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Quick install

To install Articulus RAG i.e., a private repo, we can use the Access Token of GitHub.

git clone https://<UPDATE-WITH-YOUR-TOKEN>@https://github.com/AryaChakraborty/articulus_rag

Create virtual environment

python3 -m venv env 
source env/bin/activate

or

virtualenv env
source env/bin/activate

Install all the packages within the virtual environment.

pip install -r requirements.txt

Install the beyondllm framework.

pip install -e .

API Documentation

/recommend Endpoint

  • Method: GET
  • Description: Retrieves ranked documents from the MongoDB collection.
  • Parameters: None
  • Response:
    • Success: Returns a JSON object containing the ranked documents.
    • Error: Returns a JSON object with an error message.

/rank Endpoint

  • Method: POST
  • Description: Retrieves ranked documents based on search keywords.
  • Parameters:
    • search_keywords: List of search keywords.
  • Request Body Example: 
    {
  "search_keywords": ["keyword1", "keyword2", "keyword3"]
}
  • Response:
    • Success: Returns a JSON object containing the ranked documents.
    • Error: Returns a JSON object with an error message.

/keyword_extractor Endpoint

  • Method: POST
  • Description: Extracts top 10 keywords from the given text.
  • Parameters:
    • text: Input text from which keywords need to be extracted.
  • Request Body Example: 
    {
  "body": "Input text for keyword extraction."
}
  • Response:
    • Success: Returns a JSON object containing the extracted keywords.
    • Error: Returns a JSON object with an error message.

/ai Endpoint

  • Method: POST
  • Description: Uses the enterprise RAG model to provide a response to the given question.
  • Parameters:
    • path: URL path or source of the content.
    • type: Type of content (e.g., "url", "youtube", etc.).
    • question: Question to be answered.
  • Request Body Example: 
    {
  "path": "https://highonbugs.sbk2k1.in/sows",
  "type": "url",
  "question": "What is the blog about?"
}
  • Response:
    • Success: Returns a JSON object containing the response from the enterprise RAG model.
    • Error: Returns a JSON object with an error message.