Update app.py

app.py

@@ -1,108 +1,109 @@
-import streamlit as st
-import pandas as pd
-from openai_llms import LLMHandler
-import tempfile
-import os
-
-# Load environment variables for OpenAI API Key
-from dotenv import load_dotenv
-
-load_dotenv()
-
-# Initialize LLMHandler
-llm_handler = LLMHandler()
-
-
-def process_csv(file, user_prompt):
-    """Read CSV, generate responses using LLMHandler, and return processed DataFrame."""
-    df = pd.read_csv(file)
-    responses = []
-
-    for _, row in df.iterrows():
-        try:
-            response = llm_handler.generate_response(user_prompt, row.to_dict())
-            responses.append(response)
-        except Exception as e:
-            responses.append(f"Error: {e}")
-
-    df["Generated Text"] = responses
-    return df
-
-
-# Streamlit UI
-st.set_page_config(page_title="Invitation Generator", page_icon="📜", layout="wide")
-
-# Header
-st.title("Invite AI")
-st.markdown(
-    """
-    Welcome to the Invitation Generator! This tool helps you create personalized invitations using the power of AI.
-    Follow the steps below to upload your data and generate professional invitation texts.
-    """
-)
-
-# Section: Template Download and Instructions
-st.sidebar.title("Instructions")
-st.sidebar.markdown(
-    """
-    ### Template Download
-    [Click here to download the suggested CSV template](http://surl.li/ptvzzv) 📥
-
-    ### Required Fields
-    - **Unique Identifier for each receiver**
-    - **Name of the receiver**
-    - **Designation/Job title of the receiver**
-    - **Company/Organisation where the receiver works**
-    - **Areas the receiver is interested in / has expertise in**
-    - **Categorize receivers into groups** for consistent instructions.
-    """
-)
-
-# Main Section
-st.markdown(
-    """
-    ### Steps to Use
-    1. **Download the template** from the sidebar.
-    2. **Fill out the details** as per the instructions.
-    3. **Upload the completed CSV file** below.
-    4. Enter a **prompt** to generate personalized invitations.
-    """
-)
-
-# File uploader for CSV
-uploaded_file = st.file_uploader("📂 Upload CSV File", type=["csv"])
-user_prompt = st.text_area(
-    "✍️ Enter the prompt for generating invitation texts:",
-    "Write professional invitation text tailored for the group.",
-    height=150,
-)
-
-# Processing and displaying results
-if uploaded_file is not None and user_prompt:
-    st.write("⏳ Processing your file... Please wait.")
-    processed_df = process_csv(uploaded_file, user_prompt)
-
-    # Display results
-    st.write("### Generated Invitations")
-    st.dataframe(processed_df, use_container_width=True)
-
-    # Option to download the processed CSV
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as temp_file:
-        processed_df.to_csv(temp_file.name, index=False)
-        temp_file.close()  # Ensure the file is properly closed before proceeding
-
-        st.download_button(
-            label="📥 Download Results CSV",
-            data=open(temp_file.name, "rb"),
-            file_name="generated_invitations.csv",
-            mime="text/csv",
-        )
-
-    # Safely delete the temporary file
-    os.unlink(temp_file.name)
-
-# Footer
-st.markdown("---")
-st.markdown(
-    "💡 **Tip:** Ensure your data aligns with the provided template for accurate results."
-)
+import streamlit as st
+import pandas as pd
+#from openai_llms import LLMHandler
+from Groq_llms import LLMHandler
+import tempfile
+import os
+
+# Load environment variables for OpenAI API Key
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# Initialize LLMHandler
+llm_handler = LLMHandler()
+
+
+def process_csv(file, user_prompt):
+    """Read CSV, generate responses using LLMHandler, and return processed DataFrame."""
+    df = pd.read_csv(file)
+    responses = []
+
+    for _, row in df.iterrows():
+        try:
+            response = llm_handler.generate_response(user_prompt, row.to_dict())
+            responses.append(response)
+        except Exception as e:
+            responses.append(f"Error: {e}")
+
+    df["Generated Text"] = responses
+    return df
+
+
+# Streamlit UI
+st.set_page_config(page_title="Invitation Generator", page_icon="💬", layout="wide")
+
+# Header
+st.title("Invite AI")
+st.markdown(
+    """
+    Welcome to the Invitation Generator! This tool helps you create personalized invitations using the power of AI.
+    Follow the steps below to upload your data and generate professional invitation texts.
+    """
+)
+
+# Section: Template Download and Instructions
+st.sidebar.title("Instructions")
+st.sidebar.markdown(
+    """
+    ### Template Download
+    [Click here to download the suggested CSV template](http://surl.li/ptvzzv) 📥
+
+    ### Required Fields
+    - **Unique Identifier for each receiver**
+    - **Name of the receiver**
+    - **Designation/Job title of the receiver**
+    - **Company/Organisation where the receiver works**
+    - **Areas the receiver is interested in / has expertise in**
+    - **Categorize receivers into groups** for consistent instructions.
+    """
+)
+
+# Main Section
+st.markdown(
+    """
+    ### Steps to Use
+    1. **Download the template** from the sidebar.
+    2. **Fill out the details** as per the instructions.
+    3. **Upload the completed CSV file** below.
+    4. Enter a **prompt** to generate personalized invitations.
+    """
+)
+
+# File uploader for CSV
+uploaded_file = st.file_uploader("📂 Upload CSV File", type=["csv"])
+user_prompt = st.text_area(
+    "✍️ Enter the prompt for generating invitation texts:",
+    "Write professional invitation text tailored for the group.",
+    height=150,
+)
+
+# Processing and displaying results
+if uploaded_file is not None and user_prompt:
+    st.write("⏳ Processing your file... Please wait.")
+    processed_df = process_csv(uploaded_file, user_prompt)
+
+    # Display results
+    st.write("### Generated Invitations")
+    st.dataframe(processed_df, use_container_width=True)
+
+    # Option to download the processed CSV
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as temp_file:
+        processed_df.to_csv(temp_file.name, index=False)
+        temp_file.close()  # Ensure the file is properly closed before proceeding
+
+        st.download_button(
+            label="📥 Download Results CSV",
+            data=open(temp_file.name, "rb"),
+            file_name="generated_invitations.csv",
+            mime="text/csv",
+        )
+
+    # Safely delete the temporary file
+    os.unlink(temp_file.name)
+
+# Footer
+st.markdown("---")
+st.markdown(
+    "💡 **Tip:** Ensure your data aligns with the provided template for accurate results."
+)