Update app.py

app.py

@@ -1,53 +1,82 @@
 import streamlit as st
 import google.generativeai as genai
 
-# Configure API Key
+# Streamlit app layout
+st.title('PromptLab')
+
+# Create two columns for the Shinobi and Raikage buttons
+col1, col2 = st.columns(2)
+
+mode = st.radio("Choose a mode:", ["Shinobi", "Raikage"], horizontal=True)
+
+# Retrieve the API key from Streamlit secrets
 GOOGLE_API_KEY = st.secrets["GEMINI_API_KEY"]
+
+# Configure the Google Generative AI API with your API key
 genai.configure(api_key=GOOGLE_API_KEY)
 
-# Select Gemini Model
-gemini_model = genai.GenerativeModel("gemini-2.0-flash")
+# Input field for the blog topic
+topic = st.text_area('Enter your prompt:')
 
-# Streamlit App Layout
-st.title('PromptLab')
+# Display selected mode
+st.write(f"You selected: {mode}")
+
+
+# Shinobi and Raikage templates
+SHINOBI_TEMPLATE = """
+You are an advanced prompt enhancer, specializing in creating structured, high-clarity prompts that optimize LLM performance.  
+Your task is to refine a given prompt using the **Shinobi framework**, ensuring the following principles:
+
+✅ **Concise & High-Density Prompting** → Remove fluff, keeping instructions clear and actionable (~250 words max).  
+✅ **Explicit Role Definition** → Assign a role to the AI for better contextual grounding.  
+✅ **Step-by-Step Clarity** → Break the task into structured sections, avoiding ambiguity.  
+✅ **Defined Output Format** → Specify the response format (JSON, CSV, list, structured text, etc.).  
+✅ **Zero Conflicting Instructions** → Ensure clarity in constraints (e.g., avoid “simple yet comprehensive”).  
+✅ **Optional: One-Shot Example** → Add a single example where relevant to guide the AI.  
 
-# Mode Selection (Shinobi & Raikage)
-mode = st.radio("Select a mode:", ["🌀 Shinobi", "⚡ Raikage"], horizontal=True)
-
-# User Input
-st.subheader("Enter Your Prompt:")
-user_prompt = st.text_area('Enter your prompt:')
-
-# Function to Generate Enhanced Prompt
-def get_gemini_response(prompt):
-    try:
-        response = gemini_model.generate_content(prompt)
-        return response.text if response else "Error: No response received."
-    except Exception as e:
-        return f"❌ Gemini error: {e}"
-
-# Function to Format Prompt Based on Mode
-def generate_enhanced_prompt(user_prompt, mode):
-    if mode == "🌀 Shinobi":
-        system_prompt = "You are an expert in structured prompt design. Refine the following prompt for clarity, conciseness, and structured output."
-    elif mode == "⚡ Raikage":
-        system_prompt = "You are a world-class AI strategist specializing in execution-focused prompts. Transform the following prompt for high-impact, expert-level results."
-    
-    # Generate response using Gemini API
-    return get_gemini_response(system_prompt + "\n\n" + user_prompt)
-
-# Button to Submit the Prompt
+### **Enhance the following prompt using Shinobi principles:**  
+**Original Prompt:**  
+{user_prompt}  
+
+**Enhanced Shinobi Prompt:**  
+"""
+
+RAIKAGE_TEMPLATE = """
+You are an elite AI strategist, specializing in designing execution-focused prompts that maximize LLM efficiency.  
+Your task is to refine a given prompt using the **Raikage framework**, ensuring the following principles:  
+
+✅ **Precision & Depth** → Ensure expert-level guidance, reducing vagueness and ambiguity.  
+✅ **Context & Execution Approach** → Include a structured methodology to solve the problem.  
+✅ **Defined Output Format** → Specify exact structure (JSON, formatted text, markdown, tables, or code blocks).  
+✅ **Edge Case Handling & Constraints** → Account for potential failures and model limitations.  
+✅ **Optional: Few-Shot Prompting** → If beneficial, provide 1-2 high-quality examples for refinement.  
+✅ **Complies with External Factors** → Adhere to best practices (e.g., ethical scraping, security policies).  
+
+### **Enhance the following prompt using Raikage principles:**  
+**Original Prompt:**  
+{user_prompt}  
+
+**Enhanced Raikage Prompt:**  
+"""
 if st.button("Generate Enhanced Prompt"):
-    if user_prompt.strip():
-        try:
-            with st.spinner("Enhancing prompt..."):
-                enhanced_prompt = generate_enhanced_prompt(user_prompt, mode)
-                st.subheader("Enhanced Prompt:")
-                st.write(enhanced_prompt)  # Displaying the text from the response
-        except Exception as e:
-            st.error(f"Error: {e}")
-    else:
-        st.warning("Please enter a prompt before generating.")
+    if topic.strip():
+        with st.spinner("Enhancing your prompt..."):
+            # Choose the template based on the selected mode
+            if mode == "Shinobi":
+                prompt = SHINOBI_TEMPLATE.format(user_prompt=topic)
+            else:
+                prompt = RAIKAGE_TEMPLATE.format(user_prompt=topic)
 
-# Footer
-st.markdown("Built with 🧠 by Hruday & Google Gemini")
+            # Initialize the generative model
+            model = genai.GenerativeModel('gemini-pro')
+
+            # Generate enhanced prompt
+            try:
+                response = model.generate_content(prompt)
+                enhanced_prompt = response.text  # Extract the response text
+                st.subheader("🔹 Enhanced Prompt:")
+                st.code(enhanced_prompt, language="markdown")
+            except Exception as e:
+                st.error(f"❌ Error generating enhanced prompt: {e}")
+    else:
+        st.warning("⚠️ Please enter a prompt before generating.")