To use the Embeddings API, please go through the detailed information about the API and its parameters from the Documentation.
If you don’t have an API key, please signup on the portal to generate a test key - To authenticate your API requests.

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Example

Below is a Python example demonstrating how to perform a question-answering:

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Function to get similar filings chunks


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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Function to Generate Answers Using OpenAI GPT Model


from openai import OpenAI

# Set your OpenAI API key
client = OpenAI(
  api_key='YOUR_OPEN_AI_KEY_HERE',
)

GPT_MODEL = 'gpt-4o-mini'

# To interact with OpenAI GPT model
def chat_completion_request(messages, model= GPT_MODEL, stream=False, functions=None, function_call=None):
    try:
        response = client.chat.completions.create(
            model=model,
            messages=messages,
            stream = stream,
            functions=functions,
            function_call=function_call
        )
        return response
    except Exception as e:
        print("Unable to generate ChatCompletion response")
        print(f"Exception: {e}")
        return e

# Function to construct knowledge source
def construct_knowledge_source(similar_chunks):
    knowledge_source = ""
    data = similar_chunks.get('data', [])
    
    for entry in data:
        chunk_content = entry.get('text', '')
        company_name = entry.get('company', {}).get('company_name', '')
        document_type = entry.get('document', {}).get('type', '')
        document_link = entry.get('document', {}).get('link', '')
        page_num = entry.get('metadata', {}).get('page_num', '')
        document_link_with_page = f"{document_link}#page={page_num}"
        year = entry.get('document', {}).get('year', '')
        quarter = entry.get('document', {}).get('quarter', '')
        
        # Append the context to each chunk
        knowledge_source += f"This is a section from {document_type} of company {company_name} for FY{year} {quarter if quarter else ''} from {document_link_with_page}: {chunk_content};\n\n"
    
    return knowledge_source

def get_answer_from_public_company_filings(query):
    similar_filings_chunks = retrieve_similar_filings_chunks(query)
    knowledge_source = construct_knowledge_source(similar_filings_chunks)
    response_instructions = """
         Answer user questions based on some parts of the filings/disclosures identified as most relevant to the question.
         Provide a clear and comprehensive response to the question only from the provided context. """

    setup_messages=[
                {'role': 'system', 
                 'content': response_instructions
                },
                {
                'role': 'system',
                'content': knowledge_source
                },
                {'role': 'user',
                'content': query
                }
            ]
    chat_response = chat_completion_request(messages = setup_messages,stream = False)
    message = chat_response.choices[0].message.content
    return message

query = 'What could be the reasons for decreased overseas(FII) contribution in Indian Capital Markets decreasing while the Domestic fund flows contributions are increasing'
get_answer_from_public_company_filings(query)

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Key Points

  • Replace YOUR_API_KEY_HERE with your actual API key in the Authorization header.
  • Replace YOUR_OPEN_AI_KEY_HERE with your actual OpenAI API key.
  • Modify the query parameter to suit your specific question.
  • Adjust the filters to target specific document types or time periods as needed.