u/neopixel17

For the privacy-conscious self-hosters here — I wanted to share Fluent AI: Offline & Cloud LLM, an AI chat app I've been building that can run completely offline on your device.

The self-hosted angle:

• Truly local inference — download an AI model once (Gemma, Llama, Qwen, DeepSeek, etc.) and chat completely offline. Zero network calls. Your conversations exist only on your device. Decent inference token speeds on edge devices.
• Connect to your own Ollama instance — if you're already running Ollama on your home server, FluentAI is a full-featured mobile/desktop client with NDJSON streaming, multi-profile support, and AES-encrypted auth
• OpenAI-compatible servers — works with LM Studio, vLLM, LocalAI, or anything serving /v1/chat/completions
• OpenClaw gateway — connect to your self-hosted OpenClaw instance for managed API routing
• Knowledge bases stay local — import PDFs and documents, search them with on-device semantic embeddings (EmbeddingGemma 300M). No cloud processing
• AES-encrypted storage — API keys and auth tokens are encrypted, not stored in plain text preferences

What runs on-device:

• Inference: GGUF (llama.cpp), LiteRT (Android GPU/NPU)
• Embeddings: EmbeddingGemma 300M for RAG semantic search
• Code execution: run Python, JS, Bash, etc. locally on desktop
• All chat history and settings

Available on Android and soon to be released on iOS, macOS, Windows, Linux, and Web. Free core, optional one-time upgrade removes ads.

For the privacy-conscious self-hosters here — I wanted to share Fluent AI: Offline & Cloud LLM, an AI chat app I've been building that can run completely offline on your device.

The self-hosted angle:

• Truly local inference — download an AI model once (Gemma, Llama, Qwen, DeepSeek, etc.) and chat completely offline. Zero network calls. Your conversations exist only on your device. Decent inference token speeds on edge devices.
• Connect to your own Ollama instance — if you're already running Ollama on your home server, FluentAI is a full-featured mobile/desktop client with NDJSON streaming, multi-profile support, and AES-encrypted auth
• OpenAI-compatible servers — works with LM Studio, vLLM, LocalAI, or anything serving /v1/chat/completions
• OpenClaw gateway — connect to your self-hosted OpenClaw instance for managed API routing
• Knowledge bases stay local — import PDFs and documents, search them with on-device semantic embeddings (EmbeddingGemma 300M). No cloud processing
• AES-encrypted storage — API keys and auth tokens are encrypted, not stored in plain text preferences

What runs on-device:

• Inference: GGUF (llama.cpp), LiteRT (Android GPU/NPU)
• Embeddings: EmbeddingGemma 300M for RAG semantic search
• Code execution: run Python, JS, Bash, etc. locally on desktop
• All chat history and settings

Available on Android and soon to be released on iOS, macOS, Windows, Linux, and Web. Free core, optional one-time upgrade removes ads.

Bhai log, I built something that might actually help with prep.

The problem: ChatGPT needs a subscription. Free alternatives give garbage answers for JEE/NEET. And most AI apps need constant internet — useless in hostels with bad WiFi.

The solution: Vidya + FluentAI

Vidya is an AI model fine-tuned on NCERT (Classes 6-12), IIT-JEE (Mains + Advanced), and NEET content. FluentAI is the app that runs it directly on your phone with GPU acceleration — no internet needed after download available on Google play store.

Three model sizes:

• Vidya 4B (2.7 GB) — sweet spot for most phones
• Vidya 9B (5.6 GB) — best quality, needs 8+ GB RAM

Why this beats ChatGPT for JEE/NEET prep:

• Fully offline — download Vidya inside FluentAI, use forever without internet
• Trained on Indian curriculum — knows NCERT, not American textbooks
• Step-by-step reasoning (4.5/5.0) — walks through solutions like a tutor
• Misconception correction (4.8/5.0) — catches and corrects your wrong fundamentals
• Hindi/Hinglish support — ask in whatever language you think in
• Free and open source — no "you've reached your limit" during exam season

FluentAI also gives you:

• Cloud AI access (Claude, GPT-4, Gemini) when you need heavier models
• Ollama server support if you have a PC/laptop setup
• Voice mode — ask questions hands-free while revising
• Knowledge bases — import your notes as PDFs and chat with them
• Built-in benchmarking to test model speed on your phone

Quality scores (Vidya 9B): Overall 4.6/5.0 | Misconception handling 4.9/5.0 | Step-by-step 4.7/5.0

Try asking:

• "Explain Newton's third law with a JEE-level numerical"
• "I think centripetal force is a real force — am I right?"
• "Solve: A ball thrown vertically upward at 20 m/s. Find max height. (g = 10 m/s²)"

What subjects would you want Vidya to be better at?

For the privacy-conscious self-hosters here — I wanted to share Fluent AI: Offline & Cloud LLM, an AI chat app I've been building that can run completely offline on your device.

The self-hosted angle:

• Truly local inference — download an AI model once (Gemma, Llama, Qwen, DeepSeek, etc.) and chat completely offline. Zero network calls. Your conversations exist only on your device. Decent inference token speeds on edge devices.
• Connect to your own Ollama instance — if you're already running Ollama on your home server, FluentAI is a full-featured mobile/desktop client with NDJSON streaming, multi-profile support, and AES-encrypted auth
• OpenAI-compatible servers — works with LM Studio, vLLM, LocalAI, or anything serving /v1/chat/completions
• OpenClaw gateway — connect to your self-hosted OpenClaw instance for managed API routing
• Knowledge bases stay local — import PDFs and documents, search them with on-device semantic embeddings (EmbeddingGemma 300M). No cloud processing
• AES-encrypted storage — API keys and auth tokens are encrypted, not stored in plain text preferences

What runs on-device:

• Inference: GGUF (llama.cpp), LiteRT (Android GPU/NPU)
• Embeddings: EmbeddingGemma 300M for RAG semantic search
• Code execution: run Python, JS, Bash, etc. locally on desktop
• All chat history and settings

Available on Android and soon to be released on iOS, macOS, Windows, Linux, and Web. Free core, optional one-time upgrade removes ads.

After a couple of years of work, I wanted to share FluentAI — an AI chat app I built in Flutter.

The idea started because I wanted to chat with AI models on my phone without sending my data to anyone's servers. It grew into a full-featured client that supports local on-device models, Ollama servers, and cloud providers like Claude, GPT-4, and Gemini.

What I'm most proud of:

• It runs real LLMs on your phone with GPU acceleration — not a toy demo, actual usable inference
• Three separate native inference engines (llama.cpp, Google LiteRT, Apple MLX) behind one unified interface
• An agent system that can chain multiple tool calls together, and it works even on small on-device models thanks to progressive context compaction
• Knowledge bases where you can import your documents and chat with them — all embeddings run on-device
• It runs on every platform from a single codebase. To be released soon to iOS, macOS, Windows, Linux.

Available on Android (Play Store). Free to use.