Topic Source Workflow

This guide describes the end-to-end process for connecting to data sources, extracting files, generating knowledge topics and notes using OpenAI, storing them in a vector database, and enabling chatbot-powered Q&A.

Step 1: Select and Connect to a Data Source

Supported data sources:

  • GitHub – Connect to a repository for source files and documentation.
  • Bitbucket – Similar to GitHub, for Bitbucket repositories.
  • Website – Fetch content from a public or private website.
  • File Share – Upload ZIP files or connect to a network share.

  1. Choose your data source type.
  2. Click Configure to proceed to connection setup.

Step 2: Configure Connection

Enter the required connection details for your selected provider:

  • GitHub/Bitbucket: Provider URL, API Token, Owner, Repository, Branch.
  • Website: Website URL, Username/Password (if needed), Extra Config.
  • File Share: Upload ZIP file or provide UNC path and credentials.

  1. Fill in the required fields.
  2. Click Connect to save and test the connection.
Tip: Credentials and tokens are securely stored and never exposed to other users.

Step 3: Select Files/Content

After connecting, the system fetches a list of available files. You can:

  • Review the file list.
  • Select individual files or use Select All for bulk selection.

  1. Check the files you want to process for topic generation.
  2. Click Click To Generate Topics to proceed.

Step 4: Generate Topics with OpenAI

The system sends the content of selected files to OpenAI with a prompt to extract raw notes and initial topics.

  1. Click Generate Topics to start the process.
  2. Wait for the system to process the files and receive AI-generated topics and raw notes.
Tip: You can monitor progress and view results in the status area.

Step 5: Generate FAQs and Production Notes

For each topic, you can further generate FAQs and Production Notes using OpenAI:

  • Send the raw notes to OpenAI with a prompt to generate FAQs and production notes.
  • Review and edit the generated content as needed.

Step 6: Store Topics in Vector Database

All generated topics, raw notes, FAQs, and production notes are stored in the vector database for semantic search and chatbot Q&A.

Tip: The vector database enables fast, context-aware search and retrieval for chatbot answers.

Step 7: Chatbot Q&A

Users can interact with the chatbot to ask questions about any topic. The chatbot:

  • Uses vector search to find relevant topics.
  • Answers using stored notes, FAQs, and production notes.
  • Can generate new answers using OpenAI if needed.

Best Practices & Tips

  • Preview files before processing to avoid irrelevant topics.
  • Review and edit AI-generated notes and FAQs for accuracy.
  • Use bulk selection for efficiency, but ensure only relevant files are chosen.
  • Monitor progress and check for errors in the status/result area.

Troubleshooting

  • Connection Issues: Verify credentials, tokens, and URLs.
  • File Not Found: Ensure files exist and are accessible.
  • AI Generation Errors: Retry with different prompts or split large files.
  • Chatbot Not Answering: Ensure topics are generated and stored correctly.

Security & Permissions

  • Only authorized users can connect to data sources and generate topics.
  • All actions are logged for audit and troubleshooting.

Support

For further assistance, contact your system administrator or refer to the in-app help documentation.