vector database and utilizing AI engines, gives me a solid foundation to create your desired RAG Chatbot. I can effectively integrate Google Sheets as your proprietary data source for answering user questions correctly and provide attributes to view the specific rows from the given table. Finally, let's talk budget and deadlines. My services are highly competitive at a rate that offers great value for what you're looking to achieve. Equally important is timing. Consistently delivering projects within stipulated schedules is one of my strongest suits. Given the stated timeline of 7-10 days for this project—providing a fully functional demo on a live web host with complete code repository and associated landing page isn't just feasible but guaranteed. Let's team up to bring your vision of an efficient RAG Chatbot & "Ask AI" Web Widget into reality!

@sunainawbst

✅ Lovable AI Expert | AI Development | AI Chatbot | Game Development ✅ Hi, Thank you for considering this opportunity! I bring extensive experience in implementing custom solutions powered by LLMs, conversational AI, and intelligent automation. Recently I have been working on Lovable AI for developing a gaming platform using it, complete with chat-based agent logic, expressive front-ends, and backend integrations. In other project, implemented a fully automated AI agent system for intelligent meeting creation using ElevenLabs Conversational AI and Gemini (via a custom agent brain). The flow integrates voice interaction, natural language processing, location precision, and frontend. Due to NDAs, links aren’t public—but once you open the chat, I’ll share live demos and walkthroughs. Whether you're building an internal assistant, a public-facing voice agent, or an integrated AI productivity tool, I can help bring your vision to life with robust, scalable architecture and a human-like user experience. I would love to connect and explore how we can contribute to your AI initiative. PS - Please pan the budget for now and discuss over chat. Regards,Srishti

@petermyvw

You can have me develop your AI chat it that sources answers exclusively from your Google Sheet. My approach would be to use PostgreSQL (and its PGVector extension) to store the bindings from your Google Sheet, while the AI to evaluate them would be OpenAI (or some other provider you prefer). The web application from which the user can access the chatbot will be on Django, a Python web server. An AI chatbot I helped modified & improved fairly recently was https://novik.ai. I believe that experience (and many others in my portfolio) makes me a suitable person to carry out this project. Feel free to start a text chat with me on freelancer.com in case you'd like to discuss details.

@ASirbescu

Hello, Building your RAG Chatbot and AI Widget utilizing Python, HTML, and Javascript technologies is where my specialized skillset shines brightest. As a Full-Stack Developer with a focus on backend development, I have specialized in creating powerful web applications, REST APIs and automation tools using Python - making me the perfect fit for this project. Additionally, I have honed strong abilities working with vector databases while also having experience building retrieval-augmented generation (RAG) pipelines. Moreover, my familiarity with Chroma, Pinecone, and Weaviate as local options for vector database setup combined with my use of Groq, LlamaIndex (which you prefer) or OpenAI for AI Engine Integration will enable me to effectively transform your Google Sheet data into a searchable, Answer fetching database. Furthermore, your Landing Page Development and source attribution requirements perfectly match my proficiency in HTML and basic JavaScript; I ensure both cleanliness and responsiveness for an optimum user experience. My expertise in web scraping also comes into play here as it proves to be an asset when ensuring all crucial information mentioned in key data columns is successfully attributed back to its original source. Additionally, basic privacy controls and exportable chat logs are well within my repertoire. Thanks!

@LiveExperts

Hello, With our diverse range of skills and vast experience in various domains, including Computer Science, Engineering, and Software Development, we are the perfect fit for your RAG Chatbot and "Ask AI" Web Widget project. Our team has specific expertise in Python, RAG pipelines (particularly LlamaIndex), Vector Databases, and Frontend Development (HTML/JS/React), which are precisely the skills you mention as requirements for this project. I would like to propose Chroma or Pinecone for vector database setup and Groq or our preferred option - LlamaIndex for AI Engine integration. Utilizing Streamlit for Chat Widget development seems optimal from your options. We will also ensure data privacy with no unnecessary third-party data sharing while providing a mobile-friendly design. Exportable chat logs will be available, and we'll provide a comprehensive handover of the project with a detailed 60-minute walkthrough call. Our commitment is to transform your idea into a highly functional reality with meticulous attention to detail. The result - a fully working demo on your designated landing page, a complete code repository, and most importantly, your satisfaction! Contact us today, and let's get started on this exciting project together! Thanks!

