Update app.py

app.py

@@ -2,103 +2,94 @@ import os
 import streamlit as st
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
-from langchain_community.chat_models import ChatOpenAI
-from matplotlib import pyplot as plt
-import tempfile
-from fpdf import FPDF
-import openai
-
-# 🔐 Set your OpenAI API key from Hugging Face secret
-os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
-
-# 🎯 Prompt template
-prompt_template = PromptTemplate(
-    input_variables=["product1", "product2"],
-    template="""
-Compare the following two products/services:
+from langchain_community.llms import HuggingFaceHub
+import matplotlib.pyplot as plt
+from io import BytesIO
+from reportlab.pdfgen import canvas
+from reportlab.lib.pagesizes import letter
+
+# Load Hugging Face token
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = st.secrets["HF_TOKEN"]
+
+# Initialize LLM
+llm = HuggingFaceHub(
+    repo_id="google/flan-t5-xl",
+    model_kwargs={"temperature": 0.5, "max_length": 1024}
+)
 
+# Prompt Template
+template = """
+Compare the following two products or services:
 Product 1: {product1}
-
 Product 2: {product2}
 
-1. Provide a detailed feature-by-feature comparison.
-2. Perform a SWOT analysis for each.
-3. Conclude with a comparative summary highlighting key differentiators.
+1. Feature-by-feature comparison.
+2. SWOT analysis for each.
+3. A comparative summary highlighting key differentiators.
+
+Respond in structured format with headings.
 """
+
+prompt = PromptTemplate(
+    input_variables=["product1", "product2"],
+    template=template,
 )
 
-# 🤖 LLM Model Setup
-llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.3)
-comparison_chain = LLMChain(llm=llm, prompt=prompt_template)
-
-# 📊 Helper: Draw dummy chart for features
-def draw_feature_chart():
-    labels = ['Price', 'Ease of Use', 'Performance', 'Support', 'Customization']
-    product1_scores = [7, 8, 6, 9, 7]
-    product2_scores = [6, 7, 9, 8, 6]
-
-    x = range(len(labels))
-    plt.figure(figsize=(8, 4))
-    plt.bar(x, product1_scores, width=0.4, label="Product 1", align='center')
-    plt.bar([i + 0.4 for i in x], product2_scores, width=0.4, label="Product 2", align='center')
-    plt.xticks([i + 0.2 for i in x], labels)
-    plt.ylabel("Rating (out of 10)")
-    plt.title("Feature Comparison")
-    plt.legend()
-    st.pyplot(plt)
-
-# 📝 Helper: Convert text to PDF
-def convert_to_pdf(text):
-    pdf = FPDF()
-    pdf.set_auto_page_break(auto=True, margin=15)
-    pdf.add_page()
-    pdf.set_font("Arial", size=12)
-
-    for line in text.split('\n'):
-        pdf.multi_cell(0, 10, line)
-
-    temp_pdf = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
-    pdf.output(temp_pdf.name)
-    return temp_pdf.name
-
-# 🚀 Streamlit UI
-st.set_page_config(page_title="🔍 Competitive Analysis Tool", layout="wide")
-st.title("🤖 Competitive Analysis Tool using LLMs")
-st.write("Compare two products or services with a detailed feature comparison, SWOT analysis, and summary.")
-
-# ✍️ User Inputs
-product1 = st.text_area("🅰️ Enter details about Product/Service 1", height=200)
-product2 = st.text_area("🅱️ Enter details about Product/Service 2", height=200)
-
-if st.button("🔍 Compare Now"):
-    if not product1 or not product2:
-        st.warning("⚠️ Please enter details for both products/services.")
-    else:
-        with st.spinner("Analyzing... Please wait."):
-            try:
-                result = comparison_chain.run(product1=product1, product2=product2)
-
-                # Display results
-                st.subheader("📋 Full Analysis")
-                st.markdown(result)
-
-                # Show Chart
-                st.subheader("📊 Feature Comparison (Chart)")
-                draw_feature_chart()
-
-                # PDF Download
-                pdf_path = convert_to_pdf(f"Competitive Analysis\n\n{result}")
-                with open(pdf_path, "rb") as f:
-                    st.download_button("📄 Download PDF Report", f, file_name="analysis_report.pdf")
-
-            except openai.RateLimitError:
-                st.error("🚫 You exceeded your OpenAI quota. Check https://platform.openai.com/account/usage")
-
-            except openai.InvalidRequestError as e:
-                st.error(f"❌ Invalid request: {str(e)}")
-
-            except openai.OpenAIError as e:
-                st.error(f"💥 OpenAI Error: {str(e)}")
-
-            except Exception as e:
-                st.error(f"⚠️ Unexpected Error: {str(e)}")
+comparison_chain = LLMChain(llm=llm, prompt=prompt)
+
+# Streamlit UI
+st.title("🔍 Competitive Analysis Tool (Hugging Face Version)")
+
+product1 = st.text_area("Enter details for Product/Service 1")
+product2 = st.text_area("Enter details for Product/Service 2")
+
+if st.button("Compare"):
+    with st.spinner("Generating analysis..."):
+        try:
+            result = comparison_chain.run(product1=product1, product2=product2)
+            st.subheader("📊 Analysis Result")
+            st.markdown(result)
+
+            # Optional: Simple chart visualization (Dummy feature scores)
+            features = ["Usability", "Performance", "Support", "Integration"]
+            p1_scores = [8, 7, 6, 9]
+            p2_scores = [7, 8, 8, 7]
+
+            fig, ax = plt.subplots()
+            bar_width = 0.35
+            index = range(len(features))
+
+            ax.bar(index, p1_scores, bar_width, label="Product 1")
+            ax.bar([i + bar_width for i in index], p2_scores, bar_width, label="Product 2")
+
+            ax.set_xlabel('Features')
+            ax.set_ylabel('Scores')
+            ax.set_title('Feature Comparison')
+            ax.set_xticks([i + bar_width / 2 for i in index])
+            ax.set_xticklabels(features)
+            ax.legend()
+
+            st.pyplot(fig)
+
+            # PDF Download
+            def create_pdf(text):
+                buffer = BytesIO()
+                c = canvas.Canvas(buffer, pagesize=letter)
+                width, height = letter
+                y = height - 40
+
+                for line in text.split('\n'):
+                    c.drawString(30, y, line)
+                    y -= 15
+                    if y < 50:
+                        c.showPage()
+                        y = height - 40
+                c.save()
+                buffer.seek(0)
+                return buffer
+
+            pdf_data = create_pdf(result)
+            st.download_button("📄 Download PDF Report", data=pdf_data, file_name="analysis_report.pdf")
+
+        except Exception as e:
+            st.error(f"Something went wrong: {e}")