Building a Privacy-First AI Companion with Next.js, FastAPI and Ollama
Most AI applications send your conversations to a cloud LLM. I wanted to experiment with a different approach: What if an AI companion could run entirely on your own machine? That idea led me to build MindMirror — an open-source AI companion for emotional reflection that supports local LLMs through Ollama, removing the requirement for paid AI APIs. GitHub:…
Building a privacy-focused AI companion using Next.js, FastAPI, and Ollama is the focus of MindMirror, an open-source project. The application enables users to engage in journaling and receive AI-powered reflection on their emotions, thought patterns, and cognitive distortions. MindMirror combines journaling with AI analysis to provide growth insights, voice journaling, check-in reminders, and more.
The primary motivation behind MindMirror is to offer a private space for reflection without the need for paid AI APIs, as most AI applications send user conversations to cloud LLMs, compromising user privacy. The project leverages local LLMs, open-source components, and user control over data to create a secure and personalized experience.
MindMirror is constructed using Next.js for the frontend, FastAPI for the backend, PostgreSQL for the database, and Ollama for managing local LLMs. The application architecture is streamlined, with user input entering the system, passing through Next.js, FastAPI, Ollama, and other AI components, and finally generating journal entries.
Voice input, facilitated by Whisper, enhances the user experience by making journaling more natural. Reflections are guided by CBT-style patterns, ensuring a structured and insightful interaction. To set up MindMirror locally, users can clone the repository, install Ollama, and run the application using Docker Compose. The local deployment allows for the AI to run without relying on paid APIs.
MindMirror's development has provided valuable insights into local LLMs, privacy as a product feature, prompt design, and the complexities of full-stack AI applications. Future developments include improved visualization of emotional trends, support for additional local models, advanced voice interactions, and a plugin ecosystem.
The open-source nature of MindMirror encourages collaboration, contribution, and feedback from developers interested in local AI, privacy-focused applications, open-source projects, and full-stack AI systems.
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