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Developer builds free portfolio chatbot with Gemini Flash and Supabase

A developer has created a portfolio chatbot using Google's Gemini 1.5 Flash model and Supabase's pgvector for its free tier capabilities. This setup allows the chatbot to answer questions about the developer's projects and experience without incurring any costs. The architecture leverages Gemini's free tier for LLM and embeddings, Supabase for vector storage, and Langfuse for observability, all hosted on Vercel's free tier. AI

IMPACT Demonstrates cost-effective AI application development, enabling personalized chatbots without significant infrastructure investment.

RANK_REASON The article describes the creation of a specific application (a portfolio chatbot) using existing AI models and services, rather than a new model release or significant industry event.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Rahul Gehlot ·

    How to Build a Portfolio Chatbot With RAG on the Free Tier

    <blockquote> <p><em>Gemini Flash + Supabase pgvector + Langfuse = a fully functional RAG chatbot with observability that costs exactly zero dollars.</em></p> </blockquote> <h2> The Thesis </h2> <p>I wanted a chatbot on my portfolio that could answer questions about my projects, s…