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import requests
import os
from dotenv import load_dotenv
load_dotenv()
# Get the API key from environment variable
GROQ_API_KEY = "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"
if not GROQ_API_KEY:
raise ValueError("GROQ_API_KEY is not set in the .env file")
def intiate_convo(user_query, image_description, additional_text, model="mixtral-8x7b-32768"):
# Prepare the message payload
messages = [
{
"role": "system",
"content": """You are a AI Assistant for training. Given an image description, additional context, and a user query, respond with a detailed long answer with steps, ,be polite.
IMPORTANT: When referring to the image, subtly acknowledge it by saying "as I see here" rather than explicitly mentioning "image" or "photo."
Your tone should be natural and conversational. Keep it detailed , engaging, and relevant to the query, using both the image description and the additional context as reference points."""
},
{
"role": "user",
"content": f"Image description: {image_description}. Additional context: {additional_text}. User query: {user_query}. Provide a detaile response like an ai assistant."
}
]
# Make the API request
response = requests.post(
"https://api.groq.com/openai/v1/chat/completions",
json={
"model": model,
"messages": messages,
"max_tokens": 32768,
"stop": None,
"stream": False
},
headers={
"Authorization": f"Bearer {GROQ_API_KEY}",
"Content-Type": "application/json"
},
timeout=60
)
# Process the response
if response.status_code == 200:
result = response.json()
answer = result["choices"][0]["message"]["content"]
return answer
else:
return f"Error from LLM API: {response.status_code} - {response.text}"
# # Example usage
# # Define the inputs
# user_query = "Can you tell me more about the person in this description?"
# image_description = """The main subject of the image is a person with dark complexion, short black hair, and white-framed glasses, wearing a dark-colored shirt or jacket. They are looking directly at the camera with a subtle expression."""
# additional_text = """This individual is a software engineer specializing in AI development. They are known for their expertise in computer vision and enjoy photography as a hobby."""
# # Get the LLM response
# response = intiate_convo(user_query, image_description, additional_text)
# print(response)
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