@corpmember29

I HAVE BUILT RAG CHATBOTS USING GOOGLE SHEETS AND VECTOR DATABASES FOR ACCURATE SOURCE-GROUNDED ANSWERS. Hello, I can develop a Retrieval-Augmented Generation (RAG) chatbot embedded as an “Ask AI” widget for your website, using your Google Sheets database as the sole knowledge source to prevent hallucinations. Core Features Convert Google Sheets data (1,000–2,000 rows) into a vector database (Chroma/Pinecone/Weaviate) Implement a fast, reliable RAG pipeline using LlamaIndex (or OpenAI if needed) Embed a responsive chat widget on a clean landing page (Streamlit, Tidio, or custom HTML/JS) Show sources functionality linking answers to titles, URLs, and summaries Mobile-friendly design and basic privacy protections Deliverables & Support Fully working live demo hosted on your landing page Complete, documented code repository 60-minute walkthrough call (recorded) 2 YEARS FREE ONGOING SUPPORT POST-LAUNCH for minor fixes or updates Timeline & Budget Estimated 7–10 days to delivery Budget: $400–$500 I can start immediately. Previous RAG chatbot demos and GitHub projects available upon request. This solution ensures accurate, fast, and fully source-attributed AI responses directly from your Sheets.

@khurshid040462

Hi there, I am excited about the opportunity to build your Retrieval-Augmented Generation (RAG) chatbot. With experience in developing AI-driven chatbots and expertise in Python, I am confident in transforming your Google Sheets data into an efficient, functional chat widget. My approach includes setting up a vector database using LlamaIndex, integrating a modern AI engine for swift responses, and developing a clean, user-friendly chat widget embedded on a dedicated landing page. I will ensure the implementation of source attribution, making it easy for users to trace responses back to the original Google Sheet data while incorporating mobile-friendly design and privacy controls. I propose to deliver a fully functional demo within 7 days and provide a comprehensive walkthrough call at project completion.

@anaya8777

Proposed stack: Python + LlamaIndex + ChromaDB + Groq/OpenAI, deployed via lightweight FastAPI backend and embedded JS widget. Includes source attribution, CSV chat logs, privacy-safe setup, and hosted demo landing page. Delivery in 7–9 days. Budget: $500 fixed. Ready to start immediately.

@dvcontact

Hello, Ever considered a tailored chatbot that exclusively utilizes your data for precise answers? I specialize in building efficient RAG chatbots that integrate seamlessly with Google Sheets, ensuring data privacy and accuracy. Let's connect to explore how I can help you create an impactful 'Ask AI' widget for your website. Best, Smith

@vishal1145

Your Google Sheets setup will break when you hit 2,000+ rows because vector search latency scales linearly without proper indexing. I've seen this pattern before - clients start with Sheets, then face 3-5 second response times that kill user engagement. Before building this, I need clarity on two things: What's your expected query volume per day (10 users or 1,000)? And are you planning to update the Google Sheet frequently, or is this a one-time data load? The answer changes whether we need real-time sync or a nightly batch process. Here's the architectural approach: - PYTHON + LLAMAINDEX: Build a RAG pipeline with semantic chunking that splits your long summaries into 512-token segments, preventing context loss when users ask specific questions about articles. - CHROMADB (LOCAL): Deploy a self-hosted vector store with HNSW indexing to keep query times under 200ms at 5,000 rows without paying Pinecone fees. - GROQ API: Use Llama 3.1 70B for sub-500ms inference speed - 10x faster than OpenAI for RAG tasks while maintaining answer quality. - SOURCE ATTRIBUTION: Implement metadata filtering that returns the exact row ID, title, and URL for every answer, with clickable links in the chat UI. - PHP LANDING PAGE: Since you mentioned PHP in the skills, I'll embed the chat widget using a lightweight iframe that loads the Streamlit backend asynchronously to avoid blocking page render. I bring 12+ years building production AI systems, including a RAG chatbot for a legal tech client that searches 50K case documents with 95% answer accuracy. The $400-$500 budget works if your Google Sheet structure is clean - messy data with inconsistent formatting adds 2-3 days of preprocessing. Let's schedule a 15-minute call to review your Sheet structure and confirm there aren't duplicate entries or encoding issues that'll cause retrieval failures.

@anayapallavi

I can build your RAG chatbot using LlamaIndex + Chroma (local vector DB) with OpenAI or Groq for fast responses. Google Sheets data will be embedded, indexed, and restricted strictly to your dataset (no external calls). I’ll deliver a clean mobile-friendly chat widget (custom HTML/JS) with “Show Sources,” live demo, full repo, and walkthrough. Timeline: 8–10 days. Budget: within $450.

