Update app.py

app.py

@@ -1,30 +1,34 @@
-import os
 import streamlit as st
 from langchain_community.llms import HuggingFaceHub
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
+import os
 import matplotlib.pyplot as plt
 from fpdf import FPDF
-import tempfile
+from io import BytesIO
 
-# Set Hugging Face token from secrets
+# Set Hugging Face API token from secrets
 os.environ["HUGGINGFACEHUB_API_TOKEN"] = st.secrets["HF_TOKEN"]
 
-# Load LLM from Hugging Face
+# Choose a compatible model (text-generation)
 llm = HuggingFaceHub(
-    repo_id="google/flan-t5-xl",
-    model_kwargs={"temperature": 0.7, "max_length": 1024}
+    repo_id="tiiuae/falcon-7b-instruct", model_kwargs={"temperature": 0.7, "max_new_tokens": 1024}
 )
 
-# Prompt Template
-template = """Compare the following two products/services:
-Product 1: {product1}
-Product 2: {product2}
+# Prompt template
+template = """
+Compare the following two products or services:
+
+Product 1:
+{product1}
 
-Provide:
-1. A feature-by-feature comparison (up to 5 features).
-2. SWOT analysis for both.
-3. A comparative summary highlighting key differences and similarities.
+Product 2:
+{product2}
+
+Instructions:
+1. Provide a feature-by-feature comparison.
+2. Generate a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis for each.
+3. Summarize key differentiators between them.
 """
 
 prompt = PromptTemplate(
@@ -32,56 +36,44 @@ prompt = PromptTemplate(
     template=template,
 )
 
-# LLM Chain
 comparison_chain = LLMChain(llm=llm, prompt=prompt)
 
 # Streamlit UI
-st.title("🔍 AI Competitive Analysis Tool")
-product1 = st.text_area("Enter Product 1 description")
-product2 = st.text_area("Enter Product 2 description")
+st.title("🔍 Competitive Analysis Tool")
+st.write("Compare two products or services using LLM-powered insights.")
 
-def generate_pdf(text, filename):
-    pdf = FPDF()
-    pdf.add_page()
-    pdf.set_auto_page_break(auto=True, margin=15)
-    pdf.set_font("Arial", size=12)
-    for line in text.split('\n'):
-        pdf.multi_cell(0, 10, line)
-    pdf.output(filename)
+product1 = st.text_area("Enter Product/Service 1 Description", height=200)
+product2 = st.text_area("Enter Product/Service 2 Description", height=200)
 
 if st.button("Compare"):
     if not product1 or not product2:
-        st.warning("Please enter both products.")
+        st.warning("Please enter descriptions for both products.")
     else:
-        with st.spinner("Analyzing..."):
-            result = comparison_chain.run(product1=product1, product2=product2)
-            st.success("Comparison complete!")
-
-            st.subheader("📋 Analysis Report")
-            st.markdown(result)
+        result = comparison_chain.run(product1=product1, product2=product2)
+        st.subheader("📊 Comparison Results")
+        st.write(result)
 
-            # Optional Chart (dummy data, just for visual comparison)
-            st.subheader("📊 Feature Comparison Chart")
-            features = ["Ease of Use", "Performance", "Cost", "Support", "Scalability"]
-            values1 = [3, 4, 2, 3, 4]  # Dummy data
-            values2 = [4, 3, 3, 4, 3]  # Dummy data
+        # Basic chart: Number of keywords in each description (just an example)
+        p1_len = len(product1.split())
+        p2_len = len(product2.split())
+        fig, ax = plt.subplots()
+        ax.bar(["Product 1", "Product 2"], [p1_len, p2_len], color=["skyblue", "salmon"])
+        ax.set_ylabel("Word Count")
+        ax.set_title("Word Count Comparison")
+        st.pyplot(fig)
 
-            fig, ax = plt.subplots()
-            x = range(len(features))
-            ax.bar(x, values1, width=0.4, label="Product 1", align='center')
-            ax.bar([p + 0.4 for p in x], values2, width=0.4, label="Product 2", align='center')
-            ax.set_xticks([p + 0.2 for p in x])
-            ax.set_xticklabels(features)
-            ax.legend()
-            st.pyplot(fig)
+        # Create a downloadable PDF report
+        pdf = FPDF()
+        pdf.add_page()
+        pdf.set_font("Arial", size=12)
+        pdf.multi_cell(0, 10, txt="Competitive Analysis Report\n\n" + result)
+        pdf_output = BytesIO()
+        pdf.output(pdf_output)
+        pdf_output.seek(0)
 
-            # PDF Download
-            with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
-                generate_pdf(result, tmp_file.name)
-                with open(tmp_file.name, "rb") as f:
-                    st.download_button(
-                        label="📄 Download PDF Report",
-                        data=f,
-                        file_name="comparison_report.pdf",
-                        mime="application/pdf"
-                    )
+        st.download_button(
+            label="📥 Download PDF Report",
+            data=pdf_output,
+            file_name="competitive_analysis_report.pdf",
+            mime="application/pdf"
+        )