Focused Labs Knowledge Base Demo · https://chat.withfocus.com/

Table of Contents

1. Focused Labs Knowledge Base Demo
2. Why?
   • Why build this? Why does this matter?
3. What?
   • What is in this repository?
   • Data Inputs
4. Prerequisites
5. Getting the demo running...
   • Edit Configuration Files
     • Update .env
     • Update config.py
   • The API
     • Run
     • Endpoints
   • Run accuracy test

This sample project demonstrates a possible implementation of a domain specific AI Knowledge Base using Focused Labs as the example.

The UI (frontend code) lives in this repository.

Why?

Why build this? Why does this matter?

• AI driven solutions will empower organizations to build on top of existing infrastructure and unlock legacy
• Customized AI ChatBots accelerate product development by making disparate and complex information easy to find
• Unblock teams to focus on what matters - building working software - rather than chasing down people and documentation

What?

What is in this repository?

A python codebase that harnesses the power of semantic vector search fueled by advanced LLMs.

Data Inputs:

1. Our external Notion wiki
2. Our public website: Focused Labs

Prerequisites

1. A Pinecone Vector Database. You can create a free account at Pinecone's website.
2. A Open AI API account (api key). You can sign up at Open AI's website.
3. Python (and your favorite IDE). We are using python v3.10.7.
4. (Optional) Notion API Key.

Getting the demo running...

Edit Configuration Files

Update .env

OPENAI_API_KEY = "<Open AI API Token Secure Note>"
NOTION_API_KEY = "<Notion API Token Secure Note>"
PINECONE_API_KEY = "<retrieve value Pinecone DB DEV credential>"

Update config.py

PINECONE_INDEX = "<name of your index, ex: "focusedlabs-pinecone-index">"
PINECONE_ENVIRONMENT = "<name of your pineconce env. ex: asia-southeast1-gcp-free>"

(Optional) You can explore other models. We recommend using the current configuration for best results.Then, ask a teammate to add you to the Focused Labs Knowledge Base Hub project.

The API

Run

 uvicorn main:app

Add --reload if you make a code change the app will restart on its own.

Endpoints

1. Endpoint: /
   Description: A simple endpoint that returns a "Hello World" message.
   Method: GET
   
   
2. Endpoint: /load-notion-docs
   Description: Loads documents from Notion based on provided Notion page IDs.
   Method: POST
   Payload: json
       {
         "page_ids": ["<NOTION_PAGE_ID_1>", "<NOTION_PAGE_ID_2>", ...]
       }
   
3. Endpoint: /load-website-docs
   Description: Loads documents based on provided URLs that are web scraped.
   Method: POST
   Payload: json
       {
         "page_urls": ["<URL_1>", "<URL_2>", ...]
       }
   
4. Endpoint: /query/
   Description: Accepts a question and role and returns the appropriate query result.
   Method: POST
   Payload: json
        {
          "text": "<user question here>",
          "role": "<user persona, ex: potential customer>"
        }
   Description: Accepts a question and returns the appropriate query result.
   
5. Endpoint: /delete_session
   Description: Deletes a conversation based on the provided session ID.
   Method: POST
   Payload: json
       {
         "session_id": "<YOUR_SESSION_ID>"
       }
   

Run accuracy test

Cannot be run via command line.

Edit the run configuration for accuracy_test_runner.py and add the file that contains the list of questions you want to ask. Ex: questions.txt