@AZTURK1

Hi there, I understand you need a RAG chatbot using your Google Sheets data, embedded in a clean, responsive “Ask AI” widget. Leveraging my experience with RAG pipelines, vector databases, and frontend integration, I will deliver a fast, accurate chatbot that sources answers strictly from your proprietary data to avoid hallucinations. - Convert your sheet into a vector DB using Chroma or Weaviate for local, efficient searches - Integrate LlamaIndex AI engine for sophisticated RAG processing - Develop a mobile-friendly chat widget with source attribution tied to your Google Sheet rows - Provide a simple landing page hosting the widget, complete code repo, and a recorded 60-min walkthrough **Skills:** ✅ RAG pipeline development with LlamaIndex ✅ Vector databases: Chroma, Weaviate, Pinecone ✅ Frontend dev: HTML/JS responsive chat widget ✅ Python for backend integration and data processing ✅ Source attribution and privacy controls **Certificates:** ✅ Microsoft® Certified: MCSA | MCSE | MCT ✅ cPanel® & WHM Certified CWSA-2 I am ready to start immediately and will deliver this within 10 days for your budget. Which vector database do you prefer for hosting your Google Sheets data locally or in the cloud? Best regards,

@johnallenvillan1

Hi, I am experienced in AI chatbot development and Python programming. I will build a RAG chatbot from a Google Sheets database for your project. My solution includes setting up a vector database using Chroma, integrating the AI engine with Groq, and embedding a chat widget using custom HTML/JS. The 'Ask AI' web widget will display accurate answers sourced exclusively from your Google Sheets file. Ready to start work and deliver within 7-10 days. What's the next step?

@enervell

Hi there, I'm excited about your project to build a Retrieval-Augmented Generation (RAG) chatbot from your Google Sheets database. With over 5 years of experience in AI chatbot development and implementing RAG pipelines, I am confident in delivering a robust solution tailored to your needs. 1. **Vector Database Setup**: I will convert your Google Sheets data into a searchable vector database using Chroma, ensuring fast access and relevancy. 2. **AI Engine Integration**: Adopting LlamaIndex, I'll enhance the RAG pipeline for accurate responses exclusively from your proprietary data. 3. **Chat Widget Development**: A responsive and user-friendly chat widget will be embedded on a simple landing page, designed for optimal performance on mobile devices. 4. **Source Attribution**: Implementing a feature that shows the specific rows from the Google sheet will ensure transparency in user responses. I'm dedicated to using proven technologies like Python and HTML/JS to fulfill your requirements efficiently. I'm looking forward to collaborating with you to create a stellar user experience. Thanks,

@VianRey1

Sifting through thousands of rows in a Google Sheet for accurate answers is slow and risky, especially when you need users to trust that every response comes only from your own content. The frustration of hallucinated answers or irrelevant sources can undermine user confidence and the value of your data. You can expect a clean, fast “Ask AI” chat widget that always replies using your own Google Sheets data. Each answer will show exactly which rows and sources were used, so users know they’re getting reliable information. First, your Google Sheets content will be transformed into a private, searchable vector database using a free local solution. Next, the RAG chatbot pipeline will be set up with LlamaIndex to deliver fast, accurate answers. Finally, a responsive chat widget will be built and embedded on a simple landing page, including clear source attributions. What is your preferred tech stack for the landing page and widget?

@webmasters486

Hey, I’ve reviewed your project and understand you’re looking to build a secure RAG based “Ask AI” chatbot that answers strictly from your Google Sheets database, with zero external web access and clear source attribution. The focus will be on clean retrieval logic, fast responses, and a lightweight embedded widget hosted on a simple landing page. I can implement the pipeline using Python with LlamaIndex for orchestration, Chroma as a local vector database, and OpenAI or Groq for fast inference. Your Google Sheets data will be ingested, chunked, embedded, and indexed with metadata filtering to ensure answers cite exact rows. The chat widget can be built with Streamlit or a custom HTML and JS interface for a responsive single page experience with “Show sources,” exportable logs, and basic privacy controls. You’ll receive a live hosted demo, full source code, deployment scripts, and a recorded walkthrough. Estimated timeline is 7 to 10 days within your 400 to 500 budget. Let’s connect to finalize hosting and model selection. Best regards, Muhammad Adil Portfolio: https://www.freelancer.com/u/webmasters486

@dataspro

Nice to meet you , My name is Anthony Muñoz, I express my interest in working on your project after carefully reading the requirements and concluding that they match my area of knowledge and skills. I am currently the lead engineer for the IT agency DSPro and I have more than 10 years of experience in the field. I have successfully completed a large number of similar jobs and I consider your project to be a challenge in which I would like to work and be able to make it a reality. Please feel free to contact me, it will be my pleasure to help you. I greatly appreciate the time provided and I remain attentive to any questions or concerns. Greetings