Offline Curriculum-Focused AI Chatbot -- 2
Budget: $30 – $250 USD
Project Title: Custom Offline AI Educational Chatbot (Curriculum-Based RAG)
Project Overview
I am looking for a developer to create a customized AI chatbot designed for students. The primary goal is to provide a "tutor in a box" that contains a vast knowledge base of specific educational curricula (textbooks, PDFs, and related materials).
Critical Requirement: The system must function entirely offline after the initial setup, allowing students in areas with no internet access to interact with the AI and receive accurate answers based on the uploaded curriculum.
Key Features & Requirements
* Offline Functionality: The chatbot must run on local hardware (e.g., a laptop, Raspberry Pi, or a high-end tablet) without needing an internet connection.
* Custom Knowledge Base (RAG): I will provide a large volume of PDFs, textbooks, and curriculum documents. The developer must implement a Retrieval-Augmented Generation (RAG) system to ensure the AI answers strictly based on this material.
* Local LLM Integration: Use efficient open-source models (like Llama 3, Mistral, or Gemma) that are optimized for local use (quantized versions).
* User Interface: A simple, student-friendly interface (Web-based local UI or Desktop App) where students can type questions and get instant feedback.
* Scalability: The ability to easily add or update the curriculum folders.
Technical Preferences (Suggested)
* Backend: Python (LangChain or LlamaIndex)
* Model Management: Ollama, LocalAI, or GPT4All
* Vector Database: ChromaDB or FAISS (must be local/persistent)
* Frontend: Streamlit, Gradio, or a lightweight React app
Ideal Candidate
* Experience with Local Large Language Models (LLMs).
* Proven track record building RAG pipelines.
* Familiarity with hardware limitations for offline AI.
* Experience in the EdTech space is a plus.
Tips for your post:
* Hardware: Decide what the students will use (e.g., "It must run on a laptop with 8GB RAM"). Mention this in the post so the developer knows how much to "shrink" the AI.
* Privacy: Mention that offline AI is great for student privacy, as no data leaves the device.
* Milestones: Break the project into two parts:
* Milestone 1: Building the offline engine and testing it with one textbook.
* Milestone 2: Optimizing the interface and loading the full curriculum.
Would you like me to help you draft the specific "System Instructions" (the rules the AI should follow) for the students once you find a developer?
Project Overview
I am looking for a developer to create a customized AI chatbot designed for students. The primary goal is to provide a "tutor in a box" that contains a vast knowledge base of specific educational curricula (textbooks, PDFs, and related materials).
Critical Requirement: The system must function entirely offline after the initial setup, allowing students in areas with no internet access to interact with the AI and receive accurate answers based on the uploaded curriculum.
Key Features & Requirements
* Offline Functionality: The chatbot must run on local hardware (e.g., a laptop, Raspberry Pi, or a high-end tablet) without needing an internet connection.
* Custom Knowledge Base (RAG): I will provide a large volume of PDFs, textbooks, and curriculum documents. The developer must implement a Retrieval-Augmented Generation (RAG) system to ensure the AI answers strictly based on this material.
* Local LLM Integration: Use efficient open-source models (like Llama 3, Mistral, or Gemma) that are optimized for local use (quantized versions).
* User Interface: A simple, student-friendly interface (Web-based local UI or Desktop App) where students can type questions and get instant feedback.
* Scalability: The ability to easily add or update the curriculum folders.
Technical Preferences (Suggested)
* Backend: Python (LangChain or LlamaIndex)
* Model Management: Ollama, LocalAI, or GPT4All
* Vector Database: ChromaDB or FAISS (must be local/persistent)
* Frontend: Streamlit, Gradio, or a lightweight React app
Ideal Candidate
* Experience with Local Large Language Models (LLMs).
* Proven track record building RAG pipelines.
* Familiarity with hardware limitations for offline AI.
* Experience in the EdTech space is a plus.
Tips for your post:
* Hardware: Decide what the students will use (e.g., "It must run on a laptop with 8GB RAM"). Mention this in the post so the developer knows how much to "shrink" the AI.
* Privacy: Mention that offline AI is great for student privacy, as no data leaves the device.
* Milestones: Break the project into two parts:
* Milestone 1: Building the offline engine and testing it with one textbook.
* Milestone 2: Optimizing the interface and loading the full curriculum.
Would you like me to help you draft the specific "System Instructions" (the rules the AI should follow) for the students once you find a developer?