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Contextqa

ContextQA is a self-hostable LLM application for ingesting data sources and asking conversational questions about them through a browser interface or CLI-started service. It can return relevant sources with answers and supports streaming responses. Users can configure OpenAI or Google models, ChromaDB or Pinecone vector storage, retrieval chunk settings, and embedded or Redis-backed memory.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Contextqa — 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 ContextQA when you want to run a data-backed conversational QA application yourself and configure its model and retrieval components, rather than use a hosted chat interface.

Who it is for

  • People who want a self-hosted conversational interface for querying their own data.
  • Teams that need to ingest and manage knowledge sources for LLM-powered question answering.
  • Developers who want to configure model providers, vector stores and memory settings in a Python application.

Documented uses

  • Ingest and manage data sources for later question-answering sessions.
  • Ask conversational questions and receive answers with relevant source references.
  • Configure model provider, model parameters, vector database engine, chunking and memory.
  • Use regular chat with internet-based knowledge expansion.
Before you choose

Requirements & limits

The repository identifies the project as open source under the MIT license. Its README documents installation through pip and a local browser interface launched with the CLI.

  • Model provider choices documented in the README are OpenAI and Google.
  • Documented vector database engines are ChromaDB and Pinecone.
  • Memory can be configured as embedded or external using Redis.
  • The README includes internet-enabled regular chat as well as conversational QA over ingested sources.
  • The documented local setup uses the contextqa CLI and serves the browser interface at localhost:8080.

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

Install and open the ContextQA setup interface

Install the Python package, start ContextQA from its CLI and open the browser-based initialization screen.

Before you start

  • Python environment capable of installing the contextqa package
  • A browser to open the local application

Steps

  1. Install the package with the command below.

    Documented command
    pip install contextqa

  2. Start the CLI with contextqa init.

  3. Open http://localhost:8080 in a browser to reach the initialization stepper.

Expected outcome

The local ContextQA application starts and presents its initial configuration interface in a browser.

Guide limitations

  • The guide covers installation and opening the setup interface, not completing configuration or performing a question-answering session.
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
ContextqaIngest and manage data sources for later question-answering sessions.CLI, Self-hosted, WebThe repository identifies the project as open source under the MIT license. Its README documents installation through pip and a local browser interface launched with the CLI.
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
zaldivards/ContextQA · Official homepage title · retained in its source language
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