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import gradio as gr | |
import os | |
from groq import Groq | |
# Load API key securely from environment variable | |
GROQ_API_KEY = os.getenv("Groq_API_Key") | |
# Initialize Groq client using the SDK | |
client = Groq(api_key=GROQ_API_KEY) | |
# System instruction for the bot | |
SYSTEM_PROMPT = ( | |
"You are a Construction Material Advisor Bot. Your job is to recommend the best construction materials " | |
"for civil engineering projects based on environmental conditions, budget, load requirements, and durability. " | |
"Be concise, informative, and explain pros and cons of the materials." | |
) | |
# Model name | |
MODEL_NAME = "llama3-70b-8192" | |
# Chat function using Groq SDK | |
def get_material_advice(user_query: str) -> str: | |
try: | |
chat_completion = client.chat.completions.create( | |
model=MODEL_NAME, | |
messages=[ | |
{"role": "system", "content": SYSTEM_PROMPT}, | |
{"role": "user", "content": user_query}, | |
], | |
temperature=0.7, | |
max_tokens=500, | |
) | |
response = chat_completion.choices[0].message.content.strip() | |
# Convert plain text response to Markdown for better formatting | |
formatted_response = f"### 🧱 Material Recommendations\n\n{response}" | |
return formatted_response | |
except Exception as e: | |
return f"Error: {str(e)}" | |
# Gradio UI | |
demo = gr.Interface( | |
fn=get_material_advice, | |
inputs=gr.Textbox(lines=3, placeholder="Ask about construction materials..."), | |
outputs=gr.Markdown(), | |
title="🧱 Construction Material Advisor Bot", | |
description=( | |
"Ask questions like 'What is the best material for a coastal bridge?' or " | |
"'Suggest budget-friendly wall material for cold regions.'" | |
), | |
) | |
if __name__ == "__main__": | |
demo.launch() | |