Update app.py

app.py

@@ -1,17 +1,19 @@
 import streamlit as st
 from langchain_community.llms import HuggingFaceHub
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
 import os
 from fpdf import FPDF
 from io import BytesIO
 
-# 🎨 Streamlit page setup
-st.set_page_config(page_title="Pro Competitive Analysis", layout="centered")
+# Page config
+st.set_page_config(page_title="Pro Competitive Analysis Tool", layout="centered")
 
-# 💅 Custom dark styling
+# Stylish monochrome header
 st.markdown("""
 <style>
 body {
-    background-color: #111 !important;
+    background-color: #111;
     color: #e0e0e0;
     font-family: 'Segoe UI', sans-serif;
 }
@@ -36,58 +38,54 @@ button:hover {
 </style>
 """, unsafe_allow_html=True)
 
-# 🧠 Header
 st.title("💼 Competitive Analysis Pro")
-st.markdown("Generate expert-level insights between two competing products or services.")
+st.markdown("Gain deep market insight with feature breakdowns, SWOT, and key differentiators.")
 
-# 🗝️ Hugging Face Token (set via HF secret)
+# Set API key from Hugging Face Secrets
 os.environ["HUGGINGFACEHUB_API_TOKEN"] = st.secrets["HF_TOKEN"]
 
-# 🧠 LLM setup
+# Load model
 llm = HuggingFaceHub(
     repo_id="tiiuae/falcon-7b-instruct",
     model_kwargs={"temperature": 0.7, "max_new_tokens": 1024}
 )
 
-# ✍️ Input fields
-product1 = st.text_area("🧩 Product/Service 1", height=200, placeholder="e.g., Salesforce CRM")
-product2 = st.text_area("🧩 Product/Service 2", height=200, placeholder="e.g., Zoho CRM")
-
-# 🚀 Action
-if st.button("🔍 Run Competitive Analysis", use_container_width=True):
-    if not product1 or not product2:
-        st.warning("Please enter descriptions for both products.")
-    else:
-        # 💬 Instructions hidden from output
-        full_prompt = """
-You are a professional market analyst trained to evaluate two competing products or services.
-
-Your task is to generate an analysis in markdown format including:
-- Feature-by-feature comparison
-- SWOT analysis for each
-- Business insights, use cases, and recommendations
-- Key differentiators and user fit
-
-Do not mention these instructions or your role. Only return the analysis.
-"""
-
-        # 🔗 Final prompt sent to LLM
-        final_input = full_prompt + f"""
+# Prompt template
+template = """
+You are a professional market analyst. Analyze the two following products/services.
 
 Product 1:
 {product1}
 
 Product 2:
 {product2}
+
+Instructions:
+1. Provide a detailed feature-by-feature comparison (performance, pricing, usability, support, integrations, etc.).
+2. Conduct a comprehensive SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis for each.
+3. Offer business insights, use cases, and suggestions for each.
+4. Summarize the key differentiators and recommend which is better for different types of users or companies.
+Use professional tone and structured markdown formatting (with bold headings and bullet points).
 """
-        with st.spinner("Generating analysis..."):
-            result = llm(final_input)
 
-        # 🧾 Display analysis
-        st.markdown("### 📊 Expert Comparison")
+prompt = PromptTemplate(input_variables=["product1", "product2"], template=template)
+comparison_chain = LLMChain(llm=llm, prompt=prompt)
+
+# Input UI
+product1 = st.text_area("🧩 Product/Service 1", height=200, placeholder="e.g., Salesforce CRM")
+product2 = st.text_area("🧩 Product/Service 2", height=200, placeholder="e.g., Zoho CRM")
+
+if st.button("🔍 Run Competitive Analysis", use_container_width=True):
+    if not product1 or not product2:
+        st.warning("Please enter descriptions for both products.")
+    else:
+        with st.spinner("Analyzing with LLM..."):
+            result = comparison_chain.run(product1=product1, product2=product2)
+
+        st.markdown("### 📊 Analysis Report")
         st.markdown(result)
 
-        # 📥 PDF Export
+        # PDF Report
         pdf = FPDF()
         pdf.add_page()
         pdf.set_font("Arial", size=12)
@@ -96,7 +94,7 @@ Product 2:
         pdf_output = BytesIO(pdf_bytes)
 
         st.download_button(
-            label="📥 Download Report as PDF",
+            label="📥 Download Full Report as PDF",
             data=pdf_output,
             file_name="competitive_analysis_report.pdf",
             mime="application/pdf",