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import os
import sys
import subprocess
import streamlit as st
# Check if 'groq' is installed, and if not, prompt the user to install it
def check_groq_installed():
try:
import groq
return True
except ImportError:
return False
# Check Python version compatibility
def check_python_version():
required_version = (3, 6) # Minimum required Python version
current_version = sys.version_info
if current_version < required_version:
return False
return True
# Check if the Groq client is correctly initialized
def check_groq_client():
try:
from groq import Groq
# Try initializing the Groq client with the provided API key
client = Groq(api_key="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")
return True
except Exception as e:
print(f"Error initializing Groq client: {e}")
return False
# Run all checks before proceeding
def run_checks():
# Check if groq is installed
if not check_groq_installed():
st.error("Groq module is not installed. Please install it using 'pip install groq'.")
return False
# Check if Python version is compatible
if not check_python_version():
st.error("Python version 3.6 or higher is required. Please upgrade your Python.")
return False
# Check if the Groq client can be initialized
if not check_groq_client():
st.error("Failed to initialize Groq client. Check your API key and the Groq module installation.")
return False
return True
# Function to request pattern generation from Groq API
def get_pattern_from_groq(body_measurements, garment_type):
from groq import Groq
client = Groq(api_key="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")
# Preparing the prompt for the LLM
prompt = f"Generate a 2D {garment_type} pattern based on the following body measurements:\n{body_measurements}"
# Making a request to Groq's API
chat_completion = client.chat.completions.create(
messages=[{"role": "user", "content": prompt}],
model="llama3-8b-8192",
stream=False
)
# Get the response content
return chat_completion.choices[0].message.content
# Function to simulate creating a 2D garment pattern (for demo purposes)
def generate_garment_pattern(body_measurements, garment_type):
# Here you would typically use the measurements to generate the 2D pattern.
# We'll simulate this by returning a simple placeholder pattern.
pattern = f"2D {garment_type} Pattern based on measurements:\n{body_measurements}"
return pattern
# Main Streamlit app UI
def main():
# Perform pre-execution checks
if not run_checks():
return
st.title("Garment Pattern Design Tool")
# Select garment type
garment_type = st.selectbox("Select Garment Type", ["Top Body Garment", "Bottom Garment"])
# Collect body measurements based on garment type
st.header(f"Enter Measurements for {garment_type}")
body_measurements = {}
if garment_type == "Top Body Garment":
body_measurements['Chest'] = st.number_input('Chest (in cm)', min_value=0, step=1)
body_measurements['Waist'] = st.number_input('Waist (in cm)', min_value=0, step=1)
body_measurements['Neck'] = st.number_input('Neck (in cm)', min_value=0, step=1)
body_measurements['Height'] = st.number_input('Height (in cm)', min_value=0, step=1)
elif garment_type == "Bottom Garment":
body_measurements['Waist'] = st.number_input('Waist (in cm)', min_value=0, step=1)
body_measurements['Hip'] = st.number_input('Hip (in cm)', min_value=0, step=1)
body_measurements['Inseam'] = st.number_input('Inseam (in cm)', min_value=0, step=1)
body_measurements['Height'] = st.number_input('Height (in cm)', min_value=0, step=1)
body_measurements_str = "\n".join([f"{key}: {value}" for key, value in body_measurements.items()])
if st.button("Generate Pattern"):
if all(value > 0 for value in body_measurements.values()):
# Fetch pattern from Groq LLM
st.write("Generating pattern...")
pattern = get_pattern_from_groq(body_measurements_str, garment_type)
# Simulate the 2D pattern generation (you can replace this with actual pattern generation logic)
pattern_output = generate_garment_pattern(body_measurements_str, garment_type)
# Display the result
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