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import os
import requests
from dotenv import load_dotenv
from messages import krishna_blessings
from ayush_messages import ayush_surprises
# Load environment variables (Hugging Face Space secrets)
load_dotenv()
HUGGINGFACE_API_TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")
def get_krishna_response(user_input):
"""
Generate a response from Little Krishna based on user input.
- If the input contains specific keywords, return predefined messages.
- Otherwise, use Hugging Face's Inference API with the Gemma model.
"""
if "birthday" in user_input.lower():
return ayush_surprises["birthday"]
if "shy" in user_input.lower():
return krishna_blessings["shy"]
if "hello" in user_input.lower() or "hi" in user_input.lower():
return krishna_blessings["greeting"]
headers = {
"Authorization": f"Bearer {HUGGINGFACE_API_TOKEN}",
"Content-Type": "application/json"
}
payload = {
"inputs": f"You are Little Krishna, playful and wise. Respond to this in a fun, Krishna-like way: '{user_input}'",
"parameters": {
"max_length": 60,
"temperature": 0.9
}
}
try:
response = requests.post(
"https://api-inference.huggingface.co/models/google/gemma-2b",
headers=headers,
json=payload
)
if response.status_code == 200:
result = response.json()
return result[0]["generated_text"].strip()
else:
print(f"Error with Gemma: {response.text}")
return "Sorry, I couldn’t generate a response. Let’s try something else!"
except Exception as e:
print(f"Error connecting to Hugging Face Inference API: {str(e)}")
return "Hare Krishna! I seem to be lost in Vrindavan’s magic—let’s try again!" |