OpenViSTAI · Agents · Blockchain · Crypto
Submit a project
Menu
Workflow Agents

Autonomous Hr Chatbot

An open-source Python prototype of an autonomous HR question-answering agent that invokes tools over policy documents and employee data.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Autonomous Hr Chatbot — OpenViST project profile in Workflow Agents.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you need a starting point for experimenting with an HR assistant that combines document retrieval, dataframe-based employee lookups and calculations.

Who it is for

  • Developers exploring tool-using AI agents
  • HR technology teams prototyping employee self-service assistants
  • Teams testing retrieval, structured-data lookup and calculation in one workflow

Documented uses

  • Answer questions from an HR policy document
  • Look up values in structured employee records
  • Perform calculations through an agent tool
  • Prototype a Streamlit-based enterprise assistant
Before you choose

Requirements & limits

The repository is publicly accessible and identified with an MIT license. The documented application requires API keys; local and Azure backend options are described.

  • The original implementation depends on LangChain, Pinecone, Streamlit and OpenAI-compatible services.
  • The prototype uses a sample timekeeping-policy document and dummy employee data, so organization-specific use requires replacing those inputs.
  • The repository documents a v2 agent loop using the OpenAI Responses API without LangChain or Pinecone.
  • The project is written in Python and the documented local setup uses Python 3.10.

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

Set up the original Streamlit prototype

Install and configure the documented prototype locally.

Before you start

  • Python 3.10
  • A cloned copy of the repository
  • Prerequisite modules from requirements.txt
  • API keys
  • A Pinecone account and embedding setup when using the Pinecone workflow

Steps

  1. Clone the repository to a local directory and navigate to it.

  2. Install the prerequisite modules with pip install -r requirements.txt.

  3. Add API keys to hr_agent_backend_local.py, or configure the Azure backend in hr_agent_backend.py as documented.

  4. Run the Streamlit frontend with streamlit run hr_agent_frontent.py.

  5. For policy retrieval, create a Pinecone account, add the relevant Pinecone and OpenAI keys, and run store_embeddings_in_pinecone.ipynb.

Expected outcome

A locally configured Streamlit prototype using the documented HR-agent components.

Guide limitations

  • The documented policy is a sample document and the employee data is dummy data.
  • The guide documents setup and launch, not production deployment or data governance.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
30 September 2026
Original website title
stepanogil/autonomous-hr-chatbot · Official homepage title · retained in its source language
How we review sourcesSuggest a correction