Create app.py

app.py

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+import streamlit as st
+import os
+import google.generativeai as geneai
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Apply custom CSS for styling
+def add_custom_css():
+    st.markdown("""
+        <style>
+            /* Background color */
+            .stApp {
+                background-color: #f0f2f6;
+                background-image: linear-gradient(315deg, #f0f2f6 0%, #c6e5ff 74%);
+                padding: 20px;
+            }
+            /* Sidebar styling */
+            .css-1aumxhk {
+                background-color: #fff;
+                padding: 20px;
+                border-radius: 10px;
+                box-shadow: 0px 4px 6px rgba(0, 0, 0, 0.1);
+            }
+            /* Text input styling */
+            .stTextInput, .stTextArea, .stSelectbox {
+                border-radius: 10px;
+                border: 1px solid #dcdcdc;
+                padding: 10px;
+            }
+            /* Buttons */
+            .stButton button {
+                background-color: #007bff;
+                color: white;
+                border: none;
+                border-radius: 10px;
+                padding: 10px 20px;
+                font-size: 16px;
+            }
+            /* Headers */
+            h1, h2, h3 {
+                color: #003366;
+            }
+            /* Success messages */
+            .stAlert {
+                background-color: #e6f7ff;
+                border: 1px solid #91d5ff;
+                border-radius: 10px;
+            }
+        </style>
+    """, unsafe_allow_html=True)
+
+# Google Vertex AI service class
+class GoogleVertexAIService:
+    def __init__(self):
+        self.api_key = os.getenv("GOOGLE_API_KEY")
+        if self.api_key:
+            geneai.configure(api_key=self.api_key)
+        self.model_1 = geneai.GenerativeModel("gemini-pro")
+        self.model_2 = geneai.GenerativeModel("gemini-pro")
+
+    def generate_proposal(self, client_data):
+        prompt = self._create_initial_prompt(client_data)
+        try:
+            response = self._generate_text(self.model_1, prompt)
+            refined_prompt = self._create_refined_prompt(client_data, response.text)
+            refined_response = self._generate_text(self.model_2, refined_prompt)
+            return refined_response.text.strip()
+        except Exception as e:
+            print(f"Error generating proposal: {e}")
+            return "An error occurred while generating the proposal."
+
+    def _generate_text(self, model, prompt):
+        try:
+            response = model.generate_content(prompt)
+            return response
+        except Exception as e:
+            print(f"Error in generate_content call: {e}")
+            raise
+
+    def _create_initial_prompt(self, client_data):
+        return (
+            f"Generate a base proposal for {client_data['client_name']} in the {client_data['industry']} industry. "
+            f"The client has specific requirements: {client_data['requirements']}. "
+            "Provide a foundational proposal that can be further refined."
+        )
+
+    def _create_refined_prompt(self, client_data, initial_proposal):
+        return (
+            f"Refine the following proposal for {client_data['client_name']} in the {client_data['industry']} industry. "
+            f"The client has specific requirements: {client_data['requirements']}. "
+            f"Initial proposal: {initial_proposal}. "
+            "Enhance this proposal with more contextually accurate details and ensure it addresses all client needs precisely."
+        )
+
+# Sidebar input form for client data
+def proposal_input():
+    st.sidebar.header("📝 Client Information")
+    client_name = st.sidebar.text_input("Client Name")
+    industry = st.sidebar.selectbox("Industry", ["Tech", "Finance", "Healthcare", "Education", "Other"])
+    requirements = st.sidebar.text_area("Special Requirements")
+
+    client_data = {
+        "client_name": client_name,
+        "industry": industry,
+        "requirements": requirements
+    }
+    
+    return client_data
+
+# Function to generate proposal using Google Generative AI
+def proposal_generation(client_data):
+    st.header("🚀 Generate Proposal")
+    
+    if st.button("Generate Proposal"):
+        with st.spinner("Generating proposal... 🤖"):
+            google_service = GoogleVertexAIService()
+            proposal = google_service.generate_proposal(client_data)
+            st.session_state['proposal'] = proposal
+            st.success("Proposal generated successfully! 🎉")
+            st.write(proposal)
+
+# Function to review and edit generated proposal
+def proposal_review():
+    st.header("✏️ Review and Edit Proposal")
+    
+    if 'proposal' in st.session_state:
+        proposal = st.text_area("Edit Proposal", st.session_state['proposal'], height=400)
+        st.session_state['proposal'] = proposal
+        st.success("Proposal updated successfully! 👍")
+    else:
+        st.warning("No proposal to review. Please generate a proposal first. 🕵️‍♂️")
+
+# Function to handle application settings (placeholder)
+def settings():
+    st.header("⚙️ Settings")
+    st.write("Here you can configure your AI parameters and other preferences.")
+    # Implement settings form here as needed
+
+# Main application logic
+def main():
+    st.title("AI-Powered Proposal Generator 🌟")
+    
+    # Add custom CSS
+    add_custom_css()
+
+    # Sidebar navigation
+    menu = ["Create Proposal", "Review Proposal", "Settings"]
+    choice = st.sidebar.selectbox("Menu", menu)
+
+    client_data = proposal_input()
+    st.session_state['client_data'] = client_data
+
+    if choice == "Create Proposal":
+        proposal_generation(client_data)
+    elif choice == "Review Proposal":
+        proposal_review()
+    elif choice == "Settings":
+        settings()
+
+if __name__ == '__main__':
+    main()