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