To use the Vector Database, please go through the detailed information from the Embeddings API Documentation.
If you don’t have an API key, generate one from the dashboard Getting your API key to authenticate requests.

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Example

Below is a Python example demonstrating how to make a request to the API to perform a contextual search: 

import requests
import json

def retrieve_similar_filings_chunks(query):
    url = 'https://stockinsights-ai-main-49970eb.d2.zuplo.dev/api/in/v0/documents/embeddings-search'
    headers = {'Content-Type': 'application/json',
              'Authorization': 'Bearer YOUR_API_KEY_HERE'}
    data = {
        "query": query,
        "filters": {
            "types": ["earnings-transcript", "annual-report"],
            'year': '2024'
        }
    }

    response = requests.post(url, headers=headers, data=json.dumps(data))
    return response.json()
    
result = retrieve_similar_filings_chunks("FIIs contribution to Indian Capital Markets")

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Key Points

  • Replace YOUR_API_KEY_HERE with your actual API key in the Authorization header.
  • Modify the query parameter to suit your search needs.
  • Adjust the filters to target specific document types or time periods.