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import os
from openai import OpenAI
import logging
import re
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
# Initialize Groq client
client = OpenAI(
api_key=os.environ.get("GROQ_API_KEY"),
base_url="https://api.groq.com/openai/v1"
)
def format_response_text(text):
"""Formats the response text for better frontend presentation using HTML breaks."""
text = re.sub(r'\*\*([^*]+)\*\*', r'<strong>\1</strong>', text)
# Convert line breaks to HTML breaks
text = text.replace('\n', '<br>')
# Format bullet points consistently
text = re.sub(r'•\s*', '- ', text) # Convert bullets to dashes
text = re.sub(r'[\*\-]\s*', '- ', text) # Standardize list markers
# Clean up any remaining markdown artifacts
text = re.sub(r'`([^`]+)`', r'\1', text) # Remove code blocks
text = re.sub(r'_{2,}([^_]+)_{2,}', r'<strong>\1</strong>', text) # Convert underscore bold
return text
def get_completion(prompt, context, contact_email="soufiane.sejjari@neologix.ma"):
"""Generates a website-integrated assistant response using the Groq API."""
try:
# Ensure context is within token limits
if len(context) > 8000:
context = context[:4000] + "\n...[Content truncated]...\n" + context[-4000:]
system_message = (
"You are an integrated website assistant representing yourself as part of a website and your role is assisting users with their questions.\n"
"Follow these guidelines:\n"
"1. Keep responses concise and professional (max 2-3 paragraphs)\n"
"2. Use the same language as the user's question\n"
"3. Format lists with clear bullet points using '-'\n"
"4. Use clear paragraph breaks for readability\n"
"5. if question about yourself, respond as if you are the website owner\n"
"6. Focus ONLY on information from the provided context\n"
"8. Keep bullet point items short and clear\n"
"9. End with a brief, professional closing statement\n"
"10. Ensure proper spacing between paragraphs and list items\n"
"11. Do not add any extra information or links"
)
response = client.chat.completions.create(
model="llama3-70b-8192",
messages=[
{"role": "system", "content": system_message},
{"role": "user", "content": f"Context information:\n{context}\n\nQuestion: {prompt}"}
],
max_tokens=500, # Shorter responses for better focus
temperature=0.7,
presence_penalty=0.2,
frequency_penalty=0.5
)
# Format the response with HTML breaks
response_text = response.choices[0].message.content
formatted_text = format_response_text(response_text)
# Add contact information with proper spacing
final_response = f"{formatted_text}<br>Pour plus d'informations, contactez-nous à {contact_email}"
return final_response
except Exception as e:
logging.error(f"Error generating completion: {e}")
return f"Désolé, je n'ai pas pu générer une réponse.<br><br>Contactez-nous à {contact_email}" |