Update app.py

app.py

@@ -3,10 +3,38 @@ import requests
 from bs4 import BeautifulSoup
 import gradio as gr
 from groq import Groq
+from googleapiclient.discovery import build
+from google.oauth2.service_account import Credentials
 
 # Initialize Groq client
 client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
 
+# Google Sheets setup
+SCOPES = ['https://www.googleapis.com/auth/spreadsheets']
+SERVICE_ACCOUNT_FILE = 'path_to_service_account.json'  # Update with your service account file path
+SPREADSHEET_ID = 'your_google_sheet_id'  # Update with your Google Sheet ID
+
+credentials = Credentials.from_service_account_file(SERVICE_ACCOUNT_FILE, scopes=SCOPES)
+service = build('sheets', 'v4', credentials=credentials)
+sheet = service.spreadsheets()
+
+# Save user information to Google Sheets
+def save_user_info(name, email, title, industry, target_audience, personal_background, company_background):
+    data = [[name, email, title, industry, target_audience, personal_background, company_background]]
+    sheet.values().append(
+        spreadsheetId=SPREADSHEET_ID,
+        range="Sheet1!A2",  # Assuming headers are in row 1
+        valueInputOption="RAW",
+        insertDataOption="INSERT_ROWS",
+        body={"values": data}
+    ).execute()
+    return "User information saved successfully!"
+
+# Step 1: User profile management UI
+def user_profile(name, email, title, industry, target_audience, personal_background, company_background):
+    save_user_info(name, email, title, industry, target_audience, personal_background, company_background)
+    return "Your information has been saved! Proceed to Step 2 for email generation."
+
 # Function to extract content from a URL
 def extract_content(url):
     try:
@@ -36,7 +64,7 @@ def fetch_linkedin_insights(profile_url):
         return f"Error fetching LinkedIn insights: {str(e)}"
 
 # Function to generate email using Llama
-def generate_email(name, linkedin_url, website_url, context_url, word_count):
+def generate_email(name, linkedin_url, website_url, context_url, word_count, email_purpose):
     # Fetch insights from LinkedIn and reference URLs
     linkedin_insights = fetch_linkedin_insights(linkedin_url)
     website_content = extract_content(website_url)
@@ -45,20 +73,23 @@ def generate_email(name, linkedin_url, website_url, context_url, word_count):
     # Fetch details from AdTech company website
     adtech_content = extract_content("https://www.abcd.com")
 
+    # Adjust prompt based on email purpose
+    purpose_prompt = {
+        "Job Application": "Draft a job application email tailored to the prospect's company and position.",
+        "Sales Cold Email": "Draft a sales email focusing on the prospect's specific needs and how our solutions can help."
+    }.get(email_purpose, "")
+
     # Construct the prompt for Llama
     prompt = f"""
-    You are an AI assistant helping an AdTech company draft personalized sales emails.
+    You are an AI assistant helping an AdTech company draft personalized emails.
     Here are the details of the prospect:
     - Name: {name}
     - LinkedIn Insights: {linkedin_insights}
     - Website Content: {website_content}
     - Additional Context: {context_content}
-
     The company provides the following offerings:
     {adtech_content}
-
-    Draft a personalized email addressing the prospect's specific needs and pain points.
-    Focus on highlighting only relevant solutions from the company offerings.
+    {purpose_prompt}
     Ensure the email is professional, engaging, and stays within {word_count} words (5-10% flexibility).
     Output the email in HTML format.
     """
@@ -74,11 +105,28 @@ def generate_email(name, linkedin_url, website_url, context_url, word_count):
     except Exception as e:
         return f"Error generating email: {str(e)}"
 
-# Gradio Interface
-def email_agent(name, linkedin_url, website_url, context_url, word_count):
-    return "<div style='font-style: italic;'>Hold on tight, your personalized email is on the way...</div>", generate_email(name, linkedin_url, website_url, context_url, word_count)
+# Step 2: Email generation UI
+def email_agent(name, linkedin_url, website_url, context_url, word_count, email_purpose):
+    return "<div style='font-style: italic;'>Hold on tight, your personalized email is on the way...</div>", generate_email(name, linkedin_url, website_url, context_url, word_count, email_purpose)
+
+# Gradio Interfaces
+profile_iface = gr.Interface(
+    fn=user_profile,
+    inputs=[
+        gr.Textbox(label="Your Name"),
+        gr.Textbox(label="Your Email ID"),
+        gr.Textbox(label="Professional Title"),
+        gr.Textbox(label="Industry"),
+        gr.Textbox(label="Target Audience"),
+        gr.Textbox(label="Personal Background"),
+        gr.Textbox(label="Company Background"),
+    ],
+    outputs="text",
+    title="Step 1: User Profile",
+    description="Enter and save your personal and company information."
+)
 
-iface = gr.Interface(
+email_iface = gr.Interface(
     fn=email_agent,
     inputs=[
         gr.Textbox(label="Prospect's Name"),
@@ -86,13 +134,16 @@ iface = gr.Interface(
         gr.Textbox(label="Publishing Website URL"),
         gr.Textbox(label="Additional Context URL (optional)"),
         gr.Slider(label="Email Length (words)", minimum=150, maximum=500, step=10, value=300),
+        gr.Dropdown(label="Email Purpose", choices=["Job Application", "Sales Cold Email"], value="Sales Cold Email")
     ],
     outputs=[
         gr.HTML(label="Status"),
         gr.HTML(label="Generated Email")
     ],
-    title="Personalized Email Agent",
-    description="Generate highly personalized sales emails for AdTech prospects."
+    title="Step 2: Email Generation",
+    description="Generate highly personalized emails for your specific purpose."
 )
 
-iface.launch(share=True)
+# Combine steps into one Gradio app
+app = gr.TabbedInterface([profile_iface, email_iface], ["Step 1: Profile", "Step 2: Email Generation"])
+app.launch(share=True)