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Minipilot

Minipilot is a self-hosted web chatbot for uploading CSV data, creating a Redis Stack vector index, editing prompts, and asking questions in natural language. It uses Redis vector search in a RAG flow and OpenAI ChatGPT through the ChatCompletion API to generate responses.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Minipilot — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Minipilot when you want to run a local, container-based chatbot prototype over CSV data and can supply an OpenAI API key.

Who it is for

  • People building a chat interface for CSV datasets.
  • Teams exploring natural-language queries over searchable business data.
  • Developers prototyping a configurable RAG application with Redis and OpenAI.

Documented uses

  • Upload CSV data and create a searchable index.
  • Adjust system and user prompts for the chatbot.
  • Ask natural-language questions about indexed data.
Before you choose

Requirements & limits

The documented quickstart runs the application and Redis Stack in Docker containers on a laptop and requires an OpenAI API key. The repository is public under the MIT license.

  • Redis Stack handles vector storage and search; OpenAI ChatGPT generates responses through its ChatCompletion API.
  • The quickstart loads an IMDb movies dataset and exposes the chat interface on the local machine.
  • The repository provides separate installation, usage, API, and architecture documentation.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Start Minipilot with the bundled IMDb dataset

Build and start Minipilot and Redis Stack containers, then open the chatbot with the dataset loaded by the quickstart.

Before you start

  • Docker
  • An OpenAI API key

Steps

  1. Clone https://github.com/redis/minipilot.git and change into the minipilot directory.

  2. Set OPENAI_API_KEY in the shell to your OpenAI key.

  3. Run docker compose build --no-cache && docker compose up -d and wait for Redis to load the IMDb movies dataset.

  4. Open http://127.0.0.1:5007/ in a browser, adjust the prompt, and start chatting.

Expected outcome

A local Minipilot chat interface using the IMDb dataset loaded by the quickstart.

Guide limitations

  • The documented quickstart uses the IMDb movies dataset; the repository does not describe these steps as a workflow for importing a different CSV.
  • An invalid or expired OpenAI key must be corrected, then the Minipilot container restarted or rebuilt.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Vector search

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
MinipilotUpload CSV data and create a searchable index.Docker, Self-hosted, WebThe documented quickstart runs the application and Redis Stack in Docker containers on a laptop and requires an OpenAI API key. The repository is public under the MIT license.
Chatbot with PDF for Semantic SearchPrepare document content as embeddings and save it to a supported vector database.WebThe repository is identified as open source and publicly visible on GitHub.
AI LLM PlaygroundAsk questions about PDF documents through an assistant interface.Web
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
redis/minipilot · Official homepage title · retained in its source language
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