Offline AI Is Actually Insane | Build a Local RAG App Fast | flutter python ollama
Offline AI Is Actually Insane | Build a Local RAG App Fast | flutter python ollama #flutter #ai #vectordatabase #python #ollama
Source Code & explanation : https://www.dahalniranjan.com.np/2026...
Build a Fully Offline AI App with Flutter, Python, and Ollama
Build an AI Chatbot in Flutter with ollama Locally - Step-by-Step Guide
In this video, we build a complete LOCAL AI-powered RAG (Retrieval-Augmented Generation) application that runs entirely on your own device — no cloud, no API keys, and no internet required.
What makes this insane?
✅ Fully Offline AI
✅ Zero API Costs
✅ Private & Secure
✅ Local Vector Database
✅ Flutter Frontend
✅ Python Backend
✅ Ollama-powered LLMs
We’ll use Ollama to run open-source language models directly on our computer and connect it with a Flutter app capable of uploading documents and chatting with AI locally.
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What You'll Learn
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• How to install and use Ollama
• Running Gemma 3 locally
• Building a Python backend for AI chat
• Creating a local RAG pipeline
• Document ingestion and vector storage
• Connecting Flutter with Python APIs
• Uploading documents into a vector database
• Retrieving relevant context for AI responses
• Running everything fully offline
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Tech Stack
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Frontend:
• Flutter
Backend:
• Python
• Flask/FastAPI (depending on your implementation)
AI:
• Ollama
• Gemma 3
RAG Components:
• Vector Database
• Embeddings
• Document Chunking
• Semantic Search
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Project Structure
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📄 app.py
Handles uploads, receives questions, communicates with Ollama, and sends responses back to Flutter.
📄 ingest.py
Processes documents by extracting text, chunking content, generating embeddings, and storing vectors.
📄 vectorstore.py
Manages the vector database and performs similarity searches for relevant information retrieval.
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Ollama Commands Used
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Install Ollama and verify installation:
ollama --version
Download model:
ollama pull gemma3:4b
Run model:
ollama run gemma3
Start Ollama server:
ollama serve
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Flutter Notes
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If you're using an emulator, everything should work directly.
If you're using a physical device, replace the localhost/host value with your computer’s local IP address.
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Features
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• Upload documents
• AI-powered question answering
• Local semantic search
• Offline knowledge retrieval
• Multi-file support
• Private AI assistant
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Why Local AI?
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Running AI locally gives you:
• Better privacy
• No monthly API bills
• Faster experimentation
• Full control over your data
This is the future of personal AI apps.
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If You Enjoyed This Video
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#flutter #ollama #localai #python #rag #ai #machinelearning #flutterdev #opensource #offlineai #llm #gemma #vectordatabase #generativeai