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llmops / src /utils.py

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	from src.constants import HF_API_URL
	import streamlit as st
	import requests


	# Define a function to get the output from the Huggingface Inference API
	def get_output(task, model, data, api_token, model_type=None):
	# Construct the request URL
	url = f"{HF_API_URL}/models/{model}?task={task}"
	print(f"api_token:: {api_token}")
	# Send a POST request with the payload as JSON data
	if (api_token != ""):
	headers = {"Authorization": f"Bearer {api_token}"}
	response = requests.post(url, headers=headers, data=data)
	else:
	response = requests.post(url, data=data)

	# Check if the request was successful
	if model_type is None:
	if response.status_code == 200:
	return response.json()
	elif response.status_code == 404:
	return {"error": f"Request failed with status code {response.status_code}",
	"description": "Please check whether Model id is correct or Inference API is available for this model."}
	else:
	return {"error": f"Request failed with status code {response.status_code}",
	"description": None}
	else:
	return response


	## Function for displaying the output of a epecified task choosen
	def show_output(output):
	if isinstance(output, list):
	st.text_area(label="Generated Text Output", value=output[0][list(output[0].keys())[0]])
	else:
	st.error(output['error'])
	st.error(output['description'])