Update app.py

app.py

@@ -1,12 +1,8 @@
 import gradio as gr
 import requests
-from gingerit.gingerit import GingerIt  # Import GingerIt for grammar correction
 import os
 from datetime import datetime  # Import datetime for date validation
 
-# Initialize GingerIt parser
-ginger_parser = GingerIt()
-
 # Load Groq Cloud API key securely from environment variables
 groq_api_key = os.getenv("GROQ_CLOUD_API_KEY")
 
@@ -20,16 +16,20 @@ def fetch_public_data(name, dob, city):
     
     return bio, linkedin_profile
 
-# Helper function to call Groq Cloud LLM API to generate email
-def generate_email_from_groq(bio, company_name, role):
+# Helper function to call Groq Cloud LLM API to generate and correct the email
+def generate_and_correct_email(bio, company_name, role):
     url = "https://api.groq.com/openai/v1/chat/completions"  # Updated API URL for Groq Cloud
     headers = {
         "Authorization": f"Bearer {groq_api_key}",  # Use the API key securely from environment
         "Content-Type": "application/json",
     }
     
-    # Updated prompt for Groq Cloud chat completion
-    prompt = f"Write a professional email applying for a {role} position at {company_name}. Use this bio: {bio}. The email should include an introduction, relevant experience, skills, and a closing."
+    # Updated prompt to ask the model to generate AND correct the email
+    prompt = f"""
+    Write a professional email applying for a {role} position at {company_name}. Use this bio: {bio}.
+    The email should include an introduction, relevant experience, skills, and a closing.
+    Ensure that the email is grammatically correct and formal.
+    """
     
     # Construct the data payload for the API request
     data = {
@@ -52,11 +52,6 @@ def generate_email_from_groq(bio, company_name, role):
         print(f"Error: {response.status_code}, {response.text}")
         return "Error generating email. Please check your API key or try again later."
 
-# Grammar and Tone Checker Function using GingerIt
-def check_grammar(email_text):
-    corrected_text = ginger_parser.parse(email_text)["result"]
-    return corrected_text
-
 # Function to validate the DOB format (DD-MM-YYYY)
 def validate_dob(dob):
     try:
@@ -77,16 +72,13 @@ def create_email(name, dob, city, company_name, role, email, phone):
     bio, linkedin_profile = fetch_public_data(name, dob, city)
     
     # Step 2: Generate the email using Groq Cloud LLM
-    generated_email = generate_email_from_groq(bio, company_name, role)
+    generated_email = generate_and_correct_email(bio, company_name, role)
     
     # Step 3: Add the user's email, phone number, and LinkedIn profile to the signature
     signature = f"\n\nBest regards,\n{name}\nEmail: {email}\nPhone: {phone}\nLinkedIn: {linkedin_profile}"
 
-    # Step 4: Run grammar and tone check using GingerIt
-    polished_email = check_grammar(generated_email + signature)
-
     # Return the final polished email with the signature
-    return polished_email
+    return generated_email + signature
 
 # Define interface with Gradio
 def gradio_ui():