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import requests
from dotenv import load_dotenv
import os
load_dotenv()
huggingface = os.getenv("HUGGINGFACE")
class TopicGenerator:
def __init__(self):
# Initialize API-URL and authorization headers
self.url = "https://api-inference.huggingface.co/models/google/flan-t5-large"
self.headers = {"Authorization": f"Bearer {huggingface}"}
def query(self, payload):
response = requests.post(self.url, headers=self.headers,
json=payload)
return response
def generate_topics(self, user_input, num_topics=3):
payload = {
"inputs": f"""Generate a topic sentence idea based on the user input.
The generated topics should portray the context or idea behind the given sentences or phrase.
For Instance,
- "Grocery Shopping" OR "Grocery List" OR "Shopping List": "I'm going grocery shopping tomorrow,
and I would like to get the following things on my grocery list: Milk, Soybeans, Cowpeas,
Saturated Water, Onions, Tomatoes, etc."
- "Studying For Exams" OR "Exams Studies": "Exams aare coming up and I have to prepare for the core
courses. I'll be studying for Control Systems, Software Engineering and Circuit Theory."
- "Healthy Breakfast": "To prepare a healthy breakfast, I need the appropriate combination of balanced
diet. I'll need oats, yogurt, fresh berries, honey and smoothies."
- "Fitness Routine": "Starting a fitness routine involves workout clothes, running shoes,
a water bottles, and a gym membership. With this, I can start a proper fitness plan."
- "Summer Vacation": "Packing swimsuits and enjoy the view of the ocean."
- "Coffee Break": "Sipping Coffee at the table."
- "Relaxation": "Sitting at the table enjoying."
This is what I'm expecting the model to do. Here is the input: {user_input}
""",
"do_sample": True,
"temperature": 0.7,
"num_return_sequences": num_topics
}
output = self.query(payload)
if output.status_code == 200:
topic = output.json()
return topic
else:
return f"Error: Received response code {output.status_code}"
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