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Chatbot for data knowledge

ChatBot for your company data knowledge with UI

Conversation Example

UI

Screenshot

How it works

  1. User asks a question
  2. Chatbot searches for the answer in the company's Confluence wiki or Jira or Google Chats backup (semantic search) via langchain API
  3. If the answer is not found, the chatbot asks the user to clarify the question
  4. If the answer is found, the chatbot displays it to the user

Agent uses ReAct Agent Policy from LangChain framework:

Screenshot

Installation

  1. Clone this repository:
git clone https://github.com/Xaik89/chatbot_for_data_knowledge.git
  1. Install the required packages:
pip install -r requirements.txt
  1. Create a .env file with all environment variables needed:
OPENAI_API_KEY="your_openai_api_key"

CONFLUENCE_API_TOKEN="your_confluence_api_token"
CONFLUENCE_API_USER="your_confluence_api_user"
CONFLUENCE_WIKI_URL="your_confluence_wiki_url"

JIRA_API_TOKEN="your_jira_api_token"
JIRA_USERNAME="your_jira_username"
JIRA_INSTANCE_URL="your_jira_instance_url"

G_CHATS_BACKUP_PATH="your_google_chats_backup_path"

Usage

  1. Run the server:
python main.py
  1. Open the Gradio interface in your web browser at http://127.0.0.1:7860